D/2004/6482/09

Vlerick Leuven Gent Working Paper Series 2004/08

CONSTRUCTING A TOTAL COST OF OWNERSHIP

SUPPLIER SELECTION METHODOLOGY BASED

ON ACTIVITY BASED COSTING

AND MATHEMATICAL PROGRAMMING

Z. DEGRAEVE

EVA LABRO

FILIP ROODHOOFT

Filip.Roodhooft@vlerick.be

2

CONSTRUCTING A TOTAL COST OF OWNERSHIP

SUPPLIER SELECTION METHODOLOGY BASED

ON ACTIVITY BASED COSTING

AND MATHEMATICAL PROGRAMMING

Z. DEGRAEVE

London Business School

EVA LABRO

1

London School of Economics

FILIP ROODHOOFT

Vlerick Leuven Gent Management School,

KU Leuven

running head: Total Cost of Ownership for supplier selection

Contact:

Filip Roodhooft

Vlerick Leuven Gent Management School

Tel: +32 16 32 36 36

Fax: +32 16 32 85 81

Email: Filip.Roodhooft@vlerick.be

1

Corresponding author

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ABSTRACT

In this paper we elaborate on a Total Cost of Ownership supplier selection methodology that

we have constructed using real life case studies of three different industrial components

groups in a firm. These case studies are presented in this article. Analysing the value chain of

the firm, data on the costs generated by the purchasing policy and on supplier performance are

collected using Activity Based Costing (ABC). Since a spreadsheet cannot encompass all

these costs, let alone optimise the supplier selection and inventory management policy, a

mathematical programming model is used. For a specific component group the combination of

suppliers is selected that minimises the Total Cost of Ownership. TCO takes into account all

costs that the purchase and the subsequent use of a component entail in the entire value chain

of the company. The TCO approach goes beyond minimising purchase price and studies all

costs that occur during the entire life cycle of the item in the organisation. Possible savings of

between 6 and 14% of the total cost of ownership of the current purchasing policy are

obtained for the three cases.

Keywords: Activity Based Costing, mathematical programming, supplier selection,

purchasing

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INTRODUCTION

Purchasing determines an important part of the competitive position of most firms. It

accounts for 60% to 70% of total expenditures in manufacturing (Herberling, 1993), leads to

long term relationships and influences the activities in the complete value chain of the firm.

However, in both the operations management and operations research literature a lot more

effort has been put into obtaining cost reductions in further stages of the value chain,

especially in increasing production efficiency. Although purchasing probably does not receive

the attention it deserves in Western academic literature, it is a field where large cost

reductions can be obtained, as is shown by the Japanese who have traditionally paid more

attention to this field. The cases reported on here, however, are in a traditional Western firm.

The management accounting literature has recently picked up this inter-firm setting as an

interesting area to study. Seal et al. (1997) present evidence on the role of accounting in

developing a strategic supply partnership in an action research study. Ittner et al. (1999) look

at the effect supplier selection has on company performance and the intervening variables in

this relationship. Cooper and Slagmulder (1999) present a book with case studies of cost

management in the supply chain. Van der Meer-Kooistra and Vosselman (2000) discuss

management control issues in interfirm relationships. Baiman and Rajan (2002) provide an

overview of the incentive issues in inter-firm relationships identified by the incomplete

contracting literature. Dekker (2003) looks at the provision of information to coordinate and

optimise the supply chain in a case study.

Within the purchasing framework, decisions that have to be taken include supplier

selection and determination of order quantities to be placed with these selected suppliers

through time. Supplier selection decisions have a multiple objective character. At least 23

criteria for this selection problem have been identified in the literature (Dickson, 1966;

Weber, Current and Benton, 1991). These include amongst others: net price, quality, delivery,

supplier performance history, capacity, communication systems, service, geographical

location. The problem is how to select suppliers that perform satisfactorily on the desired

dimensions.

Published vendor selection models formulate answers to this multiple objective

problem. Some authors propose linear weighting models in which suppliers are rated on

several criteria and in which these ratings are combined into a single score (e.g. Gregory,

1986; Nydick and Hill, 1992; Willis et al., 1993). These rating models are very subjective and

often very sensitive to different rating scales, weights and/or ratings by different people. Total

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cost approaches ( e.g. Monckza and Trecha, 1988; Smytka and Clemens, 1993) attempt to

quantify all costs related to the selection of a vendor in monetary units but often fail to include

the more qualitative criteria. Mathematical programming models (e.g. Chaudhry et al., 1993;

Current and Weber, 1994; Sadrian and Yoon, 1994) often consider only the more quantitative

criteria.

In this paper, we combine a total cost approach with mathematical programming

because the dimensions of the problem cannot be handled using a simple spreadsheet. We

propose a Management Information System (MIS) that simultaneously treats the supplier

selection and the inventory management decision for multiple components over several time

periods in a mathematical programming model. This MIS is based on Total Cost of

Ownership (TCO) and Activity Based Costing (ABC) information (Degraeve and Roodhooft,

2000) and programmed in LINGO (Schrage, 1998). For a specific component group the

combination of suppliers is selected that minimises the Total Cost of Ownership. TCO takes

into account all costs that the purchase and the subsequent use of a component entail in the

entire value chain of the company (Shank and Govindarajan, 1992). The TCO approach goes

beyond minimising purchase price and studies all costs that occur during the entire life cycle

of the item in the organisation. These include amongst others costs related to service, quality,

delivery, administration, inventory holding, communication and defects. ABC makes the

quantification of the cost criteria possible.

Several authors have identified TCO analysis as a way to improve purchasing (e.g.

Ellram 1995a, Smytka and Clemens, 1993). Ellram (1995b) writes about the link between

TCO and ABC, but in our opinion has a fairly limited view on ABC. She asserts that, in

purchasing, ABC focuses on the internal administrative costs of the purchasing department

and assigns costs to the product, customer or distribution channel. In our opinion, however,

ABC can also study costs in other departments that can be influenced by the purchasing policy

and “the supplier selection policy” can be used as a cost object instead of the more traditional

cost objects mentioned by Ellram.

Mathematical programming (MP) techniques have been applied to purchasing issues

frequently, mainly in the domain of determining order quantities, specifically in environments

where complex discounts are offered by suppliers (e.g. Benton, 1991; Benton and Park, 1995;

Chaudhry et al., 1993; Sadrian and Yoon, 1993; Rosenthal et al., 1995), but also in supplier

selection (e.g. Akinc, 1993; Current and Weber, 1994).

Shapiro (1999) argues that mathematical programming models can serve as a template

for cost and resource data to be extracted by ABC methods. Our use of MP is classified in

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what he calls a type 4 model where the objective is to minimise cost over supply chain

resources in a multiple period, deterministic environment. To our knowledge, Degraeve and

Roodhooft (2000) were the first to make the link between TCO, ABC and mathematical

programming for supplier selection. They illustrate this link on an imaginary case. Degraeve

and Roodhooft (1999, 1998 resp.) illustrate the use of this method on rather small case studies

of buying heating electrodes and ball bearings respectively, at Cockerill Sambre, a Belgian

firm in the steel industry.

The incremental contribution of this paper is threefold. Firstly, this is the first time that

the management accounting aspect of the methodology is elaborated on and worked out

extensively. Previous papers do not describe the value chain and ABC analysis linked to the

specificity of the different product groups, nor do these papers discuss how the data are

collected and what the problems related to this aspect are. We show how the mathematical

programming model serves to define and structure the decision problem at hand. We obtain

very good results compared to the current purchasing policy because of our thorough data

collection and ABC analysis within this structure.

Secondly, this paper situates the work specifically within the context of the

constructive case study research methodology in management accounting (Kasanen, Lukka,

Siitonen, 1993), thereby indeed focusing more on the process aspects of the case study. It

builds on the previous papers and proves that the financial results of the previous cases can be

transferred to other component groups in another firm thereby generalizing previous results.

Thirdly, the model in this paper is far more complex than those in the previous papers

on several dimensions. Because of the extended value chain and ABC analysis, the number of

criteria and different costs considered are substantially larger. Also the monetary amounts

involved are larger (16,011,000 euro vs. 200,000 (Degraeve and Roodhooft, 1999) and

1,303,000 euro (Degraeve and Roodhooft, 1998)). The complexity increase is also indicated

by the size of the component groups (1,052 different component types vs. 1 and 33

respectively) and the supplier base from which to select (88 suppliers vs. 3 and 6

respectively). This results in a substantially increased number of variables and constraints in

the mathematical programming model. Also, the overlap between the suppliers and

component types is substantial, preventing us from using a decomposition method to solve the

problem.

Using our theoretical ABC framework for supplier selection we developed a MIS for a

division in Europe of a world-wide telecommunications firm that is one of the leaders in the

high speed access and transmission market. The firm has 116,000 employees world-wide and

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is represented in 130 countries. Global sales amount to 23 billion Euro. The division studied

offers a complete portfolio of the world-wide firm from micro-electronics and

telecommunications to cables and components and employs 4600 people in the country of its

location. The purchasing department’s mission statement includes “cost of ownership” as an

expectation of their (internal) customers:

To explore the market and to purchase and deliver […] conform to the

requirements, with a maximum of flexibility and reliability, with a competitive

“Cost of Ownership”, continuously.

(stress in original documentation)

To achieve this goal the firm uses a vendor rating system that takes price, technology,

quality, flexibility and delivery reliability into account. An effort is made to buy as much as

possible from suppliers with a preferred status. An Economic Order Quantity (EOQ) model

calculates the order points, but does not link this decision to the supplier selection decision.

The MIS is developed for three major bought-in product groups: resistors,

transformers and printed circuit boards (PCB). These component groups are selected because

the relevant criteria and costs differ substantially between them. In this way, the external

validity of the study is increased by constructing a toolbox that is widely applicable to similar

decision problems in different business contexts. We assume that the component groups are

independent from each other and study them separately. Although an occasional supplier

delivers items in more than one of the component groups, these links are negligible and the

total dimensions of the cases prevent us from looking at the three component groups at the

same time. Together, the three component groups account for about 14,000,000 euro in total

costs. The dimensions of the cases studied are vast and involve a considerable amount of

money, as shown in Table 1. The first column gives the number of different types of

components used in the firm. The second column states for how many of these types there was

a demand in 1999, the year of study. The third column indicates the number of possible

suppliers. The fourth column gives the current monetary purchasing price in euro.

Insert Table 1 About Here

Prices for different types of electrical components may vary substantially. The 1,729

resistor types are classified in two basic types, thickfilm chips and minimelfs with thin film

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technology. Minimelfs have a lower temperature coefficient, better current-noise

characteristics and a better stability with respect to overheating, but are more expensive.

Prices quoted for transformers are a function of their core type, the number of windings, the

quantity ordered and insulation requirements. The production cost of the Printed Circuit Board

(PCB) suppliers depends, amongst others, on type of material, number of layers, drill size,

finishes, density, thickness and board area. Asian PCB suppliers are cheaper but have a longer

lead time, provide less service and do not have special technologies available.

The remainder of the paper elaborates on the supplier selection methodology

developed. Section 2 explores the activities performed in the value chain of the purchasing

firm. Section 3 explains how Activity Based Costing data were gathered to cost out these

activities and which types of information are collected about the performance of the suppliers

on the different supplier selection criteria that generate costs in the value chain of the firm.

Section 4 shows how the data are translated into the objective function and constraints of the

mathematical programming models. The next section interprets the results and discusses

strategic insights for the purchasing policy. The last section concludes.

THE VALUE CHAIN AND ACTIVITIES

We study the activities in the value chain of the firm that relate to the purchasing

policy in the first step of the vendor selection methodology. These can either be activities of

the purchasing department itself or activities further down the value chain that are influenced

by policy decisions made by the purchasing department. Figure 1 shows the activities, where

they are situated in the value chain and how they relate back to the purchasing policy in the

case study firm. It is important to perform this value chain analysis, as these activities and

their costs will later be modelled in the mathematical programming model. The rest of this

section describes the activities in the value chain of the firm.

Insert Figure 1 About Here

The purchasing engineer responsible for a component group negotiates with the

suppliers on amongst others price, discounts, quality, lead time and follows up the relationship

to sustain the supplier in the supply base. When the supplier is new to the firm or when quality

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problems arise too frequently, the quality team sometimes performs a quality audit on the

supplier’s site.

Ordering can start once the relationship with the supplier is set up and the supplier is

selected for a certain component type. Depending on the supplier/component combination

orders can be placed through electronic data interchange (EDI) via a private network,

automatic call-off (ACO) on a frame agreement or the manuals by sending a fax.

2

The first

time an order is placed for a specific PCB with a supplier, a tooling cost might be charged by

the supplier to cover the supplier’s one/off costs on films, drilling information and electrical

testing. Suppliers with a shorter lead-time are more flexible in that they can accommodate to a

sudden change in demand on a shorter notice period and thus agree a delivery date that is

nearer in the future than other suppliers can.

3

A supplier’s delivery reliability depends on the

history of early and late deliveries around the agreed delivery date. Importing documents have

to be filled out and import duty has to be paid when the component is ordered with a supplier

outside the European Community.

Then the receiving department receives the delivery and inspects it together with the

inspecting department.

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When no irregularities are discovered during the inspection, the

supplier accounting for the delivery is done and the invoice is paid. For transformers and

PCBs some suppliers offer component specific discounts on prices for larger orders and this

discount may rise with the quantity ordered. Some transformers and PCB suppliers add a lot

charge to the invoice. Payment delays typically range from cash payment to 60 days delay,

with 0 to 3% payment discounts. However, when a defect is discovered in inspection,

components are either sent back to the vendor who will send a credit note or will replace them

at his expense, or they are thrown away at the firm’s own expense. When the supplier replaces

2

The minimum order quantity and the lot size have to be adhered to when ordering. Orders for a component thus

have to exceed the minimum order quantity for that component with that supplier and be a multiple of the lot

size. As a rule, the lot size is always lower than or equal to the minimum order quantity.

3

Asian suppliers generally have a longer lead-time than European and American suppliers.

4

Different sorts of inspections are used, depending on the inspection class in which the supplier/component

combination is allocated and resulting in more or less time consuming inspection activities. For purchases with

certified suppliers, the receiving department may release the components without any quality verification. The

trust in these suppliers’ quality systems makes extra inspection superfluous, as the details on the specifications,

the level of quality, the criteria for acceptation of the delivery, the supplier’s auditable quality plan and the

markings on the packaging are agreed on in writing in the quality agreement. Other components are inspected

visually. A skip lot inspection may be performed for components that are delivered frequently. In this case the

first five deliveries and afterwards every fifth batch are each checked taking a sample, whereas the other four are

only checked visually. In a few exceptional cases, the reception department releases transformers and PCBs

delivered by uncertified suppliers without further inspection because their impact on business processes is

considered small. For the odd resistor delivery only the labels on the packaging are compared with the ones on

the travel documents without opening the packaging. Occasionally, every PCB lot is checked using a sample

from each lot. Some special PCBs are sent for verification to the engineer that ordered the component.

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the components, they go through the whole cycle of importing, receiving and inspecting

again. After a satisfactory inspection the components are transported to the warehouse where

they are held in inventory until the production planning triggers a demand for the component

on the production floor. The components are used to manufacture more complex electronic

components or end-user products that are sold by the marketing department. However, some

defective components that have slipped through incoming inspection turn up during

production. This causes a lot of extra work to troubleshoot the problem, complain to the

supplier, repair and re-test the component. For PCBs the cost of discovering a problem in this

phase in the value chain is the highest because usually the entire expensive PCB has to be

thrown away and other components already fixed on it cannot easily be salvaged. Sold

products are delivered to the customer who, upon discovering a defect in this final phase of

the value chain, files a complaint that results in the after sales department investigating the

problem and writing an outgoing credit note.

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DATA COLLECTION

The developments in ABC and the integration of these costing systems with company

wide information systems could enable us to collect all necessary data on activities and

supplier performance. However, in the case study firm, three data collection problems had to

be overcome.

Firstly, cost accountants in the firm put effort into defining activities, several non-unit

cost drivers such as throughput time and orders are used, and the company’s head of cost

accounting gives presentations about ABC and how it is applied in the company. The cost

accounting system is mainly used for variance analysis between the budgeted and the actual

figures as well as for calculation of the tariff for services that are provided internally, such as

information technology, training, and accounting. The company clearly expresses the wish to

be on the forefront of developments in this area by applying ABC.

But, in our opinion, the company is merely on the way to developing an ABC costing

system. The basic features of the accounting system remain of the standard costing type,

although a high level of detail is visible. The firm defines about 1500 different resource

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The external customers of this firm assess only 1.7% of all defects, while the other complaints come from

internal customers in the production department. The analysis of these external customer complaints over the

year studied shows that none of them relate back to problems with the original component bought. Instead, they

are due to faults in the production process or wrong deliveries.

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categories and 400 cost pools that are related to geographical locations, departments or

products. Strangely, purchasing department overhead and the cost pool related to reception

and inspection are allocated using a normal distribution over groups of suppliers, rated

excellent, mediocre and bad on a combination of indices on delivery, quality and flexibility, as

a percentage of the purchasing volume with these suppliers. Thus it is assumed that there will

always be a specific percentage of each category of suppliers and that purchasing volume is

the overall cost driver. Therefore, especially for this purchasing application of ABC, the

company required lots of assistance from the authors.

Secondly, the company has several databases that are not always integrated. The first

is the accounting database, discussed in the previous paragraph. The second is the Purchasing

Management System (PMS), which contains data on all component types and suppliers. Next,

the Material Requirements Planning (MRP) provides forecasted demand figures. An economic

order quantity (EOQ) calculation system that is directly fed by the MRP was put in place five

years ago. The cost updated figures are, however, not automatically plugged into this EOQ

model and have not been changed in five years. When the accountant participating in this

study was made aware of this during the process of the development of the vendor selection

model, he undertook the necessary steps to update the cost figures in the existing EOQ model.

Besides these four systems, some purchasing engineers make use of their own spreadsheets.

On some occasions, we discovered that the data in these spreadsheets did not correspond to

the data in the overall PMS system.

Thirdly, there was a big turnover of personnel involved in the study. Several people

left for other firms, including the original champion of our study in the company. Other

personnel took up completely different functions within the same company.

The process of collecting the data on costs and supplier performance and refining the

costing system to reflect ABC principles was consequently time consuming as we had to

consult several databases, always via a variety of company personnel, in order to set up our

own ABC system and sort out discrepancies between data in the different files along the way.

The most problematic discrepancy concerned the vendor lead time data, where purchasing

managers’ own spreadsheets were much more up to date than the EOQ system and mostly

showed shorter possible vendor lead times. The remainder of this section describes how we

proceeded with these difficult tasks.

First the resources available to perform all the activities discussed in the previous

section are examined. An example is the gross wage of the inspectors. Resource drivers

establish a relationship between these resources and the activities. We checked, for example,

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how much time the inspectors spend on a skip lot inspection or on a full inspection. Personnel

in the firm was asked to participate in several time estimate studies. Some resources are linked

directly to the activity and need not be assigned through a resource driver. For example, the

yearly EDI service fee is exclusively related to the EDI ordering activity. Columns 1, 2 and 3

of Table 2 indicate the direct or indirect link between resources and activities and shows

which resource drivers are used in the latter case.

Insert Table 2 About Here

Once the cost of performing an activity is calculated, activity drivers that determine

the total cost of the purchasing policy are searched, using a cost hierarchy with several

activity levels: supplier-, component-, order-, batch- and unit-level. The first hierarchical level

describes costs incurred and conditions imposed whenever the purchasing company actually

uses the supplier over the decision horizon. Costs on the supplier level include a quality audit

cost incurred by the buyer for the evaluation of a supplier and the cost of a dedicated

purchasing manager. This purchasing manager is responsible for both setting up the

relationship with the supplier (e.g. writing up an overall quality agreement) and following up

the relationship. The component level indicates costs incurred whenever the firm needs to buy

this component. Tooling costs for the PCBs are incurred on this level as they are only charged

the first time that the component is ordered with the supplier. Tooling costs vary with the

supplier/PCB combination and might even be non existent for some combinations. The order

level parameters indicate costs incurred and conditions imposed each time an order is placed

with a particular supplier and include, amongst others, costs associated with ordering and

invoicing. At batch level the firm incurs costs each time a batch is delivered e.g. costs for

reception, inspection, material handling, internal failure (components fail during production)

and late delivery of the batch. At the unit level we find costs incurred and conditions imposed

related to the units of the components for which the procurement decision has to be made, for

example, price, external failure (a component fails when used by the customer) and inventory

holding due to early delivery. The three cases studied illustrate that the ABC hierarchy is case

dependent, as is suggested in the literature (Ittner, Larcker and Randall, 1997). For the resistor

case, a hierarchy with only three levels, i.e. supplier, batch and unit, is used. Since an order

for transformers or PCBs can include more than one type of component and the bought-in

products are delivered per batch of the same component, we add an order level in these cases.

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We include a component level in the hierarchy for the PCB case, as for some suppliers tooling

costs are incurred the first time a specific PCB is ordered to cover their costs on films, drilling

information and electrical testing. Table 3 shows how the hierarchy differs from case to case

and on what levels the costs are incurred.

Insert Table 3 About Here

It is important to make this classification of activities into separate levels since the

overall process driver for each level of activity, (1) number of suppliers, (2) number of

components, (3) number of orders, (4) number of batches and (5) number of units procured, is

assumed independent of the activities in other hierarchical levels. Column 4 of Table 2 shows

the more detailed cost pools at which level the information was gathered. From the variables

in the mathematical programming model, the level of variability of these details becomes

clear: per supplier (e.g. import duty dependent on location of supplier insider or outside the

European Community), per supplier-component combination (e.g. for some components an

automatic order through the automatic call off system is possible, while the same supplier may

only accept a fax order for other components) or only dependent on the purchasing firm (e.g.

material handling). Remark, however, that the purchasing firm can still work on the efficiency

and effectiveness improvement of the latter activities, or try to eliminate them when they are

non-value-adding activities such as inventory holding.

In this way, all costs caused by the selection of suppliers and the placement of orders

with them can be determined. Column 5 of Table 2 shows the process drivers that drive the

usage of activities by the supplier selection policy. These process drivers determine the level

in the ABC hierarchy where the costs are incurred and will become the decision variables in

the mathematical programming models.

In the next step, information is gathered on supplier performance at the detailed level

of the cost pools and also data on prices, quantity discounts, supplier’s lead time, tooling

costs, minimum order quantity, lot size as well as probabilities of detecting default in

inspection, production or by the external customer, are collected.

Before we proceed, an important caveat is in order. Applying Activity Based Costing

assumes that the costs are linear (or step-linear) with the cost drivers. Research (e.g. Noreen

(1991), Bromwich (1997), Maher and Marais (1998)), however, has shown that the conditions

under which ABC provides accurate costs are rather stringent and in some cases hard to meet,

14

especially when resources are provided on a joint and indivisible basis. Noreen and

Soderstrom (1994) empirically test this linearity assumption for different categories of

overheads and conclude that it is often not met. Datar and Gupta (1994) look at other possible

errors in costing systems in general (not just ABC) and show that there exists a trade off

between reducing specification and aggregation error (which is often used as a justification for

implementation of ABC systems) and increasing measurement error. We do acknowledge all

these possible problems with any application of ABC in general and ours in particular. We

would, however, argue that the use of ABC is already a leap forwards as it approximates the

linearity of the cost functions much better than the traditional volume related approaches, by

using a cost hierarchy where costs become variable at different levels. Costs that were

previously considered fixed or falsely considered variable at the unit level, can now become

variable at one of the other levels in the hierarchy. For our case in particular we have three

further reasons why the use of ABC may not be that problematic. Firstly, we have made a

deliberate attempt to reduce measurement error in units of allocation bases (Datar and Gupta,

1994) by not asking for too detailed information of personnel in their time allocation

estimates. Secondly, as you will learn from our result section, important parts of the possible

savings (between 3 and 11% of TCO of the current purchasing policy) are immediate cash

savings on price for which there cannot exist any measurement or accounting error. We

acknowledge, however, that the other part of the savings may require a thorough re-

engineering exercise to actually get rid of the freed up capacity or put it to an alternative use.

Thirdly, and most importantly, no joint resources are (or needed to be) included in our ABC

exercise since only those resources for which the resource consumption is different if different

suppliers are used are included in the model, as it is our objective to select those suppliers that

minimise TCO. Because of the focused scale of our ABC exercise, we did not have to deal

with joint resources such as investments in marketing and the brand name of the firm, as they

do not vary with the supplier selection policy, which is our cost object.

THE MATHEMATICAL PROGRAMMING MODEL

It is impossible to optimise the supplier selection and inventory management decision

taking all the relevant costs throughout the entire value chain of the firm into account in a

simple spreadsheet. Therefore, we develop mathematical programming models to determine

an optimum sourcing strategy for the different component groups. The models generate a

purchasing policy that minimises the Total Cost of Ownership taking into account constraints

15

relevant to the problem. As a result, the quantification of the vendor selection criteria and the

trade-off between them is no longer a problem because the objective function is defined as the

TCO related to the purchasing decision, and the supplier selection criteria are weighted by

their respective ABC costs.

Typically, a mathematical programming model consists of two main building blocks:

the objective and the constraints. The objective of the model is to minimise the Total Cost of

Ownership of the supplier selection and ordering policy for the decision period of the year. As

discussed in the previous section, the structure of the models is based on case specific ABC

hierarchies. This is shown in the objective function as it reflects net prices and resources

consumed by the activities in the three to five hierarchical levels distinguished: supplier,

component, order, batch and unit level. Subsequently, the mathematical programming model

defines the costs incurred on each of these levels and establishes cost drivers as decision

variables on all of these levels. The most important constraint for this procurement model is

that demand for each component in each time period has to be satisfied.

A more detailed explanation of the mathematical programming models, the exact

mathematical notation and information on the solving procedure can be found in the appendix

to the paper.

RESULTS

We have made an extensive comparison of our suggested purchasing policy with the

actual purchasing policy used. As we are not allowed to make the actual data available due to

confidentiality reasons, we present the results in Table 6 as percentages. The first row

indicates the possible savings as a percentage of the TCO of the current policy. The second

row gives the approximate TCO figures for the different component groups in euro. The next

eight rows show the hierarchy of costs for the optimal purchasing policy, as percentages of the

optimal TCO. The final seven rows indicate how the cost hierarchy is built up for the current

policy, as percentages of the optimal TCO.

Insert Table 6 About Here-

The purchasing policy proposed is able to save 14%, 6% and 11% on TCO on the

component groups resistors, transformers and PCBs respectively, compared to the current

16

purchasing policy

6

. As the benefits of applying the vendor selection model can be measured in

terms of the possible savings compared to the current purchasing policy, this methodology

overcomes the concern raised by Foster and Gupta (1997) about the difficulty of quantifying

benefits if new management accounting systems have to stand the cost/benefit test.

Several strategic insights can be gained form the analysis of the data and the solving of

the mathematical programming model.

As is to be expected in any purchasing application of ABC, the cost structure is unit

level dominated, since the whole turnover is taken into account on this level. Price, a unit

level cost, remains an important component of the TCO, in the optimal case making up

between 92 and 98% of TCO. As most of the purchasing entailed activities (as defined in

Figure 1) that have cost drivers at a higher level in the hierarchy are non value adding

activities, a cost structure dominated by price is good business practice in this case. Most of

the costly value adding activities such as the different steps in the production process were not

included in the analysis as supplier performance does not make a difference to the use of their

activity drivers. It would, however, be this type of activities that might shift the cost structure

from unit level dominated to batch level dominated. The dominance of unit level illustrates

the importance of getting the unit level costs right, also in an ABC environment where several

other levels are studied. You can also see in table 6 that the optimal policy cuts down on these

non-value added activities compared to the current policy.

Most of the possible savings also lie at unit level. Immediate cash savings could

amount to savings of 11.5%, 3% and 9% respectively by selecting a supplier with a lower

price and making optimal use of component specific discounts for transformers and especially

PCBs. We acknowledge that this is not an effect directly related to our ABC implementation,

but more a consequence of the operations research aspect of our methodology that brings in

more structure and objectivity. Using this TCO model, the selection of these lower price

suppliers can now be made with the assurance that quality and other costs are taken into

account and that the overall effect on TCO is positive. Almost all components have a single

6

These possible savings percentages are calculated for the last year for which full data were available. The TCO

model is used to retrospectively calculate the cost of the purchasing policy for that year by fixing all the decision

variables (when what was bought from which supplier) in the model to the values they took in that particular

year’s purchasing policy. In this way, we can calculate the TCO of the purchasing policy that was executed that

year (termed “current policy”). We then run the mathematical programming model again, this time to solve for

the optimal policy and compare the total cost of both (savings indicated as a percentage of the TCO of the

current policy). These savings could have been obtained had the company used the new method to determine

purchasing policy in that year instead of using the purchasing policy they actually implemented. Because the

firm faces a quite stable demand environment for these component groups, we can predict a level of savings of a

similar size for the next year.

17

source that is clearly better than the other possible suppliers. The current policy increases

TCO by splitting orders of the same component over several suppliers and therefore does not

make optimal use of the available quantity discounts.

In the rest of this section we report on non-cash savings that amount to 2.7%, 3% and

1.7% respectively. These are possibilities to save on resources, which would require a re-

engineering exercise to turn them into cash savings. Alternative allocations and selling off of

resources would need to be considered.

For transformers and PCBs, substantial savings on inventory holding costs (also on

unit level) are possible by ordering with suppliers who do not have a record of early

deliveries, and by placing orders just in time for the suppliers lead-time to be sufficient to

deliver the component exactly when needed. This saves a lot on warehousing costs that do not

add any value to the component. The savings we find here are partially due to the main

purchasing information system (PMS) not being updated regularly with respect to vendor lead

times, that had a tendency to decrease over time, and were only correctly written down in the

respective purchasing engineers own spreadsheets that were not linked to PMS. As a result,

the automatically placed orders were placed too early. Part of these inventory holding savings

could also be considered cash savings as there is an one-off freeing up of working capital due

to a lower inventory level. For components with a low unit price such as resistors, inventory

holding costs already make up a smaller percentage of the cost structure.

Savings can also be made on the batch level, by reducing quality problems for

transformers and PCBs. In our opinion, the savings created by a smaller percentage of

expensive defects often outweigh the cost of a quality audit. The batch level cost savings for

resistors, for which quality problems are not common, are a result of a policy of less frequent

ordering.

The firm can only make minor savings at order level costs for transformers and PCBs.

Rather surprisingly, the possible way of ordering through EDI, ACO or fax, do not save much

on ordering costs for the time being. The reason for this is that the cost differences between

these ordering techniques are small since the EDI system in place still requires checking every

order confirmation line by line, as the supplier can change quantities and prices without the

purchaser immediately noticing this. This is an example of an area where the ABC results had

an important policy impact as previously management had assumed that EDI was the most

cost-efficient way of ordering and pushed EDI systems take-up with their suppliers. They

decided to first sort out the technical aspects of the EDI system and automate order

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confirmation checking, before stressing its importance in negotiations with suppliers any

further.

The component level for the PCBs turns out to be insignificant since the tooling costs

that are charged whenever an PCB is ordered for the first time with a particular supplier, are

small relative to the other costs, and often even non existent. Only minor savings are possible.

Because the purchasing engineers spend most of their time on the specifications for the

components, which are independent of the suppliers selected, the supplier level costs do not

make up a very substantial amount in the cost hierarchy. Narrowing down the supplier base

can result in savings at supplier level. The proposed supplier selection policy narrows down

supplier bases from 21 to 17, from 37 to 35 and from 16 to 13 for resistors, transformers and

PCBs respectively.

Since non-price costs make up between 3 and 9 percent of the cost structure, and still

between 2 and 8 percent in the proposed purchasing policy, it would be interesting to

investigate a broader use of vendor managed inventories (VMI), also called consignment

stocks, as this cuts down costs of activities performed in the value chain of the purchasing

firm and eliminates some of these activities. As for now, the firm is working on a pilot project

for VMI with one supplier of a component group - not studied here -. The consignment

inventory is kept at or near the purchasing firm’s site, but the inventory holding responsibility

rests with the supplier as the components remain property of the supplier until the purchasing

firm takes them out in agreed lot sizes. The supplier is responsible for keeping the

components in stock in sufficient quantities to keep production going. His inputs for the

replenishing of the inventory are forecasts directly from the purchasing firm’s MRP planning,

an agreed minimum and maximum stock level and component consumption data given by the

production department on a weekly basis. The value chain of activities related to the

purchasing process can thus be drastically shortened. Ordering is eliminated as the supplier

draws his information directly from the company’s MRP planning. Reception is also

eliminated and incoming inspection is replaced by outgoing inspection. The supplier is

responsible for material handling costs that includes transport to warehouse, removal of the

packaging and shelving the duly labelled components on the assigned locations. The

purchasing firm usually supplies the warehouse, but fire and water hazard insurance and

warehousing personnel costs, also part of the inventory holding cost are for the supplier’s

account. The supplier finds compensation in cost cuts in his own production, a larger share of

the business and increased partnership.

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In summary, our recommendations to management to reduce the TCO of their supplier

selection policy were the following: narrow down the supplier base; select some lower price

suppliers with the assurance that quality and other costs are taken into account in the model;

make better use of discounts for transformers and PCBs; rely on a single sourcing policy on

the level of each component (not for the whole component group!), on top of penalizing late

deliveries (which is already purchasing policy), also penalize early deliveries as inventory

holding costs are high; reduce quality problems for transformers and PCBs, order less

frequently for resistors, look into the possibility of extending the use of VMI and search for

improvement in the EDI system.

Apart from providing purchasing management with a better supplier selection and

inventory management policy, the model can be used in two other ways. Firstly, the model

can give decision support using scenario analyses dealing with both strategic decision making

and cost management issues. The TCO of alternative procurement strategies can be

calculated, e.g. imposing a minimum or a maximum number of suppliers, excluding a supplier

etc. Management then can decide whether they are willing to pay the increase in TCO

compared to the optimal supplier selection policy to pursue these strategies. Areas can be

identified where internal improvements such as reducing cost driver rates of performing

value-added activities and/or eliminating non-value added activities, such as moving

materials, can generate the highest reduction in TCO.

Secondly, also areas where external improvements by suppliers are able to generate

decreases in TCO can be pinpointed. The model can then be used as a negotiation tool with

suppliers since proposals of discounts, quality improvements, lead-time reduction etc. made

by suppliers can be easily assessed. This clear communication on what drives costs in the

purchasing firm will enable companies to develop interorganisational activity based

management opportunities, given the importance of close relationships between the purchaser

and a limited number of reliable suppliers that might lead to buyer-supplier partnerships.

CONCLUSION

In this paper we develop a Total Cost of Ownership supplier selection methodology

using Activity Based Costing data. In a first step, the activities in the value chain that relate to

the purchasing policy are analysed. Next, resources available to perform all these activities are

examined and resource drivers linking them are established. Once the costs of performing the

activities are calculated, activity drivers that determine the total cost of the purchasing policy

20

are defined, using case dependent cost hierarchies with three to five levels. Then, information

is gathered on supplier performance on these activity drivers. Since a spreadsheet cannot

encompass all these costs, let alone optimise the supplier selection and inventory management

policy, mathematical programming models minimising the TCO of the purchasing decision

are programmed and solved with a stepwise procedure. The ABC hierarchy forms the

backbone of the mathematical programming model, with decision variables on each level of

the hierarchy. Possible savings of between 6 and 14% are obtained for the three cases.

Along the way, several other lessons for accounting were learned. Firstly, the problem

of ABC not being applicable to joint costs (Noreen, 1991) does not need to be an issue in

every case study. Here, the focus of the case was such that we did not need to include any

joint costs since they do not vary with our cost object, the supplier selection policy. Secondly,

we illustrate that the ABC hierarchy is case dependent, even for several component groups

within the same firm. Thirdly, people may hold subjective beliefs on rankings of costs of

activities that may actually not be true. In this particular case, the belief that EDI ordering was

(a lot) cheaper than ordering via the traditional fax way turned out to be wrong when the

correct figures where put into the equation. Fourthly, from an information systems point of

view, we can re-iterate the need for regular updating of figures in all the decision models (as

e.g. in this case in the EOQ model) to ensure correct decision-making and integration of all

the databases used to avoid discrepancies between data. Fifthly, this case study illustrates how

survey evidence on the use of modern cost accounting concepts such as ABC may be

positively biased. We think that, would management accountants within this firm have been

asked to fill out such a survey, they would have ticked the ABC box. However, having dug

into the details of their costing system, we would argue that a full-blown ABC system was not