STRATEGIC CHOICE AND DETERMINISM IN

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Boer, H. and J.J. Krabbendam (1993), Inleiding Organisatiekunde, School of Management. Studies, University of Twente, Enschede (in Dutch). Child, J., (1972) ...
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STRATEGIC CHOICE AND DETERMINISM IN OPERATIONS MANAGEMENT Frans Ruffini, Harry Boer and Maarten van Riemsdijk Faculty of Technology & Management, University of Twente, The Netherlands ABSTRACT After a brief introduction to the debate on determinism versus strategic choice in the structuring of organisations, the results of field research into the design of production organisations are described. These results are used to illustrate the authors’ conclusion that both approaches fail to explain how organisation designs develop in reality. An agenda is proposed for more useful research into the design, functioning and performance of organisations. INTRODUCTION An ongoing debate in organisation theory is on the question whether or not organisations have strategic choice when designing their structure. Two recent publications, representative of the debate, propose opposite conclusions. According to Donaldson (1996), there is no question of strategic choice. Once chosen, ‘… the environment … shapes [the organization’s] strategy, technology, size and required innovation rate. These contingencies in turn determine … the structure the organization needs to adopt if it is to operate effectively’ (p.2), meaning ‘that there is no real strategic choice’ (p.51). A similar positivist approach seems to underlie most of the current thinking in the field of Operations Management and Strategy – OM/S (e.g. Hayes and Wheelwright 1984, Hill 1995). Based on partially the same sources, Gresov and Drazin (1997) argue for strategic choice: ‘the final ... performance of an organization ... can be achieved through multiple different organizational structures even if the contingencies the organization faces are the same’ (p.403/404). ‘[T]he environment ... determines the function(s) the organization must perform, but not its specific structures’ (p.407). Based on a study of the design and performance of 19 production organisations, Draaijer and Boer (1995) have drawn a similar conclusion. The purpose of the present paper is to show that this debate hardly adds to our understanding of how organisations are designed. The paper concludes with some suggestions for more useful research into the design, functioning and performance of organisations. RESEARCH DESIGN The present paper is based on eight case studies, three of which will be presented here for illustrative purposes. The process-based contingency model of organisations (see e.g. Boer & Krabbendam 1993) was used to analyse the relationships between the design and the performance of production systems. Operationalised for the purpose of analysing the relationships between the design and market performance of companies, the model regards organisations as systems of people who, either or not using resources, perform various processes. Primary processes transform informational and/or material inputs into products and/or services. The outputs of strategic and adaptive management processes are planning and design decisions on future product-market-technology-organisation combinations. Maintenance processes actually implement those decisions and keep the resulting system ‘up-to-date’. Operations management activities monitor and control the day-to-day functioning of the system. In order that the different processes can be performed, various technologies are needed, which are incorporated in

people and resources. Finally, organisational arrangements divide and co-ordinate (the constituent activities of) the various processes. For the present paper this model was operationalised using Hill (1995), Draaijer (1993) and Boer & Krabbendam (1991, 1993), to define and measure market demands, processes, technologies and organisational arrangements. THE CASES Company A Products: Top end of the middle-market segment. Cooking plates, consisting of ± 50 parts; complete cookers consisting of ± 160 parts. The complexity of the components is mostly low. Customer demands: The qualifiers for the company are: (a) delivery reliability, (b) delivery time, (c) product quality and (d) service program. Order winners are: (a) price level, (b) recognisable design, (c) fast in copying new trends and (d) high level of functional variety. Sales: 50,000 to 100,000 units a year; some small seasonal fluctuations. Production layout final assembly lines pre-assembly unit

Production characteristics • Assembly to stock • Batch size: relatively large, varying • Planning horizon: 2 weeks (frozen) • Production control: day planning • Component supply: batch and two-bin

test test test Performance: Delivery reliability is usually around 98%, but tends to drop when a large number of new products are introduced. Component stock level is high due to long supply lead times and large quantities that have to be ordered to receive discounts. Delivery times are short (delivery from stock). Company B Products: Cookers, cooking plates and ovens for the up-market segment. A lot of variants per product group. Product and component complexity are similar to company A. Customer demands: The qualifiers are: (a) short delivery time, (b) delivery reliability, (c) quality and (d) after sales service. Order winners: (a) design, (b) large variety, especially in colour combinations, (c) innovativeness of products and (d) company image. Sales: 150,000 to 200,000 units a year; seasonal fluctuations: ±10-20 %. Production layout Final assembly lines

PA

PA

PA

Test

Production characteristics • Assembly to order • Batch size is always 1 • Planning horizon: 6 weeks • Production control: day list • Component supply: order and two-bin • Check on component availability at order acceptance

PA = Pre-assembly lines

Performance: 10% of all orders are rush orders and have to be made in less than a day. The system is so flexible that this is achieved without any extra effort. Production lead time is only several hours. Changeover times between different products are zero. There is no end item stock, but component stock level is ± 7 weeks, due to the large number of variants offered. De-

livery reliability is between 95 and 100%. Company C Products: Central heating boilers for the up-market segment. About 30-40 variants for the home market; more variants for the export market. A boiler has 150 to 170 components. The component complexity is low to moderate. Parts commonality is about 70%. Customer demands: The qualifiers are: (a) delivery time, (b) delivery reliability, (c) functional variety and (d) product quality. Order winners are the company’s (a) marketing policy, (b) innovative products, and (c) corporate image. Sales: 25,000 to 40,000 units a year. Clear seasonal pattern, but weather-dependent and, thus, unpredictable demand fluctuations. Production layout

PA

FA

FA

FA

Test

Test

FA

Test

FA

Test

Test

FA Test

FA Test

Production characteristics • Assembly to stock • Batch sizes vary from 1 to 100 • Planning horizon: 3 weeks (frozen) • Production control: week list • Component supply: batch and two-bin

FA Test

PA= Pre-assembly unit FA= Final assembly unit

Performance: Delivery time is less than 24 hours. Delivery reliability is 95-100%. Significant differences between final assembly teams in terms of output (up to 30%) and flexibility. Stock levels for end items are 4 to 6 weeks. In low season stock is built for high season. Stock levels of components are high, due to low buying power, leading to large order quantities. DISCUSSION Similarities and differences As table 1 shows, there are quite a few similarities between the cases. All three companies score high in terms of the external indicators delivery time, delivery reliability and product variety. All of them are labour-intensive assembly plants. Test facilities are the only expensive equipment. In all cases parts manufacturing has been outsourced. In all three cases, customers, management and employees alike, are satisfied with the design, functioning, performance of, and products produced by, the production system. There are also some significant differences, namely in terms of process choice (CODP), the links between pre-assembly and final assembly, and stock points. These differences are reflected in the internal performance of the respective companies, such as stock levels, work-inprogress (WIP), flexibility and efficiency. Company B, for example, has optimised for time, and accepted slack in terms of efficiency and variety. Companies A and C have optimised for efficiency, at the expense of throughput time and end item stock. In other words, the case studies suggest that rather different production systems may yield very similar types and levels of external performance. At first sight, therefore, the research seems to provide evidence against determinism and for strategic choice. However, there are a number of concerns that we would like to put forward. Table 1

A comparison of the three companies Company A

Company B

Company C

Market performance Delivery time Delivery reliability Variety 1 Design choices CODP 2 Pre-assembly and final assembly Control parameter Slack in Internal performance Parts stock WIP (days) End item stock Flexibility 3 Efficiency 4

++ ++ +

++ ++ ++

++ ++ +

assembly to stock separate, both centrally controlled efficiency time

assembly to order integrated time efficiency & variety

assembly to stock separate: pre-assembly controls final assembly efficiency & flexibility time

high 5 high + +

high