Knowing is an act, not a fact. The challenge of knowledge management is to understand how to derive commercial advantage from it collectively. By Leon Gettler and David James
A view from the top
How is it possible to manage knowledge? Is it even desirable to try? Probably. The Austrian-American management thinker Peter Drucker wrote in his book Post-Capitalist Society that the most important issue for modern management is “knowledge about knowledges”. Drucker, one of the first people to high-light the importance of knowledge management (he first flagged it in his work on General Motors in the mid-20th century), identifies what managers should seek. To use knowledge effectively, it is necessary to have an overarching understanding of knowledge itself: how it is created, where it fits and how it can be applied commercially. In other words, managers need to develop “meta-knowledge”.
Knowledge is being created at an accelerating rate, and just “owning” knowledge is unlikely to afford a sustained competitive advantage. Mervyn Jacobsen, executive chairman of the US company Genetic Technologies, says the past 50 years have brought more ingenuity, inventiveness and advancement in science and medicine than in the entire previous history of mankind.
Most businesses, organisations and investors are only just starting out on this journey to acquire meta-knowledge. US analyst Peter Schwartz writes: “In the organisation of today’s new economy, it is knowledge that counts more than anything.
Knowledge has value; but so does knowledge about knowledge. It is a world where the internet spreads knowledge instantaneously around the world, and we get dramatic network effects.”
The challenge in the post-industrial economy is to turn the management of knowledge into something resembling a production line. Some companies are already trying. The Japanese biotechnology company Gene Networks Inc (GNI) is combining knowledge of industrial processes with knowledge in the field of biosciences.
GNI chief executive John Savoie believes that a big problem with most drug development is that it starts out with a single hypothesis, which is usually derived from academic research. He compares this focus on a single hypothesis to building an aeroplane the same way as the Wright brothers built theirs, then building a million wind tunnels to test whether the design works.
At GNI, the approach is to take the data, then apply multiple models to see which might work best. It is iterative: each theory is considered a prelude to the next, better, theory. The scientists are then asked to assess the models.
Savoie says: “Through iteration and iterative design processes we are able to find better targets. And our models get tighter and tighter. We are creating an industrial paradigm.”
The chief executive of Proteome Systems, Keith Williams, is a leader in his field. But as he moved into his senior management role he had to combine his scientific knowledge with his developing commercial knowledge. “What I do now is 30,000 feet stuff,” he says. “Although I still get involved. But I don’t do it with my own hands, although I am not disconnected.” What types of meta-knowledge are required? There are many, and the following provides sketches of some of the more important types.
Knowledge of risk/reward
Vladimir Antikarov, specialist in real options for the Monitor Group consultancy, says net present value analysis, the established method for pricing investments, is an “average scenario world” – a fiction unrelated to what really happens. His real options approach takes the frameworks from option pricing and applies them to corporate governance. This makes it possible to price different types of risk. Financial securities often develop in small steps; other processes, such as research and development, develop in “lumps”.
Antikarov says: “The idea of real options is to take a project, understand all the pathways that the project can go through, then go away and define the optimal action. That gives you the value of the project. You continuously update models along the tree of scenarios, which allows you to have a new contingency plan. You don’t turn on the lights of a car to see 100 metres and then turn off the lights.”
This more flexible analysis is better suited to managing the knowledge “production line” (research and development is already analysed by large corporations with the use of option pricing). Knowledge management is often not a linear procedure from idea through to final product but a process that occurs in cycles, the management challenge being to “sell” at the top of the cycle.
Mark Matthews, director of the Canberra consultancy Policy Intelligence, says: “From a business perspective, research – the ‘R’ part of the R&D equation – is something that generates options, technology options that you might or might not want to exploit. ‘D’, experimental development, is very expensive and is really something that you want to get rid of.
“Once you have decided which option you want to start to look into, basically you want to move through that process as quickly as possible and you want to spend as little as possible doing it.”
Knowledge of global industry
Another important knowledge field will be to develop an understanding of what is important in advancing a country’s “knowledge economy”. Many governments throughout Asia and the Western developed economies are looking to position themselves, mainly through the use of industry clusters.
An authority on clusters, Michael Enright, Sun Hung Kai professor of business administration at Hong Kong University, says the challenge for business and governments is to understand “clustering”, not clusters: “What businesses and governments both need to understand is that they cannot all compete in the same race. The issue is: how do you fit into the value chains of global companies?”
Enright says the knowledge economy should not be linked to particular industries, but to the company’s or country’s core advantages. Trying to emulate what is already being done means being condemned always to be behind.
Juan Enriquez, head of the Harvard Business School’s Life Sciences Project, says the creation and use of knowledge will determine the fate of nations: “If I’ve got the knowledge and you haven’t, then it really doesn’t matter how large you are. I don’t need a factory, I don’t need thousands of people.”
Enriquez says that part of managing knowledge effectively is knowing how to attract people from all parts of the world: “The guy running a knowledge business doesn’t have to move a mine or a factory.”
Knowledge of systems
Historically, management has been concerned with working within industrial systems, usually a version of the production line. So great will be the changes wrought by the knowledge revolution, however, that leaders in the knowledge field will be required to work on systems as well.
The main reason is the greater connectivity of the global economy. This is creating a need to understand the implications for whole systems, whether it be the ecological effects of new products, the amplification of crises in globally integrated financial markets, or the natural effects of changes to the natural order.
Geoff Mulgan, founder of the British think-tank Demos, describes it as the “infosphere” – a single integrated system that must be grasped in its entirety, as though it were one organism. “For the vast majority of people, the basic fact of the modern world is that it is connected. Nowhere is remote in the way that so many places were remote a century, or even a generation, ago.”
Technological networks will play a big role in knowledge management, because they make it possible to create models in a way not before possible. Steven Johnson writes in his book Emergence that computer programs will produce complex, often unpredictable behavior with established algorithmic programming. The intention is to “grow” software, rather than engineer it; that is, to mimic the processes that promote emergence in nature.
Analyst Adrian Woolfson describes the intended meta-knowledge: “These programs are programs for generating further, higher-order programs, which can then be mutated randomly to produce a new set of related variants. By repeating this process for generation after generation, the program eventually evolves higher-order programs capable of solving the problem. Interestingly, the way in which they achieve a solution is often unintelligible to the programmer.”
High tech v. low tech
Not all the best knowledge about knowledges will be in the high-tech field. Often, applying low-tech knowledge can be more efficient. An example is the Kuwaiti oil fires after the Gulf War. A high-tech knowledge worker, oil-fire specialist Red Adair, was brought in from Texas to put the fires out. He proposed setting off explosives that starved the fires of oxygen; a dangerous process that would have taken many years. Then the Kuwaitis were contacted by Bulgarians, who simply drove bulldozers over the fires (the drivers were protected by asbestos suits). Dozens of fires were out within a week. Not all knowledge management is high tech.
What is already known?
Developing leading-edge knowledge is a costly, arduous and expensive process. Far better to use what is known and tested. Gavin Rezos, chief executive of the biosilicon company pSivida, is trying to use accumulated knowledge of the use and production of silicon to gain a lead in creating viable products. “That is why silicon is so compelling; it is already being produced. It is used as a catalyst and discarded.”
Market demand and new discoveries Finding a bridge between new scientific knowledge and knowledge about the potential demand in the market is a bit like handling two onions. Scientific knowledge is like peeling away an onion’s layers. As each puzzle is solved, it reveals another level of problems previously unimagined.
Knowledge about the effect of new products in the market is like adding layers to an onion. As new product possibilities become available they will add to existing demand.
It is a truism that to have a successful strategy it is necessary to “know what you do not know”. Knowledge will eventually transform industry structures, create wealth and probably lead to great dangers. But the specifics are hard to determine, suggesting the need for the intellectual skill of parsimony (simplicity, or Ockham’s Razor). When dealing with the proliferation of new know-ledge, humility will be a big personal asset.
The enormous challenge for managers is understanding how to make something unique, turn new knowledge into something repetitive – industrial processes and customer transactions. Deriving commercial advantage from knowledge is a much subtler problem than just trying to “own” it, or developing ways of encouraging workers to think more. The act of knowing is something that cannot be owned by a company; the statement is meaningless. It is only what comes from knowledge and the systematisation of knowledge, including specific achievements of individual staff members, that can be owned. The managerial challenge is to understand how an enterprise can create and use knowledge collectively, not to focus on the advances in knowledge in isolation.
A history of uncertainty
Creativity can be slippery to manage. Innovation gives companies an edge over their competitors, but it is this very quality that can stop companies anticipating future applications. The actress Lana Turner’s grandfather, the story goes, was said to own stock in a small company that made a softdrink called Coca-Cola. He sold out because he did not think the name would catch on and invested the proceeds in a company he thought more likely to succeed: the Raspberry Cola Company.
At the other end of the scale, effects can be overestimated. The New York Times in 1938 predicted the end of the pencil because of the development of more sophisticated typewriters, and Business Week in 1975 predicted that the “paperless office” was just around the corner.
In 1919, a society of engineers in the US dismissed the refrigerating machine, declaring that the household unit would never find wide use.
There have been many inventions that took off only when the cost of other factors came down. The typical family car now has more computer power than the moon-landers of the Apollo mission, and the internet started in the 1960s as a communications system between military bases using giant IBM mainframe computers.
Other inventions assumed more importance with parallel developments in other areas. The first X-rays were used only in the diagnosis of fractures and the detection of foreign bodies such as swallowed coins.
The first false teeth used during the 16th and 17th centuries were mainly for reasons of vanity and were so badly made that they had to be removed before eating.
Many seemingly brilliant inventions actually came about by accident, not genius. The Chinese developed gunpowder as part of a Taoist plan to find the secret to immortality. Initially, the mixture of potassium nitrate, sulphur, charcoal and occasionally honey was used to treat skin diseases and as a fumigant for insects.
The first matches were made in the hope of fulfilling the medieval dream of creating gold from chemicals. In 1669, German alchemist Hennig Brand developed an experimental brew and became very excited when it gave off a glow that he hoped would transmute into gold. Unfortunately for him, it turned out to be phosphorus.
The Kellogg brothers developed cornflakes by accident in 1894. The two Seventh Day Adventists from Battle Creek, Michigan, were running the then popular Battle Creek Sanatorium and trying to produce an alternative and healthier form of bread by boiling wheat for varying periods. They put the wheat through rollers, which produced a sticky doughy mess. Deemed to be useless, the stuff was thrown it out. A few days later, the Kelloggs noticed the dough had turned mouldy. They put it through the rollers a second time and to their surprise, they produced large thin flakes of wheat that were crisp and tasty after being oven-baked.
Another accidental breakthrough happened in 1992 when a group of healthy men took part in a trial to test a new drug called sildenafil, which was aimed at treating angina, the chest pain caused by heart disease. The drug had an unexpected side effect; it was eventually rebranded as Viagra.