read the case below and write a 1000 words essay on an example of a successful implementing of high involvement innovation at an organization of your choice. Focus on the ( Advice for future manager P

High involvement innovation (For more on this theme see John Bessant, (2003) ‘H igh involvement innovation’, John Wiley and Sons, Chichester) From hands to high involvement The word manufacture comes from the Latin – meaning to make by hand. And that’s pretty much how the game started, with c raftsmen producing the things people wanted – shoes, knives, crockery. Bu t as the population grew and demand increased, so too did the opportunities to innovate in production methods. Sometimes these were changes in the tools used, sometimes in the methods. And sometimes the power source was a targ et, moving through clever gears and pulleys to amplify manpower and th en go to horses or water. By the time of the Industrial Revolution there was a massive acceleration, fuelled by steam power and by increasingly smart us es of materials like cast iron. It wasn’t just changes in the physical production – there were also changes in the way we thought about organizing and managing th e process. The gradual drift towards the cities and the increasing use of machinery led to a rethink of how operations were managed. Its origins can be tra ced back to Adam Smith and his famous observations of the pin-making proce ss which marked the emergence of the concept of the division of labour. By breaking up the task into smaller, specialised tasks performed by a skil led worker or special machine, productivity could be maximised. During t he next hundred years or so considerable emphasis was placed on trying to ex tend this further, by splitting tasks up and then mechanising the resulti ng smaller tasks wherever possible to eliminate variation and enhance overall managerial control The resulting model saw people increasingly involve d as only one of several ‘factors of production’ – and in a rapidly mechanis ing world, often in a marginal ‘machine minding’ role. At the same time the need to co-ordinate different operations in the emerging factories led to a rise in indirect activity and a separation between doing and thinking/decidin g. This process accelerated with the increasing demand for manufact ured goods throughout the 19 th century, and much work was done to devise ways of producing high volumes in reproducible quality and at low prices. A consequence of this was that by the turn of the twentieth century it was possible for people to speak of ‘thinkers’ and ‘doe rs’. Developments in manufacturing organisation and technology moved rap idly and the emergence of a ‘scientific management’ approach meant that sk illed specialists were able to analyze and devise ‘the one best way’ to accompl ish a wide range of tasks. It is hard to argue with the results they were able to achieve – for example, in a series of famous experiments Frederick Taylor was able to increase dramatically the productivity of businesses as dive rse as steelmaking, dock handling and engineering. Faced with the challenge of a widely differing work force, many of whom lacked manufacturing skills and in a lot of cases s poke poor English as a second language, Ford and his engineers used scient ific management principles to develop an alternative approach to ma king cars. From a highly variable activity with low productivity and variabl e quality the ‘mass production’ system changed car manufacturing dramat ically. There is little doubt that this was a ‘better’ way of making cars – at least in terms of the overall production figures (although t he question of whether the conditions under which manufacturing took place is perhaps more open to question), But the trap it set was to help embed th e powerful beliefs that this was something which only specialists could be invol ved in designing and refining. Henry Ford is reputed to have once compl ained ‘how come when I want a pair of hands I get a human being as well?’ The justification for this separation of hand and brain was that a well-design ed system should not be interfered with through the introduction of unneces sary variation. A consequence – easy to see with hindsight but less s o in the context of what were significant improvements in productivity and q uality - was that many early mass production factories came to resemble gi ant machines staffed by an army of human robots. The images in Charlie Cha plin’s famous film ‘Modern Times’ provide a picture of this kind of wo rk which is not heavily exaggerated!

‘With every pair of hands I get a free brain!’ The paradox which this raises is simple to express but hard to understand. Organisations need creativity and active learning i n order to survive in a hostile environment. In today’s turbulent times wi th challenges coming from all directions – uncertainty in competing in a glob al market, uncertainty in political and social stability, technological front iers being pushed back at a dizzying pace – the one certainty is that we need a ll the creativity and learning capacity that we can get. This seems an obvious point – but one which manufac turers continued to miss. For example, research on the global automobil e industry in the 1980s showed that there were very significant performance differences between the best plants in the world (almost entirely Japanese operated at that time) and the rest. The gaps were not trivial; on average th e best plants were twice as productive (based on labour hours/car), used half t he materials and space and the cars produced contained half the number of defects. Not surprisingly this triggered a search for explanations of this hu ge difference, and people began looking to see if scale of operations, or spe cialised automation equipment or government subsidy might be behind it. What they found was that there were few differences in areas like autom ation – indeed; in many cases non-Japanese plants had higher levels of auto mation and use of robots. But there were major differences in three areas – design of the product for manufacturability, the way work was org anised and in the approach taken to human resources. The idea that people can contribute to innovation t hrough suggesting and implementing their ideas isn’t new. Attempts to uti lise this approach in a formal way can be traced back to the 18th century, when the 8 th shogun Yoshimune Tokugawa introduced the suggestion box in Japan. In 1871 Denny’s shipyard in Dumbarton, Scotland employed a programme of incentives to encourage suggestions about productiv ity-improving techniques; they sought to draw out ‘ any change by which work is rendered either superio r in quality or more economical in cost’. In 1894 the National Cash Register company made considerable efforts to mobilise the ‘ hundred –headed brain’ which their staff represented, whilst the Lincoln E lectric Company started implementing an ‘incentive management system’ in 19 15. NCR’s ideas, especially around suggestion schemes, found their w ay back to Japan where the textile firm of Kanebuchi Boseki introduced the m in 1905. But although a simple principle it was neglected in much Western manufacturing until the last part of the 20 th century. In Japan, on the other hand, it thrived and became a powerful engine for i nnovation. Firms like Kawasaki Heavy Engineering (reporting an average of nearly 7 million suggestions per year, equivalent to nearly 10 per w orker per week), Nissan (6 million/ 3 per worker per week), Toshiba (4 million ) and Matsushita, also with 4 million). Joseph Juran, one of the pioneers of t he quality movement in the USA and Japan pointed out the significance of ‘the gold in the mine’ suggesting that each worker in a factory could pote ntially contribute a valuable and continuing stream of improvements – pr ovided they were enabled to do so . But it took a long time before the lessons which the Japanese had worked so hard at learning migrated to the rest of the world.

Making high involvement happen These days, of course, most organizations have atte mpted to implement some form of employee involvement and the gains for m doing so are becoming increasingly apparent. For example, the n ational UK Workplace Employee Relations Survey found a link between the use of more human resource management (HR) practices and a range of p ositive outcomes, including greater employee involvement, satisfactio n and commitment, productivity and better financial performance. Ano ther UK study concludes that ‘Practices that encourage workers to think and interact to im prove the production process are strongly linked to increased productivity’ .

So how can organizations develop and sustain a higher level of involvement of their workforce in innovation? Research suggest s that there are a number of stages in this journey, progressing in terms of the development of systems and capability to involve people but also progressi ng in terms of the bottom line benefits which can be expected. 1 Each of these takes time to move through, and there is no guarantee that organisatio ns will progress to the next level. Moving on means having to find ways of over coming the particular obstacles associated with different stages. The figure below shows the model in outline. The fi rst stage - level 1 - is characterised by little, if any, innovative involve ment going on, and when it does happen it is essentially random in nature and occasional in frequency. People do help to solve problems from time to time - for example, they will pull together to iron out problems with a new system or working procedure, or getting the bugs out of a new product. But there i s no formal attempt to mobilise or build on this activity, and many 1 Bessant, J. (2003). High involvement innovation . Chichester, John Wiley and Sons.

Figure 4.2: The five stage model (this is figure 4.3 from High involvement innovation book) Practice of high involvement innovation Performance of high involvement innovation 1 2 3 4 5 organisations may actively restrict the opportunities for it to take place. The normal state is one in which innovation is not look ed for, not recognised, not supported - and often, not even noticed. Not surpr isingly, there is little impact associated with this kind of change. Level 2, on the other hand, represents an organisat ion’s first serious attempts to mobilise high involvement innovation. It involv es setting up a formal process for finding and solving problems in a struc tured and systematic way - and training and encouraging people to use it. Sup porting this will be some form of reward/ recognition arrangement to motivate and encourage continued participation. Ideas will be managed through some form of system for processing and progressing as many as possible and handling those which cannot be implemented. Underpinning the whole set- up will be an infrastructure of appropriate mechanisms (teams, ta sk forces or whatever) facilitators and some form of steering group to ena ble it to take place and to monitor and adjust its operation over time. None of this can happen without top management support and commitment of resources to back that up.

Level 2 is all about establishing the habit of inno vation within at least part of the organisation. It certainly contributes improve ments but these may lack focus and are often concentrated at a local level, having minimal impact on more strategic concerns of the organisation. The d anger is that, once having established the habit, the high involvement innovat ion process may lack any clear target and begin to fall away. Level 3 involves coupling high involvement innovati on to the strategic goals of the organisation such that all the various local le vel improvement activities of teams and individuals can be aligned. In order to do this two key behaviours need to be added to the basic suite - those of stra tegy deployment and of monitoring and measuring. Strategy (or policy) dep loyment involves communicating the overall strategy of the organisat ion and breaking it down into manageable objectives towards which activities in different areas can be targeted. Linked to this is the need to learn to m onitor and measure the performance of a process and use this to drive the continuous improvement cycle. Level 3 activity represents the point at which high involvement innovation makes a significant impact on the bottom line - for example, in reducing throughput times, scrap rates, excess inventory, et c. It is particularly effective in conjunction with efforts to achieve external mea surable standards (such as ISO 9000) where the disciplines of monitoring and m easurement provide drivers for eliminating variation and tracking down root cause problems. The majority of ‘success stories’ (such as those of Jap anese firms) can be found at this level - but it is not necessarily the end o f the journey. One of the limits of level 3 is that the direction of activity is still largely set by management and within prescribed limits. Activitie s may take place at different levels, from individuals through small gr oups to cross-functional teams, but they are still largely responsive and st eered externally. The move to level 4 introduces a new element - that of ‘empowerment’ of individuals and groups to experiment and innovate on their own init iative. Clearly this is not a step to be taken lightly, and there are many situations where it would be inappropriate - for example, wher e established procedures are safety critical. But the principle of ‘interna lly directed’ innovation as opposed to externally steered activity is important , since it allows for the open- ended learning behaviour which we normally associat e with professional research scientists and engineers. It requires a h igh degree of understanding of, and commitment to, the overall strategic object ives, together with training to a high level to enable effective experimentation . It is at this point that the kinds of ‘fast learning’ organisations described in some ‘state-of-the-art’ innovative company case studies can be found - plac es where everyone is a researcher and where knowledge is widely shared and used.

Table 1 illustrates the key elements in each stage: Table 1: Stages in the evolution of high involvemen t innovation (HII) capability Stage of development Typical characteristics (1) ‘Natural’/background HII Problem-solving random No formal efforts or structure Occasional bursts punctuated by inactivity and non-participation Dominant mode of problem-solving is by specialists Short-term benefits No strategic impact (2) Structured HII Formal attempts to create and sustain HII Use of a formal problem-solving process Use of participation Training in basic HII tools Structured idea management system Recognition system Often parallel system to operations (3) Goal oriented HII All of the above, plus formal deployment of strategic goals Monitoring and measurement of HII against these goals In -line system (4) Proactive/empowered HII All of the above, plus responsibility for mechanisms, timing, etc., devolved to problem-solving unit Internally-directed rather than externally- directed HII High levels of experimentation Advice for future managers Implementing high involvement innovation will need skills in dealing with questions like these:

Question Response required What’s in it for people? Putting in place some form of recognition/ reward system which acknowledges their contribution How to do it? Training and skills development around problem finding and solving and related innovation capabilities Setting up suitable vehicles – problem-solving teams, quality circles or whatever – to carry through CI activities Who is going to help support them? Identification and training of suitable facilitator s Commitment of senior management to support and champion the cause How will this fit in? Ensuring that organisational structures and systems support rather than block CI behaviour Making space and time available to carry out CI activities How will the flow of ideas be managed? Putting in place some form of idea management system How to maintain momentum? Ensuring this is more than another ‘fashion statement’ by the organisation Planning for long-term strategic development of CI capability Linking CI t the organisational development strategy Where and how to get started? Identifying suitable pilot areas/ teams/ projects