Development of the subsystem of forecasting for the system of marketing information management at an industrial enterprise
DOI:
https://doi.org/10.15587/1729-4061.2017.111547Keywords:
marketing information, marketing information management system, types of forecasts, forecasting methodsAbstract
The theoretical generalization, which is revealed in the development of conceptual and methodological principles and methodical provisions related to formation and functioning of the forecasting subsystem of the marketing information management system at an industrial enterprise, is presented.
The market is a social phenomenon in which the availability of valuable marketing information reduces uncertainty, ensures the promptness of making managerial decisions, makes possible to avoid threats and creates a basis for increase in the efficiency of a production process and competitiveness. Therefore, the control of changes in the marketing environment requires the creation of a marketing information management system at an industrial enterprise, which is based on effective methods of collection and analysis of marketing information. Markets of industrial enterprises make possible to create and test progressive marketing information management systems.
There are trends that cause worsening of prospects for economic growth at the current state of the marketing environment of industrial enterprises. Growth of these risks is facilitated by trends of globalization, informatization, social changes. Such an increase in business risks causes an increase of the role of forecasting. The classical concept of a marketing information management is enhanced and system is restructured and the creation of a subsystem of forecasting is improved. The methodological approach to the functioning of forecasting subsystems of marketing information systems of industrial enterprises based on the model of statistical forecasting of sales volume is offered.
The proposed procedure to overcome a general lack of forecasting methods is related to the failure to take into account an inaccuracy of observations on which the forecast is based, – it is based on the use of fuzzy mathematical methods. It is shown on its basis how traditional forecasting methods can be successfully upgraded for the case when the initial data are given unclearlyReferences
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