DEVELOPMENT OF INVENTORY MANAGEMENT PROCESS FOR RETAIL STORE

Abstract

This research aims to find a way to forecast the sales of appropriate products of retail stores. Reduce the cost of ordering more than necessary products by using the theory of product classification according to the product sales cycle (ABC Analysis), which can divide the product into 3 categories, which
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JEET 20xx; x(x)

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are fast moving products, which can be sold within 3 days, there are 30 types. Slow-moving products are products that are sold within 4-7 days, there are 25 types. And the product does not have a turnover (Non Moving) is a product that has no sales within 7 days. Using the methodology of forecasting under 3 methods as following: Naïve Forecasting method, Moving Average and Regression Analysis by comparing Mean Absolute Percentage Error (MAPE). Considering the product group A that has an over-ordering product cost and the cost of losing the opportunity to sell from the original purchase behavior of 138,032.10 baht per month. Forecasting with the automatic forecasting program, the cost of buying excess products and losing the opportunity to sell to 11,093.10 baht per month. Representing a reduced cost of 126,939.00 baht per month, a decrease of 91.96 percent and a forecasting regression analysis method with the most actual sales, accounting for 53.85%