About a New Approach to Solving the Problem of Assessing the Level of Maturity of an Organization

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About a New Approach to Solving the Problem of Assessing the Level of Maturity of an Organization

L.V. Borisovadoctor of technical sciences, professor, head of the department «Management and business technologies» of Don state technical university, corresponding member of Academy of quality problems; Rostov-on-Don
I.N. Nurutdinovacandidate of physics and mathematics, associate professor of the department «Applied mathematics» of Don state technical university; Rostov-on-Don
e-mail: nurut.inna@yandex.ru
L.A. Dimitrovasenior lecturer at the department «Quality management» of Don state technical university; Rostov-on-Don
The methodology of self-assessment in determining the level of maturity of the organization is considered. The problem of assessing the level of maturity of an organization should be considered as a problem of decision-making under conditions of uncertainty, which is characterized by the fuzziness of relations between groups of factors of semantic spaces of the subject area. In addition, this task is characterized by the use of expert judgments with varying degrees of uncertainty. In this regard, it is proposed to use the logical-linguistic approach and the mathematical apparatus of fuzzy logic to find the specified estimate. Models of the studied semantic spaces are constructed. A base of expert knowledge has been created, quantitative estimates of the consistency of expert information have been obtained. On the basis of a system of production rules, an algorithm for fuzzy inference of decisions in the problem of assessing the level of maturity of an organization has been developed. The proposed formal logic diagram of the decision-making process is applied to solving many problems related to the assessment problem. The research carried out serves as the basis for the development of intelligent systems for information support when making decisions on the functioning of the QMS.
Keywords: self-assessment, maturity level of the organization, expert knowledge, fuzzy sets, linguistic variable, fuzzy inference, fuzzification, composition, defuzzification, intelligent systems.
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DOI: 10.34214/2312-5209-2020-28-4-47-54

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