In a competitive world, knowledge is the only enduring source of advantage for a company (Birkinshaw, 2001). However, managing knowledge effectively and efficiently is a challenge that many companies face. As employees gain expertise in their work over a period of time, the amount of tacit knowledge they build keeps on increasing. Tacit knowledge is the knowledge, skills, and abilities an individual gets with experience that is many times difficult to put into words or otherwise communicate (David Oragui, 2020).
Recently, I was able to secure a job and changed my employer. Based on my experience with both the old and the new employer, I would like to share my observations about organizations’ issues when capturing and transferring tacit knowledge.
The most significant hurdle is in the identification of domain experts. An organization has many moving parts, multiple teams, multiple office locations, and teams split across the continents. Hence, it is challenging for an organization to identify the domain experts who hold the tacit knowledge. Furthermore, if teams work in silos, the job becomes more complex as other teams and employers will not know that a particular person is rich in knowledge. Therefore, it is extremely important to codify the knowledge that s/he possesses. Therefore, teams constantly need to look for experts in their vicinity and codify those individuals’ knowledge and learnings.
Since individuals hold tacit knowledge, it is possible that when it is codified, it can carry the personal characteristics and bias of the knowledge holder. Therefore, it is extremely important that while the tacit knowledge is coded, these personal characters, choices, and bias is eliminated at the right level. For example, an individual may not like to work with the current version of the Dreamweaver application for web development due to his personal choice. Still, the latest version’s benefits can help improve other employees’ productivity.
An organization needs to deploy the latest techniques used in knowledge management to keep its knowledge repository up-to-date and easy to access. For example, my current organization uses a mix of two applications to maintain their knowledge repositories, Wiki and Confluence. These two offer excellent content management benefits, ease of data management, and content discovery.
Organizations can start using techniques like personalization, recommendation engines, and alerts. Every person has their own needs for knowledge discovery based on the nature of the work. For example, John, who works in product development, will find knowledge about search engine optimization of less importance. So, AI-powered tools can be used to render personalized KM pages instead of bombarding the user with all the possible pieces of knowledge. On the other hand, John will find the KM system very useful if content around product management is displayed prominently.
One should also consider using recommendation engines. This software suggests (recommends) content based on user profile, browsing behaviour, and history. For example, when a user completes reading an article on how to colour-correct an image in photoshop, s/he can be presented with additional relevant information about the same topic. These content pieces are contributed by subject matter experts in the same organizations. Therefore, end-users must find these relevant content pieces on the same web pages.
Utilizing an alerting system like email alerts or push notifications should also be considered by organizations to overcome the challenges around content discovery. For example, tools that allow users to sign-up to receive email alerts can help proactively reach out to users whenever new information is published in KM portals.
Based on my observations and understanding, I have discussed some of the challenges organizations face when capturing and transferring tacit knowledge above. First, it is important to codify the tacit knowledge and make the codified knowledge quickly available to the right people at the right time.
David Oragui, (2020). Tacit Knowledge: Definition, Examples, and Importance https://bit.ly/3gLbN3c
Dalkir, K. (2017). In Knowledge management in theory and Practice. essay, MIT Press.
Birkinshaw, (2001): “Why is knowledge management so difficult?” Business Strategy Review 12 (1), pp. 11 – 18
Knowledge Acquisition: Issues, Techniques, and Methodology by Yihwa Irene Liou, Merrick School of Business, University of Baltimore