Saturday, 12 July 2008

Don't Share -Build

The earliest stage of Knowledge Management was bedevilled by the curse of the idea that whoever knew the most, and could manage the most "knowledge" would run off with the glittering prize of the Global Knowledge Economy. In time the futility of this exercise was glimpsed but the promise of better search-engines, individual disciplines and meta-data tagging suggested that this was still attractive, and so the knowledge-farmers and their friends the knowledge-miners continued the trend. Did they dare to consider the possibility that the knowledge revolution was not going to be a computerized improvement on stamp-collecting or librarianship? No.

The literature of change and religious cults is littered with the accidental rubbish of ambiguous, key quotes and sayings that were crafted to mean one thing, and ended up being interpreted quite differently. When TQM (Total Quality Management) ruled the world, a key aspirational saying was: “right first-time”: this originally meant if you plan it right, it will work when you want it to. What it ended up meaning was: don’t build and test prototypes. This became a source of much amusement in Japanese companies. 
The injunction of Knowledge Gurus to share knowledge has had similar unintended effects that need to be understood and resolved in order to develop sensible knowledge strategies.

Problem 1: Implicit Economic Paradigm
The economics of supply and demand apply to knowledge. Knowledge in the public domain assumes a low value, and begins to look like a commodity whilst that which is exclusive and personalised gains value. This probably explains the traditional confusion of knowledge with power and why many books about Knowledge Management contain very little actual knowledge.

The currency of the Knowledge Economy is ideas and their exploitation. What is largely missing in the emergent debate on how to configure organisations to compete in the Knowledge Economy, is the application of economics to ideas and knowledge. 

One of the key lessons of the Soviet Experiment in nationalised economics was that in its heyday, 3 percent of privately-farmed land produced 84 percent of the edible food. Those things which were shared were run incompetently and were seen to have low value. The irony is that commentators are unwittingly suggesting the equivalent of state-economics to the exploitation of knowledge. If everything is shared, it will be perceived to have low or insignificant value. This has been obvious to anyone brought up in institutional housing, or who worked within a nationalised industry and watched it die. The economics of supply and demand apply to knowledge. The knowledge which is in the public domain assumes a low value, begins to look like a commodity whereas personal knowledge is exclusive, current and protected has the potential to maintain high value.

Imagine a 2x2 hi-lo knowledge transactions matrix for an organisation where the vertical dimension represents value, and the horizontal dimension represents transaction volumes. There are 3 areas A, B, C represented in this matrix mapping the relative positions of the knowledge within an organisation in terms of the relative value of individual knowledge transactions and their volume. 

Box A represents a healthy collection of high-value but low-volume knowledge transactions. These are delivered by creative individuals and are in transition between idea and prototype model. They are sold at a high daily rate, and have not been packaged. The individuals creating these transactions are at the leading edge of thinking in terms of emergent practice in an evolving context.

Box B is at the hi-lo dimension intersections, representing medium value knowledge transactions at medium volume of delivery, delivered by trained consultants where access to their semi-formalised methodology is controlled by agreement, and used within a relatively predictable environment, to the extent that these transactions have a branded name with relatively predictable and shared expectations in terms of outcomes. Box B is about selling a service.

It is only a matter of time before the knowledge in box B slides into the area of Box C.
Box C contains low-value transactions that have been commoditised and delivered at a high volume, probably via a secure portal with low levels of interaction, or through franchised consulting or third party trainers (like NLP, emotional intelligence, Effective Habits of Leaders, etc.). The contents of Box C are designed for immediate customer use. The 2 x 2 hi-lo matrix is an ideal. Ideally an organisation would be in command of the timing of the declining value of its knowledge. At no point would it deliberately choose to position all its knowledge onto the market (Box C) or continue to supply knowledge transactions where it was no longer economic.

What’s implicit in the model is the reality of personal knowledge power being connected to a small volume of high-value transactions, and at the other extreme: corporate knowledge power tending to be connected to a high-volume of low-value transactions. This contradiction partly explains the difficulty of attempting to translate personal knowledge power into a form of knowledge that is accessible to everyone where corporate knowledge attempts to capture all knowledge without defining the knowledge framework that is usefully shared across the organisation.

Problem 2: Purpose and Context 
So I share this "knowledge" of mine with you. How can you tell whether it's any good? How can you tell whether it is really knowledge, or information or even just structured data? How can you tell it's mine? And how can I share something with you, if I do not know what has value in your eyes and if we do not share the same purpose?

One of the commonplace experiences of Knowledge Work consulting is the request to advise an organisation on how to establish a Knowledge-Sharing Culture. This can go many ways at this point. You can either begin trying to shift the culture by inventing or documenting stories that carry the knowledge-sharing-is-good message. It may be possible to cut to the chase, and point out that until the organisation has a Market Value Strategy that explicitly identifies the kinds of knowledge that need to be created, and plans their market value lifecycles, they will be largely wasting their time.

To put it another way. If you get ever get confused about knowledge. Firmly grasp the arms or underside of your chair. Take a deep breath, close your eyes and repeat the phrase: "Knowledge Leadership for New Market Value " to yourself until you feel better. Unless you can link your business strategy to the maintenance of existing knowledge and development of new knowledge to introduce new value into the current market, you can only waste time sharing things that need to be constantly interpreted and which may have only slight value. Remember some facilitators use the phrase "thank you for sharing that", when what they really want you to do is to shut up.

Problem 3: Understanding The Psychology of Knowledge Transactions 
While the phenomenon of sharing experience has been researched, its psychology has tended to be taken as a given. There is consistent evidence that knowledge is shared among functional specialists in disparate organisations, and that it involves explicit trading in attributable ideas. The ability of individuals in specialist fields to retain complex relationships of knowledge attribution is known, but tends to be ignored. And yet the clues are there in successful communities of practice whose existence is determined by a shared, overarching sense of purpose. People will only share with those whom they respect and from whom they can expect a return or who share the same problem of preserving or reinventing identity. No-one will share knowledge (something that has high potential value) with an idiot or a fool. The sad reality is that these high-value knowledge trades tend to occur across separate organisations and not internally.

The explicit psychology of these transactions involves
  • Recognition (they are asking me this question),
  • Respect ( they think I know something they don't),
  • Attribution (you can use it as long as you say where you got it from),
  • Reciprocal Credit (I will answer on the implicit understanding that you will give me an equivalent transaction in the future) and
  • Shared perception of value (we both know this knowledge has real potential value if exploited).
Problem 4: Knowledge Work, Democracy and 30/70 Technique
Is everyone going to be in a position to share knowledge? It's largely an intellectual and creative activity carried out by the same elite constituting the Human Capital within organisations that Scandia's original Intellectual Capital was designed to measure.

Let's approach the language problem, bit by bit. What is meant by knowledge? The failure to be explicit about terms like knowledge means you're going to get a lot rubbish and expensive rework activity. A key question is: knowledge about what, to do what? After all, one person's knowledge might well be another person's structured data, or information. If we work backwards there may be some clues as to how to progress. If we tried to embed data-sharing into everyday work we would do it by identifying outcomes and success criteria and work back to the necessary processes and activities that need to be managed, then define the performance data necessary to make a decision. If we extend the question to embedding information-sharing, nominated individuals would arrange the data into structures and review it within a time-frame to capture the emergent pattern or information.

Now we can attempt to answer the key questions: are we in control of our process, is it about to do something unusual, do we need to make a decision to either stop, start something new, or continue? If we step up the hierarchy: what would embedding knowledge-sharing into everyday work involve? It would involve bringing a number of information-patterns together to create new cause and effect relationships within existing and new markets that offer the potential to either differentiate existing commodity products by wrapping them in the new knowledge or to offer completely new market values by applying existing information patterns to new contexts. In other words: combining different items of knowledge to change the rules of the game.
The truth is that Knowledge Work is not democratic, we are not all going to be Knowledge Workers. Not everyone is going to be either predisposed or equipped to create, far less share any real knowledge in a world which still confuses data with information. The solution lies in creatively reframing the problem from knowledge-sharing into knowledge-building and engaging what we know about the psychology of engagement.

Case Study

I was brought in to deal with the problem of establishing best practice in a global scientific organisation, and also to help that organisation start to apply new ideas much faster than its competitors. Fortunately or unfortunately, I was working with a lot of global technical experts, and because of the accent upon fast decision-making and action, I would come to meetings with 100% solutions, and one of the things I began to learn quite quickly was that it just wasn’t working.

I assumed that as long as I dotted the i’s, crossed the t’s, fully specced the solution and presented it to them, there would be a minor ripple of applause and then we’d get onto any other business. I was of course being extremely na├»ve.

What I didn’t realise is that these specialists were at war with each other, and that, in effect, presenting them something that didn’t come from them, would lead to massive resistance. So, I had a great mentor and she said to me one day, she said, Victor, you’ve got to stop this 100% stuff, just give them a 30% solution and just specify the shape of that missing 70%, and then invite them to participate and fill that 70% with their own ideas and their own content.

So I began to realise that if I was a bit more intelligent about how I framed the problem, and if I defined the problem for them and then defined the spaces where they could participate, I was much more likely to get a result. And it worked. The trick was to construct a 100% solution in outline, construct a 30% framework that indicated the missing 70% of knowledge in terms of the specialists’ areas of knowledge, and watch them fill the vacuum. The by-product of this kind of approach was that when they filled the solution with their content, they became ambassadors for ensuring that their specialist functions became engaged.

If we ask people to build pyramids out of their own knowledge, this is going to be difficult because we must convince them to construct something that they are unlikely to be able to inhabit themselves. In fact, we all know that it’s only mummies who get to stay inside pyramids. But, if we ask people to construct houses that they can all live in, we are likely to build worthwhile homes. If we work on defining the type of knowledge we want to build, we can then focus attention and resource to make it happen and start working on the problem of how to engage the right constituents in building it and making it happen.

  1. Reduce the number of idiots in the organisation to the bare minimum necessary. No-one will share anything with an idiot.
  2. Employ the tactic of using language with real meaning. Deliberately stop talking about Knowledge-Sharing: it only confuses people with its altruism and its implicit democratic message. Start defining aspirational knowledge frameworks within which new knowledge can be built that meets the need of delivering new market value through knowledge leadership.
  3. Create crises to focus knowledge contribution from those who can, and remove investment from the aimless sharing of everything.
  4. Use 30/70 until they notice, then do something else.
  5. Never, ever set goals for numbers of lessons documented without contextualising the issues involved: people will simply start "gaming the stats".

Friday, 20 June 2008

The Innovator's Got To Do It!

Years ago, in the early 90s, I remember watching a video of a Tom Peters’ sweat and rant guru session, where he wandered about a floor of anxious senior managers clustered around circular tables (anxious because be might ask them a question that might expose their unfitness to manage their organisations, and senior because only a senior manager could justify the cost of the ticket). Tom Peters’ style was to ask rhetorical questions in a quiet voice, answer them himself in a loud, scornful voice, and then cascade his audience with information about successful companies and entrepreneurs scavenged by his army of researchers, who happened to fit his latest theme.

Tom Peters’ guru topic this time was innovation and he said something profound (for a change) and unexpected, to the effect that the real innovators in the business world were not in the room, this day. That the real innovators are out there innovating, because they have to do it. They cannot choose to do it, they have to do it. It’s in their nature.

The connected topics of innovation and leadership, are a bit like pornography in the sense that those who consume it the most, are just not constitutionally equipped to perform the acts described in the literature. But they love reading about the stuff they can’t and won’t do. Which is the point that Peters was making.

Innovators don’t take lessons, they may not even read books, they just do it, and do it again, until the timing of their idea coincides with the timing of the market and their customers, and they make some money, or they fail. And there is a lot of luck involved, but it is a luck that is backed by persistence and perhaps a kind of autism.

It is this kind “autism” that is so valuable. A recent Royal Society of Arts publication suggested that there is a link (if only by analogy) between successful entrepreneurs and ADHD (Attention Deficiency and Hyperactivity Disorder). Governments around the world are attempting to develop entrepreneurs through their education systems, yet so many successful entrepreneurs have underachieved when it comes to education, and maybe that’s the point. At the same time, people with ADHD display many of the behavioural characteristics traditionally associated with the entrepreneur. This is not to say that successful entrepreneurs are autistic, but it is likely that their attention is not drawn to repetitive, traditional thinking that is reinforced within a conventional education that punishes or excludes heresies. So it could be the case that real entrepreneurs will innovate whether you like it, or not. And maybe the best thing to do is to either get out of their way, make it easier for them to get on with their job, or have a different kind of education that fits the psychology of those with the potential to become entrepreneurs as opposed to those who are good at education.

The problem with educating for innovation is that it creates the illusion that anyone can do it, that there is a formula that anyone can consume and succeed. The provision of this innovation education for entrepreneurs creates an illusion of success, a kind of cargo-cult of innovation reinforced by government box-ticking initiatives.

The cargo-cult was a phenomenon that grew out the indigenous people of New Guinea and Micronesia who observed the Allies’ ability to resupply their troops fighting the Japanese by air. They noted the construction of drop-zones and coloured markers and coloured smoke to indicate wind-drift and concluded that the goods (boots, water, ammunition, food and clothing) were triggered by these visual cues, and decided to copy them, and they haven’t stopped since.

What is ironic is this human tendency to construct associations between symbolic behaviour and the provision of goodness in many forms. It’s a bit like thinking that the more the government spends the better life will get. These associations between goodness and symbolic behaviour can be painful but remain hard to challenge without triggering extreme emotions amongst highly-educated people. The cargo-cult of innovation education also reinforces the idea that the highly-educated are innovative, when the reverse is more likely to be true. This explains the war against common-sense, and helps to explain why it is often so difficult to get highly-educated scientists to innovate strategically, because their thinking tends to be trapped within small academic boxes and why those scientists who are able to break out of traditional box-thinking and innovate, tend to be unpopular and driven out of the organisation. The innovation culture that is driven by academic models tends towards incremental innovation, and a fear of risk-taking which dares not challenge the prevailing formula for success that is in decay. That is why the real innovator is likely to have taught themselves in the school of hard knocks and explains why the best thing you can do with an innovator is to help them do what they are going to do anyway but help them to do it better.