This is part two of a series on Knowledge Management. We revisit why we view knowledge management as a core competence of Embrace IT, what that means, and what we are doing to build our learning capability from first principles.
In our previous post, we prescriptively labeled knowledge management as a core competence for Embrace IT. We specified that the two major tasks of knowledge management are to lift knowledge from the individual to the organisation, and to protect knowledge from erosion.
We ended on the somewhat sobering note that while the benefits of effective organisational learning are well-known, the process by which it occurs is often unpredictable and difficult to foster, and that there is no overall consensus on the best way to improve it (Falconer, 2006).
We need to deepen our mental model of knowledge to understand why.
Knowledge is more than just data or information. It encompasses a mix of experience, values, and context that jointly governs how new experience and inputs are processed and incorporated (Davenport & Prusak, 1998). This means that knowledge is not strictly factual or objective. It incorporates perspectives or beliefs applied to some end or action, and exists in relation to a specific context (Nonaka & Takeuchi, 1995).
Some knowledge can be codified and made explicit in documents, routines or processes. Explicit knowledge is objective, rational or technical. By definition, it can be identified and articulated. This makes explicit knowledge relatively easy to structure, maintain and share. An example of explicit knowledge from a software context is something like API documentation. It's a factual account, providing objectively verifiable information.
Explicit knowledge is valuable only insofar as there is an audience that can understand, evaluate and connect it to its own context (Davenport & Prusak, 1998). In order to do this, we must convey a complementary set of tacit knowledge as well. Unlike explicit knowledge, tacit knowledge is subjective and personal. It encompasses personal insights, experience and intuition.
Tacit knowledge can encompass hands-on experience, best practices and tips and tricks, rules of thumb and practical know-how. We can call this technical tacit knowledge. This knowledge has at least some codifiable dimension (Panahi, Watson, & Partridge, 2013). But other than that, tacit knowledge is hard to codify and may only exist implicitly (Talinn University, 2018; Smith, 2003). That is, we will often simply assume our audience has the requisite background, without being able to articulate exactly what that prerequisite knowledge entails.
Take that API documentation from our previous example. It's easy to see that a description of endpoints contains only a fraction of the information required to build and maintain the API. Some of that missing knowledge is codifiable, at least in principle. The technical know-how of the language or framework, and the best practices distilled from working with other APIs, for example, or the domain in which the API is used and the applications consuming it. We may or may not want to add that technical tacit knowledge to our documentation - it largely depends on the audience we have in mind.
But there are other types of tacit knowledge that aren't as easy to capture. In fact, we may simply not realise that it's there.
For example, as a contractor I've worked with a few teams at different companies. All of them operated on an understanding of REST principles (what are those anyway?), and 'good' API design for their products. Funnily enough, these principles differed wildly between companies, and were almost never laid out explicitly. Every team confidently operated on a sense of consistency with a shared ruleset that existed only as an implicit understanding.
An interesting empirical finding from an experiment conducted in 2007 is that tacit and explicit knowledge tend to have different effects on a team's productivity as measured in speed, quality and perceived competence by external stakeholders.
Acquisition of both types of knowledge had a positive impact on general productivity, but explicit knowledge mainly impacted task completion speed, while acquiring tacit knowledge had a larger impact on task quality and perceived competence. (Haas and Hansen, 2007 as cited in Hislop, Bosua, & Helms, 2018, pp.20, emphasis mine)
The same difficulties of codification and of knowing what's there to convey pertain to the communication of any professional skill, be it in the realm of craftsmanship, problem-solving or effective leadership (Hislop, Bosua, & Helms, 2018, pp. 18-20, 159).
So, why is knowledge hard to share? The first part of our answer is that a lot of what makes knowledge valuable is tacit and resists codification. And even if we manage to figure out how to codify valuable knowledge, only an audience with the proper background and context can unlock its potential.
This points to a second part of the problem that - as we'll see in our next post - is equally challenging: how do we transfer knowledge?
Davenport, T., & Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know. Boston: Harvard Business School Press.
Falconer, L. (2006). Organizational learning, tacit information, and e-learning: A Review. The Learning Organization, 13(2), 140-151.
Haas, M., & Hansen, M. (2007). Different Knowledge, Different Benefits: Toward a Productivity Perspective on Knowledge Sharing in Organizations. Strategic Management Journal, 28, 1133-1153.
Hislop, D., Bosua, R., & Helms, R. (2018). Knowledge Management in Organizations: A Critical Introduction (4th ed.). Glasgow: Oxford University Press.
Nonaka, I., & Takeuchi, H. (1995). The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press.
Panahi, S., Watson, J., & Partridge, H. (2013). Towards Tacit Knowledge Sharing Over Social Web Tools. Journal of Knowledge Management, 17(3), 379-397.
Smith, M. (2003). Michael Polanyi and Tacit Knowledge. Retrieved September 2018, from The Encyclopedia of Informal Education: http://infed.org/mobi/michael-polanyi-and-tacit-knowledge/
Talinn University. (2018). Tacit and Explicit Knowledge. Retrieved September 2018, from Key Concepts in Information and Knowledge Management
