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Supply Chain

Collaboration:Making Sense of theStrategy Continuum

MATTHIAS HOLWEG,MIT and Judge Institute of Management

STEPHEN DISNEY, Cardiff University

JAN HOLMSTROM, Helsinki University of Technology

JOHANNA SMAROS,Helsinki University of Technology

Collaboration in the supply chain has been widelydiscussed, and a wealth of concepts is at hand.Large-scale projects like the Efficient ConsumerResponse (ECR) in the fast moving consumer goodssector, for example, or Vendor Managed Inventory(VMI) and Collaborative Planning, Forecastingand Replenishment (CPFR) initiatives more gener-ally provide a rich continuum of strategies for col-laborating amongst supply chain partners. Whileindividual successful implementations of the latterhave already been reported, there has not yet beenthe widespread adoption that was originally hopedfor. In our research, we looked at implementationsacross several industries and countries, and ourfindings show that the slow progress to date maybe due to a lack of common understanding of theseconcepts, and the difficulty of integrating externalcollaboration with internal production and inven-tory control. In this paper, we set out to classify col-laboration initiatives using a conceptual water-tankanalogy, and discuss their dynamic behavior andkey characteristics. We draw upon case studies fromboth successful and less successful implementa-tions to illustrate what companies need to do to fullybenefit from their collaborative efforts, given theirparticular circumstances. We conclude that theeffectiveness of supply chain collaboration reliesupon two factors: the level to which it integratesinternal and external operations, and the level towhich the efforts are aligned to the supply chain set-tings in terms of the geographical dispersion, thedemand pattern, and the product characteristics.2005 Elsevier Ltd. All rights reserved.

Keywords: Supply chain, Collaboration, Strategy,Bullwhip effect

Collaboration in the Supply Chain Behind Expectations?

Supply chain collaboration has been strongly advo-cated by consultants and academics alike since themid 1990s under the banner of concepts such asVendor Managed Inventory (VMI), CollaborativeForecasting Planning and Replenishment (CPFR),and Continuous Replenishment (CR).1 It is widelyaccepted that creating a seamless, synchronized sup-ply chain leads to increased responsiveness andlower inventory costs. The concepts are simple andpowerful, and individual success stories have beenreported across many industry sectors. Yet main-stream implementation within these industries hasbeen much less prominent than expected, whichseems surprising considering the benefits that ini-tially had been claimed. In our view, one importantreason is that collaboration practices are not wellunderstood; despite their superficial simplicity, theseconcepts are not at all as well defined as one wouldhope. For some, supply chain collaboration meanssimply holding consignment stock; for others it is acomplete philosophy on how to control the stockreplenishment and production rates across multipletiers of their respective supply chain system.

170 European Management Journal Vol. 23, No. 2, pp. 170181, April 2005

doi:10.1016/j.emj.2005.02.008

European Management JournalVol. 23, No. 2, pp. 170181, 20052005 Elsevier Ltd. All rights reserved.

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In our research, we have analyzed a wide range ofimplementation cases in supply chains across differ-ent industry sectors. Primarily, we have worked witha range of companies in the grocery supply chain with both multinational manufacturers as well aslocal manufacturers in the United Kingdom and the

Nordic countries. On the retail side, we worked clo-sely with several large retailers in Finland and in theUK. In addition, we have analyzed supply chaincollaborations with individual companies in theautomotive, electronics and construction sectors, tocomplement our findings.

In comparison, collaborative efforts in the grocerysector have been the most developed. Yet even herewe have found accounts of both success and of unex-pected difficulty, which mirrors recent commentsmade by proponents of Efficient Consumer Response(ECR), who find a growing number of supplier com-

panies very critical of the way supply chain collabo-rations have turned out in practice (Corsten andKumar, 2003). Let us explore why such simple con-cepts can be so difficult to implement, what pitfallscompanies have encountered, and what companiesneed to do to get the most out of collaborating withtheir supply chain partners. To this extent we developa framework to guide companies in their choice of thetype of collaboration best suited to their particularcircumstances.

Visibility The Holy Grail

Collaboration in the supply chain comes in a widerange of forms, but in general have a common goal:to create a transparent, visible demand pattern thatpaces the entire supply chain. Several seminal studieshave identified the problems caused by a lack of co-ordination, and to what extent competitive advantagecan be gained from a seamless supply chain (Forrester,1961; Leeet al., 1997; Chen et al., 2000). Also, there islittle doubt that the success of the Japanese manufac-turing model is largely attributed to their collaborativesupply chain approach and the tight integration of

suppliers in Just-in-Time delivery schemes (Dyer,1994; Hines, 1998; Liker and Wu, 2000).

Recent studies on the other hand have questioned thebenefits of demand visibility, and in particular, thebenefits of information sharing. Some critics arguethat the benefit of reducing delays and replenishmentbatches exceeds the benefit of information sharing,see for example Carlsson and Fuller (2000), whereasothers point out that the order history already avail-able to the supplier provides the same informationas information sharing if both supplier and retailerknow the stochastic properties of demand and these

do not change over time (Raghunathan, 2001).

This underscores the fact that, however well thoughtout in theoretical/simulation models, in practice the

issue of how to benefit from external collaborationand use demand visibility to improve capacityutilization and inventory turnover is still not wellunderstood (Lapide, 2001). Firms often have diverg-ing interests in the short term, and such conflicts ofinterest mitigate the commitment of supply chain

collaboration and fully sharing demand information(Cachon and Lariviere, 2001).

Furthermore, the complexity of todays businessworld means that it is often impossible to link exter-nal sources of information into the vendors produc-tion and inventory control processes (Stank et al.,2001), as in many cases the same level of detailedinformation cannot be obtained from all of the distri-bution channels. We also learnt that many companiesdo not integrate the information received from theirsupply chain partners into their own operations.For example, large multinational manufacturers typ-

ically do not use the information gained through col-laboration to fine tune their day-to-day operations,but collect it in business data warehouses and useit off-line in process development and performancemeasurement studies. Considering the high hopesfor the potential benefits derived from harnessingglobal demand visibility through collaborative plan-ning to improve supply chain efficiency, this marks itas a rather sobering account of the current state ofsupply chain collaboration.

Reducing uncertainty via transparency of informa-tion flow is a major objective in external supply chain

collaboration. Unpredictable or non-transparent de-mand patterns have been found to cause artificial de-mand amplification in a range of settings (alsoreferred to as the bullwhip or whiplash effect).This leads to poor service levels, high inventoriesand frequent stock-outs. Typically, studies cite de-mand visibility as the key antidote to deal with thiscostly effect (Forrester, 1958; Sterman, 1989; Leeet al., 1997). But how can this be achieved in practice,when a supplier has hundreds of stock-keepingunits, and hundreds of customers to consider? Whatare the challenges of increasing the use of customerinformation in the production and inventory control

decision when moving from a traditional system to acollaboration framework? The different types of con-cepts at hand differ drastically in the external infor-mation sources used for production and inventorycontrol, as we will discuss in the following. Thus,in the light of the complexity of todays global supplychains, it is not obvious which approach is best atintegrating external supply chain collaboration withinternal production and inventory management pro-cesses under the given circumstances. Unsurpris-ingly, many find it is hard to reap the full benefitsfrom their efforts of collaborating with their supplychain partners.

To guide our investigation on what makes it so diffi-cult to link external supply chain collaboration andinternal production and inventory management

SUPPLY CHAIN COLLABORATION

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processes we develop a simple framework to identifythe alternative configurations a water tank analogyrepresenting the inventory and ordering policies in

the system.2 We will use this analogy to discuss thefour basic supply chain configurations that we haveencountered in practice from a traditional supply

chain to a supply chain sharing both demand visibil-ity and decision-making responsibility with suppli-ers. We discuss the subtle but crucial differences inthe control of material flows, the use of informationflows, and the decision-making processes. We high-light the opportunities and challenges of each stage,and discuss under what circumstances to apply theseconcepts.

Classification of Concepts forCollaboration

Despite their superficial simplicity, we have come tothe conclusion that the concepts for supply chaincollaboration are not as well defined as they shouldbe. In fact, we often found that managers useddefinitions interchangeably results of their imple-mentation efforts varied accordingly. Granted, thedifferences in ordering and replenishment policiesmay be subtle, but the consequences for the dynam-ics of the supply chain can be drastic, which makes itever more important to be specific. We have identi-fied four different supply chain configurations,

which will be discussed and compared (see Figure1). The configurations are distinguished by the differ-ences in inventory control and the planning collabo-ration.

We have chosen the collaboration on inventoryreplenishment and forecasting as our dimensions inthis model. Admittedly, there are more dimensionsthat one can collaborate on, such as the promotions

or new product introductions, however these arethe ones most commonly used in practice. Further-more, as Fisher (1997) points out, factors such asproduct characteristics equally have an effect on thesystem. We discuss these as contingent factors inour framework.

A set of water tank models will be used to describeeach of the four categories of collaborative arrange-ments in supply chains (Holmstrom et al., 2003).The supply chain watertank model is shown belowinFigure 2(a). We can see that there are two orderingdecisions (the ball-cock valves) in series to describea simple two level supply chain. Water representsinventory and the flow of water represents sales ofproducts.

Type 0 The Traditional Supply Chain

Definition. Traditional means that each level in thesupply chain issues production orders and replen-ishes stock without considering the situation at eitherup- or downstream tiers of the supply chain. This ishow most supply chains still operate; no formalcollaboration between the retailer and supplier.

In Type 0 supply chains the only information that isavailable to the supplier is the purchase order issuedby the retailer. Relying on purchase orders only often

cause the bullwhip problem, as there is no visibilityof the actual demand, so the human psyche is

Inventory Collaboration

YesNo

Planning

Collaboration

Yes

No

Type 0

Traditional

Supply Chain

Type 1Information

Exchange

Type 3Synchronized

Supply

Type 2

Vendor

Managed

Replenishment

Figure 1 Basic Supply Chain Configurations for

Collaboration

Figure 2 (a) Our Water-tank Model; (b) In a Traditional

Supply Chain, the Bullwhip Effect is Generated by

Independent Ordering Decisions at Each Level



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tempted to order some just-in-case. In his seminalexperiment with the so-called Beer Game, John Ster-man showed that multiple ordering decisions, delaysand also the human tendency to over-order in uncer-tain times to play it safe caused dynamic distortionsin the supply chain (Sterman, 1989). As a result, the

variance of orders increases as demand moves upchain, causing significant costs in the system. It hasbeen estimated that the economic consequences ofthe bullwhip effect can be as much as 30% of factorygate profits for manufacturing companies (Metters,1997). Bullwhip leads to excessive inventory invest-ments throughout to cope with the increased de-mand uncertainty, reduced customer service due tothe inertia of the production/distribution system,lost revenues due to shortages, reduced productivityof capital investment, increased investment in capac-ity, inefficient use of transport capacity, and in-creased missed production schedules, Carlsson and

Fuller (2000). Essentially, the bullwhip problemcomes with every plague in Pandoras industrial box.

InFigure 2(b), we have overlaid the water-tank anal-ogy with an example from the grocery retail chain,where the actual demand signal from the customersin the supermarket for a soft drink is amplified manytimes before it reaches the soft drinks supplier. Ascan be seen, the demand for this soft drink is rela-tively steady, shown here in the EPOS (electronicpoint of sale) data, taken directly from the check-outsin the supermarkets. The second level shows the or-ders placed by the stores on the regional distribution

center (RDC) to replenish the drinks sold. Already, acertain increase in variability can be observed,caused by some stores overordering, and the fact thatthe packaging used means that only a multiple of 12drinks can be ordered at a time. The orders placed bythe RDC on the drinks supplier however bear noresemblance to the actual sales to the final customer.Here, the purchaser at the RDC simply ordersagainst his own demand forecast, and unknowinglyamplifies the demand variability many times. Thelargest weekly order placed on the supplier is205,000 cases, which is no less than five times theaverage weekly sales volume in the supermarkets.

Although the presence of bullwhip becomes veryobvious once the demand patterns of all tiers in thesupply chain are plotted over time, as in this softdrinks case, one should not assume it is easy to solve.First, only once the corresponding demand data of alltiers in the system is actually analyzed does the effectbecome apparent, and even then it is not a trivialproblem to solve. The bullwhip problem is embed-ded in the structure of such traditional supply chainswhere each level decides independently on theirordering, and is therefore very difficult to avoid.The supply chains structure (mainly in terms of

decision tiers and delays in information and materialflows) drives its dynamic behavior a problem wehave encountered across all industry sectors weinvestigated.

In our research with SOK, a major Finnish grocery re-tailer, we analyzed the consumption (purchases byconsumers) of a washing detergent in its chain of re-tail stores in Finland. The weekly variability of con-sumer demand over the long-term average demandis less than 10 percent. The shops are all replenished

from a distribution center operated by the chain.When the shop orders placed on the distributionchain for the detergent from all the shops in the retailchain are aggregated however, the weekly variabilityover the long-term average demand is already some-what higher, on average 26 percent higher. The nextstep in the chain is the manufacturer. The majordetergent manufacturers typically produce deter-gents for all markets in Europe in focused manufac-turing plants. By the time the order gets to themanufacturer, the demand variability was amplifiednine times between the local market and the Euro-pean manufacturing plant, due to the aggregation

of purchase requests and production orders into lar-ger batches.

Interestingly, despite the obvious disadvantages, themanufacturer is reluctant to pursue anything otherthan a traditional supply chain structure because ofthe geographical distribution. At the time, the com-pany had six focused plants each producing a limitedrange of products for all of the more than 15 localsales companies supplying hundreds of large distrib-utors and retail chains across Europe. Because of thisstructure one collaboration implementation withanyone of the, say, 50 largest customers would also

need to be implemented in each manufacturingplant. Not all of the largest customers are willing tocollaborate in the same fashion. Further, some seetheir purchasing flexibility as a core competence,often taking advantage of low prices and promo-tions, and do not want to jeopardize this mechanismin which they compete against their competitors.

Type 1 Information Exchange

Definition: Information exchange (or information

sharing) means that retailer and supplier still orderindependently, yet exchange demand informationand action plans in order to align their forecasts forcapacity and long-term planning.

Taking end customer sales into consideration whengenerating the forecast at supplier level even whencomplete visibility is not available is a majorimprovement over simply relying on the orders sentby the retailer. Delays in translating the demand sig-nal are removed, and unnecessary uncertainty iseliminated.

Information sharing not only helps to create morevisible and predictable demand in the system, butis also easier to implement than complete customer-specific control processes. Taking information sharing



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one step further is collaborative forecasting. This stepis frequently advertised as a key objective in animplementation of VMI, but is less frequently taken.The reason is that the customer often does not have aforecasting and planning process in place that canprovide the supplier with information on the level

of detail required, and at the right moment in time.Linking the customer and supplier planning pro-cesses on a sufficiently detailed level is also a corner-stone towards implementing the CPFR strategy(Figure 3).

Another example from the consumer goods industryillustrates a typical implementation of informationsharing. As part of developing the customer-supplierrelationship a multinational consumer goods com-pany tries to collect inventory reports and sales fig-ures from large customers on a weekly basis. Tofacilitate this process the company has developed

both web-portals and standard messaging formats.The company has also taken a central role in devel-oping standards for information sharing in theindustry. However, despite the significant effortsspent on improved information sharing, a formalprocess is in place only with a handful of customers.

Why is it difficult for companies to reach a stagewhere forecasts are developed in collaboration withsupply chain partners? The case company abovehas weekly visibility of sell-through data, and at besttimes also sees the EPOS3 from up to 80 percent of itsdistributors and wholesalers. Still the company fore-

casts demand between itself and the distributor, andnot between the distributors and retailers or consum-ers. This is done because campaigns and promotionsare laborious to manage for a specific retail chain ordistributor, as in this case inventory policies alsooften change depending on the risk of obsolescenceand stock-outs. Large and seasonal peaks in demandintroduce further complications. By aggregating aforecast of what the distributor requires, the impactof distributor specific inventory strategies and differ-ences in policies is handled by human planners infor-

mally. This is a simpler solution on the salescompany level, especially as some distributors mayfind it to be to their advantage to stop providingthe sell-through and EPOS information or distort itin shortage situations.

Type 2 Vendor Managed Replenishment

Definition: Type 2 means that the task of generatingthe replenishment order is given to the supplier, whothen takes responsibility for maintaining the retai-lers inventory, and subsequently, the retailers ser-vice levels.

Under vendor-managed replenishment settings, thecustomer has given the responsibility for placing

replenishment orders to the supplier. Having full vis-ibility of the stock at the customers site, the supplieris wholly responsible for managing the inventory.That way, the inventory investment needed to main-tain customer service levels can potentially be re-duced. In effect the supplier has a dedicatedprocess to generate exactly the same replenishmentorders based on the same information that the cus-tomer previously used to make its purchase deci-sions. The difference is that in shortage situationsthe supplier prioritizes customers for whom it isresponsible for managing the inventory.

Vendor Managed Replenishment (VMR), also oftenreferred to as Vendor Managed Inventory (VMI), isa major cornerstone of the Efficient Consumer Re-sponse initiative in the grocery sector, and there aresimilar developments in the textile sector calledQuick Response Manufacturing (QRM) (Kurt SalmonAssociates, 1993; Hunter, 1990). Here, suppliers man-age inventory replenishment cycles for the customerin order to speed up the supply chain and cope withshort product life cycles.

It should be noted here that consignment stock ismerchandise which is stored at the customers site,

but which is owned by the supplier. The customeris not obliged to pay for the merchandise until theyremove it from consignment stock. The customercan usually return consignment stock, which is un-used. Counter to common perception, this arrange-ment is also a Type 0 supply chain, and is notsimply another term for vendor-managed inventory(as many managers wanted to make us believe). Thereason is because the change in the ownership of theinventory does not change how the replenishmentorders are generated: the same decisions are beingmade, based on the same information as in a tradi-tional supply chain, and thus no dynamic benefit is

derived.

Undoubtedly there are benefits in centralizing deci-sion making in the supply chain. However, from a

Figure 3 A Type 1 Supply Chain Uses Demand Infor-

mation to Improve the Suppliers Forecasts



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supply chain dynamics perspective, nothing funda-mental has changed because the same amount andtype of decisions are still being taken. When imple-menting vendor-managed replenishment, suppliersdo not make the final step and incorporate the cus-tomer information into their own production and

inventory control process. The supplier hence losesout on an important opportunity: in principle, thecustomers inventory and sales information is avail-able for the supplier to use for controlling his ownproduction and inventory control process, but wefound that in practice the supplier does not use thisinformation for his production and inventory controlprocesses. Why is it that the demand information isnot being used to improve the suppliers orderingprocesses?

The challenge is that the retailer is typically only oneof many customers of the supplier. Generating the

replenishment order in the place of the customerspurchasing department is straightforward, even formany customers at a time. It is much more difficultto set up a production and inventory managementsystem that can integrate all customers requests intothe production and inventory control process. Andsimply setting up a production and inventory controlprocess specifically for a single large customer which is not integrated with that of the rest of thesupplier company may cause problems. For exam-ple, more safety stocks, smaller production batchesor longer intervals between production runs maybe the result (Figure 4).

The problem here is that there are still two decisionpoints. The Type 2 approach, in fact, could eliminatebullwhip completely, but as two decisions are madethe danger of misalignment remains and the oppor-tunity is lost. Casting two separate decisions alsomeans that two safety buffers have to be held. If asupply chain could be configured to have a commondecision-making point, and one common inventorylevel it would have the potential to be dynamically

very stable. However, because players dont knowhow to use the available information, they are con-tent with collaborating on replenishment. We haveobserved this effect in several supply chains, and itis the most common end-result of supply chain col-laboration efforts. In our research with a UK soft-

drinks manufacturer, selling to one of the largestsupermarket chains in the UK, we have seen thatthe retailer can and does pass sell-through data andinventory levels to the manufacturers plants. Thesupplier exploits this information implicitly in strate-gic planning issues, such as capacity planning andmanning levels in the factory. But at the end of theday, the supplier is still left wondering how itswidely fluctuating delivery schedule is generated,and is surprised when it does not match the sell-through data. In our study, we have observed afive-to-one increase in the bullwhip effect at eachlevel of this two echelon supply chain, because the

manufacturer does not exploit the consumptioninformation at a tactical planning level. This matterwas further complicated by the fact that the super-markets were open every day of the week and thesoft-drink supplier only produced on five days perweek.

Hence, despite sharing operational and forecastinformation, we have found that few companies areable to fully exploit the advantages of collaborationin their supply chains even if a sophisticated sys-tem for CPFR is put in place. Let us explore what ittakes to reap the full benefits of collaboration.

Type 3 Synchronized Supply

Definition: Synchronized supply eliminates one deci-sion point and merges the replenishment decisionwith the production and materials planning of thesupplier. Here, the supplier takes charge of thecustomers inventory replenishment on the opera-tional level, and uses this visibility in planning hisown supply operations.

In our research we have seen companies benefitingfrom collaboration in several ways. Most commonly,collaboration gives suppliers a better understandingand ability to cope with demand variability animportant feature when trying to counter the costlybullwhip effect. Also, companies have achieved min-or improvements in inventory turnover.

However, the critical step that many companies havenot been able to take so far is to incorporate customerdemand information into their production andinventory control processes. We found that compa-

nies that do collaborate typically exchange informa-tion on a high-level, but the production planningprocess remains unchanged, thus foregoing theopportunity for a radical improvement of the

Figure 4 A Type 2 Supply Chain, Where the Supplier

Has Sufficient Information to Eliminate the Bullwhip

Effect, but Often Finds It Difficult to Exploit It



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dynamics in the supply chain. In our view, the criti-cal feature is not only to exchange information, butequally, to alter the replenishment and planningdecision structure. In our water-tank model, thiswould correspond to linking the two tanks together.The demand at the retailer drives the combined

inventory and production control process, togetherwith feedback on complete supply chain inventory,rather than at individual tiers in the supply chain.That way, a range of additional benefits can beachieved (seeTable 1).

To illustrate what needs to be done to synchronizesupply with demand, let us consider our water-tankmodel again. If the supplier can incorporate the com-plete supply chain inventory level (the water level inthe tanks) into his production and inventory controlprocess, this would correspond to directly connect-ing (synchronizing) the two tanks, with the water

in the connecting pipe being the replenishment intransit. Now that the tanks are leveled it is possibleto achieve the additional benefits shown in Table 1;with both tiers synchronized by a single orderingdecision, the demand pattern cannot amplify, andthe bullwhip effect does not occur. Equally, since

both tanks are linked, the overall amount of inven-tory needed to meet end customer demand and buf-fer against uncertainty is much less. Whereaspreviously two safety buffers were needed, nowthere is only need for one. Also, the visibility ofend demand facilitates the control of production

capacity requirements (Figure 5).

One company that has achieved such synchroniza-tion of the supply chain with several of its customersis Cloetta Fazer, a Finnish chocolate maker. With itslocal plants serving the local Nordic markets, thecompany has been able in its Vantaa plant (in Fin-land) to substantially benefit from linking externalcollaboration to internal processes. The Vantaa planthas been eager to set up collaborative inventory man-agement solutions with any one of the 56 largestdistributors in its local markets. Through vendormanaged inventory and collaborative forecasting in

product introductions the company is able to priori-tize production requirements according to the avail-ability situation at the distributors. As a result, 3weeks of inventory have been removed from the sup-ply chain. This directly translates to significant costsavings as the company product is perishable. The

Table 1 Benefits of Supply Chain Collaboration and Synchronization

Benefits typically achieved through supply Additional benefits, typically not achieved without

chain collaboration: supply chain synchronization:

1. Collaborative forecasting enables better 1. Elimination of the bullwhip effect by linking the

customer service levels, or a reduction in inventory and replenishment decisions. This still is

inventory (but generally not both. In fact, a technical challenge, but modeling with real

in many cases these are traded off against demand shows how collaboration can filter out the

each other, or service levels are traded bullwhip effect (Smaros et al., 2003)

2. Reduce the rationing game by giving the 2. A reduction of inventory levels by up to 50%

supplier responsibility for replenishment without compromising customer service levels

However, if there is a general shortage this (Disney and Towill, 2003), and better utilization of

collaboration can quickly break down. For production capacity as the extended visibility of the

example, when demand for a product is supply chain provides a certain additional flexibility

rising dramatically, such as for mobile to prioritize or delay customer replenishment

phones or PDAs in the 1990s, vendor without compromising service levels, thereby

managed replenishment arrangements are reducing the need for capacity buffers (Walleret al., 1999)

supply. A distributor triggers an early 3. Better utilization of transportation resources,

replenishment by transferring inventory to because shared information allows for better load

other stocking locations, which the consolidation. For example, in the collection of used

supplier then would misinterpret as oil from reclaimed cars, collectors monitor the level

consumption, and replenish of oil in on-site tanks and uses this visibility to

exploit opportunities in the routing of collection

vehicles (le Blanc et al., 2004)

4. Controlling the risk for constrained components or

materials. For example, monitoring key items with

long-lead times can create an early warning system

of future supply constraints. For example,

Volkswagen introduced their e-Cap system to

control their engine supply, as the soaring demand

for diesel engines (and complexity of sharing theseacross the Audi, VW, Seat and Skoda brands)

threatened the continuity of meeting customer

orders on time



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product has a shelf life of 4 to 6 months, of whichmore than half has to remain when received by a

distributor. Thus removing inventory from the sup-ply chain directly translates into a fresher product,less obsolescence and fewer returns from thecustomers.

However, most importantly, a reduction of bullwhipin production and inventory control is achieved.Considering the stock held by large distributorsand the manufacturer equally as stock in hand whenmaking a decision on new production orders, auto-matically levels requirements on production. This issimply because shipping a quantity of product fromthe manufacturer to the distributor i.e. moving the

product from one part of the tank to the other doesnot create a requirement for producing more. Therequirement to produce more is only generated whenthe customer requires products, which in our anal-ogy is shown as the water leaving the tank alto-gether. Driving purchase requirements using thesame logic provides the further benefit of aligningsupply of long lead-time materials with demandmore quickly. For a food manufacturer this becomesespecially important at the introduction of newproducts.

Yet problems can remain. Linking internal and exter-

nal processes works well with relatively short dis-tances between the nodes. What happens, though,if retailer and supplier are far apart? Suddenly, theinventory and lead-time incurred in the transporta-tion becomes a crucial element. In this case, collabo-ration can be extended, and the supplier plansdistribution on the customer level in addition, whichis needed when there is a long transportation delayrelative to stock cover at the customer, or wherethe products are perishable. Stock that goes in andout of the transportation system will create wigglesin the inventory feedback loop in the suppliers pro-duction planning decision. This feedback loop can be

a serious cause of the bullwhip problem in supplychains with long lead-times, and endanger supplychain collaboration as demand appears to be moreerratic than it actually is.

Whilst linking the retailers and suppliers operationstogether is a fairly straightforward task for compa-nies located in the same market, the realities of globalsourcing create complications. In the past, when sup-pliers and retailers were located far apart, the trans-portation leg made joint inventory control often

impossible. With increasing proliferation of productidentification technologies, such as radio frequencyidentification (RFID), the possibilities of tightly con-trolling inventory pipelines even over long distanceshave today become feasible. Radio Frequency Identi-fication, or RFID, is increasingly introduced in thegrocery supply chain. As the technology maturesretailers are finding that the payback time for invest-ments, in terms of reduced obsolescence and han-dling costs, are shortening from two years tomonths. Currently the challenge is to identify thesavings for supplier companies that would justifythe investments (Karkkainen, 2003).

In the water-tank analogy inFigure 6, the eye refersto such an RFID system, which creates visibility ofthe pipeline stock, even across long distances. Hence,the system allows for the transportation batches to beincluded in the production and inventory controlsystem of the supplier. SE Makinen, a specialist cardistribution company, is a good example here. SEMakinen used to operate a standard enterprise sys-tem to control the inventory of cars on hand, whichmeant that for each compound a separate inventorycontrol system was needed. Today, SE Makinentracks each car individually using ID tags, and

regardless of the location of the car, it is visible tothe inventory controller. Tracking individual prod-ucts has replaced traditional inventory book-keepingper location, and the entire notion of stocking loca-tions, or separate water tanks.

Given the complete demand and inventory visibilityin such a system, it is not of relevance whose handis actually controlling the cup, i.e. who places thereplenishment order between supplier and retailer.For this very reason we do not like to refer to thisscenario as vendor managed inventory, as it impliesthat the supplier should in fact be in control of

Figure 5 Type 3 Supply Chain, Linking External

Demand and Inventory Information to Internal Produc-

tion Control

Figure 6 Linking External and Internal Ordering Deci-

sions in Long Lead-time Supply Chains. The Cup Rep-

resents the Transportation Batch



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ordering and replenishing. However, as can be seenfrom the water tank analogy, it is indeed ambivalentwhich tier handles this activity.

Making Sense of the CollaborationConcepts

Our research made us look at a wide range of collab-oration projects across industries. We have seen suc-cesses, showing the substantial benefits for supplychain partners that find the right collaboration solu-tions for their situation. However, we have also seenthat many collaborative projects fall drastically shortof their golden objective of synchronizing supply anddemand. We have found that there is not a one-fits-all solution to supply chain collaboration, as factorssuch as geographical dispersion, logistics lead-time

and product characteristics determine which leveland type of collaboration are most suitable for a par-ticular supply chain. We have identified a set of keyfactors that need to be considered before beginningefforts towards synchronizing the supply chain (seeTable 2):

Geographical dispersion is an important factor fortwo reasons: first, the more individual nodes thereare between supplier plants and customer sites, thegreater the effort to implement synchronization,and the smaller the return on the individual collabo-ration will be. Hence, a steep Pareto curve of cus-

tomer demand in terms of volume generally yieldsgreater benefits by implementing it with few maincustomers. For example, Cloetta Fazer, the choco-late-maker, has only two plants and four of its majorcustomers are in it is home market, so collaborationyields large benefits for them. On the other handwe have often heard from large suppliers that theyhave difficulties in finding use for shared informa-tion gained through supply chain collaboration.The detergent manufacturer we discussed earlieron the other hand has centralized plants that supplyall of Europe with a particular product line, hencethe benefit of collaborating even in one market with

all the customers will only be of limited impact. A

general mismatch between producing centrally, andcollaborating locally, inevitably dilutes the benefitsof such collaboration.

The characteristics of demand have a direct impacton the amount of inventory and capacity needed in

the supply chain. Seasonal products, such as icecream or lawn mowers, require seasonal and evenweather-dependent forecasting and safety buffers,which generally mitigates the benefits of synchro-nized ordering and common inventory control. Inthis situation information sharing captures the mainbenefits. For non-fashion driven products with stabledemand, such as toothpaste or beer, the benefits ofsupply chain synchronization can be realized withcomparatively little effort.

With respect to product characteristics, two factorsare important. First of all, the shelf life of the product

dictates the speed the supply chain should operateat. Consider highly perishable fruit and vegetables,such as strawberries, which have a shelf life of afew days only, and therefore are planned three timesa day by some retailers. Here, the potential cost ofobsolescence overrides the savings through econo-mies of scale in transportation and warehousingactivities. The opportunity to collaborate on inven-tory levels is not given, because inventory cannotbe kept in the first place. The main benefits can becaptured simply with information sharing and fore-casting collaboration. However, for goods such asbasic electrical appliances or canned food, efficiency

in the supply chain is derived from low inventorylevels and high capacity utilization, thus making syn-chronization very attractive.

Having discussed the types of collaboration and thefactors that are important to consider, the simplequestion that remains is what supply chain configu-ration should be used? Or, should all companiesstrive towards a synchronized Type 3 supply chain?From our analyses across industry sectors we havecome to believe that much of the frustration withthe lack of financial return on supply chain collabora-tion effort is due to the fact that many efforts are a

mismatch between the structure of the supply chain,

Table 2 Key Factors That Guide Supply Chain Collaboration Strategy

Factors Why important?

Geographical dispersion of The closer, and more dedicated supply is, the easier it is to

customers and supplier implement synchronized production and inventory control

plants

Demand pattern of the The more stable the products consumer demand, the greater the

product dynamic benefits of eliminating bullwhip and synchronizing

demand and supply in the system

Product characteristics, in The longer the shelf life or selling period of the product, theparticular selling periods more sensible it is to consider collaborative practices. Equally,

and shelf life, as well as The more valuable the product, the more impact tighter inventory

value control yields



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product characteristics, and the type of collaborationenvisaged.

A large, multinational supplier should focus syn-chronization efforts on the products that offer thebest opportunities of linking local demand with localsupply, aiming at aType 3system. For those productsthat are supplied centrally or regionally into manymarkets from a focused manufacturing plant thecost-benefit ratio for synchronization efforts will beaccordingly reduced. It still makes sense to gatherbetter demand information in such cases, aiming atType 1collaboration, but the effort required to imple-ment must be justified by benefits from better fore-casting. In many cases, in particular when there area large number of different customers and distribu-tion channels, moving away from a traditional Type0 supply chain is not economically viable.

We also have observed multinationals using Type 2,or vendor-managed replenishment (VMR) supplychain configurations under such circumstances. Type2 is very common in both manufacturing industriesfor the nuts and bolts, as in retailing for slow-mov-ing nonperishable products, such as stationery forexample. These systems greatly reduce the transac-tion costs of replenishing the stock, and in most casesare easy to establish and maintain. Yet they servemore of a customer service and a corporate market-ing purpose than to foster operational improve-ments for the supplier itself.

For smaller-size, local suppliers the situation is dif-ferent. Here the focus should be on synchronizingwith the major customers in their market, aiming ata Type 3 system. In fact one of the key benefits ofsmaller scale operations is increased customerresponsiveness, or responsiveness to local or specificcustomer needs, Pil and Holweg (2003). Withincreasing proliferation of RFID technology in logis-tics operations, the cost of controlling inventory isdecreasing, and thus opportunities for synchroniza-tion are extending even in the case of a longertransportation pipeline.

Supply chain collaboration is undoubtedly a worth-while target: jointly creating the common pace ofinformation sharing, replenishment, and supplysynchronization in the system reduces both excessinventory and is essential to avoid the costly bull-whip effect that is still prevalent in so many sectors.Yet our research clearly highlights that these bene-fits need to be seen in perspective. The right ap-proach for a company depends very much on theindividual settings that the supply chain has to dealwith in terms of dispersion of retailers and supplierplants, as well as in terms of the product character-

istics. Also, the understanding of what the differentconcepts for collaboration entail is often sketchy,and definitions vary considerably. Using ourwater-tank analogy, we hope to have provided a

useful point of reference that overcomes thisdeficiency.

Acknowledgement

Our research was supported by a range of researchprograms at Cardiff Business School, the Cam-bridge-MIT Center for Competitiveness and Innova-tion, and the BIT Research Centre at the HelsinkiUniversity of Technology. We would in particularlike to thank all participating companies for theirsupport, not all of which could be mentioned byname for confidentiality reasons, and our colleaguesat our respective institutions for their comments onearlier versions of this paper.

Notes

1. Seewww.cpfr.comand www.ecrnet.comfor more details.2. A similar water tank analogy has been used by George Plossl

(1985)to illustrate the interplay of order release rates, inventoryand lead-times in a single echelon manufacturing system.

3. Sell-through data refers to the product quantities movingthrough the distributor warehouses to the retail outlets. EPOS(Electronic Point of Sales) is the scanning data collected onconsumer purchases in the retail outlets.

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MATTHIASHOLWEG, Center forTechnology, Policy and

Industrial Development,MIT, and Judge Institute

of Management, Univer-sity of Cambridge,Trumpington Street,Cambridge CB2 1AG.E-mail: [email protected]

Dr. Matthias Holweg isResearch Associate at MIT

and Lecturer in Operations Management at the JudgeInstitute of Management. He researches into thedynamics and optimisation of supply chain systems,

focusing on implementation of demand-driven supplychain strategies in the global automotive industry.

STEPHEN DISNEY,Logistics SystemsDynamics Group, CardiffBusiness School, CardiffUniversity, AberconwyBuilding, Colum Drive,Cardiff CFIO 3EU.E-mail: [email protected]

Dr. Stephen Disney is

Lecturer in OperationsManagement at CardiffBusiness School, Cardiff University. His researchinterests lie in the mathematical modelling of supplychains and innovative e-business scenarios.

JAN HOLMSTROM,Logistics Research Group,BIT Research Centre,

Helsinki University ofTechnology, Helsinki POB

9555, Fin-0215, Finland.E-mail: [email protected]

Jan Holmstrom is Acad-emy Fellow of the Acad-emy of Finland and SeniorResearch fellow in Supply

Chain Management at Helsinki University of Tech-nology. His research includes collaborative forecastingand identity-based supply chain management.

JOHANNA SMAROS,Logistics Research Group,BIT Research Centre,

Helsinki University ofTechnology, Helsinki POB9555, Fin-02015, Finland.E-mail: [email protected]

Johanna Smaros is a doc-toral candidate in the

Department of IndustrialEngineering and Technol-

ogy, Helsinki University of Technology, researchinginto planning, forecasting and replenishment collabo-ration in supply chains.



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