Knowledge Systems Optimization
I was bitten by the Intellectual Capital bug back in the early 90′s when I first read Tom Stewart’s book on the subject. Since then, I have pored over countless papers and articles and books and other scholarly and business writings on the subject. I have gone to the roots, and I have peered into the future, with authors old and new. I have managed to formulate a [for me] workable model of knowledge systems, which I am in the process of describing, formalizing and validating. I would appreciate comments and observations about items that I place here, in order that, together, we might advance the state of learning concerning knowledge systems.
I have divided all knowledge operations into five nodes to encompass all that one might do with knowledge, with the ambition to be able to optimize the balances and tensions among the five nodes, producing the best effect for any particular situation. Hence the comment on my blog title: “Better knowledge. Faster.” These five nodes are:
- Creation: the actual mental conceptualization of a first new bit of knowledge, completely private, entirely individual, and absolutely intangible
- Elicitation: the conversion of the intangible into an artifact for exchange, whether it is words, or pictures, or models; without this step, the new knowledge never leaves the mind of its creator
- Exploitation: the knowledge economy is, first and foremost, an economy; knowledge without application is merely interesting, but to be “intellectual capital” requires that it be economically utile
- Distribution: the process of ensuring that the required knowledge is in the hands of the person needing it, at the time that they need it, in a form that they can use
- Assessment: the value of the intellectual capital must be continually monitored and appraised, as well as an assessment of any “missing” knowledge that must be created
What do you think? Are these five sufficient? What reaction do these comments generate from you?
So what is my intellectual capital, exactly?
I was reviewing my notes from several years ago in preparation for a conference call tomorrow morning with Mary Adams, from Smarter Companies. She specializes in valuating intangible assets such as intellectual capital.
I came across notes from Tom Stewart’s book, The Wealth of Knowledge, about a concept called Company IQ, a way to measure a company’s intellectual capital. [Interestingly enough, in the book, the section on Company IQ is immediately before the section about IC Rating, the measuring system that Mary advocates.] There was a foundational concept embedded in the discussion that struck me, though, as being a core concept for identifying intellectual capital in a real sense.
The concept of Company IQ was developed by Bates Gruppen, a Norwegian advertising arm of an international company, Bates Worldwide. Having an ad agency identify the mechanics of measuring an intangible such as intellectual capital makes perfecct sense since ad agencies operate perpetually in the field of intangibles through advertising.
The process they defined is elegant; elegant because it is both simple and effective, entirely minimalist in its implementation and maximizing its output. Company IQ requires you first to consider and name what your company produces that gives it an advantage; what it does that makes a customer select your company over a competitor. It reminds us that this is not your litany of core competencies or specific skills, but rather it is features and functions that your customer finds valuable, unique aspects of what and how you deliver product and services.
Next, identify approximately 8 to 12 attributes of your company/product/service that you feel are unique and valuable. Send this list both to employees and to customers, asking for a rating between 1 and 7 on two scales: uniqueness and value to the customer.
Plot these results onto a two-axis graph, and those items appearing in the “northeast” region of the graph are those attributes that constitute your intellectual capital. Items that are not unique to you [low on the unique scale] do not sufficiently differentiate you to be considered your intellectual capital. Items that have little value to the customer are not intellectual capital because they are not attractive to your consumer base. Only those items that are high on both scales should be considered as part of your intellectual capital to be managed.
How to do that? That’s another post.
But at least we have a start.
Learning Curve?? How about Forgetting Curve??
How steep is your learning curve?
In an article titled “The Persistence and Transfer of Learning in Insutrial Settings”, Linda Argote et al. defined a learning curve as demonstrating that “the time required to perform a task declines at a decreasing rate as experience with the task is increased”. The notion is that the steeper the learning curve [the quicker that time-to-competency is achieved], the better the training.
The assumption, though, is often made in the organizational learning curve literature that learning is cumulative, that it persists through time without depreciation.
What about forgetting? If the practicing of a task by an individual is interrupted, forgetting occurs; when performance is resumed, it is typically inferior to when it was interrupted but superior to when it began initially. By focusing on the “superior” side, we seem to feel justified in overlooking this depreciation. After all, we tell ourselves, we are still better than when we started, right?
An experiment on forgetting cited in this article indicated that, without practice, the monthly retention rate of learned behaviors was about 75%, that after a month’s absence, the performer would reliably retain only 75% of what they were taught, having forgotten the other 25%. If we extrapolate this rate over extended periods, this would mean that, without replenishing the learning through continued usage, after one year, only 3.2% of the learned information would persist.
Even if retention were as high as 90%, after one year’s absence of practice, only 28% of the learned behavior would persist.
We all understand this through our own personal experience, generally in the field of languages. “Use it or lose it” is the battle cry for learners, but we don’t often realize how important this very basic maxim can be. This also sheds an entirely new importance on refresher courses: you know, the ones we all hate to endure because we “already know it”.
What measures have you built into your training programs and routines to fight the “forgetting” curve? What level fo retention do you expect from your training? Do you have the reinforcement events planned that will forestall the deterioration of learning? Without opportunites for reinforcement, training is simply a waste of time.
Keeping IT from Usurping Knowledge Management
I have probably already alienated half of the readers to the blog, but if you can call them back, I’ll try to explain.
First of all, Information Technology is to Knowledge Management like a bathroom is to a house. Without it, the house is not even considered for buying. But it is generally not the deciding factor. IT enables Knoweldge Management, but IT is NOT Knowledge Management.
Sharing and enabling the technologies needed for the active management of knowledge is not a new concept. The strategies behind the IT component must consider two distinct questions:
–How pervasive is the technology that is being contemplated/used? [It does no good to have a telephone if no one else has one.]
–How willing are people to use the technology? [If it requires a coding background or on-call support to get at the knowledge, few people will use it.]
Ultimately, in designing a Knowledge System [and in optimizing it], we must remember that most of the truly useful knowledge resides in people’s heads, and it is not easily extractable. That knowledge which has already been extracted is only an artifact, and a facsimile, of a more complete knowledge within someone’s mind. Therefore, the only truly effective knowledge managment system is face-to-face discussion. Everything else is simply an information repository- make human interaction your goal, and let the participants figure out the network that works for them.
In Stewart’s book, “Intellectual Capital”, he comments that “The world is littered with the remains of knowledge management programs that companies built and then nobody came.” Rules of thumb for avoiding designing such a program?
–If you are spending more than 1/3 of your budget on technology. you are probably missing the boat. Before you build a system based on ease of access, build a system based on value of access. People don’t care how easy it is to get to information that they don’t need.
–The more “valuable” the knowledge, the less sophisticated the technology required to convey it. Databases and data-mining are high on the technology scale, but they contain data, not knowledge. Help desks, with humans on telephones, are lower on technology but offer high knowledge value. A cup of coffee with an expert can provide more knowledge than any technology solution.
–The more tacit the knowledge, the lower the technology needed to convey it. The more explicit the knowledge, the easier it is to automate. Instead of struggling to automate “expert systems”, provide connections. Expert systems only work when things go as expected; they cannot be programmed for the unexpected. That requires a human.
All of this is part of the rationale behind my quest for “a thousand cups of coffee”. Knowledge Systems Optimization requires that you understand the capabilities of your knowledge systems. But even more so, it requires that you understand the limitations.
Since “creation” resides entirely within the domain of tacit knowledge as expressed by Polyani in his 1969 book, it is important to understand tacit knowledge to understand knowledge creation.
The basic structure of tacit knowledge involves two things:
- an indeterminate correspondent, also known as the proximal event, and
- a specifiably known outcome, also known as the distal event.
In simpler terms, if we are turning over a deck of cards and we provide a slight electric shock [distal event] to our subject every time we display a red face card [proximal event], learning will happen without specific instruction, and tacit knowledge will emerge.
There are four aspects of tacit knowledge in a generally accepted taxonomy:
- Functional: we can name the distal, but are unable to specify the proximal; we know we are being shocked, but we have no idea why.
- Phenomenal [or awareness]: we are aware of the proximal term only in the appearance of the distal term; we recognize that our shock came with the queen of hearts, and now with the king of diamonds, but there was no shock with the ten of diamonds or the three of spades
-Semantic [or meaning]” we have meaning in that the recognition of the proximal term creates anticipation of the distal; we see a red card and flinch, expecting a shock, but it doesn’t come, but then we see a red face card, flinch, and the shock DOES come
-Ontological [or understanding]: we have understanding of the comprehensive integrated entity that the two terms constitute; we know the “rule” that a red face card means we will be shocked
This taxonomy, and the progression through it, drives the entire concept of “indwelling” as the root source of new knowledge, the knowledge that can only come after endless immersion in a system with an aim to “learn the rules”. This indwelling requirement is also the explanation for the prototypical inventor story [Edison, for example] of years and years of “trying” until the breakthrough occurs
Reliable “creation” then requires an understanding and an application, as well as a deep respect for, this progressive taxonomy of experiences. How do YOU cultivate this deep indwelling in your workplace?
I am looking today for comments and observations about the process of “creation”, or”ideation” as the IBM advertisements use in ridicule.
The creation of new knowledge is COMPLETELY individual. No committee or “focus group” ever came up with an idea. It takes the inspiration of a single person to make a connection that has not been seen before, in order to generate new knowledge. It is the Archimedean “Eureka” moment of utmost discovery, when something inside our mind realizes that “we know”.
The challenge in business is to create new knowledge reliably, almost compulsarily, an “on-demand” activity. But inspiration is not “on-demand”.
I liken this process to that of farming, or gardening. I cannot GUARANTEE that I will grow corn in my garden. What I can do is plow the ground, fertilize it, plant seed corn, water it, weed it, expose it to sunlight, and protect it from cold and wind and animals. That SHOULD allow my garden to bring forth corn, and in most cases, it will. But there is no guarantee.
So it is with ideation, with the “creation” node. We can plow the ground, fertilize it, plant seeds, water it and tend it, and if we have done it correctly [whatever that may be], we SHOULD have corn – I mean, ideas.
The challenge lies in completing the metaphor: what constitutes plowing the ground, fertilizing, watering? What is, and where does one find, the seed? Innovation think tanks have some of the answers but not all.
What do YOU think?