International Journal of Production ResearchVol. 50, No. 4, 15 February 2012, 939–951

Prerequisites to vendor-managed inventory

Tarikere T. Niranjan*, Stephan M. Wagner and Stephanie M. Nguyen

Swiss Federal Institute of Technology Zurich, Department of Management, Technology, and Economics,Scheuchzerstrasse 7, 8092 Zurich, Switzerland

(Received 31 August 2010; final version received 3 December 2010)

Vendor-managed inventory (VMI) has become a widely used tool for supply chain performance improvement.However, not all VMI implementations are successful. Therefore, the aims of this research are to contributeto a better understanding of the critical issues surrounding VMI implementation, and to support corporatepractice with a methodology for evaluating the VMI readiness of firms. Fifteen features that determine thesuitability of VMI are identified. These can be broadly categorised as product-, company-, and supplier-related features. The framework developed in this research is validated through its application in 10 case studyfirms. The framework can be used by other firms to support the decision of whether or not to adopt VMI byproviding valuable insight into how firms score on suitability for VMI adoptions along several dimensions.

Keywords: supply chain management; vendor-managed inventory (VMI); case study research

1. Introduction

Supply chain co-operation has attracted increased attention among researchers in supply chain management (e.g.Langfield-Smith and Greenwood 1998, Gullu et al. 2005, Iida and Zipkin 2010, Wadhwa et al. 2010). Pioneered byWal-Mart and Procter & Gamble in the 1980s, and now implemented by many firms, vendor-managed inventory(VMI) is an important co-operation initiative where the supplier is authorised to manage inventories at customerlocations (Waller et al. 1999, Cetinkaya and Lee 2000).

Much has been written about the benefits of VMI since the 1980s. Many articles in the trade and academicliterature treat VMI’s superiority over traditional systems as a given. We believe, however, that the literature haslargely neglected to indicate when companies could benefit from using VMI (Dong et al. 2007, Sari 2007,Bookbinder et al. 2010). VMI may not be a universally applicable solution. Likewise, the potential benefits of VMIhave not always materialised. For example, Spartan Stores, a co-op grocery chain in Michigan, terminated its VMIprogramme because of higher delivery frequencies, inadequate forecasting capabilities by vendors, and inefficientco-ordination in promotions planning (Dong et al. 2007). Cooke (1998) has remarked that VMI could stand for‘very mixed impact’, and lists a number of firms that have abandoned VMI. One reason for abandoning VMI is thatit could impair visibility in the supply chain by transferring decision making authority to suppliers: ‘The farther yougo up the supply chain, the harder it is to see what’s going on’ (Cooke 1998, p. 51). Data inaccuracies and poor dataintegrity, as well as differences in technologies and systems employed by suppliers and buyers, are otherimpediments to successful VMI usage. Unless a firm sees value exceeding the cost burden of VMI, it may bereluctant to make the investments required to make the process function. Clearly, VMI is not for every firm.Therefore, practitioners need a toolkit that will enable them to determine when it makes sense to adopt VMI andwhen it does not.

This article identifies the prerequisites for VMI so that managers can evaluate their own supply chains and makebetter decisions about VMI. To accomplish this, the study uses insights from both academic and business literatureto identify these prerequisites. Next, information on the relative importance of these prerequisites is extractedthrough a survey with industry and academic experts, and crafted into a VMI readiness framework. The frameworkis then validated by 10 case studies.

*Corresponding author. Email: ttniranjan@ethz.ch

ISSN 0020–7543 print/ISSN 1366–588X online

� 2012 Taylor & Francis

http://dx.doi.org/10.1080/00207543.2011.556153

http://www.tandfonline.com

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2. Literature

2.1 Vendor-managed inventory

VMI is one of the most widely discussed partnering initiatives for improving multi-firm supply chain efficiency.Also known as continuous replenishment or supplier-managed inventory, it was popularised in the late 1980s byWal-Mart and Procter & Gamble. VMI became one of the key programmes in the grocery industry’s ‘quickresponse’. As Tyan and Wee (2003) showed from their study in the grocery industry, VMI can not only reduce costs,but also improve service levels and create business opportunities for both parties in the supply chain. VMI has beenimplemented by many leading companies from different industries, such as Campbell Soup, Johnson & Johnson andBarilla (Waller et al. 1999), GlaxoSmithKline (Danese 2004), Electrolux Italia (De Toni and Zamolo 2005), Nestleand Tesco (Watson 2005), Boeing and Alcoa (Micheau 2005).

Under VMI, the supplier makes the main inventory replenishment decisions on behalf of the buyingorganisation. This means that the ‘vendor monitors the buyer’s inventory levels (physically or via electronicmessaging) and makes periodic re-supply decisions regarding order quantities, shipping, and timing’ (Waller et al.1999, p. 183).

Although the potential benefits of VMI have been praised, little consideration has been given to the question ofwhen VMI makes sense (Dong et al. 2007). Although VMI can have many benefits, there are several impediments toits success (Fraza 1998, Holmstrom 1998, Kaipia et al. 2002). For example, great detail is required for planning,administrative costs are sometimes high and the processes of placing and filling orders can be much more ineffective.There have also been many failures on the part of the supplier to harness the customer-specific data for planning andproduction. In some cases, shortages have increased when finished goods have been reserved to a few prioritycustomers. In conclusion, VMI initiatives have failed or have been cancelled (Kuk 2004).

VMI is not a standard solution for all replenishment processes (Kaipia et al. 2002). In some situations, VMIoffers no benefits. In general, companies that do not have the proper prerequisites for VMI fail in theimplementation, and thus VMI becomes a disadvantage. It is important, therefore, to know when VMI will and willnot be beneficial.

Dong et al.’s (2007) study makes an important contribution by investigating the factors preceding firms’adoption of VMI. They used large scale survey-based exploratory research from a technology adoption perspective.Their study found that the supply chains where VMI was adopted were marked by greater competitiveness in thesupplier’s market, fewer operational uncertainties, and higher levels of buyer–supplier multifunctional co-operation.To that extent, their study provides valuable clues on when VMI ought to make sense. However, it does notnecessarily follow that the respondent firms that had or had not adopted VMI had made the right choice. Bycontrast, for this research, which has a prescriptive orientation, we broaden our search beyond Dong et al.’s (2007)study, and seek features that are known to be conducive to VMI.

2.2 Features impacting the suitability of VMI

We are interested in features of supply chains that previous literature posits to be prerequisites of successful VMI.These features (listed in the first column in Table 1) can be classified as product-, company-, or supplier-related.

Product-related features. These can be decisive in determining whether VMI makes sense. For example,Raghunathan and Yeh (2001) showed that VMI is likely to be more valuable for mature products with stableand large demand, and information sharing is likely to be more valuable for relatively new products with highdemand variances (Raghunathan and Yeh 2001). Standard product identification and an integrated informationsystem in the supply chain are also requirements for using VMI (Cooke 1998).

Product volume is another feature. A popular belief is that VMI is valuable only for high-volume items thatjustify the additional investment required for starting VMI. Disney and Towill (2003) studied the effects of VMI onthe bullwhip effect for both low- and high-volume production. The study showed that VMI does indeed havebenefits on both low-volume products that typically suffer from the Burbidge effect, and high-volume products thatsuffer from the bullwhip effect (Disney and Towill 2003). Franke (2010) concluded that contrary to popular belief,VMI can be successfully employed in small-volume production environments, and most firms are even planningto expand their VMI programmes. This corroborates Disney and Towill’s (2003) finding that VMI also providesbenefits to low-volume products.

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Table

1.Summary

ofcase

studysurvey

results.

Features

RUAG

Legacy

Louis

Widmer

Novartis

Ferring

Hilti

Daim

ler

ODLO

Merck

Serono

Procter

&Gamble

Product-related

1.

Productsare

standardised,i.e.

customisationisminim

al

(7.07)

00

02

33

32

24

2.

Productsare

repetitivei.e.

infrequentchanges

inproduct

specificationbycustomer

(8.04)

02

21

33

32

34

3.

Productshaveastandard

product

identification

throughoutthesupply

chain*(6.75)

14

42

34

42

44

4.

Dem

andvariance

islow

(4.82)

00

01

42

32

13

5.

Dem

andisforecasted

andstock

levelsare

closely

monitored*(7.40)

03

34

42

44

44

Product-relatedscore

765

65

70

114

97

116

83

100

132

Company-related

6.

Ourcompanyrevenues

havebeenstable

over

theyears

i.e.

neither

grownrapidly

norfallen

(3.86)

42

43

42

24

34

7.

Transactioncostspertainingto

purchasingare

high

(5.14)

22

01

23

32

21

8.

Inform

ationandcommunicationsystem

sare

good*

(6.75)

20

43

12

42

33

9.

Thecompanyhasnoproblem

sharinginventory/forecast

inform

ationwiththesuppliers*

(9.97)

10

23

14

34

44

10.

Purchasingisacore

competence

ofourorganisation

(7.07)

22

24

43

24

24

Company-relatedscore

63

32

77

95

71

98

94

107

96

109

Supplier-related

11.

Highlevelsoftrust

andlongterm

relationshipswiththe

suppliersexist*

(7.72)

22

42

42

23

44

12.

VMIbenefitsare

evidentto

both

ourcompanyandour

suppliers(7.07)

20

03

13

34

43

13.

Key

suppliersconstitute

ahighpercentageofpurchase

orders*

(5.14)

33

42

13

34

44

14.

Suppliersare

willingto

cooperate

withaVMIinitiative

(8.68)

21

23

22

33

44

15.

Thecompany’sinform

ationsystem

isintegratedwiththe

suppliers*

(4.50)

00

02

10

33

44

Supplier-relatedscore

62

40

69

82

65

69

92

112

132

125

VMIreadinessscore

132

137

211

247

250

264

302

302

328

366

Score

range

0–200

0–200

201–300

201–300

201–300

201–300

301–400

301–400

301–400

301–400

Decided

touse

VMI?

No

No

No

Yes

No

Yes

Yes

Yes

Yes

Yes

Notes:Academ

icandindustry

experts

ratedthefeaturesonascale

rangingfrom

0(‘notim

portantatall’)to

4(‘highly

important’).

Case

studyrespondents

ratedtheitem

srangingfrom

0(‘notapplicable

atall’)to

4(‘highly

applicable’).

Item

smarked

withanasterisk(*)are

controllable/improvable

features,theothersare

not.Theasterisksare

provided

hereforease

ofpresentationanddid

notappear

intheoriginalsurveys.

Figuresin

parentheses

nextto

item

sare

theitem

weights

expressed

inpercentage.

They

did

notappearin

theoriginalsurveys.

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Another misconception is that VMI can only be used for low-value parts because critical/high value items needto be handled in-house for greater control. Franke (2010) showed how several firms in his study have been practisingVMI even for high-value parts for more than 10 years and continue to extend their schemes to include more itemsand suppliers, thus proving that low value (high volume) of parts is not a prerequisite for successful VMI.

Company-related features. These can also affect the feasibility of VMI. For example, a company can see purchasingas its core competency. Such a company would naturally be reluctant to adopt VMI and may insist on retaining thetraditional purchase orders. One can expect VMI to fail in such companies even if it were implemented due toexternal pressure.

Yao et al.’s (2007) analytical model provides a better understanding of how ordering costs and carrying charges(important supply chain parameters) affect the inventory cost savings to be realised from VMI, and the distributionof these savings between buyers and suppliers. They also mention some other requirements of VMI, such as the needto share information and to have co-ordinated and integrated processes between buyers and suppliers. The authorsdemonstrate ‘that benefits may be generated from VMI as long as the ratio of the order costs of the supplier to thebuyer and the ratio of the carrying charges of the supplier to the buyer are favourable’ (Yao et al. 2007, p. 671).

Supplier-related features. Claassen et al.’s (2008) study of the enablers of successful VMI implementation concludedthat the quality of the relationship and information sharing are important factors in the success of VMI. Lack oftrust between the trading partners resulting in the reluctance to share information is also a reason for unsuccessfulVMI (Fraza 1998). Trust can only be developed when firms are able to demonstrate to the trading partners thebenefits of shifting to VMI (Kaipia et al. 2002). Using long-term relationships as a selection criterion to choose theirVMI suppliers results in fewer conflicts over inventory ownership, payments and trust issues and thereby increasesthe success of VMI (Franke 2010).

The purpose of VMI should be to integrate key customers in the supply chain. VMI is appropriate in a companyif key customers constitute a high percentage of the vendor’s sales figures, if the products are standardised andrequested repeatedly, if product growth is not excessive, meaning that the requirement patterns are stable and it canbe assumed that requirements will not occur spontaneously and finally if the transaction costs for order processingand production planning are high (SAP 2010).

3. Methodology

This research includes a literature review to identify features that affect the suitability of VMI, discussions with bothacademic and industry experts on these features, and case study analysis of how these features may play a role inactual business situations (Figure 1).

In the first stage, academic and industry experts rated the importance of each of the 15 features identified fromliterature (see Section 2.2). We chose five academic experts and five industry experts. Each academic expert helda doctorate in supply chain management and among them had published over 100 research papers in reputablejournals and practitioner outlets in this field. Each industry expert held a senior position in supply chain functions,

Importance15 survey item weights

elicited from experts

Features15 survey items

extracted from literature

VMI readiness score

VMI readiness score = ∑ Itemi* Item weight i

15 item scores elicited from company respondents

15i = 1

Stage 1

Case studies

Stage 2

Figure 1. Research design.

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and had deep knowledge of supply chain management. Both categories of experts were selected through

personal contacts. They were asked to rate the importance of each of the 15 features on a 5-point rating scaleanchored at ‘not important at all’ (0) and ‘highly important’ (4). There was a high degree of agreement in the

experts’ responses (Wagner et al. 2010). The importance rating resulted in a weight of each feature expressed as apercentage (listed in the first column in Table 1).

It was deemed useful to classify the 15 features based on whether they were amenable for improvement through

managerial effort, or whether these features could not be manipulated easily. This distinction is important becausethere could be cases where VMI would not be used due to some factor being unfavourable, giving the impression

that the company was justified in not using VMI, whereas in reality the company could easily have rectified thatfeature, and VMI would actually be a missed opportunity.

In the second stage, a case study methodology was used to enrich and validate this framework. Case study

research is suitable for developing firm-level understanding of a phenomenon (Eisenhardt 1989, Meredith 1998), inthis research, contextual factors underlying firms’ decision to use/not use VMI. A clear sequential process was not

followed in this research, rather, considerable iterations between the theory and development of successive casestudies preceded finalisation of the proposed framework. In other words, the framework is indeed the outcome of

both the literature review and the case studies. The survey was finalised and administered after all 10 qualitative caseinterviews had been completed.

Ten companies in Switzerland (or nearby countries, i.e. Germany and the Principality of Liechtenstein) werechosen based on convenience and accessibility. The companies were from different industries and there was a mix of

companies that did and did not use VMI. The interviews provide a context-rich description of why the companiesdecided to use or not use VMI. The interviewees were supply chain managers, material logistics managers, or

purchasing managers. The interviews typically lasted one hour. Eight were conducted at the company site and twowere done over phone due to large geographical distance.

Next, 2 to 6 weeks after finalising the case studies (depending on when the case study was conducted) the

quantitative questionnaire based on the framework was administered to respondents from the case study companies(who were different from the interviewees in the preceding case study research). The questionnaire consisted of the

15 features (whose weights were determined independently by the academic and industry experts) and therespondents were asked to rate their applicability to their supply chain on a 5-point rating scale anchored at ‘not

applicable at all’ (0) and ‘highly applicable’ (4).The weighted sum of the 15 features yields the ‘VMI readiness score’ for each company (Table 1). The possible

range of scores is between 0 and 400 (i.e. a company rating the applicability of the items to their firm as 4 for each of

the items results in a score of 4� 100¼ 400, and a firm rating 0 for each of the items results in a final score of 0. If acompany scores below 50%, then the framework indicates that the company does not meet the prerequisites for a

successful VMI. If the score falls between 50% and 75%, the framework indicates that VMI should be a seriousconsideration for that company. This means that although they do not fulfil all the requirements, a bit of effort

could still make VMI a success, especially if there are many features which, as indicated in the framework, fall intothe category of improvable factors and are cost effective. It is more likely that improvement should be focussed on

features scoring low rather than those already scoring reasonably high. If the company scores above 75%, VMI isconsidered to be appropriate.

4. Case studies

4.1 RUAG

RUAG is an international technology group focusing on space travel, aviation, security and defence technology forboth civilian and military application. RUAG is an established company with stable growth. Since work is done ona project basis, production is based on changing customer demand, meaning their products are customised and

therefore constantly changing. Products ordered from their suppliers are rarely standardised and have high demandvariances.

Exact quantities are ordered for each project, and are first printed, and then sent by fax, email or post to their

suppliers. Most parts take 3 to 5 weeks to arrive, while some high-value items take 12 to 24 months. Lead times forcommodities are usually 3 to 5 days. At the end of a project, left-over parts are either saved, if they can be used in

another project, or they are scrapped.

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RUAG also orders office supplies such as paper. Since paper is used in large quantities, the SAP system managesthe stock and places orders automatically when the level falls below a set replenishment level. The paper then arrives1 or 2 days later. The same method is adopted for screw thread inserts, which are also used in large amounts.

RUAG has chosen not to use VMI for its production site in Switzerland, citing several reasons. First of all, sinceRUAG works on a variety of projects for the customers, these projects are one-time only and the required partschange for each project. Since smaller quantities of parts are ordered, VMI is not considered to be worthwhile. Forexample, RUAG could consider using VMI to replenish its stock of paper or screw thread inserts, but since thesystem places orders automatically, the transaction costs are low and there is little real value in changing the process.

Another reason is the documentation requirements. Since every part that comes in needs to be inspected anddocumented, RUAG chose to place its own orders and control inventory more directly.

With a score of 7 (product), 63 (company), and 62 (supplier), RUAG aerospace has a total weighted VMIreadiness score of 132. Since this company scores below 50%, the framework does not recommend the use of VMI;this is consistent with RUAG’s decision.

4.2 Legacy Pharmaceuticals International

Legacy Pharmaceuticals International is a global manufacturer and seller of prescription, OTC, generic andcosmetic products. Its core business is its contract manufacturing undertaken in Basel, Switzerland, and in PuertoRico. Most of its customers are other pharmaceutical companies, mainly in China. Raw material is sourced fromaround the world, mostly from Europe and the US; China or other low-cost countries are a consideration for thefuture.

Legacy manages its inventory through a very crude IBM AS/400 system. The system, still displayed on a blackscreen with green writing, holds basic inventory data and controls the stock movement. The system shows whereinventory is and then allocates goods to an order. In addition, it allows representation of different steps of theprocess, but not process planning.

Inventory data is extracted from AS/400 into an Excel spreadsheet. Inventory is then checked on a weekly basisto update the forecast. On the customer side, forecasts are 1.5 to 2 years in advance, but on the supplier sideforecasts are rolling on a yearly basis, similar to the ‘ordering launching system’ commonly seen in automotivesupply chains (Niranjan et al. 2011). This means that they prepare forecasts for one year in advance and updatethem every month. The first three months of forecasts are the firm orders for the suppliers, whereas the remainingmonths stay as a forecast. This long forecast allows the key suppliers to block inventory.

In order to improve its inventory management, Legacy has decided to implement an ERP system to replace theAS/400. The company is looking for an appropriate system, since systems like SAP are too large and complex.

Legacy has chosen not to implement VMI. The company places only 80 orders a month, so VMI would not be ofmuch value. In addition, some of its products are publicly available and it is not possible to order in advance orreserve quantities; they must be bought quickly before competing customers do. This is not possible with VMI. Forexample, Legacy buys calf blood from Australia. Since calf blood is very limited in supply, Legacy buys as much aspossible when it is available in order to avoid shortages.

Another reason is to retain control of its operations. According to the interviewee, ‘in the pharmaceuticalindustry it is possible to make a lot of money very fast, keeping the control of operations is very important’. VMIcan deprive the company of some of this control.

Regulations are also a reason why Legacy is reluctant to implement VMI. Like other pharmaceuticalscompanies, Legacy must follow strict regulations. For example, there are strict regulations concerning shelf life. It iseasier for the company to comply with regulations if it places its own orders, rather than letting suppliers managethe inventory through VMI.

Finally, Legacy believes that when some products are ordered from different suppliers, it is less expensive andmore efficient to place their own orders. A system might not be able to manage the frequently changing suppliers forspecific products.

In general, Legacy believes that VMI will only work for high volume product with fast turnover, such as for fastmoving products. VMI is potentially attractive for only a handful of suppliers, but the company claims to manageinventory very well the way as it is done at the present time.

Legacy has a VMI readiness score of 137, which is below 50%, and the framework recommends not using VMI;this is consistent with Legacy’s decision.

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4.3 Louis Widmer

Louis Widmer is a cosmetics company with headquarters in Schlieren, Switzerland. Louis Widmer orders raw

materials from suppliers through order requests. These requests are usually printed and faxed to the suppliers withthe product type, quantity and delivery deadline. If the deadline cannot be met, the suppliers send a message to that

effect. Once the raw material arrives at Louis Widmer, the products are manufactured and packaged on site andthen distributed to its customers. These customers include subsidiaries around Europe, as well as pharmacies in

Switzerland.The lead time to acquire products from its suppliers is relatively long. It usually takes 6 to 8 weeks for deliveries

to arrive, but lead times of 14 to 16 weeks are not uncommon. Such long times require either efficient planning or alarge inventory. The inventory at Louis Widmer is managed through a process industry ERP system called Infor

ERP Blending. Each department is responsible for planning and purchasing its own products. Talented employeesare responsible for planning and optimising their inventory levels, and for ensuring that their products are available

on time. In this manual scheduling system, the purchaser receives order requests from production and is in charge ofprioritising its products. In addition, the customers order products 2 to 3 months in advance with no year-long plan

and keep the inventory in their own factories. The purchaser needs to forecast the customer requirements based onpast data and sales promotions. The purchaser’s knowledge is based on information about and experience with

changes in product, trends, and promotions.Louis Widmer has three reasons for not implementing VMI. The first reason is that there is a great amount

of specialised knowledge required in the purchase of materials from the company’s suppliers. The employees have

special expertise about the products, demand and production planning which the company believes cannot beprogrammed into a system. For example, the production department makes constant changes, often at the last

minute, so it is difficult to plan. According to the company, human effort is the best option. In addition thecompany is afraid of the suppliers’ ability to adapt to frequently changing orders.

Another reason is the balance of power between Louis Widmer and the suppliers. The company believes that

VMI, which allows suppliers to make decisions on inventory replenishment is not in the best interest of LouisWidmer. The final reason for resisting VMI is to preserve jobs for company employees.

With a score of 65 (product), 77 (company), and 69 (supplier), Louis Widmer has a VMI readiness score of 211.Therefore, this company scores in the 50% to 75% range and the framework indicates that VMI should be a serious

consideration. That means that although the company does not fill all the requirements, a bit of effort should makeVMI a success, especially if two low-scoring features which fall in the ‘improvable’ category are improved: sharing

inventory/forecast information with their suppliers and having an integrated information system with its suppliers.Although the framework recommends careful consideration of VMI, Louis Widmer has decided not to use it. In

either case, Louis Widmer’s decision matches the framework’s recommendation.

4.4 Novartis

Based in Basel, Switzerland, Novartis offers a diversified portfolio of innovative medicines, cost-saving genericpharmaceuticals, vaccines, diagnostic tools and consumer health products.

Novartis is among the leaders in supply chain management practice (O’Marah 2007). The company matched

global supply and demand with highly responsive product launch to lower inventories and improve forecastaccuracy. Novartis also employs a governance model that has driven compliance standards globally (across

manufacturing sites), based on the proven methodologies of the Toyota Production System. Vice President forMaterials Management at Novartis, Jim Edwards, once described Novartis’s supply chain thinking as ‘Inventory is

evil. Speed is cool. Integration is supercool’ (Miller 2004). With a supply chain spanning more than 12 countries,Novartis has been integrating its production plants, warehouses, distribution centres, and contract manufacturersinto a supply network. A part of this effort included the implementation of SAP, the leading ERP solution for large

enterprises. The goal was to use SAP to reduce total cost of ownership by streamlining industry-specific processesand replacing existing systems. The large quantity of products manufactured at Novartis is a challenge in itself. With

the help of SAP, Novartis has managed its growth and kept its extensive supply chain intact.When Novartis was trying to implement VMI functionality, a collaborative platform was developed in SAP.

Important suppliers were integrated into the VMI module to manage demand and deliveries. Historical data

remained in SAP, as well as the bills of materials and inventory levels.

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The screen available to the supplier is simple. It has the orders and the deliveries moving based on the speed ofproduction. The updates for all the replenishment orders are done once a day. The inventory is then automaticallyadjusted and sent to the Master Requirement Planning (MRP) system, and from there to the front page of thesuppliers.

Novartis implemented VMI to manage the growth of the company without needing more resources. Thecompany wanted to focus on more value-added processes, such as process exceptions which require humanknowledge. In addition, its strong and mature ties with its suppliers were a strong incentive to use VMI. The longerthe co-operation, the better it was to implement VMI with them. It gave its suppliers the freedom to produce in themost optimal way.

The main benefits of using VMI at Novartis were the synchronisation of processes and the improved ability tosupply on time. The process ran smoothly and inventory levels were greatly reduced.

With a score of 70 (product), 95 (company), and 82 (supplier), Novartis has a VMI readiness score of 247.Therefore, this company scores between 51% and 75% and the framework indicates that VMI should be a seriousconsideration. Since Novartis decided to use VMI, its decision is consistent with the framework’s recommendation.It appears that although its supply chain is not ideal for VMI, the company considered this option carefully andimplemented VMI successfully.

4.5 Ferring Pharmaceuticals

Ferring Pharmaceuticals is a research-driven biopharmaceutical company devoted to identifying, developing andmarketing innovative products in the fields of reproductive health, urology, gastroenterology, endocrinology andosteoarthritis.

Ferring’s quantity of purchased products in Switzerland was described by the Director of Supply ChainManagement as insignificant compared to that of other medium/large pharmaceutical companies. Its productquantity and inventory levels are not significant enough to make its purchasing process with its suppliers a challengeto them.

Therefore, Ferring manages the flow of goods with its suppliers using very standard purchase orders, but thecompany manages its internal supply among Ferring entities, with a VMI concept integrated with its Oracle ERPsystem. Ferring has decided not to use VMI for an external supplier. The main reason is the complexity of thesystem when requiring proper validation. Using VMI with hundreds of suppliers seems to pose a risk for thevalidation and the qualification of the system unless it is protected with a firewall. For example, the secondarypackaging of a drug usually contains critical information about how to use the drug. If, for any reason, theinformation is changed without authorisation, the company might be liable in case health issues arise.

The second reason is that the company has not yet found it worthwhile to set up VMI when purchasing levels arelow. In addition, VMI is thought to be most useful for low-value items such as shipper boxes and labels, not forhigh-value products. With growth expected in the future, VMI might make more sense for them, but at the moment,Ferring does not see a need for it.

Another reason is the long lead times of its products. Compared with automotive or aerospace products,pharmaceutical products do not take up much space and there is less of a need to limit inventory. In particular, theshelf life of its products is sufficiently long that there is noworry aboutmaintaining a higher level of inventory. Finally,Ferring has not implemented VMI with its suppliers because its employees fear power shifting from them to suppliers.

With a score of 114 (product), 71 (company), and 65 (supplier), Ferring has a VMI readiness score of 250.Therefore, this company falls in the 51% to 75% range, so VMI should be a serious consideration. With goodinformation and communication systems, sharing of inventory/forecast information with its suppliers, key suppliersconstituting a high percentage of its purchase orders, and an integrated information system with its supplier (theseall are features in the ‘improvable’ category), VMI could be appropriate. The framework recommends carefulconsideration of VMI. Ferring has decided not to use it, but will consider it in the future when some of the featuresare improved.

4.6 Hilti

With its group headquarters in the Principality of Liechtenstein, Hilti provides leading-edge technology to the globalconstruction industry. Hilti’s unique structure is based on a worldwide supply chain that encompasses every step,

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from purchasing the raw materials through delivery of the finished product to the customer. The company is guidedby its motto ‘order today, we deliver tomorrow’ and focuses on operational excellence and lean methods ofmanufacturing. To assist its operations, Hilti takes advantages of an automated warehouse system, the ERP systemSAP R3 and VMI. For Hilti, VMI was not a difficult choice since the Manager of Materials had a positiveexperience implementing VMI in another company. The final decision was made after determining the need toreduce administrative costs, improve supplier relationships, and optimise its supply chain.

With a score of 97 (product), 98 (company), and 69 (supplier), Hilti has a final VMI readiness score of 264.Therefore, this company falls into the 51% to 75% range and the framework indicates that VMI should be a seriousconsideration for Hilti. Since Hilti has decided to use VMI, its decision matches the framework’s recommendation.

4.7 Daimler

Daimler is a German manufacturer of premium segment automobiles, vans, buses, and trucks. Its automotivebranch Mercedes decided to use VMI to reduce administrative efforts (e.g. calls and shortage management),improve delivery reliability, reduce stock levels, have a warehouse paid by the supplier, have completely integratedprocesses which are transparent and stable, and finally to optimise the transportation system. The decision toimplement VMI was also to improve supplier relationships, increase supplier transparency of demand and optimiseproduction with both optimal lot sizes and a balanced way to deal with orders. Finally, they wanted to reduce theirtime spent on administrative and troubleshooting efforts.

With a score of 116 (product), 94 (company), and 92 (supplier), Mercedes has a VMI readiness score of 302.Therefore, this company scores over 75% and the framework indicates that VMI is recommended. Since Daimlerdecided to use VMI, its decision matches the framework’s recommendation.

4.8 ODLO International

ODLO International is a Swiss functional sportswear manufacturer. With subsidiaries throughout Europe, ODLOsells its products in 20 countries. Upstream of ODLO’s supply chain are suppliers of fabrics, accessories, and otherraw materials. The production is either done in its own factories or by suppliers, with 90% of the underwear andTEC-shirts produced in its own factories in Portugal and Romania. With an international distribution centre, thefinished goods are shipped to its subsidiaries around Europe. Finally, the goods go through the dealer, which actsas a warehouse, and are placed in shops available to the final customers.

In order to keep track of demand by the final customers, ODLO tracks ‘point of sale’ (POS) data at the shops.The products belong to ODLO until the point of sale, when the invoice is made. There are about 3000 POSworldwide. In addition, ODLO has 900 ‘shop-in-shop’ systems. This is where ODLO owns a space in a larger shop,such as Jelmoli, in which it sells its products. Since this ‘shop’ belongs to ODLO, ODLO is responsible for the shelfreplenishment of the items.

Supply chain management efficiency at ODLO can be measured through the delivery service of stock items, thecost per saving minute at its own production, the cost per piece for central distribution, and finally the lead times forinbound and outbound logistics.

ODLO uses VMI with both its customers and its suppliers. With a textile-oriented ERP system called INTEX,ODLO manages the inventory at the retailer. It then manages the availability of goods at the stores through salesreports transmitted by electronic data interchange (EDI). These sales reports contain POS data which ODLO alsouses to plan its own production.

ODLO has decided to use VMI with some of its customers. According to the Director of Supply ChainManagement, there were three reasons for the decision. The main reason was to optimise the customer relationship.If ODLO was more bound to its customers, they would be forced to rely more on each other. Having a goodrelationship means more and better work together in the future. The second reason was to increase the availabilityof the products on the shelves by managing production with POS information. The higher the availability, the moresales the company could make. High availability also prevents the loss of sales to competitors with better stockavailability. The third reason for using VMI is simply because the customers wanted it. Although it provides benefitsto both parties, some of its customers requested it and ODLO believed that it had no choice.

One of the problems with VMI at ODLO is that it is not strategically set up well. Although sales figures of mostof its customer’s shops are available, information sharing is not yet optimal. As the Director of Supply Chain

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Management repeatedly noted, ‘VMI is all about information management. It’s about getting sales data, makingstock data interpretations, and making the right conclusion about strategy.’ He emphasised that VMI is only a tool,and a tool is not worth much without intelligent management and people who can interpret the data.

An example of such information management problems has to do with the master data. For instance, eachproduct has an EAN code (barcode) and the customers have their own numbering system which is different from theother parties in the supply chain. Either a converter company in between the two parties is in charge of aligningproducts, or the ERP converts product IDs automatically. This makes it difficult to keep track of products.

Another problem of information management has to do with changes in product IDs. Apparently, there is oneemployee at ODLO who does nothing but data correction. It takes a lot of work to make changes and adjustmentsto article numbers for correction. In addition, price changes are still done manually.

As a result of poor information management, inventories throughout the supply chain often do not match withwhat the system claims is available. For example, this could happen when a sales person forgets to register solditems. Such mistakes with inventory generate substantial losses for ODLO.

With a score of 83 (product), 107 (company), and 112 (supplier), ODLO has a VMI readiness score of 302.Therefore, this company scores over 75% and the framework recommends VMI; this is consistent with thecompany’s actual practice.

4.9 Merck Serono

With headquarters in Geneva, Switzerland, Merck Serono is the division for innovative small molecules andbiopharmaceuticals of the Merck group. Since Merck acquired Serono, the manufacturing sites are divided betweenbiotech and pharma. Merck Serono manages the distribution of products from the manufacturing sites to itsaffiliates. On the biotech side, there are two main manufacturing sites in Switzerland and Italy. They are responsiblefor both packaging and semi-finished production. On the pharma side, there are four manufacturing sites inGermany, France, Spain, and Austria (in addition to local sites for which the supply chains are not managed on agroup level). Finished products are then pushed directly to their affiliates. Merck Serono has 44 distributions centresin more than 100 countries.

Merck Serono uses a VMI concept to minimise the inventory levels throughout the group. The inventory ismanaged by a system fromManugisitics, which was recently bought by JDA, a supply chain company. Although it isnot called a VMI system, the concept is similar. Merck Seono used four modules to manage demand, collaboration,fulfilment, and master planning. The first two (demand planning and collaboration) are linked to the demand side.They perform statistical forecasts based on sales, taking into account both trend and seasonality. The third module isto manage the fulfilment and works as a distribution requirement planning (DRP) module. The fourth module(master planning) is responsible for the production planning for the manufacturing sites on the biotech side.

After the implementation of the fulfilment module, it took six months to reduce inventory levels by 20%. Oncedemand planning had been implemented, the accuracy of forecasts began to improve: 20% in only one year.Customer service also improved. The company is now at 99.8% service level (ability to deliver to customers),although it is helped by having a buffer stock at the affiliates.

Inventory management using VMI is done in close collaboration with its affiliates. Although they are part of theMerck Serono group, the affiliates are independent entities. They are responsible for sharing their local sales data sothat Merck Serono can move finished items to them. They calculate delivery requirements based on the main stocklevels every month, considering safety stock and frequency of delivery. Usually, they try to keep no stock in themanufacturing sites and only produce what has to be shipped. The objective is to have minimum stock worldwide.Only when orders need to be grouped together would a shipment be held in the warehouse. Only a few local affiliatesmanage their own inventory and place orders in a traditional manner.

With a score of 100 (product), 96 (company), and 132 (supplier), Merck Serono has a VMI readiness score of328. Therefore, this company scores over 75% and the framework indicates that VMI is recommended for thatcompany, consistent with Merck Serono’s decision.

4.10 Procter & Gamble

Procter & Gamble (P&G) is a global consumer goods company that is well known for its supply chain practices, anduses VMI as part of its efficient consumer response (ECR) strategy. The objective of VMI was a strategic business

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partnership between P&G and its customers. Its decision to implement VMI was made to optimise logistics alongthe supply chains to its customers. As the supplier, it has to focus on its own products and organise and optimise theproduct flow in a more efficient way. In addition, P&G attempted to improve its overview of their supply situationand product availabilities, which the customer does not have. In the past the company often had better planningtools than the trade partners could provide. P&G’s Swiss division uses VMI only with its main customers. For somecustomers, it is a requirement for doing business.

With a score of 132 (product), 109 (company), and 125 (supplier), P&G has a VMI readiness score of 366 –above the 75% threshold. The framework indicates that VMI is recommended for that company. Since P&G usesVMI, its decision matches the framework’s recommendation.

5. Summary and conclusion

This study identified a need for a framework to guide companies in their decision to use VMI. It then proposeda framework for testing the VMI readiness of firms, based on 15 prerequisites drawn from the literature. Theframework was illustrated and validated through 10 case studies. Each case study provides a thick description of thecontext and management’s rationale for using or not using VMI. The results are then independently verified in a lessrich, but more objective manner through a questionnaire. The numerical results are reflected in the VMI readinessscore, which is the weighted sum of each of the 15 features.

The 10 cases investigated in this study largely validate the framework. As predicted by the framework,companies that decided not to use VMI had scores below 50%. These firms include RUAG and LegacyPharmaceuticals. All of the companies that decided to use VMI had scores exceeding 300: Daimler, ODLO, MerckSerono and P&G. The remaining companies fall between the 50% and 75% score range and include a mix ofcompanies using VMI and those not using VMI. To be more precise, Louis Widmer and Ferring Pharmaceuticalshave decided not to use VMI, while Novartis and Hilti have decided to use VMI.

For the practitioner, this article presents an easy-to-use methodology to evaluate firms’ VMI readiness, whichcan provide insight and aid the decision making on whether to use VMI. The methodology involves the completionof a 15-item questionnaire, where respondents rate from 0 to 4 the applicability of the features to their supply chains.The final score is simply the weighted sum of the 15 item scores with the weights expressed in percentage. The rangeof possible overall score is [0, 400]. A score below 200 suggests a ‘No Go’, a score of 200–300 suggests a ‘ConsiderVMI’ and a score of over 300 suggests a ‘Go’ for VMI implementation. Further insight can be offered on the‘Consider VMI’ category by observing whether the features scoring low fall into the ‘controllable’ or‘uncontrollable’ class. If most of the features are uncontrollable, there is not much the company can do tochange the conditions that would make VMI viable.

Although the framework offers many useful insights, some limitations of the methodology may be noted. First,the weights were chosen by experts. Weighting the survey was intended to be a step forward from the mainstreamresearch approaches. The latter approach often involves simply administering a survey and assuming that allfeatures carry equal weight. However, our improvement of assigning weights, while indeed an improvement, is notfoolproof because of our assumption that the weights apply equally (as opposed to similarly) to all firms; this neednot be the case, and it is indeed possible that some industries/firms may need a different set of weights from others.

Would the results be altered significantly if the weights assigned were different, or in other words, would theresults be reproducible if a different set of experts had been used? We checked this possibility by deriving the resultsafter completely dropping the weights (i.e. sum of raw scores). The results remained unchanged; the relative finalscores were almost identical to the previous ones. Therefore the framework is robust. There is still the opportunity torefine the weights to suit individual industries or types of firms, or other possible classifications, which we leave forfuture research. We would also add that the threshold scores were decided somewhat arbitrarily, and to be roundfigures (for example, setting the cut-off point at 200 instead of, say, 203). A more rigorous, large scale study canrefine this method and derive exact values of the threshold, thus improving the predictive power of the tool.

Further, although we claimed to ‘validate’ the framework by 10 cases, the case studies were more in the spirit ofenriching the framework, rather than validation in the strict sense. An area for future exploration is to test/refine thetool with a large scale survey. Further, the empirical validation of this study is limited to showing that companiesexhibiting features that the literature claims will lead to successful VMI do indeed use VMI. This research did notexplicitly investigate whether their VMI was indeed successful, and whether it led to significant improvement in firmperformance. However, the qualitative responses suggest that the managers believe it does: none of the managers

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regretted their decision to implement or not implement VMI, thus supporting the framework. Rigorous validationthrough suitable extensions to the survey is indeed another area that needs to be addressed in future research.

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