Linking SCOR planning practicesto supply chain performance

An exploratory study

Archie Lockamy IIISamford University School of Business Birmingham Alabama USA

Kevin McCormackDRK Research and Consulting LLC Birmingham Alabama USA

Keywords Supply chain management Performance measurement

Abstract As supply chains continue to replace individual firms as the economic engine for creatingvalue during the twenty-first century understanding the relationship between supply-chainmanagement practices and supply chain performance becomes increasingly important TheSupply-Chain Operations Reference (SCOR) model developed by the Supply Chain Council provides aframework for characterizing supply-chain management practices and processes that result inbest-in-class performance However which of these practices have the most influence on supply chainperformance This exploratory study investigates the relationship between supply-chain managementplanning practices and supply chain performance based on the four decision areas provided in SCORModel Version 40 (PLAN SOURCE MAKE DELIVER) and nine key supply-chain managementplanning practices derived from supply-chain management experts and practitioners The resultsshow that planning processes are important in all SCOR supply chain planning decision areasCollaboration was found to bemost important in the Plan Source andMake planning decision areaswhile teaming was most important in supporting the Plan and Source planning decisionareas Process measures process credibility process integration and information technology werefound to be most critical in supporting the Deliver planning decision area Using these results thestudy discusses the implications of the findings and suggests several avenues for future research

IntroductionIncreasingly firms are adopting supply-chain management (SCM) to reduce costsincrease market share and sales and build solid customer relations (Ferguson 2000)SCM can be viewed as a philosophy based on the belief that each firm in the supplychain directly and indirectly affects the performance of all the other supply chainmembers as well as ultimately overall supply-chain performance (Cooper et al 1997)The effective use of this philosophy requires that functional and supply-chain partneractivities are aligned with company strategy and harmonized with organizationalstructure processes culture incentives and people (Abell 1999) Additionally thechain-wide deployment of SCM practices consistent with the above-mentionedphilosophy is needed to provide maximum benefit to its members

The Supply-Chain Operations Reference (SCOR) model was developed by theSupply-Chain Council (SCC) to assist firms in increasing the effectiveness of theirsupply chains and to provide a process-based approach to SCM (Stewart 1997) TheSCOR model provides a common process oriented language for communicating amongsupply-chain partners in the following decision areas PLAN SOURCE MAKE andDELIVER Recently the details for the decision area of ldquoRETURNrdquo have been added tothe SCOR Version 50 model Since the SCOR model is the main framework used in the

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IJOPM2412

1192

International Journal of Operations ampProduction ManagementVol 24 No 12 2004pp 1192-1218q Emerald Group Publishing Limited0144-3577DOI 10110801443570410569010

organization of this study a short explanation is required In each decision area thereare three levels of process detail A diagram depicting these levels is provided inFigure 1 Level 1 defines the scope and content of the core management processes forthe above-mentioned decision areas For example the SCOR Plan process is defined asthose processes that balance aggregate demand and supply for developing actionswhich best meet sourcing production and delivery requirements Level 2 describes thecharacteristics associated with the following process types deployed within the coreprocesses planning execution and enable For example supply chain partners requireprocesses for planning the overall supply chain as well as planning processes forsupporting source make deliver and return decisions A diagram illustrating Level 2for SCOR Model Version 40 is provided in Figure 2 Characteristics associated witheffective planning processes include a balance between demand and supply and aconsistent planning horizon The SCOR model also contains Level 2 process categoriesdefined by the relationship between a core management process and process typeLevel 3 provides detailed process element information for each Level 2 processcategory Inputs outputs description and the basic flow of process elements arecaptured at this level of the SCOR model

Figure 1Supply-Chain Operations

Reference Model

Supply chainperformance

1193

Although the SCORmodel acknowledges the need for an implementation level (Level 4)for effective SCM this level lies outside of its current scope The rationale for itsexclusion is that the SCOR model is designed as a tool to describe measure andevaluate any supply-chain configuration Thus firms must implement specificsupply-chain management practices based upon their unique set of competitivepriorities and business conditions to achieve the desired level of performanceHowever of the various supply-chain management practices available which practiceshave the most influence on supply-chain performance Furthermore does the degree ofinfluence vary by the decision areas outlined in the SCOR model The purpose of thisexploratory study is to investigate the relationship between supply-chain management

Figure 2Supply-Chain OperationsReference Model Level 2

IJOPM2412

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planning practices and supply chain performance based on the four decision areasprovided in SCOR Model Version 40 (PLAN SOURCE MAKE DELIVER) and ninekey supply-chain management planning practices derived from supply-chainmanagement experts and practitioners

The paper is organized as follows First the paper reviews the supply chainplanning literature highlighting the need for empirical research linking supply chainplanning practices to supply chain performance Second it provides a workingdefinition of SCM and a description of the SCOR model used as a basis for the researchThird a set of research questions is proposed linking supply-chain managementplanning practices to supply chain performance Fourth the paper describes themethods and analysis conducted to explore these questions Finally the results of thestudy along with future research opportunities are offered

Review of the supply-chain management planning literatureCooper and Ellram (1993) associate the following characteristics with effective SCMChannel-wide inventory management supply chain cost efficiency long-term timehorizons joint planning mutual information sharing and monitoring channelcoordination shared visions and compatible corporate cultures supplier relationshipsand the sharing of risks and rewards The SCM research literature provides significantinsight on the role of planning in facilitating the effective management of supply chainsFor example one area of SCM research focuses on planning the design and configurationof the supply chain to achieve competitive advantages (Vickery et al 1999 Childerhouseand Towill 2000 Reutterer and Kotzab 2000 Stock et al 2000 Korpela et al 2001abHarland et al 2001) This area of research corresponds to P1 in Level 2 of theSupply-Chain Operations Reference Model Another SCM research area revealed in theliterature review is the necessity for supply chain information technology (IT) to fosterinformation sharing (Chandrashekar and Schary 1999 DrsquoAmours et al 1999Humphreys et al 2001 and Rutner et al 2001) supply chain competitiveness(Narasimhan and Kim 2001) and the use of ERP systems (Manetti 2001) advancedplanning systems (Cauthen 1999) and internet technologies (Cross 2000 Brewton andKingseed 2001 and Deeter-Schmelz et al 2001) This literature suggests that theeffective use of supply chain IT can have a dramatic impact on each of the four decisionareas provided in SCOR Model Version 40 (Plan Source Make Deliver)

The literature review also revealed the importance of partnership planning activitiesfor collaborating among supply chain partners (Corbett et al1999 Narasimhan andDas1999 Raghunathan 1999 Boddy et al 2000 Ellinger 2000 Kaufman et al 2000Walleret al 2000) integrating cross-functional processes (Lambert and Cooper 2000)coordinating the supply chain (Kim 2000) setting supply chain goals (Wong 1999 Peckand Juttner 2000) developing strategic alliances (McCutcheon and Stuart 2000Whipple and Frankel 2000) establishing information-sharing parameters (Lamminget al2001) reviewing sourcing and outsourcing options (Ansari et al 1999 Heriot andKulkarni 2001) and defining supply chain power relationships among trading partners(Cox 1999 Maloni and Benton 2000 Cox 2001abc Cox et al 2001Watson 2001) Thisliterature also corresponds to each of the four decision areas provided in SCOR ModelVersion 40 Finally the literature highlights the need for overall strategic supply chainplanning to facilitate customer and supplier integration (Frohlich andWestbrook 2001Hauguel and Jackson 2001) strategic supply chain design (Fine 2000) an alignment

Supply chainperformance

1195

between supply chain processes and strategic objectives (Hicks et al 2000 Tamas2000) effective order fulfillment and inventory management ( Johnson and Anderson2000 Viswanathan and Piplani 2001) and shareholder value via the achievement ofcompetitive advantages (Christopher and Ryals 1999 and Ramsay 2001) A directcorrespondence to P1 in Level 2 of the Supply-Chain Operations Reference Model isobserved in this area of the literature

There have been only a small number of studies attempting to empirically linkspecific SCM practices to supply chain performance One significant study utilized thetwenty-first century Logistics framework a list of six critical areas of competence inachieving supply chain logistics integration to investigate the relationship betweenlogistics integration competence and performance (Stank et al 2001b) The sixintegration competencies in the framework are customer integrationinternal integration supplier integration technology and planning integrationmeasurement integration and relationship integration Their results showed thatcustomer integration internal integration and technology and planning performanceare the dominant competencies related to performance In this research specificplanning practices related to performance were difficult to identify although somewere implied within the measurement system used

A review of this literature suggests the following conclusions First the importanceand necessity of supply-chain management planning is well established in theliterature and warrants continued research Second research published in this areacorresponds to the four decision areas provided in SCOR Model Version 40 Thirdbecause of this correspondence the planning activities illustrated in Level 2 of theSupply-Chain Operations Reference Model can be used as a framework for directingfuture supply-chain management planning research Finally there is an absence ofempirical research clearly linking specific supply chain planning practices to supplychain performance Thus this exploratory study is an empirical investigation of therelationship between supply-chain management planning practices and supply chainperformance based on the four decision areas provided in SCOR Model Version 40 andnine key supply-chain management planning practices derived from supply-chainmanagement experts and practitioners

Construct developmentThe literature review along with discussions and interviews with supply chain expertsand practitioners was used as the basis for developing the constructs for the studysupply chain planning practices and supply chain performance Through this effortnine key supply chain planning practices emerged planning processes processintegration process documentation collaboration teaming process ownership processmeasures process credibility and information technology (IT) support Planningprocesses are required to determine the most efficient and effective way to use theorganizationrsquos resources to achieve a specific set of objectives Process integration refersto the tight coupling of two or more processes through shared systems automatedfunctions and event triggers (ie auto replenishment) Process documentation requiresa clear documented understanding and agreement of what is to be done within andbetween processes It is usually achieved through process design andmapping sessionsor review and validation sessions with the process teams Maintenance and changecontrol of this documentation is also a critical component For collaboration and teaming

IJOPM2412

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to occur individuals from the various functions involved in effective SCMmust work asa tightly integrated group with shared authority to make decisions and take actionsA collaborative team based SCM structure represents the span of involvementinfluence and authority in an SCM organization and enables multi-dimensionalcross-functional authority Early research suggests that there are different types ofcollaboration based upon the intensity of the information exchanges and the nature ofthe relationship These types are transactional cooperative (coordinative) andcollaborative (McCormack 2003) The formal creation of broad cross-functional jobswith real overall supply chain process authority and ownership is a key component ofprocess ownership Process measures are used to identify and assign responsibility forsupply chain process outcomes relating to such areas as efficiency cost and quality aswell as to provide a link to the firmrsquos reward system Process credibility refers to the levelof customer confidence in the output of the process and its use in making commitmentsFinally IT support refers to the process ownersrsquo and team membersrsquo perceivedusefulness of the IT system in support of SCM processes

The literature review discussions and interviews also resulted in the emergence ofseven key supply-chain management planning decision categories operations strategyplanning demand management production planning and scheduling procurementpromise delivery balancing change and distribution management Discussions thenproceeded on how these decision categories relate to the Supply-Chain OperationsReference (SCOR) Model This resulted in Figure 3 which maps the above-mentionedsupply-chain management planning decision categories to the SCOR Model Thismapping suggests that operations strategy planning and promise delivery decisionstend to be aligned with a firmrsquos internal SCOR decision areas while decisions onbalancing change tend to span internal and external SCOR decision areas across theentire supply chain Additionally procurement along with production planning andscheduling decisions tend to span across both internal and supplier SCOR decision

Figure 3Supply chain decision

categories mapped to theSCOR model

Supply chainperformance

1197

areas while demand and distribution management decisions span across both internaland customer decision areas

The planning activities illustrated in Level 2 of the Supply-Chain OperationsReference Model were used to specify the domain of supply-chain managementplanning practices for the study (PLAN SOURCE MAKE DELIVER) The expertsand practitioners used in developing and validating the constructs were selected fromthe Chesapeake Decision Sciences (now AspenTech) user group list This list spannedacross multiple industries and contained a high number of individuals with either aMasters or PhD degree in operations research For this study a practice is defined as amethod technique procedure or process

The supply chain performance construct is a self-assessed performance rating foreach of the SCOR decision areas The construct is based on perceived performance asdetermined by the survey respondents It is represented as a single item for eachdecision area (see Appendix 1 Questions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31(DELIVER)) The specific item statement on supply chain performance for each of theSCOR decision areas is ldquoOverall this decision process area performs very wellrdquo Theparticipants were asked to either agree or disagree with the item statement using afive-point Likert scale (1 frac14 strongly disagree 5 frac14 strongly agree)

Research questionsThe following research questions were developed to operationalize theabove-mentioned constructs

RQ1 What are the most important supply-chain management planning practices inthe PLAN decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ2 What are the most important supply-chain management planning practices inthe SOURCE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ3 What are the most important supply-chain management planning practices inthe MAKE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ4 What are the most important supply-chain management planning practices inthe DELIVER decision area of SCOR Model Version 40 that relate toperceived supply chain performance

Research methodologyThe research approach for this study follows the process of investigation andmeasurement developed by Churchill (1979) A figure depicting the approach isprovided in Figure 4 The approach includes specifying the domain of the constructgenerating a sample of items which capture the domain as specified purifying themeasures through coefficient alpha or factor analysis assessing reliability with newdata assessing the construct validity and developing norms

Survey instrumentThe literature review along with discussions and interviews with supply chain expertsand practitioners was also used as the basis for developing survey questions

IJOPM2412

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representing the nine key supply chain planning practices identified in the ldquoConstructdevelopmentrdquo section The discussions were structured around SCOR Model Version40 A survey instrument was developed using a 5-item Likert scale measuring thefrequency of the practices consisting of 1 ndash never or does not exist 2 ndash sometimes 3 ndashfrequently 4 ndash mostly and 5 ndash always or definitely exists The survey askedrespondents to provide their opinion concerning ldquowhat is done how often who does itand how it is donerdquo in their supply chain The initial survey was tested within a majorelectronic equipment manufacturer and with several supply chain experts Based uponthese tests improvements in wording and format were made to the instrument andseveral items were eliminated

The Supply Chain Council board of directors also reviewed the survey instrumentBased upon this review the survey was slightly reorganized to better match the SCORmodel The survey questions grouped by SCOR decision area are provided inAppendix A The questions focus on decision making in the seven key supply-chainmanagement planning decision categories (operations strategy planning demandmanagement production planning and scheduling procurement promise deliverybalancing change and distribution management) for each of the four SCOR decision

Figure 4Churchill research

methodology

Supply chainperformance

1199

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

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distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

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Although the SCORmodel acknowledges the need for an implementation level (Level 4)for effective SCM this level lies outside of its current scope The rationale for itsexclusion is that the SCOR model is designed as a tool to describe measure andevaluate any supply-chain configuration Thus firms must implement specificsupply-chain management practices based upon their unique set of competitivepriorities and business conditions to achieve the desired level of performanceHowever of the various supply-chain management practices available which practiceshave the most influence on supply-chain performance Furthermore does the degree ofinfluence vary by the decision areas outlined in the SCOR model The purpose of thisexploratory study is to investigate the relationship between supply-chain management

Figure 2Supply-Chain OperationsReference Model Level 2

IJOPM2412

1194

planning practices and supply chain performance based on the four decision areasprovided in SCOR Model Version 40 (PLAN SOURCE MAKE DELIVER) and ninekey supply-chain management planning practices derived from supply-chainmanagement experts and practitioners

The paper is organized as follows First the paper reviews the supply chainplanning literature highlighting the need for empirical research linking supply chainplanning practices to supply chain performance Second it provides a workingdefinition of SCM and a description of the SCOR model used as a basis for the researchThird a set of research questions is proposed linking supply-chain managementplanning practices to supply chain performance Fourth the paper describes themethods and analysis conducted to explore these questions Finally the results of thestudy along with future research opportunities are offered

Review of the supply-chain management planning literatureCooper and Ellram (1993) associate the following characteristics with effective SCMChannel-wide inventory management supply chain cost efficiency long-term timehorizons joint planning mutual information sharing and monitoring channelcoordination shared visions and compatible corporate cultures supplier relationshipsand the sharing of risks and rewards The SCM research literature provides significantinsight on the role of planning in facilitating the effective management of supply chainsFor example one area of SCM research focuses on planning the design and configurationof the supply chain to achieve competitive advantages (Vickery et al 1999 Childerhouseand Towill 2000 Reutterer and Kotzab 2000 Stock et al 2000 Korpela et al 2001abHarland et al 2001) This area of research corresponds to P1 in Level 2 of theSupply-Chain Operations Reference Model Another SCM research area revealed in theliterature review is the necessity for supply chain information technology (IT) to fosterinformation sharing (Chandrashekar and Schary 1999 DrsquoAmours et al 1999Humphreys et al 2001 and Rutner et al 2001) supply chain competitiveness(Narasimhan and Kim 2001) and the use of ERP systems (Manetti 2001) advancedplanning systems (Cauthen 1999) and internet technologies (Cross 2000 Brewton andKingseed 2001 and Deeter-Schmelz et al 2001) This literature suggests that theeffective use of supply chain IT can have a dramatic impact on each of the four decisionareas provided in SCOR Model Version 40 (Plan Source Make Deliver)

The literature review also revealed the importance of partnership planning activitiesfor collaborating among supply chain partners (Corbett et al1999 Narasimhan andDas1999 Raghunathan 1999 Boddy et al 2000 Ellinger 2000 Kaufman et al 2000Walleret al 2000) integrating cross-functional processes (Lambert and Cooper 2000)coordinating the supply chain (Kim 2000) setting supply chain goals (Wong 1999 Peckand Juttner 2000) developing strategic alliances (McCutcheon and Stuart 2000Whipple and Frankel 2000) establishing information-sharing parameters (Lamminget al2001) reviewing sourcing and outsourcing options (Ansari et al 1999 Heriot andKulkarni 2001) and defining supply chain power relationships among trading partners(Cox 1999 Maloni and Benton 2000 Cox 2001abc Cox et al 2001Watson 2001) Thisliterature also corresponds to each of the four decision areas provided in SCOR ModelVersion 40 Finally the literature highlights the need for overall strategic supply chainplanning to facilitate customer and supplier integration (Frohlich andWestbrook 2001Hauguel and Jackson 2001) strategic supply chain design (Fine 2000) an alignment

Supply chainperformance

1195

between supply chain processes and strategic objectives (Hicks et al 2000 Tamas2000) effective order fulfillment and inventory management ( Johnson and Anderson2000 Viswanathan and Piplani 2001) and shareholder value via the achievement ofcompetitive advantages (Christopher and Ryals 1999 and Ramsay 2001) A directcorrespondence to P1 in Level 2 of the Supply-Chain Operations Reference Model isobserved in this area of the literature

There have been only a small number of studies attempting to empirically linkspecific SCM practices to supply chain performance One significant study utilized thetwenty-first century Logistics framework a list of six critical areas of competence inachieving supply chain logistics integration to investigate the relationship betweenlogistics integration competence and performance (Stank et al 2001b) The sixintegration competencies in the framework are customer integrationinternal integration supplier integration technology and planning integrationmeasurement integration and relationship integration Their results showed thatcustomer integration internal integration and technology and planning performanceare the dominant competencies related to performance In this research specificplanning practices related to performance were difficult to identify although somewere implied within the measurement system used

A review of this literature suggests the following conclusions First the importanceand necessity of supply-chain management planning is well established in theliterature and warrants continued research Second research published in this areacorresponds to the four decision areas provided in SCOR Model Version 40 Thirdbecause of this correspondence the planning activities illustrated in Level 2 of theSupply-Chain Operations Reference Model can be used as a framework for directingfuture supply-chain management planning research Finally there is an absence ofempirical research clearly linking specific supply chain planning practices to supplychain performance Thus this exploratory study is an empirical investigation of therelationship between supply-chain management planning practices and supply chainperformance based on the four decision areas provided in SCOR Model Version 40 andnine key supply-chain management planning practices derived from supply-chainmanagement experts and practitioners

Construct developmentThe literature review along with discussions and interviews with supply chain expertsand practitioners was used as the basis for developing the constructs for the studysupply chain planning practices and supply chain performance Through this effortnine key supply chain planning practices emerged planning processes processintegration process documentation collaboration teaming process ownership processmeasures process credibility and information technology (IT) support Planningprocesses are required to determine the most efficient and effective way to use theorganizationrsquos resources to achieve a specific set of objectives Process integration refersto the tight coupling of two or more processes through shared systems automatedfunctions and event triggers (ie auto replenishment) Process documentation requiresa clear documented understanding and agreement of what is to be done within andbetween processes It is usually achieved through process design andmapping sessionsor review and validation sessions with the process teams Maintenance and changecontrol of this documentation is also a critical component For collaboration and teaming

IJOPM2412

1196

to occur individuals from the various functions involved in effective SCMmust work asa tightly integrated group with shared authority to make decisions and take actionsA collaborative team based SCM structure represents the span of involvementinfluence and authority in an SCM organization and enables multi-dimensionalcross-functional authority Early research suggests that there are different types ofcollaboration based upon the intensity of the information exchanges and the nature ofthe relationship These types are transactional cooperative (coordinative) andcollaborative (McCormack 2003) The formal creation of broad cross-functional jobswith real overall supply chain process authority and ownership is a key component ofprocess ownership Process measures are used to identify and assign responsibility forsupply chain process outcomes relating to such areas as efficiency cost and quality aswell as to provide a link to the firmrsquos reward system Process credibility refers to the levelof customer confidence in the output of the process and its use in making commitmentsFinally IT support refers to the process ownersrsquo and team membersrsquo perceivedusefulness of the IT system in support of SCM processes

The literature review discussions and interviews also resulted in the emergence ofseven key supply-chain management planning decision categories operations strategyplanning demand management production planning and scheduling procurementpromise delivery balancing change and distribution management Discussions thenproceeded on how these decision categories relate to the Supply-Chain OperationsReference (SCOR) Model This resulted in Figure 3 which maps the above-mentionedsupply-chain management planning decision categories to the SCOR Model Thismapping suggests that operations strategy planning and promise delivery decisionstend to be aligned with a firmrsquos internal SCOR decision areas while decisions onbalancing change tend to span internal and external SCOR decision areas across theentire supply chain Additionally procurement along with production planning andscheduling decisions tend to span across both internal and supplier SCOR decision

Figure 3Supply chain decision

categories mapped to theSCOR model

Supply chainperformance

1197

areas while demand and distribution management decisions span across both internaland customer decision areas

The planning activities illustrated in Level 2 of the Supply-Chain OperationsReference Model were used to specify the domain of supply-chain managementplanning practices for the study (PLAN SOURCE MAKE DELIVER) The expertsand practitioners used in developing and validating the constructs were selected fromthe Chesapeake Decision Sciences (now AspenTech) user group list This list spannedacross multiple industries and contained a high number of individuals with either aMasters or PhD degree in operations research For this study a practice is defined as amethod technique procedure or process

The supply chain performance construct is a self-assessed performance rating foreach of the SCOR decision areas The construct is based on perceived performance asdetermined by the survey respondents It is represented as a single item for eachdecision area (see Appendix 1 Questions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31(DELIVER)) The specific item statement on supply chain performance for each of theSCOR decision areas is ldquoOverall this decision process area performs very wellrdquo Theparticipants were asked to either agree or disagree with the item statement using afive-point Likert scale (1 frac14 strongly disagree 5 frac14 strongly agree)

Research questionsThe following research questions were developed to operationalize theabove-mentioned constructs

RQ1 What are the most important supply-chain management planning practices inthe PLAN decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ2 What are the most important supply-chain management planning practices inthe SOURCE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ3 What are the most important supply-chain management planning practices inthe MAKE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ4 What are the most important supply-chain management planning practices inthe DELIVER decision area of SCOR Model Version 40 that relate toperceived supply chain performance

Research methodologyThe research approach for this study follows the process of investigation andmeasurement developed by Churchill (1979) A figure depicting the approach isprovided in Figure 4 The approach includes specifying the domain of the constructgenerating a sample of items which capture the domain as specified purifying themeasures through coefficient alpha or factor analysis assessing reliability with newdata assessing the construct validity and developing norms

Survey instrumentThe literature review along with discussions and interviews with supply chain expertsand practitioners was also used as the basis for developing survey questions

IJOPM2412

1198

representing the nine key supply chain planning practices identified in the ldquoConstructdevelopmentrdquo section The discussions were structured around SCOR Model Version40 A survey instrument was developed using a 5-item Likert scale measuring thefrequency of the practices consisting of 1 ndash never or does not exist 2 ndash sometimes 3 ndashfrequently 4 ndash mostly and 5 ndash always or definitely exists The survey askedrespondents to provide their opinion concerning ldquowhat is done how often who does itand how it is donerdquo in their supply chain The initial survey was tested within a majorelectronic equipment manufacturer and with several supply chain experts Based uponthese tests improvements in wording and format were made to the instrument andseveral items were eliminated

The Supply Chain Council board of directors also reviewed the survey instrumentBased upon this review the survey was slightly reorganized to better match the SCORmodel The survey questions grouped by SCOR decision area are provided inAppendix A The questions focus on decision making in the seven key supply-chainmanagement planning decision categories (operations strategy planning demandmanagement production planning and scheduling procurement promise deliverybalancing change and distribution management) for each of the four SCOR decision

Figure 4Churchill research

methodology

Supply chainperformance

1199

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

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distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

planning practices and supply chain performance based on the four decision areasprovided in SCOR Model Version 40 (PLAN SOURCE MAKE DELIVER) and ninekey supply-chain management planning practices derived from supply-chainmanagement experts and practitioners

The paper is organized as follows First the paper reviews the supply chainplanning literature highlighting the need for empirical research linking supply chainplanning practices to supply chain performance Second it provides a workingdefinition of SCM and a description of the SCOR model used as a basis for the researchThird a set of research questions is proposed linking supply-chain managementplanning practices to supply chain performance Fourth the paper describes themethods and analysis conducted to explore these questions Finally the results of thestudy along with future research opportunities are offered

Review of the supply-chain management planning literatureCooper and Ellram (1993) associate the following characteristics with effective SCMChannel-wide inventory management supply chain cost efficiency long-term timehorizons joint planning mutual information sharing and monitoring channelcoordination shared visions and compatible corporate cultures supplier relationshipsand the sharing of risks and rewards The SCM research literature provides significantinsight on the role of planning in facilitating the effective management of supply chainsFor example one area of SCM research focuses on planning the design and configurationof the supply chain to achieve competitive advantages (Vickery et al 1999 Childerhouseand Towill 2000 Reutterer and Kotzab 2000 Stock et al 2000 Korpela et al 2001abHarland et al 2001) This area of research corresponds to P1 in Level 2 of theSupply-Chain Operations Reference Model Another SCM research area revealed in theliterature review is the necessity for supply chain information technology (IT) to fosterinformation sharing (Chandrashekar and Schary 1999 DrsquoAmours et al 1999Humphreys et al 2001 and Rutner et al 2001) supply chain competitiveness(Narasimhan and Kim 2001) and the use of ERP systems (Manetti 2001) advancedplanning systems (Cauthen 1999) and internet technologies (Cross 2000 Brewton andKingseed 2001 and Deeter-Schmelz et al 2001) This literature suggests that theeffective use of supply chain IT can have a dramatic impact on each of the four decisionareas provided in SCOR Model Version 40 (Plan Source Make Deliver)

The literature review also revealed the importance of partnership planning activitiesfor collaborating among supply chain partners (Corbett et al1999 Narasimhan andDas1999 Raghunathan 1999 Boddy et al 2000 Ellinger 2000 Kaufman et al 2000Walleret al 2000) integrating cross-functional processes (Lambert and Cooper 2000)coordinating the supply chain (Kim 2000) setting supply chain goals (Wong 1999 Peckand Juttner 2000) developing strategic alliances (McCutcheon and Stuart 2000Whipple and Frankel 2000) establishing information-sharing parameters (Lamminget al2001) reviewing sourcing and outsourcing options (Ansari et al 1999 Heriot andKulkarni 2001) and defining supply chain power relationships among trading partners(Cox 1999 Maloni and Benton 2000 Cox 2001abc Cox et al 2001Watson 2001) Thisliterature also corresponds to each of the four decision areas provided in SCOR ModelVersion 40 Finally the literature highlights the need for overall strategic supply chainplanning to facilitate customer and supplier integration (Frohlich andWestbrook 2001Hauguel and Jackson 2001) strategic supply chain design (Fine 2000) an alignment

Supply chainperformance

1195

between supply chain processes and strategic objectives (Hicks et al 2000 Tamas2000) effective order fulfillment and inventory management ( Johnson and Anderson2000 Viswanathan and Piplani 2001) and shareholder value via the achievement ofcompetitive advantages (Christopher and Ryals 1999 and Ramsay 2001) A directcorrespondence to P1 in Level 2 of the Supply-Chain Operations Reference Model isobserved in this area of the literature

There have been only a small number of studies attempting to empirically linkspecific SCM practices to supply chain performance One significant study utilized thetwenty-first century Logistics framework a list of six critical areas of competence inachieving supply chain logistics integration to investigate the relationship betweenlogistics integration competence and performance (Stank et al 2001b) The sixintegration competencies in the framework are customer integrationinternal integration supplier integration technology and planning integrationmeasurement integration and relationship integration Their results showed thatcustomer integration internal integration and technology and planning performanceare the dominant competencies related to performance In this research specificplanning practices related to performance were difficult to identify although somewere implied within the measurement system used

A review of this literature suggests the following conclusions First the importanceand necessity of supply-chain management planning is well established in theliterature and warrants continued research Second research published in this areacorresponds to the four decision areas provided in SCOR Model Version 40 Thirdbecause of this correspondence the planning activities illustrated in Level 2 of theSupply-Chain Operations Reference Model can be used as a framework for directingfuture supply-chain management planning research Finally there is an absence ofempirical research clearly linking specific supply chain planning practices to supplychain performance Thus this exploratory study is an empirical investigation of therelationship between supply-chain management planning practices and supply chainperformance based on the four decision areas provided in SCOR Model Version 40 andnine key supply-chain management planning practices derived from supply-chainmanagement experts and practitioners

Construct developmentThe literature review along with discussions and interviews with supply chain expertsand practitioners was used as the basis for developing the constructs for the studysupply chain planning practices and supply chain performance Through this effortnine key supply chain planning practices emerged planning processes processintegration process documentation collaboration teaming process ownership processmeasures process credibility and information technology (IT) support Planningprocesses are required to determine the most efficient and effective way to use theorganizationrsquos resources to achieve a specific set of objectives Process integration refersto the tight coupling of two or more processes through shared systems automatedfunctions and event triggers (ie auto replenishment) Process documentation requiresa clear documented understanding and agreement of what is to be done within andbetween processes It is usually achieved through process design andmapping sessionsor review and validation sessions with the process teams Maintenance and changecontrol of this documentation is also a critical component For collaboration and teaming

IJOPM2412

1196

to occur individuals from the various functions involved in effective SCMmust work asa tightly integrated group with shared authority to make decisions and take actionsA collaborative team based SCM structure represents the span of involvementinfluence and authority in an SCM organization and enables multi-dimensionalcross-functional authority Early research suggests that there are different types ofcollaboration based upon the intensity of the information exchanges and the nature ofthe relationship These types are transactional cooperative (coordinative) andcollaborative (McCormack 2003) The formal creation of broad cross-functional jobswith real overall supply chain process authority and ownership is a key component ofprocess ownership Process measures are used to identify and assign responsibility forsupply chain process outcomes relating to such areas as efficiency cost and quality aswell as to provide a link to the firmrsquos reward system Process credibility refers to the levelof customer confidence in the output of the process and its use in making commitmentsFinally IT support refers to the process ownersrsquo and team membersrsquo perceivedusefulness of the IT system in support of SCM processes

The literature review discussions and interviews also resulted in the emergence ofseven key supply-chain management planning decision categories operations strategyplanning demand management production planning and scheduling procurementpromise delivery balancing change and distribution management Discussions thenproceeded on how these decision categories relate to the Supply-Chain OperationsReference (SCOR) Model This resulted in Figure 3 which maps the above-mentionedsupply-chain management planning decision categories to the SCOR Model Thismapping suggests that operations strategy planning and promise delivery decisionstend to be aligned with a firmrsquos internal SCOR decision areas while decisions onbalancing change tend to span internal and external SCOR decision areas across theentire supply chain Additionally procurement along with production planning andscheduling decisions tend to span across both internal and supplier SCOR decision

Figure 3Supply chain decision

categories mapped to theSCOR model

Supply chainperformance

1197

areas while demand and distribution management decisions span across both internaland customer decision areas

The planning activities illustrated in Level 2 of the Supply-Chain OperationsReference Model were used to specify the domain of supply-chain managementplanning practices for the study (PLAN SOURCE MAKE DELIVER) The expertsand practitioners used in developing and validating the constructs were selected fromthe Chesapeake Decision Sciences (now AspenTech) user group list This list spannedacross multiple industries and contained a high number of individuals with either aMasters or PhD degree in operations research For this study a practice is defined as amethod technique procedure or process

The supply chain performance construct is a self-assessed performance rating foreach of the SCOR decision areas The construct is based on perceived performance asdetermined by the survey respondents It is represented as a single item for eachdecision area (see Appendix 1 Questions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31(DELIVER)) The specific item statement on supply chain performance for each of theSCOR decision areas is ldquoOverall this decision process area performs very wellrdquo Theparticipants were asked to either agree or disagree with the item statement using afive-point Likert scale (1 frac14 strongly disagree 5 frac14 strongly agree)

Research questionsThe following research questions were developed to operationalize theabove-mentioned constructs

RQ1 What are the most important supply-chain management planning practices inthe PLAN decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ2 What are the most important supply-chain management planning practices inthe SOURCE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ3 What are the most important supply-chain management planning practices inthe MAKE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ4 What are the most important supply-chain management planning practices inthe DELIVER decision area of SCOR Model Version 40 that relate toperceived supply chain performance

Research methodologyThe research approach for this study follows the process of investigation andmeasurement developed by Churchill (1979) A figure depicting the approach isprovided in Figure 4 The approach includes specifying the domain of the constructgenerating a sample of items which capture the domain as specified purifying themeasures through coefficient alpha or factor analysis assessing reliability with newdata assessing the construct validity and developing norms

Survey instrumentThe literature review along with discussions and interviews with supply chain expertsand practitioners was also used as the basis for developing survey questions

IJOPM2412

1198

representing the nine key supply chain planning practices identified in the ldquoConstructdevelopmentrdquo section The discussions were structured around SCOR Model Version40 A survey instrument was developed using a 5-item Likert scale measuring thefrequency of the practices consisting of 1 ndash never or does not exist 2 ndash sometimes 3 ndashfrequently 4 ndash mostly and 5 ndash always or definitely exists The survey askedrespondents to provide their opinion concerning ldquowhat is done how often who does itand how it is donerdquo in their supply chain The initial survey was tested within a majorelectronic equipment manufacturer and with several supply chain experts Based uponthese tests improvements in wording and format were made to the instrument andseveral items were eliminated

The Supply Chain Council board of directors also reviewed the survey instrumentBased upon this review the survey was slightly reorganized to better match the SCORmodel The survey questions grouped by SCOR decision area are provided inAppendix A The questions focus on decision making in the seven key supply-chainmanagement planning decision categories (operations strategy planning demandmanagement production planning and scheduling procurement promise deliverybalancing change and distribution management) for each of the four SCOR decision

Figure 4Churchill research

methodology

Supply chainperformance

1199

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

between supply chain processes and strategic objectives (Hicks et al 2000 Tamas2000) effective order fulfillment and inventory management ( Johnson and Anderson2000 Viswanathan and Piplani 2001) and shareholder value via the achievement ofcompetitive advantages (Christopher and Ryals 1999 and Ramsay 2001) A directcorrespondence to P1 in Level 2 of the Supply-Chain Operations Reference Model isobserved in this area of the literature

There have been only a small number of studies attempting to empirically linkspecific SCM practices to supply chain performance One significant study utilized thetwenty-first century Logistics framework a list of six critical areas of competence inachieving supply chain logistics integration to investigate the relationship betweenlogistics integration competence and performance (Stank et al 2001b) The sixintegration competencies in the framework are customer integrationinternal integration supplier integration technology and planning integrationmeasurement integration and relationship integration Their results showed thatcustomer integration internal integration and technology and planning performanceare the dominant competencies related to performance In this research specificplanning practices related to performance were difficult to identify although somewere implied within the measurement system used

A review of this literature suggests the following conclusions First the importanceand necessity of supply-chain management planning is well established in theliterature and warrants continued research Second research published in this areacorresponds to the four decision areas provided in SCOR Model Version 40 Thirdbecause of this correspondence the planning activities illustrated in Level 2 of theSupply-Chain Operations Reference Model can be used as a framework for directingfuture supply-chain management planning research Finally there is an absence ofempirical research clearly linking specific supply chain planning practices to supplychain performance Thus this exploratory study is an empirical investigation of therelationship between supply-chain management planning practices and supply chainperformance based on the four decision areas provided in SCOR Model Version 40 andnine key supply-chain management planning practices derived from supply-chainmanagement experts and practitioners

Construct developmentThe literature review along with discussions and interviews with supply chain expertsand practitioners was used as the basis for developing the constructs for the studysupply chain planning practices and supply chain performance Through this effortnine key supply chain planning practices emerged planning processes processintegration process documentation collaboration teaming process ownership processmeasures process credibility and information technology (IT) support Planningprocesses are required to determine the most efficient and effective way to use theorganizationrsquos resources to achieve a specific set of objectives Process integration refersto the tight coupling of two or more processes through shared systems automatedfunctions and event triggers (ie auto replenishment) Process documentation requiresa clear documented understanding and agreement of what is to be done within andbetween processes It is usually achieved through process design andmapping sessionsor review and validation sessions with the process teams Maintenance and changecontrol of this documentation is also a critical component For collaboration and teaming

IJOPM2412

1196

to occur individuals from the various functions involved in effective SCMmust work asa tightly integrated group with shared authority to make decisions and take actionsA collaborative team based SCM structure represents the span of involvementinfluence and authority in an SCM organization and enables multi-dimensionalcross-functional authority Early research suggests that there are different types ofcollaboration based upon the intensity of the information exchanges and the nature ofthe relationship These types are transactional cooperative (coordinative) andcollaborative (McCormack 2003) The formal creation of broad cross-functional jobswith real overall supply chain process authority and ownership is a key component ofprocess ownership Process measures are used to identify and assign responsibility forsupply chain process outcomes relating to such areas as efficiency cost and quality aswell as to provide a link to the firmrsquos reward system Process credibility refers to the levelof customer confidence in the output of the process and its use in making commitmentsFinally IT support refers to the process ownersrsquo and team membersrsquo perceivedusefulness of the IT system in support of SCM processes

The literature review discussions and interviews also resulted in the emergence ofseven key supply-chain management planning decision categories operations strategyplanning demand management production planning and scheduling procurementpromise delivery balancing change and distribution management Discussions thenproceeded on how these decision categories relate to the Supply-Chain OperationsReference (SCOR) Model This resulted in Figure 3 which maps the above-mentionedsupply-chain management planning decision categories to the SCOR Model Thismapping suggests that operations strategy planning and promise delivery decisionstend to be aligned with a firmrsquos internal SCOR decision areas while decisions onbalancing change tend to span internal and external SCOR decision areas across theentire supply chain Additionally procurement along with production planning andscheduling decisions tend to span across both internal and supplier SCOR decision

Figure 3Supply chain decision

categories mapped to theSCOR model

Supply chainperformance

1197

areas while demand and distribution management decisions span across both internaland customer decision areas

The planning activities illustrated in Level 2 of the Supply-Chain OperationsReference Model were used to specify the domain of supply-chain managementplanning practices for the study (PLAN SOURCE MAKE DELIVER) The expertsand practitioners used in developing and validating the constructs were selected fromthe Chesapeake Decision Sciences (now AspenTech) user group list This list spannedacross multiple industries and contained a high number of individuals with either aMasters or PhD degree in operations research For this study a practice is defined as amethod technique procedure or process

The supply chain performance construct is a self-assessed performance rating foreach of the SCOR decision areas The construct is based on perceived performance asdetermined by the survey respondents It is represented as a single item for eachdecision area (see Appendix 1 Questions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31(DELIVER)) The specific item statement on supply chain performance for each of theSCOR decision areas is ldquoOverall this decision process area performs very wellrdquo Theparticipants were asked to either agree or disagree with the item statement using afive-point Likert scale (1 frac14 strongly disagree 5 frac14 strongly agree)

Research questionsThe following research questions were developed to operationalize theabove-mentioned constructs

RQ1 What are the most important supply-chain management planning practices inthe PLAN decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ2 What are the most important supply-chain management planning practices inthe SOURCE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ3 What are the most important supply-chain management planning practices inthe MAKE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ4 What are the most important supply-chain management planning practices inthe DELIVER decision area of SCOR Model Version 40 that relate toperceived supply chain performance

Research methodologyThe research approach for this study follows the process of investigation andmeasurement developed by Churchill (1979) A figure depicting the approach isprovided in Figure 4 The approach includes specifying the domain of the constructgenerating a sample of items which capture the domain as specified purifying themeasures through coefficient alpha or factor analysis assessing reliability with newdata assessing the construct validity and developing norms

Survey instrumentThe literature review along with discussions and interviews with supply chain expertsand practitioners was also used as the basis for developing survey questions

IJOPM2412

1198

representing the nine key supply chain planning practices identified in the ldquoConstructdevelopmentrdquo section The discussions were structured around SCOR Model Version40 A survey instrument was developed using a 5-item Likert scale measuring thefrequency of the practices consisting of 1 ndash never or does not exist 2 ndash sometimes 3 ndashfrequently 4 ndash mostly and 5 ndash always or definitely exists The survey askedrespondents to provide their opinion concerning ldquowhat is done how often who does itand how it is donerdquo in their supply chain The initial survey was tested within a majorelectronic equipment manufacturer and with several supply chain experts Based uponthese tests improvements in wording and format were made to the instrument andseveral items were eliminated

The Supply Chain Council board of directors also reviewed the survey instrumentBased upon this review the survey was slightly reorganized to better match the SCORmodel The survey questions grouped by SCOR decision area are provided inAppendix A The questions focus on decision making in the seven key supply-chainmanagement planning decision categories (operations strategy planning demandmanagement production planning and scheduling procurement promise deliverybalancing change and distribution management) for each of the four SCOR decision

Figure 4Churchill research

methodology

Supply chainperformance

1199

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

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to occur individuals from the various functions involved in effective SCMmust work asa tightly integrated group with shared authority to make decisions and take actionsA collaborative team based SCM structure represents the span of involvementinfluence and authority in an SCM organization and enables multi-dimensionalcross-functional authority Early research suggests that there are different types ofcollaboration based upon the intensity of the information exchanges and the nature ofthe relationship These types are transactional cooperative (coordinative) andcollaborative (McCormack 2003) The formal creation of broad cross-functional jobswith real overall supply chain process authority and ownership is a key component ofprocess ownership Process measures are used to identify and assign responsibility forsupply chain process outcomes relating to such areas as efficiency cost and quality aswell as to provide a link to the firmrsquos reward system Process credibility refers to the levelof customer confidence in the output of the process and its use in making commitmentsFinally IT support refers to the process ownersrsquo and team membersrsquo perceivedusefulness of the IT system in support of SCM processes

The literature review discussions and interviews also resulted in the emergence ofseven key supply-chain management planning decision categories operations strategyplanning demand management production planning and scheduling procurementpromise delivery balancing change and distribution management Discussions thenproceeded on how these decision categories relate to the Supply-Chain OperationsReference (SCOR) Model This resulted in Figure 3 which maps the above-mentionedsupply-chain management planning decision categories to the SCOR Model Thismapping suggests that operations strategy planning and promise delivery decisionstend to be aligned with a firmrsquos internal SCOR decision areas while decisions onbalancing change tend to span internal and external SCOR decision areas across theentire supply chain Additionally procurement along with production planning andscheduling decisions tend to span across both internal and supplier SCOR decision

Figure 3Supply chain decision

categories mapped to theSCOR model

Supply chainperformance

1197

areas while demand and distribution management decisions span across both internaland customer decision areas

The planning activities illustrated in Level 2 of the Supply-Chain OperationsReference Model were used to specify the domain of supply-chain managementplanning practices for the study (PLAN SOURCE MAKE DELIVER) The expertsand practitioners used in developing and validating the constructs were selected fromthe Chesapeake Decision Sciences (now AspenTech) user group list This list spannedacross multiple industries and contained a high number of individuals with either aMasters or PhD degree in operations research For this study a practice is defined as amethod technique procedure or process

The supply chain performance construct is a self-assessed performance rating foreach of the SCOR decision areas The construct is based on perceived performance asdetermined by the survey respondents It is represented as a single item for eachdecision area (see Appendix 1 Questions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31(DELIVER)) The specific item statement on supply chain performance for each of theSCOR decision areas is ldquoOverall this decision process area performs very wellrdquo Theparticipants were asked to either agree or disagree with the item statement using afive-point Likert scale (1 frac14 strongly disagree 5 frac14 strongly agree)

Research questionsThe following research questions were developed to operationalize theabove-mentioned constructs

RQ1 What are the most important supply-chain management planning practices inthe PLAN decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ2 What are the most important supply-chain management planning practices inthe SOURCE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ3 What are the most important supply-chain management planning practices inthe MAKE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ4 What are the most important supply-chain management planning practices inthe DELIVER decision area of SCOR Model Version 40 that relate toperceived supply chain performance

Research methodologyThe research approach for this study follows the process of investigation andmeasurement developed by Churchill (1979) A figure depicting the approach isprovided in Figure 4 The approach includes specifying the domain of the constructgenerating a sample of items which capture the domain as specified purifying themeasures through coefficient alpha or factor analysis assessing reliability with newdata assessing the construct validity and developing norms

Survey instrumentThe literature review along with discussions and interviews with supply chain expertsand practitioners was also used as the basis for developing survey questions

IJOPM2412

1198

representing the nine key supply chain planning practices identified in the ldquoConstructdevelopmentrdquo section The discussions were structured around SCOR Model Version40 A survey instrument was developed using a 5-item Likert scale measuring thefrequency of the practices consisting of 1 ndash never or does not exist 2 ndash sometimes 3 ndashfrequently 4 ndash mostly and 5 ndash always or definitely exists The survey askedrespondents to provide their opinion concerning ldquowhat is done how often who does itand how it is donerdquo in their supply chain The initial survey was tested within a majorelectronic equipment manufacturer and with several supply chain experts Based uponthese tests improvements in wording and format were made to the instrument andseveral items were eliminated

The Supply Chain Council board of directors also reviewed the survey instrumentBased upon this review the survey was slightly reorganized to better match the SCORmodel The survey questions grouped by SCOR decision area are provided inAppendix A The questions focus on decision making in the seven key supply-chainmanagement planning decision categories (operations strategy planning demandmanagement production planning and scheduling procurement promise deliverybalancing change and distribution management) for each of the four SCOR decision

Figure 4Churchill research

methodology

Supply chainperformance

1199

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

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areas while demand and distribution management decisions span across both internaland customer decision areas

The planning activities illustrated in Level 2 of the Supply-Chain OperationsReference Model were used to specify the domain of supply-chain managementplanning practices for the study (PLAN SOURCE MAKE DELIVER) The expertsand practitioners used in developing and validating the constructs were selected fromthe Chesapeake Decision Sciences (now AspenTech) user group list This list spannedacross multiple industries and contained a high number of individuals with either aMasters or PhD degree in operations research For this study a practice is defined as amethod technique procedure or process

The supply chain performance construct is a self-assessed performance rating foreach of the SCOR decision areas The construct is based on perceived performance asdetermined by the survey respondents It is represented as a single item for eachdecision area (see Appendix 1 Questions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31(DELIVER)) The specific item statement on supply chain performance for each of theSCOR decision areas is ldquoOverall this decision process area performs very wellrdquo Theparticipants were asked to either agree or disagree with the item statement using afive-point Likert scale (1 frac14 strongly disagree 5 frac14 strongly agree)

Research questionsThe following research questions were developed to operationalize theabove-mentioned constructs

RQ1 What are the most important supply-chain management planning practices inthe PLAN decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ2 What are the most important supply-chain management planning practices inthe SOURCE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ3 What are the most important supply-chain management planning practices inthe MAKE decision area of SCOR Model Version 40 that relate to perceivedsupply chain performance

RQ4 What are the most important supply-chain management planning practices inthe DELIVER decision area of SCOR Model Version 40 that relate toperceived supply chain performance

Research methodologyThe research approach for this study follows the process of investigation andmeasurement developed by Churchill (1979) A figure depicting the approach isprovided in Figure 4 The approach includes specifying the domain of the constructgenerating a sample of items which capture the domain as specified purifying themeasures through coefficient alpha or factor analysis assessing reliability with newdata assessing the construct validity and developing norms

Survey instrumentThe literature review along with discussions and interviews with supply chain expertsand practitioners was also used as the basis for developing survey questions

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representing the nine key supply chain planning practices identified in the ldquoConstructdevelopmentrdquo section The discussions were structured around SCOR Model Version40 A survey instrument was developed using a 5-item Likert scale measuring thefrequency of the practices consisting of 1 ndash never or does not exist 2 ndash sometimes 3 ndashfrequently 4 ndash mostly and 5 ndash always or definitely exists The survey askedrespondents to provide their opinion concerning ldquowhat is done how often who does itand how it is donerdquo in their supply chain The initial survey was tested within a majorelectronic equipment manufacturer and with several supply chain experts Based uponthese tests improvements in wording and format were made to the instrument andseveral items were eliminated

The Supply Chain Council board of directors also reviewed the survey instrumentBased upon this review the survey was slightly reorganized to better match the SCORmodel The survey questions grouped by SCOR decision area are provided inAppendix A The questions focus on decision making in the seven key supply-chainmanagement planning decision categories (operations strategy planning demandmanagement production planning and scheduling procurement promise deliverybalancing change and distribution management) for each of the four SCOR decision

Figure 4Churchill research

methodology

Supply chainperformance

1199

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

representing the nine key supply chain planning practices identified in the ldquoConstructdevelopmentrdquo section The discussions were structured around SCOR Model Version40 A survey instrument was developed using a 5-item Likert scale measuring thefrequency of the practices consisting of 1 ndash never or does not exist 2 ndash sometimes 3 ndashfrequently 4 ndash mostly and 5 ndash always or definitely exists The survey askedrespondents to provide their opinion concerning ldquowhat is done how often who does itand how it is donerdquo in their supply chain The initial survey was tested within a majorelectronic equipment manufacturer and with several supply chain experts Based uponthese tests improvements in wording and format were made to the instrument andseveral items were eliminated

The Supply Chain Council board of directors also reviewed the survey instrumentBased upon this review the survey was slightly reorganized to better match the SCORmodel The survey questions grouped by SCOR decision area are provided inAppendix A The questions focus on decision making in the seven key supply-chainmanagement planning decision categories (operations strategy planning demandmanagement production planning and scheduling procurement promise deliverybalancing change and distribution management) for each of the four SCOR decision

Figure 4Churchill research

methodology

Supply chainperformance

1199

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

areas We were unable to build a consensus for questions relating process credibility tothe SOURCE decision area of SCOR Model Therefore the survey instrument does notcontain any items corresponding to this area

SampleThe study participants were selected from the membership list of the Supply ChainCouncil The ldquouserrdquo or practitioner portion of the list was used as the final selectionsince this represented members whose firms supplied a product rather than a serviceand were thought to be generally representative of supply chain practitioners ratherthan consultants This list consisted of 523 individuals and 90 firms A sample profileis provided in Table I The sample represents 11 distinct industry typesApproximately 29 percent of the respondents were classified as ldquoOtherrdquo in relationto industry type A profile of the respondents by position and by function is providedin Tables II and III respectively Table II reveals that 38 percent of the respondentsclassified themselves as being either senior leaders or executives while 20 percentconsidered themselves to be senior managers Thirty-four percent of the respondentswere classified as managers while the remaining 8 percent were classified asindividual contributors Table III reveals that approximately 18 percent of therespondents work in the purchasing function while approximately 16 percent work inplanning and scheduling Approximately 43 percent of the respondents work infunctions other than the nine categorized in the survey instrument (sales informationsystems planning and scheduling marketing manufacturing engineering financedistribution and purchasing) Upon investigation this category represented the new

Respondent position Number of responses Response percentages

Senior leadershipexecutive 19 380Senior manager 10 200Manager 17 340Individual contributor 4 80Total 50 100

Table IIRespondent profile byposition

Industry description Number of responses Response percentages

Electronics 6 109Transportation 2 36Industrial products 2 36Food amp BeverageCPG 8 145Aerospace amp Defense 2 36Chemicals 4 73Apparel 1 18Utilities 10 182PharmaceuticalsMedical 3 55Mills 0 00Semiconductors 1 18Other 16 291Total 55 100

Table ISample profile

IJOPM2412

1200

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

supply chain oriented jobs such as ldquoGlobal Supply Chain Managerrdquo or ldquoSupply ChainTeam Memberrdquo The remaining respondents work in manufacturing (approximately8 percent) distribution (approximately 8 percent) information systems (approximately6 percent) and sales (approximately 2 percent)

Data collectionThe survey instrument was distributed by mail with a cover letter explaining itspurpose and sponsorship by the Supply Chain Council The recipients were asked tocomplete the survey within two weeks and either fax or mail the completed form to adesignated address Recipients were also encouraged to distribute the survey to otherpractitioners within their firm Of the 523 surveys distributed 28 were returned dueinaccurate addresses Fifty-five usable surveys were returned for a response rate of 105percent Upon investigation this low response rate was due to the length of the surveyand its timing It was distributed during August a traditional vacation time in most ofthe USA and Europe When questioned by phone many people stated that they were onvacation during the survey period or did not have time to complete the survey since theywere preparing for vacation An analysis of non-response biaswasmade to determine itsimpact on the data The sample was divided into quartiles based upon the time ofsubmission and means were examined No significant differences were identified Thesample was also examined for any role position or functional bias As can be seen fromTables I II and III the sample appears to represent a cross-section of roles positions andfunctions and is not heavily weighted toward a few segments From this examination itwas concluded that no bias was present The number of returned surveys (55) also metthe minimum number needed for factor analysis (Hair et al 1992 p 239)

AnalysisFactor analysis is used to examine the underlying patterns or relationships for a largenumber of variables and to determine whether or not the information can be condensedor summarized in a smaller set of factors or components (Hair et al 1992) The purpose offactor analysis in this studywas to find away to condense the variables used to describethe constructs into a smaller set of new composite dimensions or factorswith aminimumloss of information This smaller set of factors was then used in regression analysis totest the hypothesized relationships The sample size was over 50 which is the minimum

Respondent function Number of responses Response percentages

Sales 1 20Information systems 3 59Planning and scheduling 8 157Marketing 0 00Manufacturing 4 78Engineering 0 00Finance 0 00Distribution 4 78Purchasing 9 177Other 22 431Total 51 100

Table IIIRespondent profile by

function

Supply chainperformance

1201

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

IJOPM2412

1202

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

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distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

criterion for the use of factor analysis and the item significance level for this size ofsample was set at a loading of 04 using published guidelines (Hair et al 1992 p 239)

An exploratory component factor analysis using maximum-likelihood extractionand oblique (varimax) rotation was performed on the data to examine the dimensionsunderlying the construct This analysis was used to examine whether the number ofdimensions conceptualized could be verified empirically The initial analysis used afive-factor strategy for each of the SCOR areas of Plan Source Make and DeliverAdjustments were made to the measurement model as suggested by this analysis untila final factor matrix emerged for each area

Coefficient alpha measures the internal consistency of a set of items and were partlyused to assess the quality of the instrument A low coefficient alpha indicates that thesample of items performs poorly in capturing the construct and a large alpha indicatesthat the test correlates well with true scores A minimum acceptable criterion of 07 wasused for this analysis (Churchill 1979)

Plan analysisFactor analysis on variables relating to the PLAN decision area (see Table IV) resultedin loadings for the following factors demand management process supply chaincollaborative planning and operations strategy planning team The demandmanagement process factor had nine items representing critical elements of ademand management process These are items such as process documentation

FactorCoefficient

alpha Scale itemsFactorloadings

Demand planningprocess

094 P18 ndash Documented forecastingprocess

086

P19 ndash Use historical data in forecast 084P20 ndash Use mathematical methods 087P21 ndash Process occurs on scheduled basis 091P22 ndash Forecast for each product 076P24 ndash Owner for DM process 071P27 ndash Forecast is credible 082P28 ndash Used to make planscommitments 084P29 ndash Forecast accuracy measured 074

SC collaborative planning 087 P6 ndash Defined customer priorities 070

P7 ndash Defined product priorities 069P13 ndash Team examines customer profitability 056P14 ndash Team examines product profitability 070P15 ndash Participates in customersupplier

relationships 076P17 - Analyze product demand variability 062P25 ndash DM uses customer information 051P9 ndash Supply Chain performance measures 060

Operations strategyplanning team

090 P1 ndash Operations strategy planning teamestablished

077

P2 ndash Team has formal meetings 095P3 ndash Major functions represented on team 082P4 ndash Team process documented 080P5 ndash Owner for process 061

Table IVFactor analysis ndashPLAN decision area

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ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

ownership credibility and key practices (mathematical models use of historical dataetc) The supply chain collaborative planning factor had eight items representing thefollowing specific collaborative planning process elements supply chain planningteam participation in customer and supplier relationships understanding and use ofcustomer demand information and the understanding and use of customer prioritiesbalance with company priorities The operations strategy planning team factor hadfive items representing teaming elements such as the designation of a planning teamwith cross functional members conducting formal meetings a documented process forthe team and an owner for the supply chain planning process Coefficient alphas weregenerated on all factors yielding a value of 094 for demand management process 087for supply chain collaborative planning and 090 for operations strategy planningteam These were all deemed acceptable using the criteria of 07

Source analysisAn analysis of variables relating to the SOURCE decision area (see Table V) resulted inloadings for the following factors source planning process procurement planningprocess team supplier transactional collaboration supplier operational collaborationand supplier strategic collaboration Source planning process had four itemsrepresenting elements of the planning process such as process documentationunderstanding of supplier inter-relationships a process owner and informationsupport Procurement planning process team had three items representing teamingelements such as the designation of a procurement planning team with crossfunctional members conducting formal meetings and an owner for the procurementplanning process Supplier collaboration had three factors that represent the varioustypes of collaboration transactional operational and strategic Supplier transactionalcollaboration had two items representing the sharing of planning and schedulinginformation with suppliers and the measurement and feedback of supplier

FactorCoefficient

alpha Scale itemsFactorloadings

Source planning process 086 S1 ndash Procurement process documented 060S2 ndash IT supports process 082S3 ndash Supplier inter-relationshipsunderstooddocumented

067

S4 ndash Process owner identified 064Procurement planningprocess team

089 S12 ndash Procurement process teamdesignated

091

S13 ndash Team meets on regular basis 089S14 ndash Other functions work closely withteam

058

Supplier transactionalcollaboration

078 S8 ndash Share plan schedule withsuppliers

058

S11 ndash Measure and feedback supplierperformance

072

Supplier operationalcollaboration

ndash S10 ndash Collaborate with suppliers to developsource plan

075

Supplier strategiccollaboration

ndash S5 ndash Have strategic suppliers for allproductsservices

070

Table VFactor analysis ndash

SOURCE decision area

Supply chainperformance

1203

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

performance Supplier operational collaboration had one item representingcollaborative planning with suppliers Supplier strategic collaboration had one itemrepresenting the designation of strategic suppliers for all products and servicesCoefficient alphas for the factors were 086 for source planning process 089 forprocurement planning process team and 078 for supplier transactional collaborationSupplier operational collaboration and supplier strategic collaboration were bothsingle item measures making coefficient alphas non-applicable The values were alldeemed acceptable using the criteria of 07

Make analysisFactor analysis on variables relating to the MAKE decision area (see Table VI) resultedin loadings for the following factors make planning process make scheduling processand make collaborative planning Make planning process had six items representingprocess ownership process integration formal planning cycles cross-functionalrepresentation process credibility and measurement Make scheduling process hadthree items representing process integration constraint based methods andinformation system support Make collaboration had three items representing theinclusion of supplier lead times the inclusion of customer planning and schedulinginformation and change control Coefficient alphas for the factors were 084 for makeplanning process 077 for make scheduling process was 077 and 070 for makecollaborative planning These were all deemed acceptable using the criteria of 07

Deliver analysisAn analysis of variables relating to the DELIVER decision area (see Table VII) resultedin loadings for the following factors deliver planning process deliver processcredibility IT support and ownership deliver process measures and deliver processintegration Deliver planning process had seven items representing processdocumentation process ownership measurements cross-functional participation andspecific order management practices Deliver process credibility had three itemsrepresenting customer satisfaction with delivery performance process credibility

FactorCoefficient

alpha Scale itemsFactorloadings

Make planning process 084 M2 ndash Integratedcoordinated acrossdivisions

065

M3 ndash Process owner designated 076M4 ndash Weekly planning cycles 066M10 ndash Measure adherence to plan 045M11ndash Adequately address needs of business 054M12 ndash SalesMfgDistribution collaborate inprocess 056

Make Scheduling Process 077 M7 ndash Using constraint-based planningmethods

051

M8 ndash Shop Floor scheduling integrated 096M9 - IT supports process 067

Make Collaborative Planning 070 M6 ndash Supplier lead times updated monthly 042M13 ndashIntegrate customerrsquos planschedule 051M14 ndash Formal change process 095

Table VIFactor analysis ndash MAKEdecision area

IJOPM2412

1204

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

concerning delivery commitments and specific finished goods safety stock practicesIT support and ownership had three items representing IT support for the ordercommitment distribution management processes and distribution managementprocess ownership Deliver process measures had three factors representingunderstanding and documentation of DELIVER network interrelationships(variability and metrics) distribution management process measures and usingthese measures to recognize and reward participants Deliver process integration hadtwo items representing distribution network inventory measures and controls and theuse of automatic replenishment in the network Coefficient alphas for the factors were081 for deliver planning process 085 for deliver process credibility 076 for ITsupport and ownership 077 for deliver process measures and 071 for deliver processintegration These were all deemed acceptable using the criteria of 07

7 ResultsDescriptive statistics for the supply chain performance variable and SCOR variablesderived from factor analysis is provided in Appendix 2 Single variable linearregression analysis was used to test the hypothesized relationships between theidentified factors in each SCOR area and the self-assessed performance rating of eacharea The independent variables are a summation of the scale items within each factorextracted via factor analysis (see Tables IV-VII) The dependent variable in each case isa self-assessed performance rating for each of the SCOR decision areas It isrepresented as a single item for each decision area and reflects the survey respondentrsquosview of their performance in a particular SCOR decision area (see Appendix AQuestions 32 (PLAN) 15 (SOURCE) 16 (MAKE) and 31 (DELIVER)) The results of the

FactorCoefficient

alpha Scale itemsFactorloadings

Deliver planning process 081 D1 ndash Order commit process documented 079D2 ndash Promise delivery process owner 075D3 ndash Track on time customer orders 069D7 ndash Measure customer requests v actual 053D10 ndash Promise orders beyond inventory levels 053D11 ndash Capability to respond to unplanned

orders066

D13 ndash Salesmfgdistrplanning collaborate 045Deliver process credibility 085 D4 ndash Customers satisfied with deliver

performance090

D5 ndash Meet short term demands with inventory 067D9 ndash Delivery commit credible to customers 076

IT support and ownership 076 D14 ndash IT support of order commit process 054D18 ndash IT support distribution management 090D20 ndash Distribution management owner 070

Deliver process measures 077 D19 ndash Network inter-relationships understood 065D29 ndash Distribution management process

measures068

D30 ndash Measures used to recognizereward 073Deliver process integration 071 D27 ndash Inventory measures and controls 071

D28 ndash Use auto replenishment in distribution 069

Table VIIFactor analysis ndash

DELIVER decision area

Supply chainperformance

1205

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

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1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

regression analysis are illustrated in Table VIII Since each regression model containsonly one independent variable these models are equivalent to bivariate correlations

71 Regression resultsIn the PLAN decision area Table VIII shows that the demand planning processvariable has the strongest relationship to supply chain performance followed bysupply chain collaborative planning and operations strategy planning team Based onthe beta values demand-planning process is the most important PLAN variablerelative to supply chain performance followed by supply chain collaborative planningand operations strategy planning team Additionally the supplier transactionalcollaboration variable has the strongest relationship to supply chain performancefollowed by source planning process procurement planning process team supplieroperational collaboration and supplier strategic collaboration in the SOURCE decisionarea An examination of the beta values show that supplier transactional collaborationis the most important SOURCE variable relative to supply chain performance followedby source planning process procurement planning process team supplier operationalcollaboration and supplier strategic collaboration

In the MAKE decision area Table VIII reveals that the make planning processvariable has the strongest relationship to supply chain performance followed by makescheduling process and make collaborative planning Based on the beta values makeplanning process is the most important MAKE variable relative to supply chainperformance followed by make planning process and make scheduling processFinally the deliver process measures variable has the strongest relationship to supply

Beta values Significance level Adjusted R2

PLAN factorsDemand planning process 072 000 050SC collaborative planning 046 000 020Operations strategy planning team 043 000 017

SOURCE factorsSource planning process 066 000 043Procurement planning process team 065 000 041Supplier transactional collaboration 074 000 054Supplier operational collaboration 057 000 031Supplier strategic collaboration 047 000 020MAKE factorsMake planning process 071 000 050Make scheduling process 049 000 023Make collaborative planning 055 000 029

DELIVER factorsDeliver planning process 030 003 007Deliver process credibility 033 002 009IT support and ownership 055 000 029Deliver process measures 069 000 048Deliver process integration 049 000 022

Notes dependent variable frac14 supply chain performance independent variable frac14 SCOR decision areafactor

Table VIIISingle variable regressionanalysis

IJOPM2412

1206

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

chain performance followed by IT support and ownership deliver process integrationdeliver process credibility and deliver planning process in the DELIVER decision areaAn examination of the beta values show that deliver process measures is the mostimportant DELIVER variable relative to supply chain performance followed by ITsupport and ownership deliver process integration deliver process credibility anddeliver planning process

ConclusionsBased upon the aforementioned results conclusions regarding the impact of SCORplanning practices on supply chain performance for each SCOR planning decision areaare provided below Additionally generalized conclusions with respect to the impact ofthe nine identified key supply chain practices are offered and summarized in Table IX

PLAN conclusionsFor the PLAN decision area demand planning which includes forecast developmentactivities has a significant impact on supply chain performance This also includes themeasurement of forecast accuracy along with the establishment of a process owner forthe demand process Collaborative planning process activities were also found to havea significant impact on supply chain performance within this decision area Theseactivities include defining product and customer priorities establishing customer andsupplier relationships analyzing customer and demand variability informationreviewing product and customer profitability information and establishing supplychain performance metrics The creation of an operations strategy team was found tohave an impact on supply chain performance The team should be comprised ofrepresentatives from the major supply chain functions (ie sales marketingmanufacturing logistics etc) hold regular meetings and have a documentedoperations strategy process In addition an owner for the supply chain planningprocess is required to ensure its effectiveness

SOURCE conclusionsSupplier transactional collaboration activities have a significant impact on supply chainperformance within the SOURCE decision area These activities include the sharing ofplanning and scheduling information with suppliers The source planning processwhich includes the documentation of procurement processes the establishment ofinformation technology that supports theses processes and themanagement of supplierinter-relationships also has a significant impact on supply chain performance in this

PRACTICE PLAN SOURCE MAKE DELIVER

Planning processes X X X XCollaboration X X X IndirectTeaming X X ndash ndashProcess measures Indirect Indirect Indirect XProcess credibility ndash ndash ndash XProcess integration ndash ndash ndash XIT support ndash ndash ndash XProcess documentation Indirect Indirect Indirect IndirectProcess ownership Indirect Indirect Indirect Indirect

Table IXGeneral conclusions for

the nine key supply chainpractices

Supply chainperformance

1207

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

decision area Supplier inter-relationships included in the source planning processinclude the management of product and delivery variability along with metrics formonitoring such variability Additionally the designation of a source planning processowner is required to ensure its effectiveness The establishment of a procurementprocess planning teamwas found to have an impact on supply chain performancewithinthe SOURCE decision area This team should meet on a regular basis and work closelywith other functional areas such as manufacturing and sales Supplier operationalcollaboration also has a significant impact on supply chain performance in this decisionarea This involves the development of a joint operational plan that is supportive ofstrategic sourcing activities and outlines how routine transactional activities are to beconducted by the participants Supplier strategic collaboration activities also impactsupply chain performance in the Source decision area These activities include electronicordering and supplier-managed inventory In addition the presence of on-site employeesof key suppliers facilitates strategic supplier collaboration activities that enhanceoverall supply chain performance

MAKE conclusionsMAKE planning process activities have a significant impact on supply chainperformancewithin theMake decision area These activities include collaboration tasksamong the sales manufacturing and distribution organizations during the planningand scheduling process a joint assessment of the needs of the business among the salesmanufacturing and distribution organizations and the establishment of performancemetrics which facilitate the monitoring of ldquoadherence to schedulerdquo requirements Toensure its effectiveness the process must be integrated and coordinated acrossfunctional and organizational boundaries In addition weekly planning cycles arerequired to facilitate necessary changes to the plan based on relevant data andinformation Finally the establishment of a make planning process owner is required toensure the effectiveness of the process Make collaborative planning also has asignificant impact on supply chain performance in this decision area This involves theintegration of customer planning and scheduling information into the manufacturingplanning process the development of a formal document and collaborative approvalprocess for schedule changes and the periodic updating of supplier lead times based oncollaborative information Themake scheduling process also has a significant impact onsupply chain performance within the MAKE decision area Key elements of this processincludes the integration of shop floor scheduling with the overall scheduling processthe use of constraint-based planning methodologies (eg the use of advanced planningand scheduling software based on the Theory of Constraints) and the use of informationtechnology to support the make scheduling process (ie MRP and ERP systems)

DELIVER conclusionsFor the DELIVER decision area delivery process measures have a significant impacton supply chain performance These metrics should document supply chaininter-relationships in a manner that is understandable by the supply chain tradingpartners and be used to reward and recognize the process participants The degree towhich the information system supports the distribution management process was alsofound to impact supply chain performance within this decision area The systemrsquosspecific support of the order commitment process was found to be critical to effective

IJOPM2412

1208

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

distribution management A designated distribution management process owner isrequired to ensure the effective use of information technology in support of the process

Delivery process integration along with delivery process credibility were found tohave a significant impact on supply chain performance within the DELIVER decisionarea Key integration features include the establishment of inventory controlmechanisms and metrics for each node in the distribution network along with the useof automatic replenishment throughout the network Indicators of delivery processcredibility include the degree to which customers are satisfied with current on-timedelivery performance the ability to meet short-term customer demands and thecustomerrsquos confidence level in projected delivery commitments Delivery planningprocess activities were also found to have a significant impact on supply chainperformance within this decision area These activities include establishing ordercommitments based on a collaboration process among the sales manufacturing anddistribution organizations tracking the percentage of completed customer ordersdelivered on time and measuring variations between customer requests versus actualdelivery In addition the deliver planning process should monitor deliveryover-commitments and delivery flexibility A designated planning process owner isrequired to ensure its effectiveness

Generalized conclusions for the nine key supply chain practicesTable IX provides a summary of general conclusions regarding relationships betweenthe nine identified key supply chain planning practices based on a review of theliterature and discussions with supply chain experts and practitioners and the SCORModel areas included in the study (PLAN SOURCE MAKE DELIVER) A review ofthe table reveals that the planning process variables in all four SCOR Model areas havethe strongest relationship to supply chain performance Collaboration variables werefound to have a direct impact on SC performance in the PLAN SOURCE and MAKEareas of the SCOR Model Additionally collaboration was found to have an indirectimpact on supply chain performance in the DELIVER decision area The collaborationresults of the study are consistent with the findings of a study conducted by Stank et al(2001a) which found that collaboration improves supply chain service performance

The table also reveals that teaming variables were found to have a direct impact onsupply chain performance in the PLAN and SOURCE areas In addition a processmetrics variable was found to have a direct impact on supply chain performance in theDELIVER area of the SCOR Model However process metrics was found to only havean indirect impact on supply chain performance in the PLAN SOURCE and MAKEareas A process credibility process integration and information technology supportvariable was found to have a direct impact on supply chain performance in theDELIVER area The process integration results of the study are consistent with a studyconducted by Stank et al (2001b) that reveals a relationship between supply chainintegration and performance Process documentation was found to have only anindirect impact on supply chain performance in the four SCOR Model areas included inthe study Finally process ownership was found to have an indirect impact on supplychain performance in all four SCOR Model areas

ImplicationsThis study although preliminary and exploratory in nature provides a beginningframework for the comparison and discussion of supply chain planning practices that

Supply chainperformance

1209

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

relate to supply chainperformanceThe supply chainplanningpractices related to processintegration collaboration teaming process measurement process documentation andprocess ownership have been shown to be important to supply chain performancecurrently lack broad implementation by supply chain partners This suggests thatintegrated supply chain management may be more difficult to operationalize in practicethan the popular supply chain press or consultants would have one to believe

This study also suggests is that some of the best practices proposed as mechanismsfor improving overall supply chain management performance may not have the degreeof impact often presented in the literature The study shows that some best practiceshelp to improve supply chain performance only in specific decision areas Furtherresearch on this topic might indicate that some practices are industry orldquoconfigurationrdquo specific and do not provide the same results for every supply chain

The final implication of this study is that information technology solutions are onlypart of the answer to improved supply chain performance The study suggests thatintegration is an organization and people issue and that IT should serve as an enablerto organization and process change Thus firms who have purchased an informationtechnology solution and expect it to drive improvements in supply chain managementmay be disappointed with the final results due the limitations of ITrsquos impact on supplychain performance revealed in the study

LimitationsThis study provides an exploratory view of the relationship between supply chainmanagement planning practices and supply chain performance using a limited dataset Thus a major limitation of the study is that it is not possible to make crossindustry comparisons or to draw generalizable conclusions about this relationship forall supply chain populations based on the presented results The purpose of this studyis to provide some preliminary insights regarding supply chain management practicesand their impact on performance and to offer a research framework using the SCORmodel to facilitate future studies Finally this study has resulted in the development ofa valid assessment instrument that is capable of gathering relevant informationregarding the supply chain planning decision areas Thus future researchers canfurther assess the validity of the implications offered in the study

Future researchA future research opportunity lies in using the assessment instrument used in thisstudy to gather and develop cross industry best practice information to determine ifindustry type plays a significant role in the applicability of specific SCM planningpractices Another research opportunity resulting from this exploratory study is toexamine why there appears to be a gap between the recognition of a SCM planningpractice as important to supply chain performance and the implementation of thepractice Finally the role of supply chain structure on the degree to whichthese practices influence performance also warrants future research

References

Abell DF (1999) ldquoCompeting today while preparing for tomorrowrdquo Sloan Management ReviewVol 40 No 3 pp 73-81

IJOPM2412

1210

Ansari A Lockwood DL and Modarress B (1999) ldquoSupplier product integration a newcompetitive approachrdquo Production and Inventory Management Journal Vol 40 No 3pp 57-61

Boddy D Macbeth D and Wagner B (2000) ldquoImplementing collaboration betweenorganizations an empirical study of supply chain partneringrdquo The Journal ofManagement Studies Vol 37 No 7 pp 1003-17

Brewton T and Kingseed K (2001) ldquoGetting the most from your B2B-enabled supply chainrdquoThe Journal of Business Strategy Vol 22 No 1 pp 28-31

Cauthen R (1999) ldquoAPS technology powering supply chain managementrdquo Enterprise SystemsJournal Vol 14 No 9 pp 41-8

Chandrashekar A and Schary PB (1999) ldquoToward the virtual supply chain the convergence ofIT and organizationrdquo International Journal of Logistics Management Vol 10 No 2pp 27-39

Childerhouse P and Towill D (2000) ldquoEngineering supply chains to match customerrequirementsrdquo Logistics Information Management Vol 13 No 6 pp 337-45

Christopher M and Ryals L (1999) ldquoSupply chain strategy its impact on shareholder valuerdquoInternational Journal of Logistics Management Vol 10 No 1 pp 1-10

Churchill GA (1979) ldquoA paradigm for developing better measures of marketing constructsrdquoJournal of Marketing Vol 16 No 1 pp 64-73

Cooper MC Lambert DM and Pagh JD (1997) ldquoSupply chain management more than a newname for logisticsrdquo The International Journal of Logistics Management Vol 8 No 1pp 1-14

Cooper MC and Ellram LM (1993) ldquoCharacteristics of supply chain management and theimplications for purchasing and logistics strategyrdquo The International Journal of LogisticsManagement Vol 4 No 2 pp 13-24

Corbett CJ Blackburn JD and Van Wassenhove LN (1999) ldquoPartnerships to improve supplychainsrdquo Sloan Management Review Vol 40 No 4 pp 71-82

Cox A (1999) ldquoPower value and supply chain managementrdquo Supply Chain Management Vol 4No 4 pp 167-75

Cox A (2001a) ldquoThe power perspective in procurement and supply managementrdquo Journal ofSupply Chain Management Vol 37 No 2 pp 4-7

Cox A (2001b) ldquoUnderstanding buyer and supplier power a framework for procurement andsupply competencerdquo Journal of Supply Chain Management Vol 37 No 2 pp 8-15

Cox A (2001c) ldquoManaging with power strategies for improving value appropriation fromsupply relationshipsrdquo Journal of Supply Chain Management Vol 37 No 2 pp 42-7

Cox A Sanderson J and Watson G (2001) ldquoSupply chains and power regimes toward ananalytic framework for managing extended networks of buyer and supplier relationshipsrdquoJournal of Supply Chain Management Vol 37 No 2 pp 28-35

Cross GJ (2000) ldquoHow e-business is transforming supply chain managementrdquo The Journal ofBusiness Strategy Vol 21 No 2 pp 36-9

DrsquoAmours S Montreuil B Lefrancois P and Soumis F (1999) ldquoNetworked manufacturing theimpact of information sharingrdquo International Journal of Production Economics Vol 58No 1 pp 63-79

Deeter-Schmelz DR Bizzari A Graham R and Howdyshell C (2001) ldquoBusiness-to-businessonline purchasing suppliersrsquo impact on buyersrsquo adoption and usage intentrdquo Journal ofSupply Chain Management Vol 31 No 1 pp 4-10

Supply chainperformance

1211

Ellinger AE (2000) ldquoImproving marketinglogistics cross-functional collaborations in thesupply chainrdquo Industrial Marketing Management Vol 29 No 1 pp 85-96

Ferguson BR (2000) ldquoImplementing supply chain managementrdquo Production and InventoryManagement Journal Vol 2 No 2 pp 64-7

Frohlich MT and Westbrook R (2001) ldquoArcs of integration an international study of supplychain strategiesrdquo Journal of Operations Management Vol 19 No 2 pp 185-200

Fine CH (2000) ldquoClockspeed-based strategies for supply chain designrdquo Production andOperations Management Vol 9 No 3 pp 213-21

Hair JF Anderson RE Tatham RL and Black WC (1992) Multivariate Data AnalysisMacmillan New York NY

Harland CM Lamming RC Zheng J and Johnsen TE (2001) ldquoA taxonomy of supplynetworksrdquo Journal of Supply Chain Management Vol 37 No 4 pp 20-7

Hauguel P and Jackson N (2001) ldquoOutward-looking supply-chain strategyrdquo European BusinessJournal Vol 13 No 3 pp 113-8

Heriot KC and Kulkarni SP (2001) ldquoThe use of intermediate sourcing strategiesrdquo Journal ofSupply Chain Management Vol 37 No 1 pp 18-26

Hicks C McGovern T and Earl CF (2000) ldquoSupply chain management a strategic issue inengineer to order manufacturingrdquo International Journal of Production Economics Vol 65No 2 pp 179-90

Humphreys PK Lai MK and Sculli D (2001) ldquoAn inter-organizational information system forsupply chain managementrdquo International Journal of Production Economics Vol 70 No 3pp 245-55

Johnson ME and Anderson E (2000) ldquoPostponement strategies for channel derivativesrdquoInternational Journal of Logistics Management Vol 11 No 1 pp 19-35

Kaufman A Wood CH and Theyel G (2000) ldquoCollaboration and technology linkages astrategic supplier typologyrdquo Strategic Management Journal Vol 21 No 6 pp 649-63

Kim B (2000) ldquoCoordinating an innovation in supply chain managementrdquo European Journal ofOperational Research Vol 123 No 3 pp 568-84

Korpela J Lehmusvaara A and Tuominen M (2001a) ldquoCustomer service based design of thesupply chainrdquo International Journal of Production Economics Vol 69 No 2 pp 193-204

Korpela J Lehmusvaara A and Tuominen M (2001b) ldquoAn analytic approach to supply chaindevelopmentrdquo International Journal of Production Economics Vol 71 Nos 1-3 pp 145-55

Lambert DM and Cooper MC (2000) ldquoIssues in supply chain managementrdquo IndustrialMarketing Management Vol 29 No 1 pp 65-83

Lamming RC Caldwell ND Harrison DA and Phillips W (2001) ldquoTransparency in supplyrelationships concept and practicerdquo Journal of Supply Chain Management Vol 37 No 4pp 4-10

McCormack K (2003) ldquoB2B collaboration what is itrdquo Supply Chain Practice Vol 5 No 1pp 18-28

McCutcheon D and Stuart FI (2000) ldquoIssues in the choice of supplier alliance partnersrdquo Journalof Operations Management Vol 18 No 3 pp 279-301

Maloni M and Benton WC (2000) ldquoPower influences in the supply chainrdquo Journal of BusinessLogistics Vol 21 No 1 pp 49-74

Manetti J (2001) ldquoHow technology is transforming manufacturingrdquo Production and InventoryManagement Journal Vol 42 No 1 pp 54-64

IJOPM2412

1212

Narasimhan R and Das A (1999) ldquoManufacturing agility and supply chain managementpracticesrdquo Production and Inventory Management Journal Vol 40 No 1 pp 4-10

Narasimhan R and Kim SW (2001) ldquoInformation system utilization strategy for supply chainintegrationrdquo Journal of Business Logistics Vol 22 No 2 pp 51-76

Peck H and Juttner U (2000) ldquoStrategy and relationships defining the interface in supply chaincontextsrdquo International Journal of Logistics Management Vol 11 No 2 pp 33-44

Raghunathan S (1999) ldquoInterorganizational collaborative forecasting and replenishmentsystems and supply chain implicationsrdquo Decision Sciences Vol 30 No 4 pp 1053-71

Ramsay J (2001) ldquoThe resource based perspective rents and purchasingrsquos contribution tosustainable competitive advantagerdquo Journal of Supply Chain Management Vol 37 No 3pp 38-47

Reutterer T and Kotzab HW (2000) ldquoThe use of conjoint-analysis for measuring preferences insupply chain designrdquo Industrial Marketing Management Vol 29 No 1 pp 27-35

Rutner SM Gibson BJ and Gustin CM (2001) ldquoLongitudinal study of supply chaininformation systemsrdquo Production and Inventory Management Journal Vol 42 No 2pp 49-56

Stank T Keller S and Daugherty P (2001a) ldquoSupply chain collaboration and logistical serviceperformancerdquo Journal of Business Logistics Vol 22 No 1 pp 29-48

Stank T Keller S and Closs D (2001b) ldquoPerformance benefits of supply chain logisticalintegrationrdquo Transportation Journal Vol 41 No 23 pp 32-46

Stewart G (1997) ldquoSupply-chain operations reference model (SCOR) the first cross-industryframework for integrated supply-chain managementrdquo Logistics Information ManagementVol 10 No 2 pp 62-7

Stock G Greis NP and Kasarda JD (2000) ldquoEnterprise logistics and supply chain structurethe role of fitrdquo Journal of Operations Management Vol 18 No 5 pp 531-47

Tamas M (2000) ldquoMismatched strategies the weak link in the supply chainrdquo Supply ChainManagement Vol 5 No 4 pp 171-5

Vickery S Calantone R and Droge C (1999) ldquoSupply chain flexibility an empirical studyrdquoJournal of Supply Chain Management Vol 35 No 3 pp 16-24

Viswanathan S and Piplani R (2001) ldquoCoordinating supply chain inventories through commonreplenishment epochsrdquo European Journal of Operational Research Vol 129 No 2pp 277-86

Waller MA Dabholkar PA and Gentry JJ (2000) ldquoPostponement product customization andmarket-oriented supply chain managementrdquo Journal of Business Logistics Vol 21 No 2pp 133-60

Watson G (2001) ldquoSubregimes of power and integrated supply chain managementrdquo Journal ofSupply Chain Management Vol 37 No 2 pp 36-41

Whipple JM and Frankel R (2000) ldquoStrategic alliance success factorsrdquo Journal of Supply ChainManagement Vol 36 No 3 pp 21-8

Wong A (1999) ldquoPartnering through cooperative goals in supply chain relationshipsrdquo TotalQuality Management Vol 10 No 45 pp 786-92

Further reading

Helms MM Ettkin LP and Chapman S (2000) ldquoSupply chain forecasting ndash collaborativeforecasting supports supply chain managementrdquo Business Process Management JournalVol 6 No 5 pp 392-407

Supply chainperformance

1213

Appendix 1 Survey questions with individual correlations

Figure A1

IJOPM2412

1214

Figure A2

Figure A3

Supply chainperformance

1215

Figure A4

IJOPM2412

1216

Appendix 2 Descriptive statistics for factor scale items

SOURCE factors Mean Std dev

S1 351 121S2 333 117S3 300 118S4 370 122S12 335 139S13 315 133S14 298 120S8 285 117S11 321 115S10 260 108S5 354 099

Table AIISOURCE

PLAN factors Mean Std dev

P18 296 140P19 346 134P20 317 144P21 357 143P22 352 138P24 328 155P27 265 119P28 340 122P29 294 147P6 313 116P7 307 121P13 200 107P14 268 124P15 272 124P17 287 125P25 281 119P9 307 137P1 339 138P2 315 136P3 309 148P4 252 141P5 335 149

Table AIPLAN

Supply chainperformance

1217

DELIVER factors Mean Std dev

D1 346 140D2 322 140D3 387 137D7 320 150D10 300 127D11 332 128D13 270 122D4 362 088D5 335 120D9 347 108D14 318 111D18 287 113D20 324 127D19 251 101D29 280 112D30 222 111D27 243 122D28 268 136

Table AIIIDELIVER

Supply chain performance factors Mean Std dev

P32 267 112S15 307 110M16 281 089D31 283 102Table AV

MAKE factors Mean Std dev

M2 261 116M3 341 118M4 320 138M10 286 126M11 277 111M12 280 117M7 255 128M8 285 134M9 296 102M6 224 114M13 212 101M14 242 124

Table AIVMAKE

IJOPM2412

1218

Figure A2

Figure A3

Supply chainperformance

1215

Figure A4

IJOPM2412

1216

Appendix 2 Descriptive statistics for factor scale items

SOURCE factors Mean Std dev

S1 351 121S2 333 117S3 300 118S4 370 122S12 335 139S13 315 133S14 298 120S8 285 117S11 321 115S10 260 108S5 354 099

Table AIISOURCE

PLAN factors Mean Std dev

P18 296 140P19 346 134P20 317 144P21 357 143P22 352 138P24 328 155P27 265 119P28 340 122P29 294 147P6 313 116P7 307 121P13 200 107P14 268 124P15 272 124P17 287 125P25 281 119P9 307 137P1 339 138P2 315 136P3 309 148P4 252 141P5 335 149

Table AIPLAN

Supply chainperformance

1217

DELIVER factors Mean Std dev

D1 346 140D2 322 140D3 387 137D7 320 150D10 300 127D11 332 128D13 270 122D4 362 088D5 335 120D9 347 108D14 318 111D18 287 113D20 324 127D19 251 101D29 280 112D30 222 111D27 243 122D28 268 136

Table AIIIDELIVER

Supply chain performance factors Mean Std dev

P32 267 112S15 307 110M16 281 089D31 283 102Table AV

MAKE factors Mean Std dev

M2 261 116M3 341 118M4 320 138M10 286 126M11 277 111M12 280 117M7 255 128M8 285 134M9 296 102M6 224 114M13 212 101M14 242 124

Table AIVMAKE

IJOPM2412

1218

Figure A4

IJOPM2412

1216

Appendix 2 Descriptive statistics for factor scale items

SOURCE factors Mean Std dev

S1 351 121S2 333 117S3 300 118S4 370 122S12 335 139S13 315 133S14 298 120S8 285 117S11 321 115S10 260 108S5 354 099

Table AIISOURCE

PLAN factors Mean Std dev

P18 296 140P19 346 134P20 317 144P21 357 143P22 352 138P24 328 155P27 265 119P28 340 122P29 294 147P6 313 116P7 307 121P13 200 107P14 268 124P15 272 124P17 287 125P25 281 119P9 307 137P1 339 138P2 315 136P3 309 148P4 252 141P5 335 149

Table AIPLAN

Supply chainperformance

1217

DELIVER factors Mean Std dev

D1 346 140D2 322 140D3 387 137D7 320 150D10 300 127D11 332 128D13 270 122D4 362 088D5 335 120D9 347 108D14 318 111D18 287 113D20 324 127D19 251 101D29 280 112D30 222 111D27 243 122D28 268 136

Table AIIIDELIVER

Supply chain performance factors Mean Std dev

P32 267 112S15 307 110M16 281 089D31 283 102Table AV

MAKE factors Mean Std dev

M2 261 116M3 341 118M4 320 138M10 286 126M11 277 111M12 280 117M7 255 128M8 285 134M9 296 102M6 224 114M13 212 101M14 242 124

Table AIVMAKE

IJOPM2412

1218

Appendix 2 Descriptive statistics for factor scale items

SOURCE factors Mean Std dev

S1 351 121S2 333 117S3 300 118S4 370 122S12 335 139S13 315 133S14 298 120S8 285 117S11 321 115S10 260 108S5 354 099

Table AIISOURCE

PLAN factors Mean Std dev

P18 296 140P19 346 134P20 317 144P21 357 143P22 352 138P24 328 155P27 265 119P28 340 122P29 294 147P6 313 116P7 307 121P13 200 107P14 268 124P15 272 124P17 287 125P25 281 119P9 307 137P1 339 138P2 315 136P3 309 148P4 252 141P5 335 149

Table AIPLAN

Supply chainperformance

1217

DELIVER factors Mean Std dev

D1 346 140D2 322 140D3 387 137D7 320 150D10 300 127D11 332 128D13 270 122D4 362 088D5 335 120D9 347 108D14 318 111D18 287 113D20 324 127D19 251 101D29 280 112D30 222 111D27 243 122D28 268 136

Table AIIIDELIVER

Supply chain performance factors Mean Std dev

P32 267 112S15 307 110M16 281 089D31 283 102Table AV

MAKE factors Mean Std dev

M2 261 116M3 341 118M4 320 138M10 286 126M11 277 111M12 280 117M7 255 128M8 285 134M9 296 102M6 224 114M13 212 101M14 242 124

Table AIVMAKE

IJOPM2412

1218

DELIVER factors Mean Std dev

D1 346 140D2 322 140D3 387 137D7 320 150D10 300 127D11 332 128D13 270 122D4 362 088D5 335 120D9 347 108D14 318 111D18 287 113D20 324 127D19 251 101D29 280 112D30 222 111D27 243 122D28 268 136

Table AIIIDELIVER

Supply chain performance factors Mean Std dev

P32 267 112S15 307 110M16 281 089D31 283 102Table AV

MAKE factors Mean Std dev

M2 261 116M3 341 118M4 320 138M10 286 126M11 277 111M12 280 117M7 255 128M8 285 134M9 296 102M6 224 114M13 212 101M14 242 124

Table AIVMAKE

IJOPM2412

1218