83. "Evolving From Data Expertise to Expert Data"

SUMMARY

Data expertise is the expert gathering, processing, and analyzing of data. Expert data is data expertise for use by experts in application. The management research community, in our opinion, needs to evolve from data expertise to expert data if it hopes to match the expertise of our research to the expertise needed when applied by an expert.

Expert managers are thoroughly involved in the specific context and situation of their organizations, have experience and a purpose or goal guiding their behavior. They are not just logical but also intuitive. The usual research paper attempts to produce context and situation free knowledge which is to be applied in a logical, detached manner, irregardless of the users' purposes. Thus, there is a mismatch between the expertise of the management research and the requirements for expertise in application. We need to evolve from data expertise to expert data in order to improve the match.

The article bases its description of expertise on the work by the Dreyfus brothers (1988). Chunks of knowledge provided by data expertise might only rise the level of competence for the expert manager. The article describes how expert data involves multiple streams of data and multiple stages. It describes the application of the expert data process as the manager moves from problem finding to problem formulation to implementation and an audit and review. This process is often interrupted and changed while it is in progress due to events occurring inside or outside the organization.

This article is a continuation of the previous concluding chapters in Current Topics in Management (Vol. 3 and Vol. 4) and picks up on some of the themes introduced in these previous volumes.