posted 1 Apr 1999 in Volume 2 Issue 7
Innovating: The Core Knowledge Competence
Knowledge management in stasis is a complete paradox. In order to keep the influence of successful KM moving, according to Victor Newman , a balance between knowledge management and knowledge development is required . There is no perfect formula for dynamic and creative communication which leads to powerful innovation; the only solution can be constant flux where formulae for success are re-invented in accordance with the passage of time.
BMW's recent attempt to leverage a UK government subsidy for the Rover Longbridge Auto Assembly plant was based on the argument that its survival required significant plant productivity gains, whilst at the same time Peugeot was recruiting a new workforce to build an attractive new car, the Peugeot 206. The futility of the 'optimisation mindset' within the context of a global knowledge economy is clearly not understood by either government or some major organisations. It was only in 1996 that Steven Roach, the high-priest of downsizing and hollowing-out corporations chose to recant his highly profitable philosophy by saying that such lean strategies were ultimately recipes for industrial extinction1 . Simultaneously, research at Cranfield directly connected the adoption of a primary strategy of optimising existing processes or products with an increasing degradation of an organisation's ability to innovate2
Roach's recantation explicitly suggested that downsizing and efficiency was a betrayal of workforces by management, a management that was unable to innovate and so chose to optimise instead. The long-term danger of focusing on optimising products and processes is one of choosing to shift one's basis of competition from differentiated value to price, to becoming the seller of capacity having lost the ability to create new forms of knowledge and deliver them to a global economy in the form of New Market Values, and ultimately determine prices in the world market. The Japanese lean approach of optimisation and their approach to R&D is largely unable to deliver genuinely new products. The extension of lean production into the supply chain to enforce process control and reduced variation means that lean production acts as a brake on the potential rate of innovation through forcing its prisoners to compete on price and not on value.3 4
It is only when CEOs and MDs within the supply-chain structure plot the cost-reduction curve over time that they realise the nature of their dilemma. They begin to understand the need to move from continuous improvement to a higher rate of discontinuous improvement in order to outpace the cost-reduction curve. This creates a new unanticipated margin to invest in developing new customers in a more balanced risk-portfolio. In other words, lean production is just a strategy, and once it became public-domain it was no longer a competitive form of knowledge. This doesn't mean it can be ignored. It becomes part of the baseline but no longer a differentiator.
Returning to the Automotive arena, in my opinion the ultimate configuration of world car manufacture is probably going to lead to a single, truly agile European Automotive plant jointly owned in a Keiretsu/Kaibatsu-type arrangement where different cars are made according to demand. The factory itself will no longer be seen as an asset; the ability to design new configurations of product will become the core competence. In other words, the Nike approach of focusing on developing the ability to create and sell new products, concentrating on differentiating on product and brand associations and realising that manufacture and procurement is a commodity, is gradually migrating from street-fashion to the still-monolithic automotive sector.
A similar pattern of thought is emerging out of pharmaceutical/ life science organisations. Global pharmaceuticals are probably closest to practically understanding the implications of Drucker's Global Knowledge Economy in driving them to reconfigure their business models to align around an Internal Knowledge Economy model. In other words, in order to compete within a Global Knowledge Economy whose real currency is ideas and the timing of their exploitation, it is necessary to focus on accelerating time to market processes in order to reduce investment over time and introduce the product at an acceptable price. The new thinking suggests that anything outside the creation and delivery of New Market Values is non-core and should be outsourced. This includes factories and project management, often mistaken as the heart of the business.
It seems as though the purpose of thinking is to create formulae that remove the need to think at all. Academics and organisations are always searching for formulae and tend to be surprised at the time-based nature of the models they create. This is the problem at the heart of knowledge management. In other words, whatever new forms of competitive knowledge are created, they degrade over time into becoming mere information, appearing in specialist journals, then mere data, published and taught by academics.
The knowledge opportunity: creating and delivering new forms of knowledge
The issue for organisations is how to balance their emphasis between knowledge management and knowledge development. Organisations need to understand the continuum between these two extremes and take care with their location along it to invest in both. Shell and BP led the world in their application of what we used to call IT to develop knowledge management. They became very adept at the capture and re-use of expertise in structural/ process capital involved in the delivery of what was rapidly becoming a commodity.
What was missing was the wake-up call from relevant scenario planning or learning exercises. In both organisations, scenario planning had become sidelined from the decision-makers and misunderstood. The cue for shifting from knowledge management to developing new forms of knowledge is often based on the realisation that the existing assets are becoming seen as commodities. In this situation, you either create a knowledge-wrap in the form of new, or tacit knowledge around the utilisation of the commodity that becomes more valuable than the original product or service, or you create a genuinely new form of knowledge. Shell and BP failed to develop new market values and ended up selling a commodity. They even failed to utilise the data from their customer loyalty cards to develop customer information patterns like Tesco and Merck, and exploit new positions either up or down the value-chain.
The next time you get into a black taxi-cab in London, ask the driver about 'The Knowledge'. What you will learn is fascinating. 'The Knowledge' is the ability to recall 400 routes across London; it means that you can get into a black cab and not have to carry your own London A-Z to direct the driver. Does 'The Knowledge' represent the kind of knowledge we are interested in? Can we learn something about the kind of knowledge necessary to deliver knowledge leadership with the potential to make our business profitable? 'The Knowledge' is a useful differentiator, but once it becomes a standard it does not guarantee that the driver will make a future profit.
In 1997 the North West Ambulance Trust featured on a Radio 4 Business programme as being unusual in the way it managed itself. You might think that the Trust had applied knowledge of its route-structures within the North West of England to optimise its response-timings. This would only be a partial answer and would not really differentiate this service.
If we return to the black cab, the key to the driver's profitability lies not in 'The Knowledge' of the 400 routes, but in the knowledge of where to be and at what time, in order to harvest the most profitable journeys. This knowledge or information remains fairly tacit. What the North West Ambulance Trust did was to create a new form of knowledge that was pattern-based by analysing their data of call-outs over previous years to look for patterns in timings, locations, and types of injuries. They created a predictive schedule for pre-locating ambulances and Paramedics before incidents occurred and in so doing, delivered a service with new value.
What is the knowledge opportunity?
The knowledge opportunity lies in deliberately creating new forms of knowledge out of understanding the patterns within our own data; in other words recognising the patterns over a period of time to create information. The most fundamental pattern to the Global Knowledge Economy lies in understanding the commoditisation process that takes niche products, and rapidly turns them into commodities.
Clearly, the competitive nature of knowledge in terms of value and time shows us that knowledge is not a static commodity. Its value lies in its exploitation to deliver New Market Values or expectations by destabilising existing positions of competitive products in terms of entry to market and relative value. Similarly, as Peter Drucker observed, it is too easy to confuse data with knowledge and information technology with information. If de Geus was right, and the only true competitive advantage lies in ability to learn faster than the competition, then the nature and relationship of certain key words including knowledge, technology, data and information needs to be understood.
The figure below connects these words within a transitional process. Let's begin by looking at the first transition between data and information. This is perhaps the most fundamental transition and certainly the most difficult to manage within the DIKT learning process above. Basically, data exists in infinite volume and variety, but its transition into information remains problematical, as anyone knows who has attempted to teach Statistical Process Control to either senior executives or shopfloor operatives. This transition is difficult because we confuse data and information. Within the media and everyday business, they tend to be treated as the same thing. This means that we have professors of information technology who are really professors of data technology.
We confuse the meaning of the word 'information' with being informed. Similar confusion exists in articles about 'information overload' stresses being caused through the Internet. The overload stress that is being discussed is due to the difficulty individuals have in processing the variable-quality data available on the Internet and turning it into usable information. In other words, we don't have time to make sense of it all and therein lies the clue as to the meaning of information. Information only exists when we can either see or create patterns or structures within the field of data. This information is highly contextual and is defined by the means of collection, the media of presentation and the purpose involved.
The next transition from information to knowledge is defined by an approach that begins with the context of what is known about the past and with a style of thinking about the future as a process that identifies opportunities for delivering New Market Values. This transition involves a creative technique that takes an existing pattern or structure in an existing form of thinking and locates that pattern within a new, contrasting context or deliberately reverses its flow or direction. This essential patterning or P7 technique involves pattern recognition, making, breaking, playing, reversing, shifting and antithesis.
Useful examples include the development of the Stealth fighter technology from a dense Russian technical paper that predicted how to calculate geometric configurations to control electromagnetic reflections. A Lockheed mathematician read the paper to its end and realised that translating this thinking to the defensive radar-systems context meant that the apparent size of an object could be reduced by manipulating the shape of the attacking aircraft.5 . Another example is Richard Branson's approach to attacking markets. He reversed the conventional logic that says avoid highly-developed markets with virtual cartel management where the costs of entry are high. Branson realised that over time, new niche customers always emerge within such a stable market and if this group is targeted through New Market Values, the existing stable cartels can be destabilised and profitable fragments can be picked off.
Two interesting examples of future knowledge as opportunities that are currently under development include:
|The use of Product Data Management systems out of their original engineering context|
|The application of Supply-Chain methodologies out of their original automotive context and with a reversal of original direction away from supplier to customer.|
Financial services organisations are working on developing Product Data Management systems to allow the decomposition of product features across a range of existing offerings. This will create new product offerings specifically customised to offer novel combinations that meet evolving customer expectations. Similarly, the reversal of Supply-Chain Management Technology through 180 degrees creates a new approach which can tentatively be described as Customer Portfolio Management. Customer Portfolio Management is the CEO strategy described earlier for reversing the tendency of Supply-Chain Management strategies to commoditise supplier products, sub-assemblies or processes by adopting the perspective of the supplier to quantify the risk, devaluation of value, the farming of profit, and the requirement to develop risk-reduction strategies that lead to a more balanced portfolio of customers.
The final difficult stage of the process is the exploitation of knowledge as an opportunity within the form of an application or a technology. This phase involves the organisation in developing stable processes and a culture that is the product of learning to overcome a series of crises to stabilise the technology that delivers the products, that create new expectations in the market. The DIKT learning process is time and value-based. Over a period of time, the leading technology introduces the new standard. This becomes an opportunity or form of knowledge for emulators, which over time becomes information as the patterns become obvious until eventually it becomes public domain.
Creativity is essential to this process:
|Creativity to adopt new perspectives in order to recognise or create new patterns|
|Creativity to play and reverse these patterns within contrasting contexts|
|Creativity to manage the process of learning through anticipating and solving the problems of implementing the technology in a stable form.|
This creativity requires innovative people with different approaches to their creativity. Unfortunately Knowledge Management is currently largely developed by people who prefer to ignore the need to understand creativity or creative environments.
Towards an ecology of innovating: Understanding innovating stereotypes & their interactions
Unfortunately, creativity is very largely intrinsically motivated, whether it involves optimising to improve performance or innovating to create new expectations. If we understand the largely intrinsic nature of motivation behind creative behaviour and if we connect this understanding or information with the DIKT learning process, then it becomes essential to understand the nature of these 'Innovating Stereotypes' which combine to deliver new technologies.
Over a period of years, an intriguing and misleading statistic of 80% has been ascribed to the failure-rate of systematic change programmes. It is noticeable that the content of serious books about implementing change in organisations is largely taken up with how to manage project programmes or concurrent projects. Why is this? Innovating Stereotypes have been developed to explain this problem of failure and repetitive presentation of information on how to implement it.
The Innovating Stereotypes consist of three essential stereotypical behaviours that are essential for organisations to continue to innovate. The model does not suggest that there are three discreet populations, but that individuals have different predisposition's toward all three crude behaviours. The Innovating Stereotypes can loosely be described as populations who must interact to deliver successful innovating performance. These populations are described as Creators, Implementors and Stabilisors.
A useful illustration of the model and the interactions of the stereotypes lies behind the story of the arrival of Graphical User Interface technology pioneered by Xerox's Palo Alto Research Centre and delivered by Steve Jobs of Apple. Xerox set up its Computer Systems Laboratory as insurance against the paperless office under Bob Taylor, who filled his flat organisation with Creators whose only task was to come up with new ideas and turn them into stable prototypes. Unfortunately, Taylor's introverted Creators found it impossible to translate their technologies into the world of the Xerox Stabililisor executives.
In December 1979, Steve Jobs attended a demonstration and recognised the opportunity that the prototypical Graphical User Interface technology offered. He had a context for application and a hunger to deliver a stable, customer-friendly technology. Jobs demanded another demonstration and returned with the Apple programming team. Apparently within one hour, Jobs' team understood the implications of the technology and within another hour had spotted the mistakes and suggested improvement. He was lucky to see the CSL PARC demonstration developed by the Xerox Creators, whose technology was a stable prototype. Jobs came along and acted as Implementor, developing GUI as an Implementor Technology via LISA (the 16-bit microprocessor, bit-mapped display, a mouse for controlling the on-screen cursor and a keyboard that was separate from the main computer-box). Although LISA failed, this Implementor prototype led to a stabilised technology which enabled the Apple Macintosh to introduce a new standard in computing by delivering New Market Values.
Jobs' success lay in his ability to bridge the gap between Creators and Stabilisors. All three stereotypes are interdependent. Between the future thinking of the Creator (what could be) sits the now-thinking of the Implementor (how to make it happen now) and the Stabilisor' s measurement of today's performance in terms of the past. The explanation for the high failure-rate of systemic change programmes lies in the Stabilisor's role in commissioning the change programme. Being a Stabilisor, the future can only be imagined in terms of the past. Stabilisors will always be disappointed with their purchase of change because they want something they cannot have (i.e. change without change). Having driven their own source of change out of their business in order to optimise it, they attempt to purchase a step-change technology that contradicts their existing culture. The pain of attempting and failing to change is traumatic. The Innovating Stereotypes model can also be retrospectively applied to the famous 3M Post-It story6 . Spencer Silver and Robert Oliveira, company chemists within 3M were the Creators who decided to play with an adhesive formula to see what might happen if the variables were shifted. They created an adhesive which didn't adhere very well, and spent 5 years trying to sell it internally within 3M. Arthur Fry, a part-time choir-director possessed a context for an adhesive that had no memory for marking places in scores. He was a classic Implementor, and managed to persuade Geoffrey Nicholson and Joseph Ramsay into fighting a marketing paradigm that only saw opportunities in market gaps. The company did not understand market-making through the introduction of products with New Market Values. The rest of the story is the interaction of Implementors and Stabilisors basically problem-solving the technology.
A review of the content of serious change-management books tends to demonstrate that apart from a differentiating chapter at the beginning of books, the remainder of the useful content is largely concerned with project programme management. In other words: how to run and manage a programme of multiple, interconnected projects without losing control. What is interesting lies in the intriguing possibility that the same book is being published and sold again and again. An explanation of the largely identical content of serious change literature lies in the inability of Stabilisors to absorb the lessons from change programmes since these imply that their personal identification with a particular technology is a mistake, and that the future will involve continual instability. Stabilisors will tend to breath a sigh of relief and rapidly obliterate their experiences with optimisation routines. This unlearning process is abetted by the expulsion of Implementors who burnt their political bridges in fighting to implement the change programme and accordingly have to leave the Stabilisor-dominated organisation, or on discovering their Implementor nature find that they cannot return to their old roles. These change books are popular with Stabilisors because they remain data, and are not translated into information or knowledge in the form of opportunities. In other words, Stabilizors cannot learn how to change. This means that they have to outsource their Implementors through consultancies, and are predisposed to optimisation strategies.
1. Optimising your processes and products can kill your ability to innovate.
2. The longer the period between innovating, the harder it gets.
3. Consider your location within a continuum between Knowledge Management and Knowledge Development.
4. Remember that useful knowledge is pattern and time-based.
5. Because knowledge is time-based, it degrades into becoming someone else's information, and ultimately ends up as market data.
6. Everything becomes commoditised eventually. It is your job to create new forms of knowledge to stay ahead of this process.
7. Understand the Innovating Stereotypes within your innovating ecology, try to balance the stereotypes and support processes that facilitate their interactions.
Victor Newman is Director of the Knowledge Development Centre at Cranfield University. He can be contacted at: