The Search for Modern Methods for the Statistical Quality Control of Services

Kbiladze David () and Metreveli Shorena
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Kbiladze David: David Agmashenebeli University of Georgia, Guram Tavartkiladze Teaching University,Tbilisi, Georgia
Metreveli Shorena: Georgian Technical University, Georgian National University,Tbilisi, Georgia

Ekonomika (Economics), 2017, vol. 96, issue 2, 102-109

Abstract: The countries with developed market economies have vast experience in using the statistical methods in running business. In this respect, the use of Six Sigma techniques and tools to control the output (service) quality is worthwhile. This technique, if introduced in Georgia, can be much beneficial for the businessmen. Different-profile companies use different statistical methods for the output (service) quality control. However, it is the Six Sigma techniques that yield the most pragmatic outputs. This tool enables the different-tier managers to rely not only on their intuition in making managerial decisions but also on the quantitative data obtained through the introduction of 6σ to their companies. The measures to search for the modern methods of introduction and better use of the 6σ concept seek to improve the output (production) quality of different sites of a corporation, while also meeting the changing demands of customer markets and shareholders. In the search of such measures, the authors of the present article attempted to examine the effect of the 6σ set beyond the limits of a corporation and, by considering the public opinion about the corporation, conduct the statistical control of the output (service) offered by the corporation to its clients. The pilot study, accomplished with this purpose by the authors of the article, together with their students, gave quite interesting results.

Keywords: output (service) quality control; 6σ (Six Sigma); sampling observation; managerial decision (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ekonom:v:96:y:2017:i:2:p:102-109:n:7

DOI: 10.15388/ekon.2017.2.11003

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