(Co-Authored with Steven A. Cavaleri)
This post is the third discussing the question of enhancing processes and activities we use to develop new ideas.
Fourth, current organizational knowledge bases don’t distinguish knowledge from information, and given the importance of previous cultural knowledge for creating new ideas, this is a very big problem for present technology. Most current organizational knowledge bases don’t record the track record of past performance of knowledge claims used by the enterprise. So, from the point of view of people using them, everything in the knowledge base is just information. It would be a big help to people thinking up new solutions to confront their thinking with past organizational knowledge, as well as their own personal knowledge. But it is hard to do that in the absence of real knowledge bases that distinguish between cultural knowledge, just information, and error.
Turning again to Toyota for an example, it gets a good deal closer to the requirement for a knowledge base track record I’ve mentioned. It uses a discipline of detailed documentation of lessons learned from team problem solving efforts, and adopts an experimental and organizational learning point of view toward work. As new knowledge is created in a problem context, it is documented in “A3 reports” which capture on an A-3 size sheet of paper, partly in a visual format, the story of a team problem solving effort including summarizing the process of team problem solving, in addition to the solution arrived at. The process includes documenting alternative solutions and a team’s reasons for selecting a preferred solution. A-3 reports are used to produce “lessons learned” books in each area of process design. The “lessons learned” books frequently change to incorporate experiences (using audit sheets) of new process deviations and refinement of solutions (knowledge) for meeting them. Toyota’s A-3 reports and “lessons learned” books incorporate the structured and unstructured information about problem and process context necessary for creating what we mean by a “real” knowledge base, but their design doesn’t make fully explicit the idea of a track record of alternative solutions, and, in addition, the integration of the A-3 reports and “lessons learned” documents is accomplished primarily through human knowledge and know-how about them with little Information Technology support.
It should be a priority of organizations to construct real knowledge bases, including:
– “Practices and Solutions systems” that actually track the performance of practices and solutions with collaborative tags and annotations, rather than just identifying practices that are claimed to be “best” (such systems would include both “lessons learned” and “best practices,” but both would be placed in a much richer problem and process context of meaning than in the past and, therefore, are much more likely to be used.)
– Collaboratively tagged and annotated narrative databases that express the perspectives and evaluations of people in concrete detail understandable to people. In the Toyota case, this would mean collaboratively tagging and annotating A-3 reports and “lessons learned” e-books,
– Collaboratively tagged and annotated blog posts, and wiki contributions,
– Collaboratively tagged and annotated podcasts and youtube-like videos, and
– Other collaboratively tagged and annotated structured and unstructured content.
For flexibility and variety, the real knowledge bases we have in mind, ought to be distributed, rather than centralized, and Enterprise 2.0 and 3.0 technology including tagging, annotating, and mashups, and new semantic web applications, should be applied to create both a new and richer layer of meaning and integration across stove pipes. To be effective in creating high quality knowledge bases that will be most useful in enhancing thinking up new ideas, social computing technology must be applied both collaboratively, and in a way that includes all ideas, no matter how new and untested they are. The rule should be to let the knowledge base reflect the track record of performance of ideas comprising solutions, or the absence of such a track record, and leave it up to people to factor that into their own creative thinking.
Distributed Organizational Knowledge Bases (DOKBs) should be “objective” in the sense that they incorporate a track record of performance reflecting fair critical comparisons among alternative solutions. We’ll discuss fair critical comparison a bit in a later post in this series. But here the important point is that creating such knowledge bases involves more than just using Enterprise 2.0 software. It also involves knowing how to use it and other software applications to create a new layer of cultural meaning that reflects performance tracking and fair critical comparison of ideas.
Fifth, information technology initiatives that support individuals generating new ideas are very important to implement. We’ve already indicated that Web 2.0 cluster technologies can be a big help in generating new ideas, both because they enable the mechanics of idea creation and expression in a social context, and also increase transparency, and sometimes inclusiveness. In addition, there are many applications that are helpful as aids to individual level creative thinking such as visual mind mapping software, text and data mining software, decision support software, and simulation modeling software.
To Be Continued