Comparative Assessment of Planned and Actual Production Indicators Based on the Measure of Information Uncertainty

The possibilities of applying information theory at comparison of planned and actual distributions of identical indicators are considered. A brief justification of the application of the most promising methods from information theory in relation to the development of the methodology of entropy-synergetic content analysis is presented. The mathematical apparatus proposed in the present work is based on the use of models cross-entropy and Kullback–Leibler divergence, which is based on the model of determination of entropy as a measure of information uncertainty. This mathematical apparatus allows to determine the connection between two different probability distributions, that is, to calculate the distance between the distributions and to identify the degree of difference between the actual and planned indicators. To obtain the final result, it is necessary to have a planned and actual distribution of indicators, the value of which allows to determine the probabilities of two distributions of discrete quantities. The obtained result of the divergence of these distributions allows to judge the quality of the preparation of the plan and the need to adjust them in order to reduce the level of information uncertainty. Comparative assessment of planned and actual indicators is a tool for analyzing the quality of estimates of future events included in financial accounting or integrated reporting.