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Grundel L.P., Biryukov V.V. Application of fuzzy modeling function to determine key performance indicators

Published in journal "Software systems and computational methods", 2016-3 in rubric "Mathematical models and computer simulation experiment", pages 268-286.

Resume: The subject of research is the development of key performance indicators of tax consultants. Object of research are the key performance indicators. It is proved that the key performance indicators of the business process tax advice is a measure to achieve the strategic objectives of the company, with which you can evaluate the activities and improve the performance of tax consultants, as well as to develop optimal approaches to the professional development of staff. It clarified that each figure should be: (1) clearly defined; (2) is achievable; (3) comparable; (4) contribute to the motivation of the personnel; (5) is the basis for the analysis.In this paper, using econometric and statistical methods, as well as using the program «Mathlab» (application «Fuzzy Logic») performance indicators tax consultants decomposed under the Balanced Scorecard and are considered by categories: (1) finance; (2) markets and customers; (3) business processes; (4) training and development.Decompose the evaluation parameter "Finance" on several input parameters (1) the level of income; (2) the level of costs; (3) the level of intangible assets (goodwill).Decompose option "Markets and customers" on the following inputs: (1) the level of customer savings (the base value for the customer); (2) the level of image and reputation; (3) quality of service (compliance with the law, the level of efficiency); (4) to attract customers; (5) retention of customers.Decompose option "Business Processes" on the following inputs: (1) maintain the level of competence (knowledge of the legislation, industry knowledge, experience); (2) the level of maintenance of lobbying the interests of taxpayers; (3) the level of effectiveness of the internal quality control; (4) the level of understanding of customer needs, the effectiveness of communication with customers; (5) The effectiveness of the internal exchange of information; (6) the level of compliance with the requirements of the services market; (7) the level of costs.Decompose option "Training and education" on the following input parameters: (1) the level of provision of search and recruitment of professional staff; (2) the professional qualifications of staff; (3) quality control and knowledge management; (4) the level of compliance with corporate and personal goals.The evaluation of the linguistic variables for the index of "Finance". To solve the problem of fuzzy set of input rules. The question of the application of fuzzy modeling functions in the selection of key performance indicators.

Keywords: fuzzification of input variables, fuzzy inference rules, thermae, estimation parameters, function fuzzy modeling, Key Performance Indicators, accumulation, defuzzification, fuzzification, aggregation of data

DOI: 10.7256/2305-6061.2016.3.19471

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Bibliography:
www.toastmasters.org
www.hr-portal.ru
Kaplan Mobray “The 10Ks of Personal Branding”, New York, 2009.
www.e-xecutive.ru
Rampersad. K.Kh'yubert. Universal'naya sistema pokazateley deyatel'nosti. Kak dostich' rezul'tatov i sokhranit' tselostnost': Per. s ang. 2-e izd. M.: Al'p Bizn.Buks., 2005. 352 s.
Klochkov A.K «KPI i motivatsiya personala: polnyy sbornik prakticheskikh instrumentov». M.: Eksmo, 2011. 16 s. – (HR-biblioteka).
Parmanter D. «Klyuchevye pokazateli effektivnosti. Razrabotka, vnedrenie i primenenie reshayushchikh pokazateley. M.: ZAO «Olimp-biznes», 2009. S. 43.
Kaplan Robert S., Norton Deyvid P. Sbalansirovannaya sistema pokazateley. Ot strategii k deystviyu. 2-e izd., ispr. i dop.: Per. s angl. M.: ZAO «Olimp-Biznes», 2010. 320 s.
Karandashev A.N. Sbalansirovannoe upravlenie predpriyatiem. M.: KNORUS, 2009. S. 224.
Leonenkov A.V. Nechetkoe modelirovanie v srede Mathlab i Fuzzytech. SPb.: BVKh-Peterburg, 2005. 73 6s.
Bashkirova N.N., Sugrobova E.B. Osnovy nalogovogo konsul'tirovaniya. M., 2008. 175 s.
Vylkova E.S, Romanovskiy M.V. Nalogovoe planirovanie. izd. Piter, 2009. S. 76.

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