Methods of Correlation Analysis in Procurement and Supplier Management

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MAGAZINE  №2 (97) April 2020

AUTHORS ELYASHEVICH I.P.

CATEGORY  Optimization and mathematical modelling Inventory management

 

ABSTRACT

When managing procurements and suppliers, one often has to deal with heterogeneous information from various sources that is not always amenable to formalization, since it can be defined by qualitative characteristics. Under the sanction pressure on the Russian economy, changes in the market trends for the sale of many goods and services are revolutionary in nature, making it difficult to objectively use mathematical statistics and probability theory for business planning purposes. The increase in the share of sales of innovative products with a short life cycle also limits the use of science-based forecast approaches to the need for supplies. Therefore, issues of improving and standardizing methods of processing and analyzing information reflecting the results of companies’ activities in various business sectors are quite relevant.

The article discusses the specifics of constructing non-linear dependencies of stock consumption on various environmental factors that can be used in calculating insurance stocks. In addition, the article substantiates the possibility of using mutually and autocorrelation functions when planning the need for supplies, as well as methods of multiple correlation and regression analysis. For the procedures for selecting counterparties in procurement, issues of using rank correlation methods are considered. The conclusions made in the article, methodologically, are based on a systematic approach to the analysis of the relationship between the companies’ performance and the influence of macro and microeconomic factors. When processing statistical information, econometric methods and models were used as ways to study quantitative and qualitative economic relationships. The results of the calculations carried out in the article show the effectiveness of the proposed stochastic methods that can be actively used in analyzing consumption trends and planning stocks of raw materials, materials, finished products, operational resources in production, trading and logistics companies.

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ISSN 2587-6775

Published since 2004

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