Where Knowledge Management Has Been and Where It Is Going- Part One

KM has changed in many ways since its beginning some fifteen years ago, with new tools and new strategies. But what is most interesting to me is the profound change in the way we conceptualize knowledge and the implications of that conceptualization for how we do our work as knowledge professionals. What I mean when I say, “how we conceptualize knowledge” are issues like, “Who in the organization has useful knowledge;” “How stable >is knowledge over time;” “How we can tell if knowledge is valid or trustworthy.” These are not trivial issues because how we conceptualize knowledge greatly impacts the way we design our KM systems and strategies.

If the goal of KM is, as I believe it to be, to make use of the collective knowledge in an organization – then we have been learning how to do KM since early in the 90’s. It has been a steep learning curve and we still have a steep curve head of us, but we are learning as evidenced by how our thinking about our strategies for dealing with organizational knowledge has changed and evolved.

I will classify this evolving landscape into three categories. The first is leveraging explicit knowledge and it is about capturing documented knowledge and creating a collection from it - connecting people to content. The second category is about leveraging experiential knowledge and it gave rise to communities of practice and social networks. It's primarily a focus on connecting people to people. The third category is about leveraging collective knowledge and it is primarily about conversation both in its virtual and face-to-face forms. It is primarily about who is in the conversation and what the conversation is about - it is connecting employees and decision makers.

For each category I will describe, 1) how those who were leading the field of KM conceptualized knowledge, 2) the strategies those concepts engendered, 3) the difficulties and successes those strategies and conceptualizations presented to the field of KM.

The diagram shows the three categories with a beginning date, but each category then continues past where the next category begins. I have extended each category for two reasons, one, the strategies prominent in each category continue to remain viable, and two, as new organizations take up KM their initial entry, (perhaps based on the charge management has dictated) tends to be focused on the earlier categories.

Three categories are a lot to cover in one post so I have made this a series. In this post I will tackle not only the first category but also paint a brief picture of how organizational knowledge was conceptualized before the rise of KM – the precursors of knowledge management.

Knowledge Management Precursors
Before the first wave of KM in the early 90s there had been document and information management, both clearly labeled as such. If organizations thought about knowledge at all, they thought of it as the content of training classes and training was focused on individual development. For example, in the 1980’s there was a rise of competency models, many of which were further developed into instruments (Boyatzis, 1982; CCL.) The underlying assumption of that pre-KM period was that if you trained each individual with the competencies required for their specific job, the combined effort would lead to organization effectiveness - a kind of additive view of organizational knowledge. I was a part of that period and remember how hard we struggled to word competencies so they could be actionable and measurable.

Following on the heels of the competency push, was Organizational Learning or the Learning Organization, depending on what you were reading at the time. This view depicted learning in terms of the whole system rather than the individual. Senge’s book, The Fifth Discipline, came out in 1990 and my book the Organizational Learning Cycle was published in 1994.

The language of knowledge management drew most directly from Peter Drucker,
who wrote about the Knowledge Age. Framing the growing importance of knowledge, Drucker predicted the knowledge based economy, noting that wealth and power, which had previously been based on land and capital, was shifting and would increasingly be based on knowledge. He coined the term “knowledge worker,” to describe a new kind of work and worker in the knowledge based economy.

The First Category of Knowledge Management - Leveraging Explicit Knowledge
Building on Drucker’s framing, the new way of thinking about knowledge, that began in the mid 90s (the red bar on my diagram), was that knowledge was an organizational asset and if an asset then it needed to be managed. After all, organizations manage their other assets, (e.g. capital, people) so it made sense to also manage an organization’s knowledge – thus the term (which nearly everyone now regrets) “knowledge management”. CEOs began to declare, “Knowledge is our competitive advantage.”

The early thinking about how we should manage this knowledge asset, was to use technology, taking advantage of the growing capability of intranets. There was an effort to collect all the important knowledge that an organization possessed into one database. The analogy was of a warehouse or a library. People were to put knowledge in the warehouse and those that needed it could take the knowledge out and use it. And much like the contents of a real warehouse, knowledge was thought of as stable. That is, you could put knowledge in the warehouse today and get it out in six months or even two years later without any degradation of its value. In this first era of knowledge management, knowledge repositories were the strategy of choice and they contained best practices and lessons learned as well as technical documents.

Management had a great deal of concern about the quality and validity of the knowledge being captured. The salient question was, how can we be certain that a practice is “best.” Many organizations brought together teams of experts from each field to identify and then write up the best practices. In other organizations everyone was invited to contribute, then a panel of experts would vet the contributions so that only the “best” made it into the repository. In some companies experts categorized employee contributions into levels of practice, e.g. “local practice,” “good practice,” “validated practice,” all the way up to “best practice”. Having identified the “best practice” some organizations required everyone to implement that practice, making knowledge management a move toward standardization. The assumption was that there was a best way to accomplish any task – so knowledge management professionals were expected to identify and then capture it.

Leveraging Explicit Knowledge was conceived as a dissemination task; expert knowledge was sent out to those who did not know as much about their jobs as the experts did. It was based on a model that we were all familiar with, the school model, with an expert providing knowledge to those who were less knowledgable. So it was a natural model for knowledge professionals to use.

Repositories were so ubiquitous that in many organizations the term “knowledge repository” was synonymous with “knowledge management.” And since IT necessarily built the repositories, KM was frequently placed under the IT department.

There was one further assumption, which was that employees would seek out the captured knowledge and use it. But of course in many organizations people did not readily submit knowledge nor were they inclined to take it out of the warehouse. Managers determined they would have to incentivize employees to get them to use the knowledge. Lots of schemes were put in place, from offering frequent flyer points for input to requiring teams to go through the database for ideas before starting a new project – and checking a box in the project plan to prove they had looked the ideas over.

For the most part these databases, even with incentives in place, did not produce much improvement. In a few organizations, where the work was repetitious and standardized, they were successful. Ford Motor Company was a great example, saving millions of dollars by sharing best practices. But for the most part front line workers had little interest in putting things in or taking things out.

Some of the assumptions made about leveraging explicit knowledge were incorrect, but many were not inaccurate, rather they were limited to one kind of knowledge - explicit knowledge that can be documented.

What knowledge management professionals began to discover was that technology alone was not enough to manage knowledge. “People to content” was a necessary step but fell far short of being sufficient to leverage an organization’s knowledge.
• It left out all the important knowledge that was in people’s heads.
• Employees resisted using other’s knowledge. It made them feel a bit child like or incompetent to be the recipient of the knowledge that some unknown expert had declared as “best.”
• A great deal of important knowledge is, in fact, not stable over time but is constantly changing, in some situations even daily.
• It left out considerations of the context in which the practice would be implemented, because for practices to be useful to a larger number of situations, they had to be generalized.

Having spent thousands of dollars with little return on investment, in many companies, management became disillusioned with knowledge management.

Then some time around 2000 organizations began to think about knowledge in a new way and Leveraging Experiential Knowledge breathed new life and capability into knowledge management. That will be Part 2

Comments

[Nick Milton]

Great post Nancy, though as you know we were doing "learning before, during and after" in BP in 1997 (and indeed earlier in BP Norway, and in the Virtual reamworking project) so I would shift your yellow box a little!

I think there another step, though I am not quite sure how to express it as a three-word phrase beginning with "leveraging" and ending with "knowledge". That is the step of introducing governance. That's the step that takes it from "working with knowledge" to "knowledge Management". It's the step that brings the M into KM.

[Nancy Dixon]

Nick,
I agree, BP was way ahead of the game, but I believe most organizations much before 2000 were still in that first category. Let's see what others say.

I'd love to hear more about your "other step" leveraging xxxxx Knowledge. Keep thinking about it. I'll post the second installment in about a week and maybe when all three are up we can have a conversation about what's missing.

Nancy

[Steve]

This a great overview, Nancy. I've been in a similar, reflective mood about the path of organizational learning and knowledge, such as how to define KM for any given context or simply enjoy the ambiguities and contraditions.
Steve

[Rajagopal, Sukumar]

Brilliant post Nancy.

[Nimmy]

H'mm..! Thanks for this post, Nancy! I am looking forward to the rest of the series. I myself was pondering over the history of KM some months ago and came up with this post here - http://nirmala-km.blogspot.com/2008/08/thinking-about-kms-growth-as-concept.html [Would love to know what you think about my conclusions.]

[pbr]

In a knowledge based society, quality of knowledge is theoretically important provided it is valid knowledge; when it is propaganda, it can be a disturbing tool through which a knowledge-based society can be undermined, and destroyed - over time, if not immediately.

Moving from an agrarian to an industrial to a knowledge based society is extremely critical in that it presumes that the utility of knowledge based society has the same importance and function as a productive society based upon agrarian or industrial principles. When knowledge (or its accumulation, in theory, based upon merit)serves the purpose of deception and disguise, rather than truth, the result is propaganda which tends to be unreliable and destroys the purpose and productivity of those who produce it, as well as those who rely upon it.

The best example are scientific studies that are deceptive but which call for peer review, or reliance, upon which other scientists construct theorems intended to work, which may never work, because the underlying data was wrong, filled with errors, or overtly deceptive. In short, they may generate profits and fame but have no enduring value. The same could be said of Audit and Accounting reports that others rely upon to estimate market share, or share value, and earnings that are embedded into the marketplace for investments and private placements for raising capital. Many banks, government, and industries rely upon valid data from legitimate and honest sources to make such decisions. If what they receive is propaganda, and dishonest data, there is no way the data can have solid, enduring value. They may be good for profits and promotion of the moment, but lack efficacy for anything else. To the extent that Americans have just endured the outcome of this brand of knowledge mismangement may be the source of the banking bailout, Wall Street demise that has hit Americans, organizations, companies, and the nation hard, and unmercifully in the recognize of the result of devastating losses - and consequential lack of trust in all markets.

At what point does the work of any nation have little or no value?
At the point where any productivity is bad productivity with no utility or value because of its quality and content. Where America goes after it moves its manufacturing overseas, and concentrates on its knowledge management productivity if that effort is poor, is once of the reasons that many question her future as an international power among nations of excellence.

If moving toward a useless society rather than a useful society doesn't bother government, it should, and it is of great consequence to all Americans, today and in the future.