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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|6824||2001||11 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Technovation, Volume 21, Issue 2, February 2001, Pages 67–77
In today's complex and turbulent environments the need for continuous improvements in products and processes is widely recognised. But the mechanisms whereby such a continual stream of innovation can be achieved are often less clearly identified. One option is to mobilise a high proportion of the workforce in a process of sustained incremental problem-solving, but experience with this approach suggests that successfully doing so is far from simple. Although many programmes for ‘kaizen’ or ‘continuous improvement’ based on employee involvement are started, the failure rate is high. This paper reports on extensive case-study based research exploring how high involvement in continuous improvement can be built and sustained as an organisational capability. It argues that this phenomenon needs to be viewed as a cluster of behavioural changes which establish innovation routines in the enterprise, and presents a reference model for assessment of progress in the evolution of such capability.
Much current thinking on strategy concerns what is often termed the ‘resource-based’ model, in which competitive advantage is seen as coming from the particular bundle of tangible and intangible assets to which a firm has access (Kay, 1993 and Teece and Pisano, 1994). Accumulating these assets is seen as a key task in strategic management, and the ‘core competence’ of the enterprise is essentially the outcome of this process (Pavitt, 1990 and Prahalad and Hamel, 1994). The more firm-specific and difficult to copy these resources are, the more likely it is that sustainable competitive advantage can be built and maintained. Resources come in various shapes and sizes but can be grouped into tangible assets — buildings, plant, equipment, etc. — and intangible assets. This latter group is made up of knowledge assets — what an enterprise knows about (its core technologies, its market knowledge, etc.) — and behavioural patterns — how it organises and operates. The important feature here is that, unlike tangible assets, they are difficult to acquire and copy because they are often the product of extended learning processes. This makes them highly firm specific and a much stronger source of potential competitive (Teece, 1998). As a UK manager put it, “…there is no other source of competitive advantage! Others can copy our investment, technology and scale — but NOT the quality of our people…”1 In other words, what makes a firm competitive is not so much the equipment, location, buildings, etc. which it possesses (since anyone with deep enough pockets can duplicate this resource position) but what it knows about and how it behaves. A firm like 3M owes its competitive position to deep knowledge (around the fields of coatings and related technologies) which it has built up over nearly a century and to ways of working which are particular to the organisation (such as the encouragement of ‘bootlegging’) which give it the ability to introduce new products on a sustained basis. Both these sets of attributes — the knowledge base and the behaviour patterns — the ‘culture’ or ‘way we do things around here’ — are specific to the company and cannot easily be duplicated. One of the strongest barriers to imitation is that much of this asset base is a mixture of formal and tacit elements. Although 3M has formal codified knowledge in the form of patents, process designs, etc., much of what it knows is tacit knowledge, held in the experience and ‘fingertips’ of its employees. In similar fashion although some of its behaviour patterns are formalised into structures and procedures, much of ‘the way we do things around here’ is essentially tacit, a shared understanding about norms of behaviour and underlying values which have evolved over time. This paper is concerned with such behaviour patterns and with how particular patterns can confer competitive advantage. They are often described in the literature as ‘routines’ and there is growing interest in this approach as a way of understanding organisational behaviour. Winter, for example, defines routines as “…a relatively complex pattern of behaviour…triggered by a relatively small number of initiating signals or choices and functioning as a recognisable unit in a relatively automatic fashion…” (Winter, 1986). This is not to say that routines are mindless patterns; as Giddens points out “…the routinised character of most social activity is something that has to be ‘worked at’ continually by those who sustain it in their day-to-day conduct…” It is rather the case that they have become internalised to the point of being unconscious or autonomous (Giddens, 1984). Tranfield et al suggest that three sets of routines are important — those concerned with maintaining performance of current processes, those concerned with improving existing processes and those concerned with transforming or changing to new processes. In this article we are concerned with the middle option — routines for incremental innovation, for, ‘doing what we do better’. (As we shall see, there is scope for employing such routines to help with more radical innovation but extended discussion of this lies outside the scope of this paper). Our focus is on the ways in which such behavioural patterns can be built up across organisations to provide operational and eventually strategic advantage through high and regular involvement in the innovation process.
نتیجه گیری انگلیسی
In this paper we have argued that continuous improvement (CI) is of considerable strategic importance, but that its management is often poorly understood. The problem occurs in part because of confusion surrounding the term itself since CI refers not only to the outcomes but also to the process through which these can be achieved. We have argued that managing this process effectively depends upon seeing CI not as a binary state or a short-term activity but as the evolution and aggregation of a set of key behavioural routines within the firm. (Arguably it was simplistic interpretation of the nature of CI that contributed to the experience of disappointment and failure in many CI programmes started during the 1980s as part of the ‘total quality’ movement). Building behavioural capability of this kind constitutes an important contribution to the resource base of the firm and one which it can deploy in pursuit of a variety of strategic goals — lower costs, improved quality, faster response, etc. However the process of accumulating such a resource is a long and difficult one involving articulation and learning of behaviours and practising and reinforcing them until they become routines — ‘the way we do things around here’. Experience in a variety of case examples suggests that the development is essentially an evolutionary process, and that it is possible to identify several discrete stages on the journey towards CI. Learning has to take place both within a particular stage (establishing and embedding routines) and between stages (moving to add new routines and integrate them with earlier ones). This process is analogous to the concept of ‘double loop’ or ‘generative learning’ identified in the literature (Argyris and Schon, 1970 and Senge, 1990). It is also clear that although there is contingent variation amongst firms, there is also commonality in the nature of problems encountered in building CI capability. At the same time there is widespread experimentation with different approaches to dealing with such problems and with finding ways around particular blocks to progress. Finding mechanisms to share experience of this kind and to enable transfer of useful ‘enablers’ is likely to be of considerable benefit and is being used in an increasing number of policy initiatives — for example, the ‘Industry Forum’ programme in UK automotive components. One last point is worth mentioning. In this paper we have addressed the question of CI largely as a set of routines for doing what we already do better. But there is emerging evidence that this capability, once established, can also contribute to doing new things — to ‘innovation’ routines. Many of the characteristic behaviours at the higher levels of our model are essentially similar to those routines identified in work on innovation — for example, experimentation in R&D.