ESTONIAN ACADEMY
PUBLISHERS
eesti teaduste
akadeemia kirjastus
PUBLISHED
SINCE 1952
 
Proceeding cover
proceedings
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2020): 1.045

Optimization of enterprise analysis model for KPI selection; pp. 371–375

Full article in PDF format | https://doi.org/10.3176/proc.2019.4.04

Authors
Sergei Kaganski, Martin Eerme, Ernst Tungel

Abstract

Nowadays, a number of methods and principles are available in literature for KPIs (key performance indicators) selection. However, they are facing with the same issue – lack of optimal procedures for selection of suitable metrics for particular company. The purpose of the study is to optimize enterprise analysis model (EAM) for KPIs selection and to reduce the time and resources necessary for the analysis of the enterprise. In the current study four outlier’s detection methods for eliminating “outliers” in the answers are utilized. Furthermore, the experts from production and academic institutions are participating in evaluation and analysis of questionnaires. The optimized EAM is going to help simplifying the choice of KPIs, reducing the amount of data and optimizing the data flow. The optimized set of questions in EAM and KPIs that could be used in companies for improving their productivity are determined. The research is focused on SMEs (small and medium enterprises) and intention is to increase their competence on the market. The general procedure for KPIs selection/optimization for SME is pointed out.


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