Development of a methodology for reducing uncertainty in conditions when making management decisions

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DOI: https://doi.org/10.32782/2307-9770.2023.11.04.03

Paper Language: ENG

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Abstract

The article is dedicated to the development of a methodology for reducing uncertainty when approving the management decisions under unexpected situations and risks. The importance of improving the management decision-making process for modern organizations and systems is emphasized. Various types of uncertainties, such as quantitative, informational, cost-related, professional, and others, are identified, highlighting the need for diverse methods to identify and reduce them. Cases of incomplete situational clarity requiring the development of effective solutions are discussed. Probabilistic assessments are introduced to reduce uncertainty, especially in risky conditions. Defining conditions of uncertainty allows for increased operational efficiency and reduced costs in choosing target checks. Despite the available risk analysis information, the article points out that many decisions are still made intuitively. The main focus is on a developed methodology that utilizes information technology to assess the level of uncertainty in different situations. This methodology contributes to enhancing the efficiency of the management decision-making through mathematical models and uncertainty reduction methods. Additionally, it organizes and systematizes the student learning process. To reduce uncertainty, it is proposed to select distribution laws of external environment states that best match the sample data and to calculate necessary probabilities, for which students are encouraged to use the STATISTICA software package (TIBCO Statistica™ Evaluation trial version). After determining the probabilities of external environment states, solving the problem under uncertainty conditions becomes a problem under risk conditions, for which the decision acceptance criteria can be applied. The article concludes with a description of the developed methodology for teaching computer science student’s management decision-making under uncertainty. The methodology utilizes information technology to assess the level of uncertainty and teaches learners to reduce the uncertainty of the external environment conditions for effective management decision-making. As a result of using this methodology, learners will acquire the ability to apply fundamental principles of management decision-making, in particular, reducing uncertainty in the external environment conditions.

Keywords

training, methods, STATISTICA, decision-making

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