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Journal of Operations Management 20 (2002) 675–689

Analysis and design of focused demand chains

Paul Childerhousea, James Aitkenb, Denis R. Towilla,∗a Logistics Systems Dynamics Group, Cardiff University, Cardiff, Wales, UK

b IBL Lighting, Unit C60, Barwell Business Park, Leatherhead Road, Chessingten, Surrey, KT92NY, UK

Abstract

The paper describes the evolution of focused demand chains over an extended period of time as a major UK lightingmanufacturer has sought to remain an international player in a fast changing business environment. Analysis and designprocedures make use of the concepts of Wickham Skinner and Marshall Fisher to answer the strategic questions “whatfacilities are required and how should they be laid out to enable the necessary focused demand chains?” and to answer thetactical question “which focused demand chain is appropriate for this product?” The case study then details how the companyhas been transformed from operating within a traditional supply chain to driving change via the engineering of four focuseddemand chains. The paper concludes with a comparison of operations enablers, customer choice, and business performancemetrics covering the transition period culminating in the current focused demand chain scenario. By matching products tothe appropriate value stream there is a consequential reduction in product development time of 75%; manufacturing costsreduction of up to 27%; and up to 95% reduction in delivery lead times.© 2002 Elsevier Science B.V. All rights reserved.

JEL classification: L22; L23; L64

Keywords: Demand chain management; Classification; Case study

1. Introduction

The need for focus in manufacturing is long estab-lished (Skinner, 1974) and is defined as “the conceptthat simplicity, repetition, experience and homogene-ity of tasks breed competence. Furthermore, each keyfunctional area in manufacturing must have the sameobjective, derived from corporate strategy.” In the1990s this concept was expanded, first to cover logis-tics (Fuller et al., 1993) and then the entire demandchain (Fisher, 1997). This paper specifically addressesthe question of how does an organisation enable focusin their demand chain?Brace (1989)explained theconcept of a demand chain as “. . . the whole man-

∗ Corresponding author. Tel.:+44-29-208-76083;fax: +44-29-208-74301.E-mail address: [email protected] (D.R. Towill).

ufacturing and distribution process may be seen as asequence of events with but one end in view: it existsto serve the ultimate consumer.” This perspective canbe traced back toLevitt (1960), when he emphasisedthe need for organisations to be customer and marketorientated.

A structured methodological framework is pre-sented to specifically aid the practitioner in the devel-opment of a focused demand chain strategy. This istested on an in-depth case study application in a UKlighting company. As a consequence, the pragmaticand successful approach adopted by the companyis codified and made transparent. The methodologymay, therefore, be transferred to other companies andto other market sectors. This is a requirement laiddown byMicklethwait and Wooldridge (1996)for theestablishment of any new component of managementtheory.

0272-6963/02/$ – see front matter © 2002 Elsevier Science B.V. All rights reserved.PII: S0272-6963(02)00034-7

676 P. Childerhouse et al. / Journal of Operations Management 20 (2002) 675–689

In order to overcome the averaging effects(Fuller et al., 1993), which mask both exemplars andpoor practice alike, the focused methodology tailorsdemand chain competencies so as to best servicevaried marketplace environments. Our classificationapproach is, therefore, presented to segment productsbased on market demands. Hence, alternative strate-gies can be developed for each taxon to maximisecompetitive objectives.

The paper commences with an integrated frame-work for the development of focused demand chains.The particular product classification system utilisedis a five parameter (duration of life cycle; time win-dow for delivery; volume; variety; and variability, withthe acronym DWV3) scheme due toChristopher andTowill (2000). To provide operational benchmarks,this system has been applied to both the 1996 and1999 lighting company products. By 1999, there werefour product clusters defining the four implementedfocused demand chains. Our case study then describesthe implementation and operation in some detail. Thisincludes the utilisation of core competencies in thecurrent and future marketplace. The paper concludeswith a review of the actual industrial performance im-provements for each chain, together with the key en-ablers made possible by moving towards the focuseddemand chain scenario.

2. An integrated framework for the developmentof focused demand chains

Fig. 1 illustrates the major steps in our integratedframework for the development of focused demandchain strategies. Step one is the development of aholistic demand chain strategy. This leads from high-lighting of core competencies and resources, and itsprimary purpose is the identification of specific mar-kets to be targeted plus the overall corporate strategy.Hence, inputs from the marketplace in the form of keyorder winner and order qualifier (Hill, 1985) charac-teristics are used, together with information about thecompetitive situation in the form of knowledge of thestrategies and tactics of competitors.

Once the overall demand chain strategy has beenestablished, specific products and their related ser-vice levels are identified. These are tailored to the tar-get markets with emphasis placed on prioritisation of

service, quality, cost or lead times, thereby emphasis-ing the all important trade-offs to be made in eachfocused demand chain. The next step is the criticalpart of the integrated framework, i.e. categorisation ofdemand chain types. Given the specific products andtheir related service criteria the DWV3 classificationvariables proposed byChristopher and Towill (2000)are used to categorise the products into clusters withsimilar characteristics. The reasoning behind the useof the DWV3 variables is explained in the followingsection. The output of this key step is a clear definitionof the requirements for each demand channel, alongwith specific objectives to maximise competitivenessin each targeted market segment.

The specific demand chain types require earmarkedfacilities. This is the task of the fourth step of theframework shown inFig. 1. The facilities need to betailored to achieve the desired objectives, e.g. thoseproducts necessitating high service levels in the formof availability may require distribution warehouseslocated near to the marketplace. The penultimate steptakes the facilities requirements to a more detailedlevel in relation to the production layouts and controlmechanisms required at each level, e.g. if multiplevariants are offered with short lead times then post-ponement is applicable (Lee and Billington, 1993).Furthermore, the use of Lean principles in the formof Kanban is applicable for reasonably stable demand(Naylor et al., 1999), but MRP control mechanismsare more appropriate for special or after-marketproducts.

As mentioned earlier, the selection of the variablesused to classify alternative demand channels lies atthe heart of the methodology for the developmentof focused demand chains.Table 1 illustrates anin-depth review of empirically available classifica-tion approaches in the field of supply/demand chainmanagement. Most of the classifications are basedaround product characteristics, especially in relationto market and customer requirements.Fuller et al.(1993)classification of logistically distinct businessesprovides a great deal of insight into the need to avoidaveraging effects with the consequential dangers ofmismatching products to marketplace.Fisher (1997)has also been a major influence via his identificationof the two extreme types of products, i.e. functionaland innovative. Our preferred classification systemwill now be described.

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Fig. 1. Integrated framework for the development of focused demand chains.

3. Applicability of DWV3 classification variablesfor demand chains

Christopher and Towill (2000)have produceda series of papers comparing the Lean and AgileParadigms. The thrust of their work has been on es-tablishing the extent to which these two paradigmshave synergy and the extent to which they are inconflict. The purpose is to define the best “mix andmatch” strategy to be adopted in a given businesssituation. This leads to various combinations of lean-ness and agility, of which the best known isleagility(Naylor et al., 1999). In their researchChristopher and

Towill (2000) have been seeking a simple classifi-cation system, which would codify the selection ofa value stream according to lean and agile princi-ples. Their industrial experience plus literature review(most notablyShewchuck, 1998) led them to proposeDWV3 as such a codifer. The posteriori use of thisclassification system on the lighting company data isthe first industrial evaluation of the new system andas such is one of the original features of this paper.

There are five key characteristics that influence de-cision making in the design selection of demand chainstrategies. These attributes are:duration of life cy-cle; time window for delivery; volume; variety; and


Table 1Classification of demand/supply chains within the literature

Authors Classification variables Taxa

Hoekstra and Romme (1992) Position of de-coupling point Make and ship to stockProcess constraints Make-to-stockProduct-market constraints Assemble-to-orderDelivery service requirements Make-to-orderInventory cost considerations Purchase- and make-to-order

Fuller et al. (1993) Annual sales revenue System ordersAnnual unit volume Customer inventoryCo-ordination requirements ReplenishmentDestination volume Rapid responseHandling characteristics Nuts and boltsCustomer order fulfilment interval Slow movers

Bulk cable

Lampel and Mintzberg (1996) Level of aggregation Pure standardisationLevel of individualisation Segmented standardisation

Customised standardisationTailored customisationPure customisation

Fisher (1997) Product innovation Functional productsDemand volume stability Innovative productsProduct life cycle durationMake-to-order lead timeProduct varietyEnd-of-sale mark down

Pagh and Cooper (1998) Product life cycle Full speculationProduct customisation Logistics postponementProduct variety Manufacturing postponementProduct value Full postponementRelative delivery timeDelivery frequencyUncertainty of demandEconomies of scaleManufacturing and logistics

Naylor et al. (1999) Cost, quality, lead time and service level LeanStability of demand Agile

Leagile

Lamming et al. (2000) Product innovation Innovative-unique and complexProduct uniqueness Innovative-unique and non-complexProduct complexity Functional and complex

Functional and non-complex

variability (DWV3). Table 2summarises the key rea-sons why the original authors included each of thesefive classification variables.

Duration and stage of product life cycle have beennoted by many authors as key characteristics that re-quire demand chains to recognise and thereby adopttailored strategies.Hayes and Wheelwright (1979)

stress the important link between the manufactur-ing process and product life cycles, whilstCavinato(1987)illustrates how logistics rides the roller coasterof product life cycles. The timewindow for deliv-ery or delivery lead time, reflects the responsivenessrequirements placed on the demand chain. In combi-nation with manufacturing and logistics lead times,


Table 2Key reasons for the use of DWV3 variables to classify demand chain types, adapted fromChristopher and Towill (2000)

Classification variables Some key reasons for use to classify demand chain types

Duration of life cycle Short life cycles require rapid time to marketShort life cycles require short end-to-end pipelines to enable demand to be continuously replenished duringthe life cycleShort life cycles require a demand chain to be able to ‘fast track’ product development, manufacturing andlogistics to exploit ever decreasing windows of opportunityReplenishment lead times need to be matched to stage of the product life cycle, so to reduce lost sales andobsolescence risks

Time window for delivery Rapid response is required to replenish fashion goods that are selling well at a particular point in timeCompetitive pressures are continually reducing acceptable response times, with many demand chainscompeting on the basis of very short windows for delivery of customised products

Volume Products aimed at high volume mass markets allow for the lean-type production and make-to-forecaststrategies to take advantage of economies of scaleLower volume markets benefit from flexibility both in production and the entire demand chain

Variety Greater variety results in a larger number of stock keeping units because the volume is split betweenalternativesContinuous appraisal of the proportional breakdown between variants must be conducted during the productlife cycle because those variants popular at the introductory stage may be less popular in the decline stage

Variability Variability relates to spikiness of demand and unpredictabilitySpikiness drastically effects capacity utilisation and resultant production techniquesUnpredictability increases the risk of obsolescence and lost sales and can be addressed via informationenrichment (Mason-Jones and Towill, 1997), consultative forecasting (Fisher, 1997) and lead time reduction(Watson, 1994)

it identifies the feasible position of the de-couplingpoint (Hoekstra and Romme, 1992).

Volume is the third of the DWV3 variables.Fulleret al. (1993)emphasise the attention that should beplaced on key products that are both high volume andhigh margin because of their critical importance to anorganisation.Parnaby (1993)explains theLucas wayby which the manufacturing processes are segmenteddependent on annual volume.

Productvariety is constantly increasing at the mar-ketplace as demand chains attempt to compete on thebasis of added value in relation to colour, form andfunction. Postponement is a feasible mechanism toease these problems (Lee and Billington, 1993). How-ever, there will always remain some additional costassociated with increased variety, either in the formof stock holding costs to cover variant demands orincreased production costs caused by the flexibilityrequirements of postponement.

The final classification variable of the five is demandvariability and is the most significant in the opinionof the present authors.Fisher (1997)emphasises theimpact unpredictable demand can have on the chain in

the form of stockouts and resultant lost sales or alter-natively excessive obsolescence costs.Harrison (1997)emphasises that because of unstable original equip-ment manufacturers (OEM) schedules there is a needfor increased lead times, buffer stocks and capacity.

4. A UK lighting company case implementationof focused demand chains

A detailed historical account of the change pro-gramme in the lighting company used as a test bedherein was written byAitken (2000). The present pa-per is based on that description but uses additionalmaterial from that same industrial source as neededto substantiate the value stream classification systemwhich is our major original contribution. The richnessand utility of that contribution byAitken (2000)has al-ready been recognised elsewhere. For example, a ver-sion has been developed by Cranfield University as aformal management school case study. It has also beenused as a demonstrator for evaluation of a proposedmodel for enabling change in the agile enterprise and


as such appeared in an invited paper (Aitken et al.,2002). However, the emphasis therein was on the ex-tent to which lean production, flexible response, ag-ile supply, and organisational agility impacted on thatparticular company and its business strategy. As such,it is of peripheral interest to the present investigation,which is concerned with the exploitation of a productclassification system to analyse and design focuseddemand chains.

The case information available verifies the clas-sification approach to identification of the requiredfocused demand chains. Our approach is centred inthe lighting company via a two-phase re-engineeringprogramme. The first phase ran from 1996 to 1998,whilst the second phase was conducted from 1999to 2000. The first phase concentrated on developingand exploiting demand chain competencies. Then,phase 2 specifically addressed how these core skillsare fully utilised in current and future marketplaceenvironments.

Prior to 1996, the company’s organisation and man-agement of its internal and external demand chainswas based on a traditional functional approach. Man-ufacturing managed all of its material flow on a pushprinciple driven by MRP. Hence there was no differ-entiation between low and high volume products andbetween regular or irregular demand items. Produc-tivity was low as manufacturing orders ranged in sizefrom 1 to 1000. Each production order was preceded,and followed by, changeovers and downtime. All sevenforms ofOhno (1988)wastes (or muda) were apparentin the internal demand chain and material conversionoperations. Management of the external demand chainwas at an arm’s-length contractual basis (Sako, 1992).The supply base was broad as the strategy of the buy-ing function of the company operated on the principleof ‘lowest price wins’. Buyers routinely moved thesource of components to a new supplier if the price waslower. So new vendors would be assessed on the basisof price and component quality only. Consequently,there was no obligation for repeat transactions if theexisting supplier did not retain the lowest price.

5. Exploitation of current demand chaincompetencies

In order to rectify the foregoing current situa-tion, the need for focus was identified as a potential

solution. As a first step and to gain maximum impactas quickly as possible, it was realised that the existingproduct portfolio should be categorised and demandchains designed to maximise competitiveness in eachcategory. In effect this is equivalent to starting inthe middle of the integrated framework, illustratedin Fig. 1. The product champion in conjunction withthe senior management team decided to segment theproducts into two groups.Fig. 2 illustrates this clas-sification in relation to the five DWV3 variables. Thesequence of the five variables was shifted and sorteduntil a near perfect match was achieved betweentheory and practice. The two clusters are differenti-ated predominantly on market demand volumes andresponsiveness requirements. This 1996 analysis ledto the engineering of two distinct and focused de-mand chains based on MRP and Kanban principles,respectively.

Order winning (OW) and order qualifying (OQ)characteristics for the high and low volume productclusters used are based onJohansson et al. (1993)total value metric. Here, the key to winning in themarketplace for the high volume products is deter-mined to be cost. Given the current resources andcompetencies of the demand chain, in combinationwith the relatively stable demand patterns, the com-pany decided that lean principles (Womack and Jones,1996) were most appropriate.

In the case of the low volume products, servicelevel (or availability) is the key order winner. Theunpredictable nature of the demand patterns in com-bination with a high ratio of product codes to annualvolume meant the existing MRP strategy was mostappropriate for the second focused demand chain.As a result, the low volume products continued witha push (MRP) strategy, whilst the high volume sec-tion operated a pull (Kanban) strategy. This dualMRP/Kanban approach is well established in materialflow control (Parnaby, 1988).

6. Development of demand chain competencies

Once the internal demand chain had been re-engi-neered to operate two parallel strategies, attentionwas switched to the supply base. The result ofthese activities was a shrinkage in direct suppliernumbers from 267 to less than 100. Such a move

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Table 3Performance improvements resulting from re-engineering phase 1 of the lighting demand chain (Aitken, 2000)

Product attributes 1995 1998

Low volume High volume

Product codes 8000+ 5000 850Material flow Push Push PullMaterial control MRP MRP KanbanDemand predictability Mix of high and low Low HighMinimum order quantity Pallet Single unit PalletService offered Made-to-order Made-to-order Ex-stockProduct development (months) 24 6 6Order cycle time (weeks) 8–12 2–4 0–2Costs (1995 index= 100) 100 85 73Sales volume (1995 index) 100 110 125

has many benefits (Lamming, 1993) including riskreduction.

Following the segmentation of the internal demandchain and the reduction of the supply base, it be-came possible to simplify the ordering and commu-nications system between “players” in the chain. Thehigh volume operation introduced, with the assistanceand agreement of its suppliers, a two-bin, Kanbanmaterial ordering system. Muda previously observedin these operations included inappropriate process-ing, unnecessary inventory, unnecessary motion, ex-cess waiting time and unnecessary transportation. Allwere reduced following Kanban installation in this fo-cused demand chain.

The final part of the re-engineering conducted dur-ing phase 1 involved improvements in new productintroduction. Lead times for new product develop-ment in the lighting industry in 1996 were typically18–24 months but, the time from concept to productdelivery was proving costly in terms of pay-back andmarket leadership. Hence, suppliers within the newpartnership ethos became involved at the new prod-uct design stage. Consequently, the lighting companyis, therefore, becoming a fast innovator with manyconsequential benefits (Stalk and Hout, 1990). Theperformance improvements resulting from phase 1 ofthe re-engineering of the lighting company’s demandchain are illustrated inTable 3. The major benefit wasthe reduction of averaging effects masking both out-standing and poor performance. The products were nolonger paced by the slowest, and previously conflict-ing competitive objectives were now maximised foreach of the two clusters of products.

These very creditable performance improvementswere achieved through the efforts of both supplier andbuyer alike. Integration of demand chain activities andinformation flows accelerated the implementation oflean practises, such as Kanban. Operational improve-ments followed a consistent and deliberate strategyof developing trust and openness in the relationshipbetween supplier and buyer. Suppliers working inpartnership with the company to develop improve-ments gained additional sales volumes, which in turnincreased the interdependence of both parties to theexchange. Improvements in the relational as well asoperational performance developed a virtuous circlefor both parties in the exchange. In other words, theeffective design and operation of business interfacesplayed a vital role in enabling effective change ashighlighted by Towill (1997a,b) when adopting asystems approach to supply chain design.

7. Identification of the lighting company’sdemand channels

Phase 1 of the re-engineering programme providedthe company with a firm basis for a more comprehen-sive overhaul of its demand chain strategies. There-fore, phase 2 was able to start at the beginning of theintegrated framework illustrated inFig. 1. This wasbecause partial benefits already accumulating from thedevelopment of focused demand chain strategies hadgained buy-in from senior management, operators andstrategic demand chain partners alike.

Environmental feedback in relation to marketplaceconditions and competitors strategies highlighted two

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major factors to be addressed. First, the lighting indus-try had become a global marketplace. This, in combi-nation with the fact that a number of the products hadbecome commodity in nature, meant a UK based com-pany would struggle on the basis of price when com-peting with imports from low labour cost countries,such as China. Secondly, the environmental feedbackfactor illustrated the movement of the lighting indus-try towards increased demands for customised prod-ucts. This, in turn necessitated working much more ona one-to-one basis.

The feedback of competencies effect was extremelybuoyant. Phase 1 of the re-engineering programmeshad resulted in the demand chain being able to in-troduce new products four times faster. The new leandemand channel was capable of responding ten timesfaster to specific customer orders for existing prod-ucts. All these factors meant that the overall context inwhich the lighting demand chain operated within wasin good health but must further develop to stay aheadof the competition.

To fully exploit the new competencies, the prod-uct champion in collaboration with the senior man-agement decided to increase the number of productgroups from 2 to 4.Fig. 3 is an updated version ofFig. 2, illustrating the new classification of the light-ing company’s products relevant to the business needsof 1999. In this instance three of the five variables arepivotal in classifying the product types. These are: du-ration of product life cycle, annual volume, and prod-uct variety. Cluster 1 is exactly the same as 1996, i.e.low volume and unresponsive. Clusters 2 and 3 wereoriginally aggregated to make up cluster 2 in 1996.But this cluster of products is now split into two, basedupon high and low variety. Cluster 4 comprises totallynew products. These are potential customised productsreflecting the new opportunities in the lighting sector.

8. Utilisation of competencies in the currentand future marketplace environment

The four clusters highlighted inFig. 4 exploit theoverall context within which the lighting demandchain is currently operating. They have been seg-mented specifically to exploit the resources and corecompetencies available to the extended enterprise.Cluster 1 consists of the low volume products. This

is very similar to the previous cluster 1, as of 1996.The major difference is the removal of products dur-ing their introductory stages. Hence, this cluster ismore akin to automotive after-market products or“strangers” in Lucas terminology (Parnaby, 1993).The existing MRP control mechanisms are, therefore,still utilised and the resultant internal demand chainis illustrated inFig. 4, together with the other threedemand channels. The major order winner for thiscluster of products remains the service level in termsof availability of small volume products. Therefore,the application of a make-to-order approach, viaMRP control, with common raw material stocks andshared manufacturing resources, maximises avail-ability within acceptable lead time, cost, and qualityparameters.

Cluster 2, the high volume, low variant productsare increasingly becoming commodity-like in natureand are exposed to competition from low labour costcountries. The major order winner here is cost. How-ever, since the UK lighting company cannot competeon the basis of cost, very short lead times are the onlyremaining competitive avenue. This is facilitated viaa lean demand channel and a make-to-stock policy,so that deliveries to specific customer orders can bemade in very short lead times (1 day if required). TheKanban controls and the two-bin system operated inconjunction with the supply base maximises efficiencyfor these products, which have relatively predictabledemand patterns. The resultant internal demand chainis once more illustrated inFig. 4.

Despite the very short lead times offered for thecommodity type products, the UK lighting company,as with many UK organisations, is in danger of beingpushed out of the marketplace. To combat this thelighting company and its associated demand chain in-creased customer service by offering multiple variantsof relatively standard products. The products utilisingthis strategy make up cluster 3. These are high vol-ume, high variant products. The order winner in thisinstance is still cost, closely followed by availabil-ity of multiple variants. To achieve these objectivesthe application of postponement was seen to be op-timal (Lee and Billington, 1993; van Hoek, 1998;Pagh and Cooper, 1998). This was partially due tothe nature of lighting products in that they are assem-bled from three major sub-assemblies. Therefore, thede-coupling point has been placed at the sub-assembly


Fig. 4. Focused demand chains designed to maximise OW and OQ objectives for each of the four product clusters.

level as illustrated inFig. 4. Prior to the de-couplingpoint, lean principles are applied to maintain desiredstock levels as in the case of the cluster 2 prod-ucts. After the de-coupling point in the final packingcentre specific customer orders are assembled anddispatched, therefore, offering multiple variants costeffectively in very short order cycle times. Thus, aleagile strategy (Naylor et al., 1999) was adopted soas to obtain the best from both worlds.

In the final product cluster, four were seen as newopportunities in the marketplace in line with theincreased demand of customised products.Fig. 3 il-lustrates these particular products as having short lifecycles. In addition, those products already in theirintroductory stages have been included, as the dura-tion of the life cycle remains uncertain. A completelynew approach to operating the demand chain is re-quired in this instance and has been noted as agile

in nature (Aitken et al., 2002). The new design com-petencies developed in phase 1 of the re-engineeringprogramme are exploited to the full via offering themarket a comprehensive design-and-build strategy.Fig. 4shows the internal demand chain for this clusterof products. It has been specifically designed to offercustomised products in short development lead timesas effectively and efficiently as possible, therefore,maximising the order winning objectives.

9. Dynamic appraisal of product routing basedon stage of product life cycle

Phase 2 of re-engineering was completed by 2000,at which time focus had been achieved in the shapeof the lighting company’s four established demandchains. The resultant strategies had been implemented


Fig. 5. Generic lighting product life cycle stages and corresponding OW, OQ and demand chain strategies.

and competitive advantage gained in each via theremoval of conflicting objectives and the shapingof focused demand chains to suit particular market-places. However, at this point it was noted that theproduct routing was not static. In fact the marketplaceOWs and OQs are dynamic for any specific productas it proceeds through its product life cycle. This isnoted by numerous authors, includingHill (1985),Kotler (1994) and Porter (1980). Furthermore, asHayes and Wheelwright (1984)andDuBois and Oliff(1992)have stated, the production and manufacturingprocesses must also dynamically adapt to best ser-vice these changing marketplace conditions.Fig. 5,therefore, traces a particular lighting industry genericproduct, its OW and OQs for each life cycle stage,and the resultant most applicable focused demandchain strategy.

During the introduction stage of the product lifecycle, the capability of design is the key OW fol-lowed closely by the design lead time. Therefore, thedesign and build strategy is most applicable. Oncethe product has entered the marketplace and if thedemand increases, then the product enters its growthstage. During this time the service level in terms ofavailability of a product with unpredictable demand isthe key OW. As a result, the product is transferred tothe MRP push based demand chain. When the prod-uct has reached its mature stage it is switched to the

Kanban demand chain, so to best compete on the keyOW of cost. During the saturation stage, low labourcost countries enter and compete in the marketplace,so the UK lighting company competes by offeringmultiple variants. In order to do so the packing centrefocused demand strategy is utilised. Finally, as thedemand for the product tails off and enters the declinestage of the product life cycle, it is transferred back tothe MRP demand chain so as to maximise the servicelevel for the low volume highly unpredictable product.

10. Discussion

The lighting company’s case study offers a greatdeal of insight into the feasibility of developing fo-cused demand chain strategies. All major processsteps in the integrated framework proposed inFig. 1were performed by the company industrial engineers,although not necessarily in exactly the same order.The resultant four focused strategies greatly enhancedthe competitiveness of the company and their demandchain partners.Table 4illustrates the four strategies,together with some of the observed benefits fromusing the focused approach. Costs have been greatlyreduced for three of the four channels. In the caseof the design and build strategy the apparent priceincrease is because re-engineering has facilitated


Table 4Resultant performance of the four demand chain strategies

Strategy name year implemented Original MRP 1995 MRP 1998 Design andbuild 2000

Kanban 1998 Packing centre 2000

EnablersProduct codes 8000+ 3500 N/A 400 450Material flow Push Push Pull Pull PullMaterial control MRP MRP Discrete orders Kanban KanbanDemand predictability Mix of high and low Low High High MediumMinimum order quantity Pallet Single unit Single unit Pallet Single unitService offered Made-to-order Made-to-order Design and

build-to-orderEx-stock Assemble-to order

Performance metricsProduct development (months) 24 6 6 6 6Order cycle time 8–12 weeks 2–4 weeks 1–4 weeks 0–2 days <5 daysCosts (1995 index= 100) 100 80 150 73 80

identification of the true costs. Thus, the cross-subsidyfrom commodity-like products at the expense of otheritems, which is one ofFuller et al. (1993)averagingeffects is avoided. The order cycle times have beenmassively reduced for all four strategies, but espe-cially for the Kanban and packing centre strategies,which often win orders on the basis of this respon-siveness. Similarly, the competitiveness of the designand build products has been greatly enhanced via thecompression of the product development lead times.

The DWV3 classification variables are generic andit is the contention of the authors that these holdfor many industries and marketplaces. The simplisticclustering mechanism based on binary scales and al-ternating the order of the five variables is manifestlysubjective. But it must be so in order to incorporatethe tacit knowledge of the management team taskedwith identifying the clusters of product types. Thebest sequencing of these during value stream analy-sis variables is an area of potential further research.For example, during phase 1 of re-engineering of thelighting demand chain volume is the bottom line and,therefore, as shown inFig. 2, is the most significantvariable. But during phase 2 the duration of life cycleplays a more critical role, as seen inFig. 3. This maynot be coincidental; the ranking in priority of thefive variables seems dependent upon the present levelof sophistication used to segment demand channelswithin an organisation, i.e. the extent to which thevalue streams are focused.

11. Conclusions

The advantages of focus have been long understoodin context of manufacturing management and can betraced back to the fundamental theoretical work ofSkinner (1974). Fuller et al. (1993)extended the ap-proach to logistics, whilstFisher’s (1997)argumentencompassed the whole demand chain. However, re-grettably few examples exist in the literature of how toachieve this desired focus in practice. This paper haspresented a structured framework for the practitionerto confidently implement focused demand chains intheir own organisation. The in-depth experience andinsight from the implementation by a forward look-ing company in the lighting industry has providedinvaluable case based evidence of the validity of theapproach.

The theory of focused demand chains is basedon the premise that modern day marketplaces havediverse requirements for alternative products and ser-vices. No one demand chain strategy can best serviceall these requirements. Hence, focus is required to en-sure demand chains are engineered to match customerrequirements. Such focus is enabled via segmentationon the basis of each product’s characteristics. There-fore, the classification variables used to segment theproducts lies at the heart of the methodology. Thispaper has reviewed the empirically available classi-fication approaches, their key variables and resultanttaxa. The classification system based on the five


variables of DWV3 has been evaluated via a casestudy and can be seen to have great potential in iden-tifying focused demand channels ahead of design andimplementation.

The lighting case study has provided some valuableinsight into the methodology for engineering focuseddemand chains. Over a 4-year period the companytransformed their traditional supply chain to a highlycompetitive market orientated focused demand chain.The results speak for themselves, via increased salesvolume, decreased costs, and increased customer ser-vice levels in relation to order cycle times, productdevelopment lead times and variety. They are highlysignificant and point the way for further industrialapplication of the classification methodology basedon the DWV3 variables. Finally, the classificationsystem enables specific results obtained in one in-dustry to be placed in a generic context. As suchit aids “transferability” between companies and be-tween market sectors which is arguably one factor inestablishing management theory.

References

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