|I just got back from a two-day conference in Ottawa on Knowledge Management, sponsored by the Conference Board of Canada. The entire discipline is at a crossroads, and the discussion was urgent and intense. I have already written about where I think KM is headed:
What was eye-opening to me was the perspective of the substantial number of representatives from the public sector present at the meeting. I tend to think about KM in the context of large corporate and entrepreneurial environments, which I’m most familiar with, and how their information needs dovetail with those of individual citizens and consumers. But I often forget that public sector organizations have different needs, and it’s dangerous to assume that the answers that make sense in the private sector translate to not-for-profit organizations.
So I decided to see if I could develop a Knowledge Management model that would work for any user, public or private, organization or individual. Models that focus on strategy, systems, information structures and value propositions didn’t work — they vary too much by organization type and size. I found only two bases for KM models that seem to apply ubiquitously: principles, and processes.
I’ve addressed what I believe to be the ubiquitous principles of KM in a recent article, and will have more to say about that soon. But as I started to think about the processes of KM, I realized that we have been looking at it all wrong, from above, from a systems perspective, instead of from ground level, from an activity level. The best-known KM process models are Nonaka’s four-step ‘knowledge creation’ process — codification, enhancement, internalization, sharing — and the consultants’ megaprocess model — acquire, store, add value, apply/deploy. Show either of these models to a front-line worker or an individual citizen/consumer, and you’re likely to get either yawns or raised eyebrows. They just don’t describe in a meaningful way what people do — their ‘knowledge activities’.
After a few hours’ research and discussion with some of my KM colleagues, I came up with this alternative model:
I’ve never liked the term ‘Knowledge Management’, so having circumscribed the set of activities that KM was supposed to be about, I decided to ponder what would be a less presumptuous and more precise name for a discipline that would purport to improve the effectiveness and efficiency of how we do these things. It is broader than just ‘thinking’ or ‘information processing’ or ‘learning’, but narrower than ‘productivity’ (which can describe physical as well as intellectual activity). It has much to do with helping people carry out these activities better — enablement and facilitation and making work easier. There are no words for this in the English language, or any other language I’m familiar with, which is perhaps why the awful term Knowledge Management came to be used. How do you reduce making workers’ intellectual activities easier, and more effective to a couple of words? The best I can come up with is the clumsy ‘Intellectual Work Effectiveness Improvement Facilitation’, and since most work today is intellectual, and most of what support departments do is facilitation, we might drop the first and last words. But ‘Work Effectiveness Improvement’ is perilously close to the ’90s fad called Business Process/Performance Improvement (BPI, also known as Re-engineering).
As noted above, KM has traditionally been about building and populating databases with useful content, creating portals — generally, making more information readily available. The consequence has often been to drown workers in hard-to-find information of dubious value just in case they should find themselves in a position to use it. We have actually made workers’ intellectual activities harder rather than easier, by presuming, top-down or back-office-to-front-lines, to understand what information they need, and how, when and why they need it. In a world where jobs are more and more specialized, and everyone’s information needs are increasingly unique, it’s not surprising that KM has failed to live up to its promise.
If we were to start over again, with the mandate to help make people’s intellectual work (the 12 activities in the chart) easier and more effective, what would we do differently? Consultants will tell you there are four ways to make work more effective: Improve the tools, the information (content), the processes, or the behaviours. Tools have always been the primary domain of the IT people, and behaviours (culture) have always been the primary domain of the HR and Learning people. Re-engineering tried to focus on the processes, only to discover that standard business processes and procedures still exist only in a few highly-prescriptive jobs, most of which are subject to automation or offshoring. That left only content for the KM people to focus on, and they’ve done their best for a decade to improve the amount of information available to front-line workers, working with the IT and Learning people. But for the most part, the information people want either doesn’t exist, or is only valuable with the context of the person who provides it (most effectively communicated in conversations), so the plethora of massive new databases and information feeds are of limited use.
What is the problem KM has been trying to solve? What problems do front-line workers have doing the 12 intellectual activities in the chart above? I surveyed the people of Ernst & Young about this three years ago, and here’s how some of them answered this question:
So if we started KM over again as Work Effectiveness Improvement (Drucker, who saw this as precisely the greatest business challenge of the 21st century, would surely approve), what would our ‘Job Description‘ look like, to address the eight problems above? Here’s a stab at it:
Ten years ago when I was first appointed Chief Knowledge Officer, one of my first tasks was to pull together my own job description. At the time, I did my best, but after reading all the hype about KM I fell victim to it — my job description was all about establishing a Knowledge Vision, Knowledge Strategy, developing Knowledge Infrastructure and Architecture, and changing Knowledge Culture from “knowledge hoarding to sharing, collaboration and innovation”. Pretty high-falutin’ stuff. It was fascinating, but ultimately futile, misdirected, overly ambitious, and endlessly frustrating. If I’d had the foresight to have put the six bullets above on my job description instead, it would certainly have raised lots of questions and eyebrows, but ultimately would have probably achieved much more substantial results, and made everyone happier, especially those poor, abused, neglected, front-line workers who, a decade later, are still waiting for the realization of KM’s extraordinary promise, and promises. If only they’d named me Chief Work Effectiveness Improvement Officer instead.