User education for KM:The problem we won't recognize
By Michael Koenig
The observation that KM is more about people and organizational culture than it is about IT is common currency in our field. That observation is translated into a variety of prescriptive forms—don't leave KM to the IT folks, don't assume that if you build it they will come, recognize the importance of social capital, and the list goes on. What has not been adequately recognized, however, is the importance of user education and training.
A recent report from KPMG (kpmg.com) is a compelling documentation of both the problem and the fact that we don't or won't recognize the problem. In its biannual study of the status of KM, entitled “KM 2000,” KPMG analyzed more than 400 firms. The researchers found that of the 288 firms that had KM systems in place or were setting them up, benefits failed to meet expectations in 137 cases—nearly half (48%). Furthermore, of that base of 288 firms, 127 were still in the setting up phase. That implies that of 161 firms with KM systems in place, 137 (85%) reported instances where benefits failed to meet expectations. (Note, however, that some companies were reporting on more than one KM initiative, so that the percentage of KM initiatives that failed to meet expectations is not as high as 85%, but it is still obviously quite high.) The breakdown of why benefits failed to meet expectations is as follows:
What is striking is that three reasons: #1) lack of user uptake due to insufficient communication, #3) lack of time to learn/system too complicated, and #4) lack of training, are all fundamentally the same reason--inadequate training and user education. With that recognized, the table can be recast in a more informative fashion:
The problem is clear: Inadequate training and user education is by far the most prominent reason why benefits failed to meet expectations, accounting for the majority of failures, exceeding all other reasons combined. There weren't a bunch of middling size reasons; there is one overwhelming reason.
The lack of recognition of the problem is also clear. The KPMG report, for instance, goes just this far in recognizing the importance of the lack of training/education, when it observes, “These responses confirm the fundamental flaw in viewing KM as a technology issue: It is not the technology that is holding organizations back but a lack of strategy and a failure to build KM in the organization’s day-to-day operations and its culture in order to encourage end-user buy-in.”
The obvious lesson is to pay attention to the key role played by training and user education. How can we make that concrete and operational?
The first corollary is a logical one: If user education and training is so important, put it up front—design the training and education program first.
That is really just a recasting of the systems analysis precept of writing the user manual first. The point is that taking the time to write the user manual first, or at least very early on in systems development, forces the design team to put themselves in the user’s shoes and to think clearly about what the system will and will not do. It helps avoid the common problem of systems development drifting off in the direction of the easily doable, or what the programmer thinks is clever or neat, rather than proceeding in the often more prosaic direction of what the user needs. And, of course, it helps ensure that the system does what is needed in a way that is effective and easy to use.
The KM analog is designing the training and education program first, or at least as early on as is practicable. Implementing KM is a systems development project in which the cultural aspects are of even more critical importance than in most projects. And because of the importance of those cultural aspects, the team must think not only about how the system will be used, but also about why. In answering why, the team is forced to address what the system is trying to accomplish, whether it is likely to be accomplished, and what stands in the way--typically cultural issues. Then the question arises, what is being done and can be done to address those issues?
Tactical components of training and educationExamining the classic IBM tableau of the domain of KM and keeping in mind two central information usage phenomena leads to more conclusions. First, these two phenomena are:
1.) The 20%-25% rule
An intriguing finding that emerges from studies of the work practices of white-collar professionals is that they spend a rather consistent 20%-25% of their time information seeking. That proportion is surprisingly independent of the apparent information intensity of the job domain. Line business managers and administrators spend as much time information seeking as do research scientists. There seems to be a sort of homeostasis, or perhaps more accurately, a satisficing mechanism at work. Knowledge workers, whether managers or administrators or researchers, need substantial information input to perform satisfactorily. But when the amount of time devoted to that function approaches 20%, knowledge workers appear to begin to satisfice. They begin to conclude that they have to get on with the rest of their job; that if they have not already done so, they will soon run into diminishing returns in their information seeking; and that it is time to proceed based on the information they have.The obvious conclusion is that if knowledge workers spend so much of their time information seeking, they are likely to perform better if the systems and environment allow them to spend their time efficiently. It is unlikely that the 20%-25% figure arises because most knowledge workers coincidentally arrive at just the information they need at just that same point. It is more likely that they share an intuitive satisficing mechanism, and that they often proceed in their decision making with poorer information than they would have if a more supportive environment and more capable information and knowledge systems were in place. Good systems, though, aren't enough. If that information search time is to be used effectively, good training and user education programs must be in place.
2.) Rich communications, browsing and serendipity
An extensive body of research documents the relationships between knowledge worker and organizational productivity, with rich communications, browsing and serendipity. What is intriguing in those studies of the correlates of successful R&D is the phenomenon that when various factors are considered, the information-related factors consistently jump to the head of the list. Equally intriguing is the frequency with which the authors of the studies fail to remark on that factor (from “Information Sciences and Downstream Productivity” by Michael Koenig, The Annual Review of Information Science and Technology, 1990).
Also consistent within the studies is the importance of browsing and serendipity. In a study of the pharmaceutical industry, for example, the researchers at the more productive pharmaceutical companies not only had used their corporate library or information center more recently, they used it proportionately much more for browsing and keeping abreast, as opposed to addressing a specific information need. Indeed at the pharmaceutical company most highly rated for research success, Pfizer (pfizer.com), the corporate message encouraging such browsing was abundantly clear. At the entrance to the library at research headquarters were two long tables, one prominently labeled “Today’s Journals” and the other labeled “Yesterday's Journals.” Researchers were obviously expected to be in the library frequently, and to be following the most current literature (from “The Information Environment and the Productivity of Research” by Michael Koenig, Recent Advances