USING PREDICTIVE ANALYTICS FOR MANAGING SUPPLY AND DEMAND IN SMALL AND MEDIUM-SIZED ENTERPRISES

Mikhail Stepanov

Abstract


The article discusses the use of predictive analytics to manage supply and demand in small and medium-sized enterprises. The methods of machine learning, time series analysis and regression modeling are being investigated, which make it possible to predict changes in market demand, optimize the supply chain and increase the efficiency of production processes. Modern tools such as programming languages and machine learning libraries, data visualization tools and cloud services that provide computing power for processing large amounts of data are analyzed. Special attention is paid to the advantages of these methods, such as reducing operating costs, automating management decisions, and improving forecast accuracy. Obstacles to their implementation are being explored, such as limited resources, difficulties integrating predictive models into business processes, and data security issues.

 

JEL: C45, C53, L25, L86

 

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Keywords


predictive analytics, demand forecasting, machine learning, small and medium-sized enterprises

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References


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DOI: http://dx.doi.org/10.46827/ejefr.v9i3.2006

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