РОЗРОБЛЕННЯ МОДЕЛЕЙ ПРОГНОЗУВАННЯ ОБСЯГУ РЕАЛІЗАЦІЇ ПРОДУКЦІЇ СІЛЬСЬКОГОСПОДАРСЬКОГО ПІДПРИЄМСТВА

Abstract

The financial and economic activities of economic entities in modern terms require constant plans comparison with real developments. Taking into account the peculiarities of the economic situation in the country, comparing the supply and demand, analysis of financial results, etc. The development of market relations increases the responsibility and independence of enterprises in making decisions about strategy and tactics for the future. That is why, while taking substantiating management decisions the application of techniques and methods of economic and mathematical modeling is relevant. One of the types of communication between the producer and the consumer is sales volume. It directly affects the amount of costs, profits and profitability of the enterprise. Therefore, the analysis and forecasting of such an indicator is important to increase the competitiveness of economic entities. Statistical data of one of the agricultural enterprises of Poltava region are analyzed, several influential factors are highlighted. It is proposed to perform a regression analysis, develop a linear multifactor model and build an adaptive model for forecasting the volume of sales of agricultural enterprises to select the optimal model for forecasting the studied indicator for the future. The author performed calculations on the obtained models. The analysis of the obtained results confirmed model’s adequacy, so they can be used for forecasting. As a result of comparison forecasts of sales volumes at the enterprise the adaptive model is recommended for practical application as it has the best quality of the forecast and the minimum sum of deviations squares. This model giving more weight to the latest statistics provides an optimistic forecast for the future. Thus, developing economic and mathematical forecasting models will provide an opportunity to improve the operational planning of production the certain types of products, as well as allow (after receiving new statistics) to quickly change the production monthly plans. Thus, conditions will be created to improve the quality of management, increase competitiveness and ensure the stabilization of the financial state at agricultural enterprises.