Abstract number: 002-0158

Achieving both fast response and low cost via global supply

Second World Conference on POM and 15th Annual POM Conference, Cancun, Mexico, April 30 - May 3, 2004.

Corresponding author: Roy Stratton, Nottingham Business School, Nottingham Trent University, Nottingham NG1 4BU (E-mail: ) (Tel: +44 115 848 2715) (Fax: +44 115 848 6512)

Second authorRoger D.H. Warburton, Griffin Manufacturing, Fall River, Ma,

02722 USA, and University of Massachusetts, Dartmouth, Ma, 02747 USA. (E-mail: )

Abstract

Markets are increasingly characterised by demand uncertainty and short product life cycles, while at the same time supply is shifting to remote low cost global sources. The importance of acknowledging the resultant cost versus response trade-off is clearly apparent, especially in the fashion apparel industry.

Various practical approaches to minimising, postponing or otherwise managing the source of demand uncertainty have emerged in widely cited cases. However, even when the trade-off results from planned management action, as in the case of outsourcing, there is little evidence of the implications being acknowledged and actively addressed. This paper reports on three case studies from the USA and UK that demonstrate how outsourcing decisions are commonly made with little or no attempt to address the fast response requirements of the market. The paper explores the underlying reasons for this and offers means of making the trade-off implications and potential solutions more explicit.

Introduction

Addressing the strategic as well as the cost implications of functional decisions continues to be elusive. In the past the resulting misalignment was commonly associated with the incremental nature of such change (Hill, 1998), but this does not fully explain the mismatch commonly resulting from outsourcing decisions. Research suggests that such decisions often lack a holistic perspective (Baines, 2003) resulting in a sub-optimal cost focus. The growth in global sourcing, however, is increasingly encroaching on markets characterized by short product life cycles and demand uncertainty. Global supply from low cost sources is therefore increasingly prone to aggravating the cost versus response trade-off - a problem that is now widely cited, particularly in the apparel industry (Lowson, 2003).

Practical strategies to address such supply chain misalignments have been widely reported over the years, as in the cases of Bennetton, Sports Obermeyer (Fisher et al., 1994), Hewlett Packard (Feitzinger and Lee, 1997) and more recently Zara. However, the tendency to think functionally rather than holistically persists (Fisher, 1997; Fisher, 2000; Ferdows, 2003)

This paper seeks to explain the growing significance of the cost versus response trade-off as well as present a conceptual approach to managing such trade-offs in the context of the supply chain. Three case studies, associated with outsourcing, are subsequently analysed in relation to this approach.

Research Programme Design

The research reported in this paper is part of a wider research project aimed at exploring strategies and supporting concepts used to improve the level of stability within a supply chain.

The conceptual framework derived from the initial secondary research is shown in Exhibit 1 and from this some key questions were derived:

  • How does internal and external system variation and uncertainty impact on a supply chain?
  • How and why do different strategies limit such variation and uncertainty?
  • How and why does the trade-off concept support the strategy development process?
  • How can a company use investments in inventory and capacity to provide greater stability in the internal and external phases of a delivery system?

In choosing case study sites that explicitly exhibit the instability associated with the cost versus delivery speed trade-off, a number of companies involved in realigning their strategies following outsourcing decisions were selected.

This resulted in a further question:

  • Under what conditions does local rather than holistic decision-making tend to predominate?

This paper addresses these questions in relation to the three case studies associated with outsourcing.

The case-based research method was adopted, inline with the how and why questions being asked (Yin, 1994). The cases were chosen and administered in accordance with replication logic and theory development (Eisenhardt, 1989). The unit of analysis was the company and data was collected with a research protocol using multiple sources of evidence. The data collection method included plant observation, multiple semi-structured interviews, archival records and documents, with due attention being given to triangulation and subsequent analysis (Miles and Huberman, 1994).

Secondary research used in the derivation of the conceptual model

The research has identified three conceptual approaches to managing trade-offs in supply chains, with particular reference to the cost versus delivery speed trade-off. This review of previous research and practice is structured to reflect the associated conceptual model.

The trade-off concept and continuous improvement

The emergence of management science in the early part of the last century was functionally structured and resulted in local optimization centred on cost. In this way the level of inspection and the size of batches were determined via cost models, as illustrated in Exhibit 2 & 3, which provided a means of optimizing the conflicting requirements.

By the 1960s it became apparent that organisations needed to be aligned to meet specific needs (Burns and Stalker, 1961) and Skinner (1969) exposed the strategic need to align the operations management sub-functions to satisfy market requirements other than price. This work was further developed (Hayes and Wheelwright, 1979; Hill, 1985) with concepts to help distinguish the different market characteristics and classic process alignments.

In Japan, however, they had already embarked on a different approach. Deming’s (1982) Japanese lecture series from the 1950s had created an awareness of the strategic importance of not just realigning the strategic choices but reducing special and common causes of variation in an organization, and thereby attacking the conformance quality-cost trade-off at source. Deming’s work was considered to be central to Toyota’s successand Ohno (1988) applied this thinking to production flow and similarly challenged the waste associated with poor process reliability and the process inflexibility associated with long set-up times. Hence, it is not surprising that some authors were questioning the merits of the ‘either or’ mentality associated with the trade-off concept (Schonberger, 1982). Ferdows and De Meyer (1990) used empirical research in support of ‘a new theory’ that integrated these findings and argued that the trade-off concept, although still relevant to strategic decision-making, needed to acknowledge the opportunity to systematically reduce the cause of the trade-off directly. Their sand cone model suggested a natural sequence to improvement they referred to as cumulative capabilities. This commenced with quality, then dependability, then flexibility and finally cost. This extended earlier work by Nakane (1986), which stressed the importance of improving quality and dependability before imposing demands for increased flexibility on a delivery system. Ferdows and Meyer’s study led to the conclusion that focusing on quality reduces the sources of variation in the system, which in turn improves efficiency and reduces cost; however, focusing on costs does not result in a corresponding improvement in quality. This work stresses the importance of understanding how the order of priority, particularly concerning cost, impacts trade-offs and although conformance quality versus cost is still listed as a trade-off by some industrialists it is now commonly acknowledged to be a ‘perceived’ rather than ‘real’ trade-off (Da Silveira and Slack, 2001). Similarly, Mapes et al. (1997) conducted survey research that also acknowledges the fact that good performance on one measure leads to good performance on other measures. Their work stressed the need to eliminate uncertainty and unreliability as well as waste, arguing that much surplus stock, labour and capital equipment is there as a consequence of uncertainty and unreliability. Slack’s (1998) generic trade-off approach similarly identifies the role of flexibility in reducing the impact of variation and uncertainty and therefore the trade-off implications.

Schmenner and Swink (1998) in developing this conceptually have proposed a ‘theory of performance frontiers’ distinguishing between an asset and an operating frontier. Exhibit 4 illustrates this concept in relation to the cost versus supply lead-time trade-off. An asset frontier defines the performance trade-off under ideal operating conditions, so defining the performance limits of the physical assets. Whereas, an operating frontier acknowledges the limitations of the infrastructure system variables (such as quality, process reliability, set-up times, etc) associated with policies. Therefore, in line with the above, simultaneously improving the system performance on all fronts is possible and under these circumstances the operating frontier shifts closer to the limiting frontier of the current assets. Vastag (2000) usefully adds to this work by stressing the significance of the operating frontier as opposed to the asset frontier in gaining competitive advantage. He relates this to the tacit performance improvements associated with Toyota that have been so difficult to replicate. This view is supported by close analysis of Toyota’s NUMMI plant (Alder et al., 1999) that demonstrated the organic means by which the flexibility versus efficiency trade-offs were incrementally improved through the plant’s exceptional capacity for first-order and second-order learning. Their work shows how this was achieved through ‘ambidextrous’ mechanisms and trust across the supply chain. These mechanisms involved meta-routines (making non-routine activities routine), job enrichment, role switching (e.g. switching between improvement tasks and production tasks) and partitioning (separating out units in line with specialist requirements). They reported that these flexible technologies enable firms to shift the trade-off curve between efficiency and flexibility. Illustrating how much of the innovation associated with shifting the trade-off lies in the domain of organisational structures and procedures. Their research stressed the importance of cooperation and trust across the supply chain together with the establishment of mechanisms to support the shifting of these trade-off boundaries.

Goldratt (1990) similarly argues, in what is now commonly known as ‘the theory of constraints’, that the performance of a system is rarely constrained by resources and the corresponding asset frontier but by what he refers to as policy constraints. His work stresses the importance of challenging the assumptions underpinning such policies that give rise to the trade-off models typified in Exhibit 1 and 2. Focusing on cost models does not address the strategic needs and consequently gives rise to policies that sustain the associated wasteful variation.

Whereas Deming and later Ohno universally targeted wasteful variation associated with non-conformance, reliability and inflexibility under the umbrella of continuous improvement, Goldratt developed the use of the trade-off concept to focus improvement. In this way he found a means of systematically exposing and challenging the policies that limited (constrained) the throughput of the system, akin to shifting the operating frontier associated with specific products and markets. His contention was that improving the systems throughput, unlike cost reduction, was an inherently focused activity and very few policies or resources constrained a system at one time.

In an attempt to illustrate how the trade-off concept may be used to focus improvement, the batch size model has been presented (Exhibit 5) in such a way that the policies and associated thinking underpinning the model may be challenged systematically. This is in the form of an Evaporating Cloud Diagram (Goldratt, 1990) otherwise known as a Conflict Resolution Diagram (CRD) (Scheinkopf, 1999).

Exhibit 5 represents the logic of the traditional batch optimization diagram (Exhibit 3), where requirements B and C are necessary (but not sufficient) to achieve the objective A. Similarly the prerequisites D and D’ are necessary (but not sufficient) to achieve the requirements at B and C, respectively. The pre-requisite requirements are normally shown as opposites to make the contradiction as explicit as possible, so enabling the logic underpinning it to be challenged. In TOC terms, the Cloud is evaporated (i.e. the problem is solved) if one of the assumptions embodied in an arrow can in some way be invalidated. By way of example, Toyota challenged the assumptions underpinning the arrow B-D (Shingo, 1990), which states that large batches are a necessary prerequisite for reducing set-up costs. The arrow AB was effectively evaporated when the associated cost accounting assumptions were challenged in the 1980s (Kaplan, 1984). Goldratt (1983) more specifically stressed the fallacy of using the inherent spare capacity in batch processing to increase excess inventory rather than shortening lead-times through increasing the number of setups. This critique therefore calls for a rewrite of the diagram to represent the strategic as opposed to ‘cost’ trade-offs, which will be developed further.

Investment choice: managing variation

The above research and practice stresses the importance of reducing the sources of variation and uncertainty and highlights how policies embodied in sub-functional cost models have and, in many cases, continue to constrain the operating frontiers.

Skinner (1969) advocated making investment choices that were geared to the market or what Hill (1985) called order winning and qualifying criteria. In this way investments suited to high volume low variety manufacture would typically compete on price with high levels of capacity utilization and low levels of WIP inventory. Alternatively, low volume high variety products, typically competing on delivery speed, would demand more responsive capacity and/or inventory to meet the product variation and demand uncertainty. In such circumstances there is inherently more variation and uncertainty that needs to be managed.

Supply chains may be protected from the disruptive nature of variation and uncertainty by using inventory or capacity to protect the flow. However, although capacity is widely used in service environments, the perception that an idle resource is a waste has resulted in it commonly being a blind spot in the design of supply chains.

Newman et al. (1993) address the need to deal with the uncertainties in manufacturing; linking flexibility at the macro and micro level to buffering through capacity, inventory and extended lead-times [order backlogs] in the form of a dynamic equilibrium model. He emphasises the trade-off choices of investing in capacity or inventory to protect the flow. Correa (1994) links uncertainty and variation to the concepts of flexibility and its role in relieving the associated trade-offs. Caputo (1996) explores the role of capacity and inventory buffers being used in combination and he identifies many forms of capacity and inventory buffers, advocating that when effectively planned they do not necessarily result in the hiding of problems.

Fisher et al. (1997) stresses the importance of ‘reactive capacity’ in configuring a supply chain to address constraints and illustrates this by challenging the concept of minimum lot size policies.

Goldratt’s (1984) early work on the role of bottleneck resources in the management of delivery systems was based on the fact that batch-processing environments have very few bottlenecks (resources constraints). However, the inherent spare capacity in such processes was not effectively utilised to enable flow (Conway et al., 1988) as cost models and local efficiency measures typically drove the operational decisions, as already discussed.

The Drum-Buffer-Rope planning and control system (Blackstone and Cox, 2002) is based on the selective use of capacity and inventory to protect flow in a delivery system and the inventory buffers are then systematically managed to identify and target the sources of disruption. By this means the protective inventory may be systematically reduced as with kaizen but, unlike lean, the system is designed to explicitly utilise protective capacity on most resources. It should be noted, however, that under capacity scheduling is a lean concept also.

With this improved understanding of the role of capacity and inventory together with the existence of bottleneck resources, the batch size conflict (Exhibit 6) does not disappear but operates at a higher level, or as Schmenner might put it, as the operating frontier is closer to the asset frontier. The batch size is no longer fixed but varies depending on the availability of capacity, a common feature of Advanced Planning and Scheduling (APS) systems.

In Exhibit 6, requirement C reflects the drive for reduced inventory, which is achieved through reducing the batch size. Whereas requirement B reflects the primary need to ensure sufficient capacity is available, which drives the need to enlarging the batch size and thereby reduce the capacity committed to set-ups and the associated losses.

The agile-lean supply debate has helped to highlight the growing importance of managing capacity to enable flow in a volatile market. Exhibit 7 serves to illustrate the fact that variation and uncertainty associated with the product and particularly demand, distinguishes lean from agile supply. Lean supply is associated with level production scheduling and the use of finished inventory to decouple fluctuations in demand. However, the uncertain demand and short life cycles of many innovative products cannot be effectively decoupled by inventory and, therefore, capacity is more actively utilised to protect delivery. Fisher (1997) has combined these two aspects of variation in what he refers to as functional and innovative products and the associated choice between designing an efficient or responsive supply chain. The efficient supply chain with minimal variation is akin to lean, whereas the responsive supply chain is dependent on strategically located inventory and capacity to enable flow and may be classified as agile (Stratton and Warburton, 2003). Fisher provides practical guidelines on the need to avoid or reduce sources of variation and uncertainty in the first place, but stresses the need to acknowledge the uncertain nature of some product-market combinations and the corresponding need for responsive supply chains. This is achieved through the strategic location of responsive capacity and decoupling inventory to act as a hedge against variation and uncertainty.