Sharing Knowledge and Organizational Learning

Actually, this is yet another extract, because I found out that it is also relevant to the topic of this blog, and because I want to be able to quote it in the future ...

On the management literature best-seller is P. Senge’s book The 5th Discipline, which I have quoted earlier. This great book focuses on the collective intelligence of an organization (and, by consequence, collective learning). This leads naturally to the concepts of collective skills and collective knowledge. Looking at analysis and thinking as collective activities is not as easy or simple as it sounds. This type of collective behavior emerges in companies as a response to the increasing demands and the increasing competition. A major part of his book is devoted to the analysis of systems and their complexity, which P. Senge considers to be the most significant issue of organizational (team) learning[1]. Sharing knowledge is a topic which is neither simple nor intuitive. There exists a wealth of dubious quotes or proverbs that claim that sharing knowledge is a way to get richer, that knowledge is the only wealth that is not lost when given away, and so on. In practice, sharing one’s knowledge is difficult (which is why one must learn to become a teacher), it is time-consuming (thus it is nothing but free) and it may yield to feel a loss of status to the one who is “sharing” away her knowledge. A necessary condition is to establish a culture that promote knowledge passing, both in the general sense (as a principle) and in a practical sense (so that the time which is spent is recognized and rewarded). The fame of “knowledge management” has declined over the years since it has been associated with heavy and costly projects, which came with new technologies that appeared overly complex. The “knowledge management” (KM) expression is used to designate both a process (which is our focus here) and a project. Ten years ago, projects to extract knowledge out of a group of specialists (through interviews to build a so-called “knowledge base”) were quite popular. They are still useful and relevant in a few specialized cases, but this approach is too heavy and too static to be applied in a continuous manner[2]. The next figure is an attempt – some readers may find it unduly abstract or complex – to represent the complex transformation which an enterprise must go through, as explained in this last section. There are two parts: the left part is a “traditional view” of the enterprise, the right is a newer vision centered on collective intelligence. The left part represents a traditional perspective on the employee, who is appreciated for his actions. We use a classical representation of knowledge as a process which transforms information into action (small rectangular box associated to each employee on the figure). In a traditional perspective, knowledge is a personal matter (even if some information is shared). The domain of the company is the coordination of individual actions into collective ones, which is represented, in Figure 6.3, with a dashed-line triangle. The “bubble” on top of the figure represents the “governance mode”, which is the “control-command” approach that we discussed earlier. The right part of the figure represents the result obtained when the transformation towards collective intelligence is achieved. The first difference with the previous situation is that knowledge is no longer an individual matter. A new part of collective knowledge (the grey rectangle in Figure 6.3) has appeared, which is precisely the field of knowledge management. Since the company is immersed into a constantly evolving world, this collective knowledge needs to be continuously revisited and updated. This continuous activity (circle arrow) is the knowledge management process’s goal. Let us notice that, when the surroundings change constantly, knowledge management and organizational learning become synonymous. The goal for companies is not simply to “know the right things” but to be able to “learn all the necessary things”. The second difference with the left part lies with the distributed management style (illustrated with the bubble). Top-down hierarchical command is replaced by a dual flow: a situation occurs that triggers a reaction, while a common goal influences the way situations are analyzed. The company goals are re-evaluated according to the situation changes. Moreover, they may be interpreted locally by “field managers” who enjoy more responsibilities. A distributed control emphasizes the interest of managing collective knowledge, which supports the coherence control that may no longer be enforced by a centralized and autocrat vision.

Figure 6.3: Collective Management of Knowledge and Learning

As far as the process of knowledge management within the enterprise is concerned, we may summarize the key principles as follows:

• Knowledge capitalization is mostly an internal communication process. This is why tools that support “practice communities” (cf. the previous discussion about blogs) are playing a key role.
• A global management of knowledge throughout the company is made necessary by the distribution of management and decision taking[3].
• Structuring collective knowledge is an emerging process, which is not directed towards goals, but, in the opposite direction, yields opportunities[4].

Managing knowledge may not be separated from skill management, nor, more generally, from human resource management. Managing skills require producing assessments, to draw skill maps and to articulate a growth strategy. In a way that complements the emergent process of knowledge management, skill management is better carried in a planned and top-town manner. Necessary skills may be bought, recruited or trained … All this takes time, on a multi-year scale. Skill management is an operational responsibility that devolves upon business divisions, but which requires the methodological assistance from the human resource division. This is not simply because skills are a person-related matter, but also because the time scale that is required to implement a strategy is too long for a purely operational perspective.

[1] Peter Senge makes a key difference between detail complexity (many sub-parts) and dynamic complexity (many steps for the associated processes). Chapters 6 and 7 provides with a clear illustration of what « system thinking » (a favorite expressions from this book) is. On the other hand, Chapter 12 deals with « team learning », which is precisely about organizational learning. To P. Senge, organizational learning is the fifth step of a maturity scale, which follows more classical maturity stage that are borrowed from total quality management.
[2] On this topic, see the previously quoted book from E. Awad et H. Ghaziri, Knowledge Management, which is very thorough, even though on the descriptive side. The reader will find there definitions for terms such as “information” and “knowledge”, as well as a complete taxonomy of knowledge, together with the associated extraction and capitalization processes.
[3] These ideas are brilliantly developed in L. Morris’s book, Managing the evolving corporation, which was introduced in the previous chapter. I especially recommend the fifth chapter which has been a key source for my own thinking. It explains the relationships between information, knowledge and decisions with much more detail than what is given here.
[4] About this fascinating but complex topic, one should read the book from F. Julien: “Treatises on Efficacy: Between Western and Chinese Thinking”. He starts with a brilliant comparison between strategic military thinking in Occident versus China. He then deals with the concept of efficiency and contrast our goal-directed strategies with « situation intelligence » which is the trademark of Chinese thinkers. A large number of fashionable theories, proposed in management books, about the « networked enterprise » may be analyzed and explained with this treasure of knowledge and erudition.