Measuring logistics performance

Engineering Costs and Production Economics, I7 ( 1989) 253-262 Elsevier Science Publishers B.V., Amsterdam-Printed in The Netherlands

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MEASURING LOGISTICS PERFORMANCE*

Psr Andersson, Hgkan Aronsson and Nils G. Storhagen

Linkiiping Institute of Technology, S-58 1 83 Linkiiping (Sweden)

ABSTRACT

A planned strategy of measurement is a pre- requisite of successful planning, realization and control regarding the different activities which together form the business logistics function. It is of special importance to coordinate the processes of planning and realization in order to supply the right information to the right deci- sion-maker. The main objective in logistics should be the overall coordination. Previous research within the field of measuring logistics performance shows a great deal of interesting results, but also some gaps, especially when it comes to methods applicable on illustrating the entire logistics performance. In the present paper we deal with logistics performance measurement mainly from such an overall perspective. The contents are founded on the preliminary results achieved at Linkiiping In- stitute of Technology within the scope of a research programme initiated by an association of Swedish companies, the Swedish Programme for Logistics Research.

The first part of the project has contained a search for and structuring of quantitative methods applicable to the field of logistics performance. The methods were grouped in two main

groups according to how they have evolved in the company: (1)financial measurement methods such as: budgeting techniques, cost estimat- ing methods, mission costing etc, and (2) engineered physical measures such as: productivity, leadtimes, quality, customer service, turnover rates, etc. Thefollowing aspects of measures are discussed in the paper: the purpose of measuring, the historical development of measures at- tached to logistics performance and how measures can be structured along different vectors. We conclude that the weaknesses of today’s measuring systems often stems from a “measurement gap” between the economist’s approach, focusing on measures for financial control, and the engineerrs approach, focusing on measuring physical quantities.

The second part of the paper includes a brief discussion on how the measurement system should be incorporated in a strategic review process in the company. As a result, a measuring model for evaluating a company’s overall logistics performance is presented, focusing on balancing the conflicting purposes of financial and physical measurement.

*Presented at the 5th International Working Seminar on Production Economics, Igls, Austria, February 22-26, 1988.

0167-188X/89/$03.50 0 1989 Elsevier Science Publishers B.V.

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INTRODUCTION

The concept of measuring logistics performance includes a wide range of planning and control measurements related to the company’s logistics management. Usually included in this kind of performance measurements are different productivity measures, customer service levels, leadtimes, turnover-rates, etc., as well as financial measures and techniques like: cost accounting, cost determination, budgeting, standard costing and so on. Observe that creating inventory control models, route scheduling and other quantitative methods of mathematical programming is not the main purpose when measuring performance. Then why do we need this kind of motivating and controlling performance measures? There is not one but several answers to that question, but it is of great importance that the measures give support in: ( 1) illustrating different aspects of the logistics activities: (2) managing the direct flow of materials; (3) setting goals; and (4) controlling the ful~llment of objectives. We can see that the purpose of measuring varies and there are also different kinds of dif~culties that emerge. Except general problems - such as which measures do best illustrate the activities we want to describe -many practical aspects remain; how can the basic information needed be computed, is it possible to find the right data and how much does it cost?

One of the most basic problems is the question of which factors that can be regarded as directly measurable, and how to interpret the measured result and turn it into the proper corrective action. The following example illustrates the problem [ 1 ] :

During the second part of the seventies some major american industries were out-concurred-on their own domestic market - by foreign (mainly Japanese) industry. The ptoduc- tion costs of the domestic american products simply ran too high. The natural reaction which followed was an extensive cost reduction programme, which ought to increase productivity. But the expected effects of the pro~amme did not show up: the emerging problems shown in the productivity measurements. which seemed to cause the difficulties on the market, were merely symptomatic. One of the reasons was of

course the japanese’ ability to accomplish more with less resources, that is. reaching higher productivity. But the american prodnct~vity programme failed due to several other reasons:

The actions focused on the efficiency of the labours. but the direct labour cost is rarely more than 10% of the production costs. The focus on factory labours only drew too much attention towards shortsighted questions ofminor importance. The far-sighted decisions concerning process technology and manufacturing systems were often neglected. Cost reduction as the main purpose gave little attention to important variables such as short leadtimes, quality, flexible manufactu~ng and other elements of customer service.

While dealing directly with the productivity problem, the symptoms of the difficulties were hidden, but the basic problem remained! Awareness of what different measures really do illustrate can help in drawing better conclusions and avoiding false moves.

THE PROBLEM OF COORDINATION

The scope of the logistics function is to in- tegrate the activities performed by conven- tional departments (purchasing, manufacturing, etc.) in order to achieve an effective flow of materials. Different kinds of performance measures usually appear in different departments and at different levels, often lacking in overall coordination. A question of great importance is at what extent and at which level it is possible - an meaningful - to create such an integrated Iogistics measurement system. It is thus of great interest to increase the knowledge in at first which measures and methods are interesting from the coordinating point of view, but also which of them can best serve as “critical measures” in, for example, different industrial sectors and in different departments. Bearing this in mind, our focus is on systematically integrating and coordinating different measurements in an overall strategy for measuring logistics performance. But first some comments to previous research and a historical perspective on the development of logistics performance measures.

THE DEVELOPMENT OF LOGISTICS PERFORMANCE MEASURES

As we will show beneath, very much of the existing methods and techniques have evolved

Development of the logistics performance measures

Engineered measurement Flnanclal measurement (physical units) (monetary units)

“Measurement gap”

Fig. 1. The historical development of logistics performance measures.

TABLE I

Major empirical research on logistics performance measures

Reference Country and number of companies

* AT Kearney [2] U.S. - 418 companies . Stevens, J. [ 31 Great Britain - 105 companies . Grochla, R. et al. [4] West Germany - 127 companies . Torremans, H. [ 5 ] Netherlands - 10 companies * Hayes A. and [6] U.S. - 250 companies

Renard, G.

tant variables. Some major examples are: the productivity matrix (showing inputs and out- puts on department level); the ROI tree (ag- gregated financial relations); the pyramid model (grouping the use of ratios and indices

according to the company’s hierarchy); the lo-

gistics ,process-chain model (illustrating the planning, realization and control processes ) .

from more traditional productivity measurements, financial ratios, etc., and a lot of these methods flourish in the logistics area, but very few tailored methods of measuring logistics performance exist.

The previous empirical research on the use of indices and ratio measures includes only a few extensive studies that directly cope with the usefulness of different logistics performance measures. The most important ones are summarized in Table 1. Observe that three of the investigations deal mainly with purchasing. The AT Kearney report [ 2 ] focus on productivity and only the Dutch study by Torremans [ 5 ] covers the overall logistics performance.

Financial measuring methods. The econo-

mist’s approach to determine costs and reve-

nues related to logistics. The methods have evolved from traditional cost control and pric- ing methods. But traditional accounting sys-

tems are quite often designed for other purposes, which means they are not directly

applicable to logistics measurement. The adaptions which best Iit logistics can be found

in methods for budgeting (standard costing

and flexible budgeting, mission costing) and

cost determination and allocation.

In connection with a mapping of different performance measurement methods [ 71, the methods were grouped according to their in- herent characters:

Measuring methods controlling physical quantities. Mainly ratios of time and/or vol-

umes used in communication between hierar- chical levels. This kind of engineered measures

were originally created to help increase effi-

ciency and accomplish a better use of resources through measuring productivity, but

have developed to cover areas of quality control and customer service as well.

Overall measuring models. Models which are Measuring performance within logistics de- supposed to explain relations between impor- partments. In purchasing, production, physical

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distribution etc, the use of major key indices and ratios can be categorized in: financial ratios, turnover ratios, productivity, leadtimes, volumes, quality control rates and customer service.

We have found that behind these groups of methods lies a historical explanation which is illustrated in Fig. 1.

The fact that the development has followed two approaches - one “engineer’s approach” focusing on measuring physical quantities, and on e“economist’s approach” focusing on measuring monetary units for financial control - has resulted in a struggle to bridge the gap between those traditional measuring methods. And that is another main purpose of the logistics performance measures.

The “measurement gap” is very often found at the middle management level, where financial ratios are being used communicating results “upwards” and physical quantities “downwards” to the operational level.

HOW TO BRIDGE THE “MEASUREMENT GAP”

Many of the problems in measuring logistics performance discussed today, derives from the mentioned “measurement gap”. It is consid- ered of great importance to find out how changes in physical quantities, such as leadtimes and customer service levels, influence the company’s costs and revenues. Unfortunately, the kind of total-cost analysis necessary are often time-demanding and difficult to perform. One of the reasons is that a change under the responsibility of one department usually affects the results achieved by other departments. It becomes necessary to trade off a lot of different factors in order to find the best al- ternative. We even doubt if it is possible to make a complete total-cost analysis. Let us give an example why we think that is the case. A central question in that type of analysis would be, “how do different customer service levels influence the company’s revenues?“. The an-

swer would be some kind of optimization of all possible customer service elements and service levels. As far as we know there are no companies that have tried this type of approach. Apart from the problem of measuring, decisions about customer service levels take an important part in positioning the company on the market in relation to its competitors.

There are, however, other ways of collecting information than through measurements. We do all have experience, and if we have the right experience it is of great help in decisions like this. We do also, in our daily lives, aquire knowledge that is not possible to formalize, or to quantify, knowledge that only leaves an impression and a feeling that we ought to do this or that. When we make decisions, both privately and in more formal situations in our working lives, this type of unquantifiable knowledge plays an important role. Successful companies that we have visited do make these kinds of decisions even if they are hard to mo- tivate. Weaker companies have a tendency towards not making this type of decisions. They tend to keep on doing what they always have done as a way of avoiding difficult decisions. A way of dealing with these problems that many successful companies use is outlined below.

In order to plan and control the logistics system it is becoming increasingly important to develop strategies and use coordinating objectives. A way to deal with for example costomer service levels is to consider questions like “what level of customer service to offer the market” in an approach which incorporates an overall logistics performance measurement system together with more intuitive and qual- itative estimates in an objectives formulation process.

The strategic planning demands a continu- ous evaluation of changes that occur inside as well as outside the company plus the ability to relate them to both strategic and operational objectives. The development of business logistics objectives is affected by the overall corpo-

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rate strategy, manufacturing strategy, market- ing strategy etc, in an interactive process meaning examination and evaluation of the existing organization, distribution channels and logistics systems. The purpose of auditing the logistics system is usually assumed to con- sist of [ 81: - judging the logistics performance; - supporting the design of materials manage-

ment, production, distribution and customer service strategies with sufficient information; and

- controlling the arisen costs so as to reach the profit targets. An important aspect, which is easily “for-

gotten”, is the possibility to use the logistics strategy to guide the extent of the logistics measurement system. Designing the logistics strategy gives an opportunity to consider coordinating effects and non-quantifiable factors and through overall objectives support the operational level activities. A consistent set of objectives can mean better guidelines and del- egated responsibilities and thus less need of detailed control measures at higher levels.

We have already indicated that all trade-off situations must be analyzed by the time of per- forming the audit, and certain variables such as customer service levels must be “locked” and form goals in the logistics strategy. In this way a consistent management of the overall logistics in the company will be possible. But the design of an auditing methods, which will be able to incorporate the strategies and objectives necessary to obtain the discussed coordinating effect, is the next step we will consider in our research and thus beyond the scope of this paper.

In the remainder of the paper we will present a measuring model which focuses on the trade- off between Iinancial and physical measurements, and that is in itself a good starting-point when initiating a systematic logistics audit.

DESIGNING AN OVERALL MEASURING MODEL

In our contacts with Swedish industry we have found that the usual way to measure a department’s performance is via budget control, trying to include the costs associated with the logistics activities in order to encourage cost effective behaviour. But the mission of a department is not to strive for efJiciency and cut costs alone - in that case the best thing would be to do nothing! There is also a responsibility towards the surrounding departments and the entire company, and this calls for a need to quantify the department’s effectiveness. Re- sponsibility and commitment are usually measured through some kind of customer service measures and quality control. Hence we can divide the measures in a department’s internal (efficiency) and external (effectiveness) logistics performance measures. Internal and external performance are not new as terms, but they have hitherto been used only when judging an entire company’s performance. It is, therefore, of interest to see how it can be used also at the departmental level when describing the logistics of a company, something which has not been done earlier. We will show that this is a very useful approach when describing and measuring logistics performance. If only efficiency is measured and used for judging performance, as the case study below will give an example on, it is likely to cause the effectiveness to go down. The reason being that conflicts between keeping costs down and doing what you are assigned to do will often be resolved in favour of cutting costs.

With the measurement gap in mind we have used the “internal vs. external” approach and studied how the conflicting financial and customer service objectives can be measured and structured in order to balance the demands on different departments’ logistics performance. Two examples from our research, a survey and a case study, will show that the approach is well suited for our overall measuring model.

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The survey example

The indicators given in Fig. 2 are the preliminary results of a survey* covering Swedish companies’ evaluation of the most important logistics performance indicators.

The scheme in Fig. 2 illustrates financial and physical indicators. The measures have been structured according to the internal vs. external approach so that: the measures between the vertical lines are those indicating the corre- sponding department’s interna/ efficiency, while those situated oy1 the vertical lines are in- fluenced by the proceeding activities and have an effect on the following departments’ performance and results and can be said to describe the external effectiveness. The survey gave as a result that the most important groups to measure, according to Swedish industry, are external performance via:

- different aspects of customer service and internal performance via:

Overall ratios

budget control (logistics cost elements);

capital costs (supply, work in process, fin-

ished goods ) ; and

turnover rates.

The concept did in this way help us to pick the central logistics performance indicators and

relate them to each other in a structured pre-

sentation according to the example in Fig. 2. The focus is not on financial OY physical quan-

tities, but on the trade-off between the two groups and the total result of the logistics activities.

The structure which is formed by the different measures can in this way also be used the

other way round: to help us trace the reasons

of a change in performance.

The case study example

This example is fetched from a case study

based on extensive interviews with about 15 managers in the departments influencing the

~~ ,_;;b - Rate of timely - Rate of timely

deliverfes Rate of timely Rate of timely

deliveries deliveries deliveries

-Material shollages - Material shortages - Backorder rate Backorder rate

- Rate of quality failures - Rate of qua&y failures Rate of quailiy failures

O>> Supplier Materials management

Production Physical distribution >O Customer

- Price index - Direct - Cost for tradeaccounts

purchased products materials costs lnvemory carrying pay&k

COStS -Transportation costs

- Supply inventory value

Cost of purchased - Value of wlk - Inventory value

producls compared lo in process inventory finished goods

turnover Production cosb

- Scrap costs

Financial rafios

Fig. 2. Important logistics performance measures.

*The survey covers about 150 Swedish companies. The preliminary results (94 companies) are presented in [ 91.

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flow of materials in a multinational Swedish company.

The products are sold as OEM as well as to end users. Figure 3 illustrates the flow of materials through the company: The company produces many of the important components in their own production units, and the final products are assemblied in assembly units. All of the finished products are stored in a central finished goods inventory and after that distrib- uted to sales companies are warehouses all over the world.

The performance within the different units in Fig. 3 was earlier measured only as the result (real costs) against budget. (There did, and still does, of course exist a number of other performance measurements within each unit, but we will exclude them in this short sum- mary. ) As a direct effect of this measuring system, which focused only on cost reduction (efficiency), the company’s ability to manage the flow of materials was growing worse and worse (effectiveness). We can illustrate the problems in the following way:

The performance of a unit was only measured through the ability to manage the internal resources. The important thing for the re- sponsible managers was to keep the costs down to reach the budget target which was something they also were really good at doing. But the mission for the logistics system, to make the products available for the customers in a

fast and reliable way, was “forgotten”. The variance in leadtimes and delivery time between the units grew only higher. To protect themselves from shortages, the warehouse managers started to order products way ahead of the time the customer needed them. The only result of this ought to be a build-up of stock in finished goods inventory and the different warehouses. But the awareness that the orders were placed to early made the producing and assemblying units calculate with longer time margins. and so the uncertainty was spread throughout the entire company. Both prom- ised and real delivery leadtimes grew longer and longer, and the time of delivery was rarely held.

Something had to be done. After having an- alysed the situation it was of course found that delivery leadtimes and reliability had to be brought under better control. To achieve this, the customer service factors was given a simi- lar status as the budget in the system for judging a unit’s total performance. It was possible to get the wanted information available through the existing reporting systems and hence could a measuring model be developed in short time. Figure 4 shows the different new information systems that were created for measuring external performance (suppl perf - supplier performance, prod perf - production performance, and cust serv - customer service ) .

L 0 Warehouse

Fig. 3. The flow of materials through the studied company.

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Fig. 4. The case study: external performance measuring systems

A lot of different factors are measured in the different systems, and they differ a little de- pending on which system we consider, but they all give comparable results based on two central factors: availability (the ability to deliver according to the customer’s - the next unit’s - wish) and reliability (the ability to deliver according to made promises).

Substantial improvement were reached al- most at once. Planning as well as control of the performance of the logistics system was now made through balancing between economic measures (budget control) and physical logistics measures (customer service).

It is obvious that the company, although without using the terms “internal vs. external”, uses the same approach that we suggested. In this case the measurement gap at middle management level still exists, but the conceptual approach has proven to be a help for managers to do a better job. The new system for measuring logistics performance focuses on the trade off between cost effective behaviour and customer service and this gives the manager better possibilities and incentives to pay attention to these questions.

THE PROPOSED MEASURING MODEL

We think that the two examples clearly illustrate which components to include in an overall measuring model. The survey and the eval- uated measures presented in Fig. 2 gave us a great deal of help to choose which groups of measures that are of the greatest importance. The internal vs. external approach can be sum-

Cust serv

1 Cust serv

4

marized in the following areas which need to be covered when measuring overall logistics performance (the suggested performance measures can be seen as examples, since a discussion and motivation of individual measures would consume too much space ) :

Internal performance within the units (for example: materials management, production, distribution ). Important measurements:

-

-

result vs. budget (logistics costs) inventory value, capital cost turnover rates productivity internal leadtimes External performance between the different

units in the company: availability (lead time and/or service level) reliability (quality and timing)

External performance between the different units in the company: availability (lead time and/or service level) reliability (quality and timing)

External performance for the entire company towards the customers: customer service elements (availability, reliability, lead times, etc.) turnover

Supplier performance towards the company: quality reliability lead time price

The relation between the logistics performance and the performance of the entire company:

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She company’s external logistics

performance:

Customer service Lead times S&S

I

Fig. 5. A conceptual view of the measuring model.

- result vs. budget - return on assets - total turnover rate - total value in stock - total capital cost

The conceptual approach of the model is shown summarized in Fig. 5.

CONCLUSIONS

We have found that much of the problems associated with measuring logistics performance lie in the “measurement gap” between the traditional financial measurement and engineered measurement of physical quantities.

This is very much a middle management problem. The financial measures are common as objectives and for controlling the company’s activities at higher management level, while the physical measures are being used at the operational level for controlling the physical movement of the material. In the proposed

overall measuring model we have combined those two approaches with the help of a discussion in terms of “internal vs. external” measures to illustrate the quantifiable aspects of the logistics system.

The holistic view we have tried to use in the project has focused our work on the more “strategic” aspects of measurement. We think it is necessary at least to try to deal with these questions in order not to lose the non-quantifiable aspects when developing a system for measuring logistics performance.

The proposed measuring model will, together with a descriptive model (auditing method ) covering non-quantifiable aspects, provide a very powerful tool when analyzing and describing a company’s logistics system. Hence, an important and challenging question is to develop an auditing method which can help us to deal more systematically with the performance measures in the planning and control processes and relate them to the company’s strategic goals.

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REFERENCES 6

I

Skinner. W., 1986. The productivity paradox. Harv. Bus. Rev., 4: 55-59. AT Kearney, 1984. Measuring and Improving Productiv- 8 ity in Physical Distribution. NCPDM, Chicago, IL. Stevens, J.. 1978. Measuring purchasing performance, Business Book, London. 9 Grochla, R. et al., Zum Einsatz von Kennzahlen in der Materialwirtschaft mittelstlndischer Industrieunterneh- mungen. Schmalenbachs Z. Betriebswirtsch. Forsch., 6: 569-580. Torremans, H., 1984. Het gebruik van prestatie-indika- toren in de logistiek, NEVEM. Afstudeerrapport Tech- nische Universiteit Eindhoven, September (in Dutch).

Hayes, A. and Renard, G., 1964. Evaluating Purchasing Performance. Research Study No 66, AMA, New York. Aronsson, H. Andersson, P. and Storhagen, N.G., 1988. Materialadministrativa matt och matmetoder. Studentlit- teratur, Lund. Lambert, D. and Sterling, J.A., 1985. A methodology for assessing logistics operating systems. Int. J. Phys. Distrib. Mater. Manage., 15 (6): 3-29. Andersson, P. and Aronsson, H., 1988. Matstrategi - en utvardering av generella MA-matmetoder. Dept. of Man. and Economics, Linkoping: Linkoping Institute of Tech- nology, Research Report 16 1.

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