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Title:Odprava znanjskih ozkih grl v poslovnih procesih z uporabo mehke logike
Authors:Zajec, Maja (Author)
Roblek, Matjaž (Mentor) More about this mentor... New window
Kofjač, Davorin (Co-mentor)
Files:.pdf MAG_Zajec_Maja_2012.pdf (3,71 MB)
 
Language:Slovenian
Work type:Master's thesis (m2)
Organization:FOV - Faculty of Organizational Sciences in Kranj
Abstract:Želja po večjem, boljšem, hitrejšem in kvalitetnejšem je v nas prisotna že od nekdaj. Da bi lahko dosegli ta cilj, moramo odgovoriti s pravimi poslovnimi in delovnimi procesi. Odločilen pomen pri oblikovanju procesovpredstavljajo tudi inovacije, ki jih generirajo osebe s pravim znanjem in talentom. Izhajali smo iz dejstva, da vsaka nova sprememba v procesih lahko spremeni strukturo znanja določenega delovnega mesta ali delovne vloge. To pomeni, da oseba, ki zaseda vlogo, lahko postane t. i. znanjsko ozko grlo v procesu. Če se oseba nahaja na časovno kritični poti procesa, potem proces ne daje izhoda v želeni obliki, obsegu ali kvaliteti, kolikor bi ga lahko, če bi znanjska ozka grla razbremenili. V ta namen smo razvili odločitveni model, ki temelji na uporabi mehke logike. S pomočjo le-tega smo pokazali, da se da osebe razporejati ne le na podlagi njihove časovne razpoložljivosti, temveč tudi na podlagi razpoložljivosti njihovega znanja. Rezultat modela je ocena znanja, ki temelji na odstopanjih med zahtevanim in dejanskim znanjem. Zahtevana znanja smo pridobili iz aktivnosti izbranega realnega procesa, dejanska znanja pa so bila ocenjena s pomočjo metode 360°. Za lažjo predstavo in posledično hitrejšega sprejemanja odločitev o razporejanju oseb na vloge glede na njihovo znanje smo uporabili tehniko toplotnega zemljevida. Na podlagi ugotovitev smo potrdili postavljeno hipotezo, da je s pomočjo mehke logike možno razviti odločitveni model, ki bo alociral znanja resursov na delovne vloge glede na zahteve procesov.
Keywords:razporejanje znanja, management znanja, poslovni procesi, poslovna inteligenca, mehka logika
Year of publishing:2012
Source:Kranj
COBISS_ID:7015955 Link is opened in a new window
NUK URN:URN:SI:UM:DK:N3PNTKPR
Views:1570
Downloads:118
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Categories:FOV
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Secondary language

Language:English
Title:Knowledge Bottleneck Elimination in Business Processes with Fuzzy Logic
Abstract:The need for bigger, better, faster, and better quality has been part of us for a very long time. To achieve this goal, we have to respond with the right business and working processes. In the process of formation, 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 to be found on a critical path then the process can’t produce the output in a desired form, extent or quality, unless we disburden this knowledge bottleneck. For that reason, we developed a decision model which is founded on fuzzy logic. This model shows that we can allocate people not only on their time availability, but also on their knowledge availability. The result of the fuzzy model is knowledge estimation based on knowledge deviation between the required and actual knowledge. The required knowledge was derived from activities in the real process. However, the actual knowledge was assessed with a 360 degree feedback. For faster decision making we made a presentation of allocated people on desired roles using the heat map technique. According to the results we confirmed the hypothesis saying that it is possible to develop a decision model for allocating resources’ knowledge on working roles using the fuzzy logic.
Keywords:knowledge allocation, knowledge management, business processes, business intelligence, fuzzy logic


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