The Bottleneck of Organizational Knowledge Transfer

Photo by Damir Spanic on Unsplash

How can we ensure that knowledge is efficiently shared and transferred between the members of an organization?

Research-intensive organizations may struggle to get an actionable
overview of their research activities. The skills set that a member of an organization possesses is not apparent. Essentially, the skills of an employee are only assessed in the initial job interview, and they are only periodically re-evaluated in annually meetings with the line manager. But how do other members of an organization get to know the skill set of another employee?

In research organizations, one way of getting to know a person is by talking to them, and looking at their research output: publications in journals, conferences, and in social media. Another method is to talk to other employees about a person’s skills.

These two methods face several challenges:

1. A person’s output may not represent the full skill set of the person.
2. Some knowledge of a person is intangible.
3. Discovering a person’s skill set up front is a difficult task.

In a paper published in the conference for Crowdsourcing and Human Computation (HCOMP) in 2018, we reported on a preliminary architecture of a socio-technical system that aims to uncover potential areas for transfer of knowledge between an organization’s employees. The aim of this architecture is to facilitate knowledge transfer in research-intensive organizations.

Two important roles may be part of this human-powered system:

1. The Community Manager works together with the researchers in the organization. The goal of the community manager is to elicit an initial set of project information from the researchers. This information is entered it into a semantic wiki which stores information in structured form. Via Linked Data, associations (potentials for knowledge transfer) are made between the data in this knowledge base.
2. The Knowledge Transfer Manager (KTM) acts as a curator for the identified potentials for knowledge transfer. Both the Community Manager and the KTM engage the researchers to contribute to the socio-technical system.

More information, and the description of this proposed architecture in the context of a museum for Natural History, can be found in the Works-In-Progress contribution to HCOMP 2017: https://www.humancomputation.com/2017/papers/91-hcomp-paper-final.pdf
and the short paper published at the MKWI 2018:
http://mkwi2018.leuphana.de/wp-content/uploads/MKWI_140.pdf