Eliminating Knowledge Bottlenecks Using Fuzzy Logic

Zajec Maja (), Kofjač Davorin () and Roblek Matjaž ()
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Zajec Maja: University of Maribor, Faculty of Organizational Sciences, Kidričeva cesta 55a, 4000 Kranj, Slovenia
Kofjač Davorin: University of Maribor, Faculty of Organizational Sciences, Kidričeva cesta 55a, 4000 Kranj, Slovenia
Roblek Matjaž: University of Maribor, Faculty of Organizational Sciences, Kidričeva cesta 55a, 4000 Kranj, Slovenia

Organizacija, 2013, vol. 46, issue 5, 206-213

Abstract: In the formation of new processes, innovations generated by people possessing the right knowledge and talent play a crucial role. Our starting point was the fact that every new change in processes can alter the knowledge structure of a work position or work role. This means that a person can become a knowledge bottleneck in the process. If this person is found on a critical path, the process cannot produce the output in a desired form, extent or quality, unless the bottleneck is removed. For this reason, we developed a decision model founded on fuzzy logic. The result of the fuzzy model is knowledge estimation based on deviation between the required and actual knowledge. For faster decision making, we made a presentation of allocated people on desired roles using the heat map technique. Therefore, the employers make better decisions on actual knowledge allocation, acquiring missing knowledge, or defining knowledge required for the future, which makes them more competitive.

Keywords: knowledge allocation; knowledge management; business processes; business intelligence; fuzzy logic (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:organi:v:46:y:2013:i:5:p:206-213:n:2

DOI: 10.2478/orga-2013-0018

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