The Transitional Data Presumption、 Expected Daily Maximizing Profit and Inventory Optimization of the First Associated Product of One Product with Surging Sales in the FMCG Enterprise

Gang Bao () and Vitliemov Pavel ()
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Gang Bao: University of Ruse “Angel Kanchev”, Bulgaria
Vitliemov Pavel: University of Ruse “Angel Kanchev”, Bulgaria

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 1816-1828

Abstract: The consumer market is fickle. The increase in surging sales of a certain product will be often sudden and has time-effectiveness due to some reason. Meanwhile, there are incomplete sales data or vague information in the early stage of product sales surge. Although the sales volume of products associated with product with surging sales is also sudden and time effective, it is predictable and diverse. Enterprises are faced with many challenges if they want to seize the market sales opportunities of such related products and get the maximum expected profit and inventory optimization management. Here, our research in this area becomes important. This paper presents a new method to simulate the transition and replacement process from presumptive data to real data, especially the balance between profit decision and inventory optimization. Emphasize the importance of associated product screening, maximizing expected profits and inventory optimization. Basic steps and modules include: firstly, grey relational analysis has the feature of finding the relational degree between variables in the complex system with incomplete data and fuzzy information, and using this feature to find the first associated product and relational degree of the product with surging sales before the sales did not surge. The second step: the limited sales data of the product with surging sales is multiplied by the relational degree to obtain the presumptive sales data of the first related product after sales surge; The third step: based on the presumptive sales data of the first associated product after the sales surge calculated in the second step, the newsboy model is used to calculate the optimal daily order quantity. Finally, because this kind of sales phenomenon is sudden and time effective, the grey forecasting model is used to optimize inventory management, so as to avoid the cost waste caused by inventory overstocking. The modules will be connected in series using MATLAB software series instructions. Theoretical analysis and software programming simulation are carried out to determine the effectiveness and feasibility of the scheme. The advantage of this system can help enterprises quickly find associated target products, seize sales opportunities, maximize expected profits and optimize inventory management when the early data is incomplete or fuzzy.

Keywords: Grey relational analysis; Division function; Newsboy model; Grey model; The first associated product; Maximum expected profit; Inventory optimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:1816-1828:n:1015

DOI: 10.2478/picbe-2025-0141

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