07-001

Copyright 2006 Rogelio Oliva and Noel Watson

Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be cited or reproduced without permission of the copyright holders. Copies of working papers are available from the authors.

Cross Functional Alignment in Supply Chain Planning: A Case Study of Sales & Operations Planning

Revised October 11, 2006 Professor Rogelio Oliva* Professor Noel Watson**

*Mays Business School, Texas A&M University, College Station, TX 77843-4217 roliva@tamu.edu **Harvard Business School, Boston, MA 02163-1010 nwatson@hbs.edu

Cross Functional Alignment in Supply Chain Planning: A Case Study of Sales & Operations Planning

Abstract

In 2002, Leitax, a niche consumer electronics company, suffered serious supply chain planning mishaps

due to poor cross-functional integration in the supply/demand planning activities. The poor integration

resulted from organizational differentiation among the functions and an unsophisticated approach to

integration. In response to the planning mishaps, the organization introduced significant changes, which

we examine in this case study. After highlighting the constituent responsibilities, structures, and

processes, we recognize a system, as opposed to a list of mechanisms, as responsible for cross-functional

integration. Operationalizing integration as functional alignment with generated plans, we find

collaborative engagement of the functions to be a consistent process feature and operational norm

encouraged and maintained by integrators. In particular, the information processing nature of the sales

and operations planning (S&OP) process introduced at Leitax is argued effective as a result of this

collaborative engagement. We argue that this collaborative engagement positively influences alignment

even in the absence of an overall reduction in the level of differentiation exhibited by an organization,

which stands in contrast to academic structural recommendations for changes in incentives for achieving

integration. Examining a systemic tradeoff consciously acknowledged by the organization, we further

argue that alignment encouraged by this collaborative engagement can be more important than achieving,

superior performance along such dimensions as speed or accuracy in individual information processing

steps of the S&OP process, a tradeoff which to our knowledge has not been highlighted in the supply

chain management literature.

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1. Introduction Within most organizations, the administration of its supply-facing and demand-facing sides so as to minimize

mismatches and thus create and capture value is a cross-functional effort. Traditionally functional areas e.g.,

sales, marketing, finance, operations have tended to specialize in portions of these supply chain planning

activities. However, this specialization or differentiation is notorious for generating conflicts in organizations

(Shapiro 1977), conflicts which generally center around differing expectations about both demand and

supply, and differing functional preferences and priorities on how the matching of demand and supply should

be accomplished. Poor reconciliation of such inter-functional conflicts has the potential to create huge

demand/supply mismatches and their attendant inventory holding, production, and opportunity costs

(Christopher 1998), and even contribute to the bull-whip effect (Hammond 1994). Consequently, the need for

explicit attention to coordinating or integrating the functional efforts to achieve particular planning results

has been considered significant (Stank et al. 1999; Stank et al. 2001), but difficult to achieve as a result of the

persistence of the differentiation inducing factors (Barratt 2004; Fawcett and Magnan 2002; Kahn and

Mentzer 1996). In this paper we focus on cross-functional integration to support the mid-term (from a couple

weeks to a year) supply/demand planning and execution of the plans in highly differentiated organizations.

We consider planning that involves simultaneously assessing the demand and supply side potentials and

managing the flow of inventory and the creation of demand so as to minimize mismatches.

We expect this type of planning in a highly differentiated organization to require quite an explicit and

broad cross-functional reach for integration. Although particular interfaces have been developede.g.,

marketing and logistics (Ellinger 2000; Stank et al. 1999), purchasing and manufacturing (Fawcett and

Magnan 2002)very few organizations have achieved broaderreaching integration within the

organization (Barratt 2004; Fawcett and Magnan 2002). With opportunities and challenges for planning

within supply chain management increasing as a result of such forces as increased competition and

globalization (Raman and Watson 2004), a clear understanding of the behavioral processes and systems

associated with successful interdepartmental integration is needed. While researchers have addressed the

roles and infrastructure required for integration, most of their proposals result from attempts to address

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particular shortcomings identified in a setting (e.g., Chen 2005; Porteus and Whang 1991) or from

organizational-level analysis across firms (e.g., Lawrence and Lorsch 1986; O'Leary-Kelly and Flores 2002).

To date, however, very little empirical research has been done on functioning integration approaches

(Malhotra and Sharma 2002) and a comprehensive understanding of interdepartmental integration based on

micro-level data has yet to be established (Griffin and Hauser 1996; Kahn 1996; Kahn and Mentzer 1998).

This work aims to shed light on this issue by exploring how cross-functional integration can be achieved in a

functionally differentiated context.

In this article we report the findings from a detailed case analysis of a functioning and successful

integrated planning process. As a first contribution, the case study provides an empirical account of such an

integration approach in this particular planning setting. Our analysis of the responsibilities, structures, and

processes provide insights into how features of the approach encourage not only integration but also effective

planning. We find preliminary evidence that a collaborative planning process that encodes efficient

information processing encourages effective integration even though the incentive structure does not directly

support this integration. That is, the organization is capable of effective integration while retaining different

incentives across functions that enable the participating functions to maintain their focus on their

stakeholders needs. Our analysis also suggests that the specification of the coordination system needs to go

beyond the definition of responsibilities, structures, and explicitly consider the social and organizational

dimensions of the process to achieve alignment. In our case study, the characteristics of the process

generated collaborative engagement, i.e., active participations from all functions, that resulted in better

information sharing across functions, accurate and validated plans, and alignment in the execution of those

plans.

In the next section, we provide a review of the literature, then describe in section 3 our research setting and

methodology. In section 4, we detail the supply chain planning process that was implemented and the

organizational and structural changes that accompanied implementation, and in section 5 analyze the process

and explore how and why it works. We discuss the implications of our findings for organizational operations

and performance in section 6, and current practice and research in supply chain integration in section 7.

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2. Literature Review Why is integration so difficult? Classical research suggests that the effort required to achieve integration

increases with the level of differentiation in the organizational environment (Lawrence and Lorsch 1986;

Lorsch and Allen 1973), differentiation being defined as differences in the cognitive and emotional

orientation of managers in different functional departments. This differentiation provides a breeding ground

for conflict between the groups when these cognitive and emotional orientations such as goals, incentives,

and perspectives on time and relationships create short-term conflicts and deemphasize long-term

organization goals. The effort required to achieve integration has also been found to increase with the

complexity of the collective effort. Funk (1995), for example, finds that greater logistics complexity requires

more mechanisms for coordination. Integration is made more difficult by its effects on power relationships

and organizational dynamics (Christopher 1998); it occasions resistance by giving rise to a more process-

oriented structure which is likely to affect the position of the functional manager, his/her role in the

hierarchy, and the function itself (Skjoett-Larsen et al. 2003). Although functional differentiation seems to

be the norm within supply chain organizations (Kahn and Mentzer 1996), questions about organizational

structure and its impact on performance have only recently begun to be asked.

The academic literature on integration within planning contexts has primarily concentrated on the

roles/responsibilities and structures supporting integration. By responsibilities we mean the participants and

the distribution of decision rights among them in the collaborative effort (e.g., Lawrence and Lorsch 1986),

and by structures we mean the accompanying formal systematic arrangements, relationships and

infrastructure (Anand and Mendelson 1997; Malone and Crowston 1994).

The literature on responsibilities primarily draws on that from organizational behavior literature. Lawrence

and Lorsch (1986) recommends explicitly the role of integrators for coordinating unity of effort. These

integrators act as translators, mediators and integrative goal setters facilitating the differing cognitive and

emotional perspectives of the various functions and directing collective efforts.

Structural recommendations for improving integration have come from analysis of the informational and

organizational infrastructure impeding integration. Such infrastructure includes the level of information

sharing among functional decision makers (Dougherty 1992; Shapiro 1977; Van Dierdonck and Miller 1980)

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including that facilitated by enterprise information systems (Al-Mashari et al. 2003); evaluation and

incentive systems whether for individual functions (Chen 2005; Gonik 1978; Kouvelis and Lariviere 2000;

Porteus and Whang 1991) or collective incentives (Mallik and Harker 2004); support for complex decision

making whether from quantitative models (Yano and Gilbert 2004), decision support systems (Crittenden et

al. 1993), and outsourcing planning decision-making to competent third parties (Troyer et al. 2005); and

formal arrangements systematizing the desired integrative norms (Stonebraker and Afifi 2004) such as

standardization of policies, compatible communications formats, and formal hierarchies and

departmentalization

In terms of general process features for integration, the academic literature posits that interdepartmental

integration is fostered by two types of activities (Barratt 2004), (1) interaction/communication activities

(Dougherty 1992; Griffin and Hauser 1992; Ruekert and Walker 1987), and (2) collaboration-related

activities (Lawrence and Lorsch 1986; Pinto et al. 1993). Both types of activities are facilitated by norms

and specific responsibilities and goals. Interaction/communication activities, however, relate to the activities

that enable the existing types, quantity, quality, and frequency of information flows (structure) between

functions. Collaboration activities, on the other hand, relate to the roles (responsibilities) spread across

functions that in combination and usually in the short term have shared goals. Whereas integration and

communication activities are necessary for collaboration, collaborative activities are generally believed to be

a precondition for full integration (Barratt 2004).

The type of collaborative planning processes we examine in the case study are referred to in the

practitioner literature as sales and operations planning (S&OP) processes (Bower 2005; Lapide 2004a; b;

2005a; b). Among the primary roles of S&OP processes is to facilitate master planning and demand planning

and the flow of information between them. Practitioners and academics alike argue that the process can move

beyond the superficial synchronization of master and demand planning and begin to approach coordinated

joint planning with sophistication in the quality of plans generated (Lapide 2005a; Van Landeghem and

Vanmaele 2002).

The above review begins to suggest that a systemic perspective on integration is appropriate as the three

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components of responsibility, structures and processes are inter-related and it is reasonable to expect that a

better fit between them will encourage greater integration. The review also reveals that the dimension of

process and its contribution to integration is one of the lesser understood components of the system. The

present in-depth case study provides the opportunity to develop insights into the dimension of process in

mid-term supply chain/demand side planning and its relation to the system needed to achieve broader-

reaching integration. Given the emphasis on coordination in supply chain management in general we refer to

this system for generating cross-functional system as a coordination system (Oliva and Watson 2004).

3. Research Methodology

3.1 Overview of the Research Site The case site is a consumer electronics firm with headquarters in northern California, and with a global sales

presence. Leitax (the firms name and industry have been disguised) sold its electronic items primarily

through retailers such as Best Buy and Target and has distribution centers (DC) in North America, Europe

and the Far East. Production is handled by contract-manufacturers with plants in Asia and Latin America.

Leitax maintained seven to nine models in its product portfolio, each of which had multiple SKUs. Product

life ranged from fifteen to nine months and was getting shorter. High-end, feature-packed products tended to

have the shortest product lives.

Prior to 2001, the demand and master planning processes at Leitax were ill defined. For new product

introductions and mid-life product replenishment, the sales group initially made forecasts that were

informally disseminated to the operations and finance groups, sometimes via discussions in the hallways.

These shared forecasts were intended to be used by the operations group to guide the communication of build

requests to the supply chain, and by the finance group to guide financial planning and monitoring.

Traditionally, Leitaxs sales directors forecasted sell-in sales, the expected sales from DCs to resellers.

Sell-in sales tended to be a distorted signal of demand since the sales force had an incentive to influence sell-

in in the short-term and retailers had time-varying appetites for inventory. Not surprisingly, these sales

forecasts were often mistrusted or second-guessed when they crossed into other functional areas. For

example, with inventory shortages as its primary responsibility, the operations group would frequently

generate its own forecasts to minimize their perceived risk of an inventory discrepancy, and marketing would

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devise its own forecast when they suspected possible deviations to the sales forecast because of promotions

(Figure 1 depicts this re-processing and proliferation of functional forecasts). Moreover, the sales

organization believed that the final group exerted too much pressure on forecasts, frequently urging sales to

increase forecasts that did not enable the company to meet its financial goals.

Other aspects of a true demand planning process were also absent. It was not unusual for sales to arrange

deals to extend production of products for which and end-of-life decision had been approved and the supply

chain had been depleted. Data relevant to forecasting were usually inaccurate, incomplete, or unavailable,

and the lack of objectives and monitoring mechanisms for the demand planning meant that process

improvement could not be managed. Support for supply management was equally ill-defined as master

production schedules were irregularly generated and unreliable, and suppliers had learned to mistrust those

signals.

These inefficiencies and lack of coordination, previously hidden by booming growth in the sector, caught

up with Leitax in 2001 when poor planning and execution resulted on an inventory charge of roughly 15% of

revenue for FY 2001-2002. The inventory write-offs were followed by major changes during the fall of 2001

including the appointment of a new CEO and new vice-presidents for product development, product

management, marketing, sales, and operations. In December, the new senior vice-president for Global

Operations recruited Kevin Fowler, made him responsible for the new Demand Management Organization

(DMO), and charged him with defining and managing a set of initiatives for improving the planning process.

Fowler assessed the situation as follows.

The truth was that the root of the problem was not a classic forecasting issue in that it was not about getting another perfect data stream; it really didn't matter. We already had a number of forecasts that functional areas were utilizing. [the problem was that] there was no tie, no formal sales and operations planning process. There was no getting together to discuss what are you guys building vs. what do you want vs. what is the financial target.

In April 2002, Fowlers group launched Project Redesign with the goal of improving the velocity and

accuracy of planning information throughout the supply chain. By the summer of 2003 a stable planning and

coordination system was in place that resulted in dramatic improvements in forecast accuracy and

operational performance (see 4.3 below).

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3.2 Research Method The primary tool used to derive insights from this study was intensive case study research (Eisenhardt 1989;

Yin 1984) following established protocols for grounded theory development (Glaser and Strauss 1967; Miles

and Huberman 1984). The research was retrospective; the primary initiative studied was, although evolving,

fully operational at the time the research was undertaken.

Data were collected through 25 semi-structured interviews and reviews of archival data. We interviewed

leaders, analysts and participants from all the functional areas involved in the S&OP process, as well as

heads of other divisions affected by it. We conducted most interviews in the organizations northern CA

facility, but some follow up interviews were done by telephone. Interviews lasted from 45 to 90 minutes and

given the nature of the research, interviewees were not required to stay within the standard questions;

interviewees perceived to be exploring fruitful avenues were permitted to continue in that direction. All

interviews were recorded. Several participants were subsequently contacted and asked to elaborate on issues

they had raised or to clarify comments. The interviews were supplemented with extensive reviews of archival

data and direct observation of two planning and forecasting meetings. We summarized the data in the form of

a detailed case study that relates the story of the initiative and current challenges (**citation ommited**).

Feedback was solicited from the participants, who were asked to review their quotations, and the case, for

accuracy.

In addition to mapping the forecasting methodology and processes, we analyzed the case data using two

explicit frameworks to address planning and cross-functional integration. First, we relied on an information

processing framework to analyze the planning process (Simon and Newell 1972). The process begins with

the sharing of functionally generated data between the relevant groups. The shared information, along with

any private information that the function possesses forms, the problem space of planning for that particular

function. The functions process or make inferences from this information in order to develop their individual

plans, which they then execute. Such an approach will foster coordinated action across the different groups if

the following conditions for efficient information processing and coordination are satisfied: 1) the functions

information package is appropriate, in terms of both content and form, to the development of adequate plans;

2) the rules of inference used by the different functions are sound; and 3) planning and execution are

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coordinated in the aggregate and also inter-temporally across functions. The second framework was utilized

to assess cross-functional integration. According to Lawrence and Lorsch (1986), the difficulty of resolving

integration problems flows from the inevitable conflicts occasioned by the functions differing cognitive and

emotional orientations resulting from the natural division of labor. The more differentiated the functional

areas are, the more variety the coordinating mechanism needs to accommodate (Ashby 1956). An explicit

mapping of the functional orientations along the dimensions proposed by Lawrence and Lorsch (1986)

(goals, time, formality in structure, and interpersonal), and documentation of the characteristics of the

coordination system allowed us to assess its appropriateness and uncover the impact of collaborative

engagement on the quality of information processed and degree of alignment reached.

4. Coordination System To improve forecasting and planning, Fowler introduced organizational changes that supported the needed

cross-functional activities and their coordination. These mechanisms are highlighted by first examining the

causes of the breakdown of planning at Leitax before the implementation of the coordination system. Prior to

Project Redesign, the sales force provided coordination signals in the form of forecasts and from these

signals the functional groups generated their own forecasts and plans for managing supply or demand (see

Figure 1). This approach proved ineffective at Leitax because of the mistrust other functional areas had on

the original forecast, misalignment among functions, and poor inter-temporal coordination of plans. Below,

we explore each of these causes in detail.

Forecasts communicated by the sales group were thought, and sometimes found, to be inaccurate. Among

possible reasons for the inaccuracy or perception thereof were the effects of sales incentives, insufficient

motivation to generate accurate forecasts, and faulty forecasting processes. Commissions on sell-in might

have prompted forecasts that positioned excess inventory in the chain to prevent stockouts. A history of poor

demand and supply planning might have fostered complacency in the preparation of forecasts. Finally, faulty

forecasts might have been a consequence of forecasting shortages instead of unconstrained demand or of

other judgmental forecasting biases.

While the primary repercussion of mistrust of the sales organizations forecasts was the generation of

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multiple forecasts, mistrust was not the only reason for misalignment. Functions naturally differing

orientations also hindered alignment. Differentiation in goals among functions at Leitax arose from natural

differences in functional objectives and resulted in specific biases. For example, incentives biased the sales

organization to want sufficient inventory to avoid stockouts, and the operations group, which was responsible

for shortages and excess inventory and for managing relationships with suppliers, to want more measured,

stable inventory levels. Sales emphasis on current sales opportunities, and operations medium- to long-term

focuses on inventory and capacity planning requirements are examples of differentiation with respect to time.

Finally, differentiation in formality of structure was observed in terms of formal reporting relationships,

criteria for rewards, and control procedures. Operations, for example, had more established routines and need

for specific details in order to communicate manufacturing requests to its contract manufacturers than did the

sales group for managing its sales accounts.

Executing a medium- to long-term demand and supply plan, especially a dynamic one, ultimately requires

coordinating over time the activities that support the plan. Poor inter-temporal coordination of auxiliary

activities and plans will compromise even a well-intentioned aggregate supply and demand plan (Barratt

2004). The setting at Leitax worked against good inter-temporal coordination, there being no explicit

processes for effecting appropriately timed broadcast and reception of inter-temporal coordinating signals.

This was exacerbated by distrust of sales forecasts and by the natural differentiation among functions,

particularly with respect to time, which hindered the generation and reception of inter-temporal coordinating

signals.

In the next section, the changes introduced at Leitax are described through the lens of the coordination

system introduced in 1 and 2, the explicit definition of processes, responsibilities, and structures meant to

facilitate the coordination of activities (Oliva and Watson 2004).

4.1 Responsibilities and Organizational Structure Organizationally, ownership of the forecasting and planning process was assigned to a newly formed

operations unit, the Demand Management Organization. The DMO was (and still is) responsible for:

synthesizing the necessary data; managing the planning process; resolving conflicts; and challenging,

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creating, and disseminating demand projections to pace worldwide operations.

Fowlers previous experience with establishing a demand forecasting group had involved heavy reliance

on statistical and simulation models. But it was his realization that the buy-in of different functional groups

was critical to the improvement of demand planning that gave rise to the consensus forecasting process that

was developed at Leitax. In soliciting functional support for the proposed new forecasting process, Fowler

offered assurances that the voices and perspectives of those in the different groups would be heard. Even

though there was general agreement that the forecasting process needed to be changed, Fowler took the time

to acquaint each group with the companys forecast and inventory performance to date, and emphasized that

the problem was not localized in a particular group but collective. Instead of developing another statistically-

based forecasting stream, he created mechanisms that would ensure that a single forecast drove the

organization. Fowler emphasized that one of the tasks of the DMO was to eliminate bias within the planning

process.

Since we started the process we were clear that we wanted to align separate but equal data streams. It is a simple idea, but in practice it is difficult to put in place. You are trying to address bias, and it starts by just explicitly stating what the bias of each functional group is.

Fowler had begun to integrate Leitaxs disparate information streams in May 2002, but was soon

promoted to senior director of Planning and Fulfillment with responsibility for supply and demand

management. The new position afforded him an opportunity to integrate an even broader set of activities.

Fowler named Brian McMillan, whom he had hired into the DMO, to head the organization and assigned him

responsibility for driving the forecasting and demand planning processes.

4.2 Sales and Operations Planning Process The principal output of the planning process was a consensus forecast that was used to drive all supply and

demand management decisions. The consensus forecast was generated monthly by a group that included the

sales directors and VPs of marketing, product strategy, finance, and product management. Before describing

the steps in detail, here we provide an overview of the Sales and Operations Planning (S&OP) process (see

Figure 2). The first step was the preparation of an information package referred to as the business

assumptions package (BAP). The elaboration of the BAP also functioned as the strategic planning step of the

process as it contained the current supply and demand plans for the supply chain via the decisions on price,

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product offerings, promotions, launch and end-of-life dates for each product line. The BAP was followed by

careful validation of the strategic plan via functional forecasts, a consensus forecasting, and financial and

supply chain validation of the proposed forecast to assess whether the plans as captured in the BAP are

feasible and financially attractive. The consensus forecasting process determined the potential demand based

on the strategic decisions in the BAP. Validation by operations revealed whether capacity to accommodate

that demand was available, and validation by finance the financial attractiveness of the strategic plans. If

there were capacity or financial concerns, the assumptions in the BAP were changed, that is, the strategic

plan was changed and the process of validation repeated. Additional planning, feedback, and learning were

facilitated by directed interaction within the consensus forecasting meeting.

Information Collection and Strategic Planning: Business Assumptions Package The BAP integrated primarily two types of information, (1) current plans for product offerings including

marketing campaigns, price plans for each SKU, and end-of-life and new product introduction dates, and (2)

information that reflected the market environment such as intelligence about market trends and competitors

products and marketing strategies and other information that had relevance for the industry in general. The

entire BAP, including current plans, was updated monthly and discussed and agreed upon by the forecasting

group during a (usually) two-hour meeting. The product planning and strategy, marketing, and DMO groups

used the information on the marketing environment to provide guidance in assessing the impact of the

information on future business performance and entered their recommendations (carefully labeled as such)

into the BAP.

Interestingly, the BAP was not initially part of the planning process. In early iterations, varying

assumptions about product price changes and promotion schedules were a significant source of variation in

the forecasts. Realizing that business assumptions were crucial to the overall process, the DMO devoted

considerable attention to developing and refining a package that summarized promotional as well as

competitors product information.

Validation: Functional Forecasts Once the BAP was agreed upon, the information in it was used to elaborate three functional forecasts. Fowler

and McMillan decided on three methodological changes that would help to standardize and improve the

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accuracy of forecasts across the organization. First, the focus of the forecast was switched from sell-in to

sell-through, that is, the quantities sold from the resellers in North America or shipped from the resellers

DCs in the other regions. Second, these forecasts ignored capacity constraints in estimating demand.1 Third,

for the planning meetings, forecasting and planning would be at the product family level.

Product planning and strategy (PPS), a three-person group that supported all aspects of the product life

cycle from launch to end-of-life, assessed competitive products and effects of price changes on demand, and

prepared a top-down forecast of anticipated global demand for Leitax products. The PPS forecast, derived

from a worldwide estimate of Leitaxs product demand, derived product- and region-specific forecasts from

historical and current trends in market share.2

The sales directors (SDs) utilized a bottom-up approach to generate their forecast. SDs from all regions

aggregated their account managers as well as their own knowledge about channel holdings, current sales,

and expected promotions to develop a forecast based on information about what was happening in the

distribution channel. The SDs bottom-up forecast was first stated as a sell-in forecast, then translated into a

sell-through forecast by maintaining for each SKU a maximum level of channel inventory (inventory at

downstream DCs and resellers). SDs bottom-up forecast, being based on orders and retail and distribution

partner feedback, was instrumental in determining the first 13 weeks of the master production schedule.

A third forecast of sell-through by region, prepared by the DMO entirely on the basis of statistical

inferences from past sales, was intended primarily to provide a reference point for the other two forecasts.

Significant deviations from the statistical forecast dictated that the other forecasting groups investigate and

justify their assumptions.

All forecasts included, for each product type and by region, monthly expected sales that were spread

1 It was common at this time for forecasts to be affected by perceptions of present and future supply chain capacity, which resulted in a subtle form of self-fulfilling prophecy. Even if manufacturing capacity were to become available in the future, deflated forecasts would have positioned lesser quantities of raw materials and components. Thus, expected capacity constraints could give rise to real ones.

2 The PPS group relied on market research provided by NPD Group and IDC, among others, to spot current trends, and used appropriate history as precedent in assessing competitive situations and price effects.

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evenly over the month to yield weekly forecasts. The PPS and DMO groups forecasts had one-year

horizons; the SDs forecast was for the next two quarters.

Validation: Consensus Forecast The three groups forecasts were submitted on Excel templates and merged into a proposed consensus

forecast using a formulaic approach devised by the DMO that gave more weight to the SDs bottom-up

forecast in the short term and increased the weight of the top-down forecast as it went out to the future. The

forecasting group evaluated, in a monthly meeting, the proposed consensus forecast and three independent

forecasts. All parties were acquainted with the assumptions that drove the different forecasts with the object

of arriving at a final consensus. Discussion tended to focus on the nearest two quarters.

Whereas the first few had sometimes consumed an entire day and been characterized by heated

discussions, by the fall of 2003 consensus meetings were lasting between 2-4 hours and conversations were

cordial. McMillan focused participants on understanding the reasons behind significant differences among

the functional forecasts. The underlying reasons for diverging forecasts would be identified and discussed

and the proposed consensus forecast revised by open conversation. When justified on the basis of the SDs

intimate knowledge of upcoming sales deals or prospects, bottom-up sales forecasts that were slightly higher

than the PPSs or DMOs were often accepted. Given its understanding of the revenue potentials at stake, the

finance group, although it did not submit a forecast, voiced opinions and concerns about the forecasts. With

little functional stake in the outcomes of the meetings, the PPS group tended to be vocal, objective, and

unemotional about the forecasts and demand planning.

Validation: Financial and Operational Assessment The final consensus forecast was sent to the finance department for financial roll up. Finance combined the

consensus forecast with pricing and promotion information from the BAP to determine expected sales,

thereby converting forecasted quantities into their revenue equivalents. Forecasted revenues were compared

with the companys financial targets. If gaps were identified, the finance group would first ensure that the

sales group was not under-estimating the products market potential. If revisions made at this point did not

result in satisfactory financial performance, the forecasting group would return to the business assumptions

and, together with the marketing department, revise the pricing and promotion strategies to meet financial

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goals and analyst expectations. These gap-filling exercises, as they were called, usually occurred at the end

of each quarter and could result in significant changes to forecasts. The approved forecast was released and

used to generate the master production schedule (MPS).

Operations validation of the final consensus forecast was an ongoing affair. In response to more consistent

and reliable MPSs, suppliers would improve the accuracy of information flows to Leitax about the status of

the supply chain and their commitment to produce received orders. More reliable MPSs also translated into

suppliers better prepared to meet future expected demand. Capacity issues were also communicated and

discussed in the consensus meetings. The feedback to the planning group provided by operations validation

in essence synchronized, and ensured compatibility between, the demand and supply plans.

Tactical Planning and Learning: The Other Roles of Consensus Meetings Consensus forecasting meetings were also planning meetings. The group considered new product

introductions and determined initial inventory for product launches. As a launch date drew nearer, the

consensus forecasting meeting was used to report the expected inventory status at launch, revise regional

requests, and seek consensus on regional allocations, taking into consideration any expected shortfalls.

Products to be discontinued in the current quarter were also discussed during the consensus forecasting

meetings. Proposed drop dates were presented together with sales to date, predicted sales for the rest of the

product life cycle, and available inventory. Consensus was sought on how a products end-of-life should be

managed.

For ongoing products, sell-in and sell-through rates and channel inventory were analyzed and compared to

expected sales. Finance aggregated channel inventory and sales data from resellers weekly EDI reports.

Discrepancies between reported inventories and inventories calculated from sell-in and sell-through data

were resolved and consensus sales forecasts updated based on the latest available information. Promotion or

price-change decisions were also revised in light of these data.

Throughout these tactical discussions, the group was, in effect, simultaneously planning supply and

demand operations. The consensus forecast and derived sales plans and master production schedules

reflected the strategic alignment between demand and supply plans, and the detailed discussion of product

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introductions, withdrawals, and replenishment ensured alignment down to the technical and operational level

(e.g., shipping schedules).

The consensus forecasting meeting was also a source of feedback on forecasting performance that

emphasized, specifically, biases exhibited by functional forecasts in past meetings. The DMO, being

responsible for forecast accuracy, continuously monitored this information and used it to improve its

forecasting algorithms and heuristics and to help functional areas improve their forecasting processes. In

recent meetings, for example, the DMO had presented evidence that sales forecasts tended to over-estimate

near-term and under-estimate long-term sales.

4.3 Performance Dramatic improvements in forecasting accuracy were observed by the fall of 2003. Three-month ahead sell-

thru (sell-in) forecast accuracy improved from 58% (49%) in the summer of 2002 to 88% (84%) (see Figure

3). DMO estimated, using a formula that reflected the fractional variance of the forecast error (FA=1-

ABS(sales-forecast)/forecast), the 13-week forecasting accuracy of both the sell-in and sell-through

forecasts, thirteen weeks being the longest lead-time for a principle component in Leitaxs supply chain.

Better forecasts translated into significant operational improvements: inventory turns increased from 12 the

previous year to 26 in Q4 03; average on hand inventory decreased from $55M to $23M (see Figure 4); and

excess and obsolescence costs decreased from, on average, $3M for financial years 2000-2002 to practically

zero in financial year 2003.

5. Analysis Having related the changes made by Leitax from the perspective of a coordination system, we can now

examine the resulting insights into the mechanisms that link these features to performance improvements.

5.1 The Role of Integrators As revealed by the examination of the context before Project Redesign, one issue at Leitax was lack of

alignment among its differentiated functions. The coordination system requires specific organizational

devices to promote integration that facilitates decision-making across functions and the general resolution of

ensuing conflicts to the approximate satisfaction of all parties and the general good of the enterprise. From an

organizational perspective, Leitax had recourse to two options for addressing the integration problems that

16

plagued it, (1) reduce the level of differentiation between the functions sufficiently to enable integration to be

achieved through existing approaches, or (2) develop a new coordination approach that could effect better

integration among the differentiated functions. Leitax primarily implemented process changes and

organizational devices that improved integration.

A common organizational arrangement for achieving integration across differentiated functional areas is

the integrating department. Lawrence and Lorsch (1986) found that six factors determine the effectiveness of

such integrating groups. Three of these factors relate to characteristics of the integrating group. Specifically,

integrators tend to be successful to the extent that they (1) are seen as having the most important voice in

cross-functional decisions, (2) are evaluated and rewarded in accordance with the overall performance of

cross functional decision making, and (3) have a departmental structure and orientation midway between

those of the other functions. The DMO had these attributes of a successful integrating department. The DMO

was publicly mandated to improve demand planning. The case study recounts a growing influence of the

DMO over demand and supply planning due, in part, to their competence and experience in managing these

processes. The DMOs incentives were based on forecast accuracy, which Fowler had realized early on was

in principle a cross-functional goal. The DMO exhibited flexibility and the ability to communicate with both

extremes of the organizational orientation spectrum, as reflected in its ability to take in detail sell-in forecasts

from the SDs and long-term aggregated global demand forecasts from the PPS group.

The other three factors that determine the effectiveness of integrating groups relate to interactions between

integrators and functional specialists. Effective integration is supported when (4) the managers in other

departments feel that they have influenced decisions, (5) this influence is concentrated at the managerial

level where decision-making knowledge is available, and (6) conflicts are confronted rather than avoided

(Lawrence and Lorsch 1986). At Leitax, these factors related both to organizational norms that were actively

generated and maintained by Fowler and the DMO and to features of the S&OP process. Recall that Fowlers

approach to implementing planning process changes was to generate functional support by promising total

functional involvement in forecasting and planning. The forecasting and planning group consequently

included individuals from different functions who had sufficient knowledge or influence related to

17

forecasting, planning, or execution. As its principal designers and maintainers, Fowler and McMillan ensured

that the S&OP process incorporated these factors as well. A hallmark of the S&OP process was collaborative

engagement, a feature we define as the extent to which functions commit to, and actively participate in,

collaborative activities. This engagement was visible in many areas of the S&OP process, as we discuss in

the following section. A relevant example related to conflict resolution is that, as moderated by Fowler and

McMillan, collaborative engagement in the consensus meetings enabled conflicts over forecasts to be

confronted rather than avoided.

5.2 Coordination System Process Within a decentralized planning context, integration is most straightforwardly operationalized as alignment,

that is, unity in action and purpose in the aggregate and also inter-temporally. In this section, we elucidate the

mechanisms implicit in the S&OP process that facilitate, either directly or through learning, the conditions

for coordinated planning derived from the information processing framework presented in 3.2. Specifically,

we assess how the process supports effective integration by examining its steps: information collection and

assessment; validation; and tactical planning and learning.

Information Collection and Assessment The BAP is both a component of, and a crucial first step in, the S&OP process. That consensus meetings

proved difficult to manage when dissemination of the information package was omitted from the process

strongly suggests that, in part, informational inefficiencies hindered integration between functions. It is also

likely that these inefficiencies negatively affected the quality of individual functional forecasts and plans.

The supply and demand plans and information about the market and competitors contained in the BAP

compensated for the following informational inefficiencies: functions not being acquainted with explicit

strategic plans in terms of the assumptions about assortments, pricing roadmaps, and so forth that they were

expected to support; and information or the interpretation thereof about competitors or the market, these

being private to specific functions. The BAP directly addressed these inefficiencies through the breadth of

relevant content for validation activities, as it provided not only a similar initial starting point with respect to

data, but also an interpretation of some of the data. Recall that the PPSs assessments of the threat levels of

competitors products helped to frame the problem space for functions in a manner that facilitated forecasting

18

and planning.

The manner in which the BAP was generated also fostered integration. Consensus in the S&OP process

was sought in the BAP and consensus forecasting meetings. But consensus is a loaded term. It is a stretch,

for example, to believe that all members believe the forecasts that are generated to be true. But what is true

about the BAP meetings and validation of the strategic plan in the consensus meeting is that all of the

functions have been engaged in developing the strategic plan. In the BAP meetings, the different functions

are engaged in determining, and collecting information relevant to assessing the implications of, the strategic

plan. We do not interpret engagement to mean only that members of the forecasting group and their

represented areas were passive recipients of shared information and interpretations thereof. What we

observed at Leitax was collaborative engagement, an active involvement by the participants in collecting,

validating, and processing information, and in voicing and defending their interpretations, resulting in greater

commitment to the resulting decisions.

Collaborative engagement in information collection and assessment. The collaborative engagement

that characterized this first step of generating the BAP provided two major benefits in terms of its effect on

the quality of the information package available to the functions. First, engagement led to the more complete

collection of information. As more functions became involved and actively engaged in its development, it

became more likely that the BAP would include private information and information required for planning.

Norms against private information and towards cooperative interpretation of public information were thereby

being established and reinforced. Second, in the aggregation step of generating the BAP, engagement implied

that the individual functions found the information accessible. Functional idiosyncrasies in its submission

that would hamper widespread dissemination of information were recognized and addressed here.

Idiosyncrasies in the interpretation and receipt of information were also acknowledged and adjustments made

as needed.

Validation The processes involved in validation influenced the effectiveness of planning at Leitax directly through their

effect on the quality of the rules of inference used to interpret the information package. Honest and complete

19

assessments are crucial to the proper validation of plans. Among the primary biases against which validation

processes needed to mitigate is that of desired outcomes that compromise assessments of plans validity. The

forecasting literature documents that this bias is mitigated by separating decision making from forecasting

(Armstrong 2001). The approaches employed in Leitaxs S&OP process to mitigate these biases were of two

types: specific mechanisms within a validation process that promoted focus and quality; and separate and

explicit validation that matched the concerns of each stakeholder.

Mechanisms within validation. Mechanisms that promoted focus and quality included the combination of

multiple forecasts in the consensus forecasting process and focus on sell-through instead of sell-in. It is well

known in the forecasting literature that combining forecasts, even through simple averaging, potentially

improves forecast accuracy (Lawrence et al. 1986). The emphasis on forecasting of sell-through provided a

reality check on sell-in forecasts, and shifted the focus away from sell-in, the sales organizations incentive

that could compromise forecast accuracy.

Separate and explicit validation. The separate and explicit validation step further improved the quality of

assessments. For example, introducing the practice of ignoring capacity constraints improved forecast

accuracy by separating demand from sales forecasting. The explicit validation approaches employed at

Leitax, moreover, ensured that functions individual concerns were considered. The separate but explicit

operations validation, for example, directed the influence of these concerns on plans appropriately so that

desired or undesired outcomes could be planned for rather than inappropriately assumed away. An example

of properly directed validation concerns is the manner in which the feedback from operations and finance

validations prompted changes to the strategic plan in the BAP, and then indirectly to the forecasts, rather than

inappropriately affecting forecasts directly.

Collaborative engagement in validation. The collaborative engagement described in the previous section

was also in evidence in plan validation. It improved the effectiveness of validation by providing mechanisms

within a particular validation approach and also by ensuring explicit, separate and diverse types of validation.

Recall that the sales force and product planning groups were actively engaged in forecasting via the

individual forecasting streams they created. In consensus forecasting meetings, the attending functions were

20

actively engaged in reconciling differences in the forecasting streams. Objections to the proposed consensus

forecast and differences between the subjective forecasts of sales or PPS and the statistical forecast were

frequent topics of discussion. By surfacing the private information (or private interpretation of public

information) that motivated objections, these discussions strengthened the quality of validation. Open

interaction and discussion that elicited from participants the logic used for their inferences served to filter

poor rules that might have been used to arrive at forecasts. Collaborative engagement was also in evidence in

validations that matched the concerns of different functions as the finance group, operations and even the

suppliers were all engaged via the validation of the logistical details of capacity requirements and financial

implications.

Collaborative engagement also fostered alignment with strategic plans. Engagement, such as the

operational planning involved in validation, led to a focus on the strategic plan. Functions subsequent

allocation of resources to support the plan reinforced it by generating operational momentum and impeding

the allocation of resources to the generation and pursuit of alternative plans. Engagement also led to more

locally-efficient plans for the functions. Locally-efficient plans, due to the involvement of the individual

functions in validation, possess a certain ease of execution that is important for alignment. Validation of

strategic plans via operational planning undoubtedly provided feedback that suggested specific changes to

facilitate execution by individual functions. Engagement increased the imprint of every function on the

strategic plan and its validation. The resulting plans possessed more explicit and total organizational

ownership, a quality that promotes alignment. Finally, engagement gave rise to the impression among

participants that the other participants would adhere to the plans, again, promoting alignment.

Tactical Planning and Learning in the Consensus Meetings As described in 4, consensus meetings were also planning meetings in the sense that specific tactical

contingencies or needs related to events such as product introduction or end-of-life were discussed.

Consensus meetings, beyond validation and the provision of feedback from validation, afforded the inter-

temporal coordination needed for execution. The frequent, well-attended meetings accommodated timely

dissemination of coordination signals that ensured execution of original or modified plans for new or end-of-

21

life products or mid product life replenishment. The consensus meetings also afforded participants an

opportunity for learning via feedback on process performance. Such feedback was particularly helpful

because it was not simply performance feedback, but could relate performance to specific process changes or

deviations for which participants had been responsible. This kind of constructive feedback, akin to root-cause

analysis, promoted learning by reducing process deviations, whether by voluntary conformance or by the

introduction of constraining mechanisms.

Collaborative engagement in tactical planning and learning. Collaborative engagement ensured that all

parties received the coordinating signals that initiated inter-temporal coordination and performance and

process feedback, which were particularly crucial for single-occurrence events such as new product

introductions and end-of-life situations. Performance and process feedback facilitated identification of

process deviations that required modifications to improve performance. Such feedback to the sales force, for

example, revealed short- and long-term biases in forecasting accuracy. If the sales force had internalized this

feedback but been unable to mitigate the bias, probably due to its short-term orientation, collaborative

engagement implied that a modification was likely needed to the process.

6. Discussion The quality of demand and supply planning can be roughly related to the quality of information used, the

quality of the inferences made from available data (e.g., forecasts and plans), and the organizations

conformance to the plans that are generated. The Leitax case study reveals an obsession on the part of the

creators of the S&OP process with ensuring consistency in the information flows, quality of decision-

making, validation of the decision-making process, and ability to transform decisions into actionable plans

sufficiently responsive to adjust dynamically to changes in the supply of parts and components or demand for

products. A significant fraction of the reported benefits, however, is not exclusively the result of a logical

and efficient information-processing algorithm. The coordination system (responsibilities, processes, and

structures) generated some organizational alignment, which was improved by the processs ability to engage

participants. It can be argued that improvements in forecast accuracy and other operating metrics were less

the result of a better forecasting process than of an aligned organization working with unity of purpose to

22

realize those forecasts and plans.

Collaborative engagement brought Leitax more complete and accessible information for the planning

process, sharpened-through-debate rules of inference, and more accurate and validated forecasts.

Engagement fostered by the S&OP process yielded efficient and coordinated functional plans, and strategic

plans that reflected not only the interests of the multiple stakeholders in the organization, but the functional

groups accountability for and explicit commitment to adherence. Finally, collaborative engagement opened

the S&OP process itself to scrutiny and continuous revision, enabling the agents charged with executing it to

adjust the process and improve its performance.

Leitax achieved this engagement not by reducing differentiation among the functional groups involved in

demand and supply planning, but by mediating that differentiation through an agency (the DMO) that was

held accountable for the resulting forecast and plans. The S&OP process implemented by Leitax was open,

transparent, and participatory, enabling all participants to influence outcomes, and explicitly confronted

conflicts between groups. Retaining functional differentiation, specifically their incentives, enabled the

participating functional organizations to maintain their focus on stakeholders needs. In contrast to strategies

that attempt to align incentives, differentiation at Leitax was accommodated, and used to empower

collaborative engagement towards the end of collective planning. Open debate and explicit accommodation

of conflicting functional goals moved the S&OP process from a coordination and information sharing

process (Dougherty 1992) to a highly integrated collaborative process (Pinto et al. 1993).

The unity of purpose and action, that is, alignment, that resulted from this planning process yields two

important benefits. First, as action plans become credible, accurate statements of organizational intentions,

the organizations reputation grows in the eyes of customers, suppliers, employees, and investors, affording

powerful leverage through trusted relationships. Second, if the organization is capable of executing according

to stated plans, the door is opened to continuous improvement as stable and predictable processes are the first

requirements for reliably interpreting historical data and making inferences for learning and improvement.

Given the benefits of alignment and resulting buy-in to the developed plan, an organization might be

willing to give up accuracy of information or efficiency of information processing if overall the process

23

affords alignment or conformance to plans. In fact, the DMO had evidence that for the second half of 2003

the statistical forecast was more accurate than the consensus forecast approved by the group. Although doing

so would save the cost of management time consumed in lengthy BAP and consensus forecast meetings,

Fowler was reluctant to streamline the process if it meant eliminating opportunities to engage participants

through confrontation and validation of the forecast and resulting plan. In the event of a major forecasting

error, absent a participatory process, the statistical forecast could be considered suspect and treated with the

same skepticism as the sales forecast had been treated prior to the Project Redesign.

The value of organizational alignment revealed through this study suggests a new dimension in the design

of coordinating systems that pursues, beyond the simple sharing of information and coordination of action,

organizational alignment.

7. Conclusion The purpose of case studies is not to argue for specific solutions but rather develop explanations (Yin 1984).

Still the question of how far an explanation goes to help with a particular range of problems is a fair one. In

terms of whether this is a problem faced by other firms, by breaking down the cause of the poor planning to

three prevalent causes in supply chain management mistrust of forecasts, functional differentiation, and

poor intertemporal coordination we are addressing a range of planning dysfunctions that may not show up

as specifically as they do at Leitax but are similarly engendered. We believe, and conversations with

management from diverse industries have confirmed, that these dynamics are not only prevalent in industry

but are also persistent. Similarly, when we examine the S&OP process and coordination system that were

implemented at Leitax, we are not trying to generalize a solution, but rather generate an explanation of why it

worked; thus our development of a coordination system, our abstraction of an information processing

framework for planning, and our discussion of engagement. Since these ideas (coordination system,

information processing framework, and engagement) are based on much broader theories and frameworks,

we expect the insights developed from them to be generalizable and fruitful for extension in other settings

requiring such cross-function integration. In general the evidence for generalizability comes from the

analysis of case site and the general nature of the theory used and generated (Meredith 1998).

24

Our findings have implications for practitioners and researchers. For practitioners, the Leitax case is, first

of all, a proof-of-concept that coordinating systems are capable of integrating both the information

requirements and advantages of simultaneous demand and supply management while retaining the

organizational differentiation required for different stakeholders to serve their constituencies. Furthermore, a

consensus planning system, with all its embedded advantages for buy-in and integration, was shown to be

capable of making prompt and responsive adjustments to plans in a dynamic and challenging supply chain

environment. Finally, the details of the coordinating system (responsibilities, structures, and processes) put in

place by Leitax make it clear that more is required to achieve true integration than the implementation of an

information sharing tool and the efficient information flows that result. For researchers in the supply chain

management area, the case illustrates the organizational and behavioral dimensions of coordination systems,

dimensions that, to our knowledge, have not been explicitly addressed before. The coordination system is

more than the definition of responsibilities, processes, and structures to bring together multiple functions and

organizations; it is also the explicit consideration of the social and organizational dimensions of the process

by which alignment is achieved. The case also shows the potentially powerful benefits of combining the field

of organizational behavior, which has a long tradition of recognizing the behavioral aspects of organizational

interactions, with operations management, which seeks to deepen its recognition of behavioral dynamics.

Recognition of behavioral dynamics within operations management can improve our understanding of the

mechanisms whereby processes and systems effect more efficient operations, which, in turn, can empower

the field to provide more actionable and effective process and system recommendations.

Bibliography Al-Mashari, M., A. Al-Mudimigh, M. Zairi. 2003. Enterprise resource planning: A taxonomy of critical

factors. Eur. J. Oper. Res. 146(2) 352-364. Anand, K.S., H. Mendelson. 1997. Information and organization for horizontal multimarket coordination.

Management Sci. 43(12) 1609-1627. Armstrong, J.S. (ed.). 2001. Principles of Forecasting: A handbook for Researchers and Practitioners. Kluwer

Academic Publisher, Boston. Ashby, W.R. 1956. An Introduction to Cybernetics. Champman and Hall, London. Barratt, M. 2004. Understanding the meaning of collaboration in the supply chain. Supply Chain Manag. 9(1)

30-42. Bower, P. 2005. 12 most common threats to sales and operations planning process. J. Bus. Forecast. 24(3) 4-

25

14. Chen, F. 2005. Salesforce incentives, market Information and production/inventory planning. Management

Sci. 51(1) 60-75. Christopher, M. 1998. Logistics and Supply Chain Management: Strategies for reducing costs and improving

services. Prentice-Hall, London. Crittenden, V.L., L.R. Gardiner, A. Stam. 1993. Reducing conflict between marketing and manufacturing.

Ind. Market. Manag. 22(4) 299-309. Dougherty, D. 1992. Interpretive barriers to successful product innovation in large firms. Organ. Sci. 3(2)

179-202. Eisenhardt, K.M. 1989. Building theories form case study research. Acad. Manage. Rev. 14(4) 532-550. Ellinger, A.E. 2000. Improving marketing/logistics cross-functional collaboration in the supply chain. Ind.

Market. Manag. 29(1) 85-96. Fawcett, S.E., G.M. Magnan. 2002. The rhetoric and reality of supply chain integration. Int. J. Phys. Dist.

32(5) 339-361. Funk, J.L. 1995. Just-in-time manufacturing and logistical complexity: A contingency model. Int. J. Oper.

Prod. Man. 15(5) 60-71. Glaser, B.G., A.L. Strauss. 1967. The Discovery of Grounded Theory: Strategies for Qualitative Research.

Wiedenfeld and Nicholson, London. Gonik, J. 1978. Tie salesmen's bonuses to their forecasts. Harvard Bus. Rev. 56(3) 116-123. Griffin, A., J.R. Hauser. 1992. Patterns of communication among marketing, engineering and manufacturing:

A comparison between two new product teams. Management Sci. 38(3) 360-373. Griffin, A., J.R. Hauser. 1996. Integrating R&D and marketing: A review and analysis of the literature. J.

Prod. Innovat. Manag. 13(3) 191-215. Hammond, J. 1994. Barilla (A). Harvard Business School, Harvard Business School Case, 694-046. Boston. Kahn, K.B. 1996. Interdepartmental integration: A definition and implications for product development

performance. J. Prod. Innovat. Manag. 13(2) 137-151. Kahn, K.B., J.T. Mentzer. 1996. Logistics and interdepartmental integration. Int. J. Phys. Dist. 26(8) 6-14. Kahn, K.B., J.T. Mentzer. 1998. Marketing's integration with other departments. J. Bus. Res. 42(1) 53-62. Kouvelis, P., M.A. Lariviere. 2000. Decentralizing cross-functional decisions: Coordination through internal

markets. Management Sci. 46(8) 1049-1058. Lapide, L. 2004a. Sales and operations planning Part I: The process. J. Bus. Forecast. 23(3) 17-19. Lapide, L. 2004b. Sales and operations planning Part II: Enabling technology. J. Bus. Forecast. 23(4) 18-20. Lapide, L. 2005a. An S&OP Maturity Model. J. Bus. Forecast. 24(3) 15-20. Lapide, L. 2005b. Sales and operations planning Part III: A diagnostic model. J. Bus. Forecast. 24(1) 13-16. Lawrence, M.J., R.H. Edmundson, M.J. O'Connor. 1986. The accuracy of combining judgmental and

statistical forecasts. Management Sci. 32(12) 1521-1532. Lawrence, P.R., J.W. Lorsch. 1986. Organization and Environment: Managing Differentiation and

Integration. Harvard Business School Press, Boston. Lorsch, J.W., S.I. Allen. 1973. Managing Diversity and Interdependence: An Organizational Study of

Multidivisional Firms. Harvard Business School Press, Boston. Malhotra, M.K., S. Sharma. 2002. Spanning the continuum between marketing and operations. J. Oper.

Manag. 20(3) 209-219. Mallik, S., P.T. Harker. 2004. Coordinating supply chains with competition: Capacity allocation in

semiconductor manufacturing. Eur. J. Oper. Res. 159(2) 330-347.

26

Malone, T.W., K. Crowston. 1994. The interdisciplinary study of coordination. ACM Computing Surveys 26(1) 87-119.

Meredith, J. 1998. Building operations management throry through case and field research. J. Oper. Manag. 16 441-454.

Miles, M., A. Huberman. 1984. Qualitative Data Analysis. Sage, Newbury Park, CA. O'Leary-Kelly, S.W., B.E. Flores. 2002. The integration of manufacturing and marketing/sales decisions:

impact on organizational performance. J. Oper. Manag. 20(3) 221-240. Oliva, R., N. Watson. 2004. What drives supply chain behavior? Harvard Bus. Sch. Working Knowledge,

June 7, 2004. Available from http://hbswk.hbs.edu/item.jhtml?id=4170&t=bizhistory. Pinto, M.B., J.K. Pinto, J.E. Prescott. 1993. Antecedents and consequences of project team cross-functional

cooperation. Management Sci. 39(10) 1281-1297. Porteus, E.L., S. Whang. 1991. On manufacturing marketing incentives. Management Sci. 37(9) 1166-1181. Raman, A., N. Watson. 2004. Managing global supply chains. In Quelch, J. A., R. Deshpande (eds.), The

Global Market: Developing a Strategy to Manage Across Borders, Jossey-Bass, San Francisco, CA, pp. xx-xx.

Ruekert, R.W., O.C. Walker. 1987. Marketing interaction with other functional units: A conceptual framework and empirical evidence. J. Marketing 51(1) 1-19.

Shapiro, B.P. 1977. Can marketing and manufacturing co-exist? Harvard Bus. Rev. 55(5) 104-114. Simon, H.A., A. Newell. 1972. Human Problem Solving. Prentice-Hall, Englewood Cliffs, N.J. Skjoett-Larsen, T., C. Thernoe, C. Andresen. 2003. Supply chain collaboration: Theoretical perspectives and

empirical evidence. Int. J. Phys. Dist. 33(6) 531-549. Stank, T.P., P.J. Daugherty, A.E. Ellinger. 1999. Marketing/Logistics interaction and firm performance. Int.

J. Logistics Man. 10(1) 11-24. Stank, T.P., S.B. Keller, D.J. Closs. 2001. Performance benefits of supply chain logistical integration.

Transport. J. 41(2-3) 32-46. Stonebraker, P.W., R. Afifi. 2004. Towards a contingency theory of supply chains. Manage. Decis. 42(9)

1131-1144. Troyer, L., J. Smith, S. Marshall, E. Yaniv, S. Tayur, M. Barkman, A. Kaya, Y. Liu. 2005. Improving asset

management and order fulfillment at Deere & Company's C&CE division. Interfaces 35(1) 76-87. Van Dierdonck, R., J.G. Miller. 1980. Designing production planning and control systems. J. Oper. Manag.

1(1) 37-46. Van Landeghem, H., H. Vanmaele. 2002. Robust planning: A new paradigm for demand chain planning. J.

Oper. Manag. 20(6) 769-783. Yano, C.A., S.M. Gilbert. 2004. Coordinated pricing and production/procurement decision: A review. In

Chakravarty, J. E. (ed.), Managing Business Interfaces: Marketing, Engineering, and Manufacturing Perspectives, Springer, New York, pp. 39-xx.

Yin, R. 1984. Case Study Research. Sage, Beverly Hills, CA.

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Figure 1. Initial Situation

Operationsinfo

Financeinfo

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.

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.

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Figure 2. Sales and Operations Planning Process

Gap-fillingActivities

InformationCollection and

Sharing

AggregateValidation

Financial andOperationalValidation

FunctionalValidation

Forecast AccuracyAssessment

BAP FunctionalForecastsConsensus

Forecast

Financial Forecast & Supplier Commitments

Assumptions Changes

ForecastFeedback

ForecastFeedback

Figure 3. Forecast Accuracy Performance

0%

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Dec-Feb 2002 Mar-May 2002 Jun-Aug 2002 Sep-Nov 2002 Dec-Feb 2003 Mar-May 2003 Jun-Aug 2003 Sep-Nov 2003

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Figure 4. Inventory Turns Performance

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