Abstract
Knowledge is recognized as an organizational resource for business value creation. The work with knowledge—knowledge work—is thus an important part of value-adding processes in organizations. The ability of knowledge workers to analyze complex phenomena, interpret them and develop meaningful actions is one central part of knowledge work. The advancements of digital aids and especially the ability to analyze big amounts of data is a new phenomenon that is increasingly seen in organizations. In this work, we assume that there needs to be an interplay between digital aids and knowledge workers to allow new, deep insights into phenomena and support business value creation. We develop a model that describes how this interplay could look like and critically discuss it using real-world cases. From that, we find that it is crucial (1) separating data-driven and expert-based analysis in knowledge discovery, (2) clearly describing the problem that should be solved by the analysis, (3) understand the particular domain that analysis is applied to, (4) complement data-driven with expert-based analysis and (5) understand the entanglement of analysis and action implementation.
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Notes
- 1.
The manifestations of External/Internal Process Regime, Knowledge Culture and Level of Formalization can be low (no or ad hoc setup of actions), medium (structured setup of action that is not consistently implemented across the organization) and high (structured setup of action that is consistent across the organization). The manifestation of the Extent of involved parties can be low (ad hoc organized, small group of people), medium (group of people that is organized with the help of communication standards only shared by the group) or high (large group of people, relying on formal communication standards that are implemented organization wide).
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Kohlegger, M., Ploder, C. (2018). Data Driven Knowledge Discovery for Continuous Process Improvement. In: North, K., Maier, R., Haas, O. (eds) Knowledge Management in Digital Change. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-319-73546-7_4
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DOI: https://doi.org/10.1007/978-3-319-73546-7_4
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