Research On Demand Forecast And Inventory Management Of Garment Products Of P Company

Nowadays,consumer demand for clothing has spurted up,and sportswear has grown first.At the same time,there has been a large fluctuation in demand.At the same time,many companies in the clothing industry are responding to market demand for safety stock Dominated by fluctuations,problems such as the continuous increase in inventory of apparel companies caused by inaccurate demand forecasts have also become more serious.Company P,as a large-scale multinational company with a world-renowned sports brand,has a high rate of slow-moving sportswear products and a long-standing inventory,which has caused more serious problems in inventory management.The backlog of inventory has not only restricted the company.The cash flow has led to an increase in the cost of additional inventory,and the annual loss in this area is countless.Therefore,company P's problems in product demand forecasting and inventory management need to be solved urgently.This article starts with the demand forecast of company P's new and old products,based on the sales data of old sportswear,and uses this as a bridge to find a new product demand forecast method through similar relationships,and then makes more accurate demand analysis and forecast.On the other hand,from the perspective of inventory cost,this article analyzes the purchase and ordering methods of products objectively and effectively,and provides more economical and reasonable ordering decisions,thereby improving inventory under control then making inventory management more efficient.This article first introduces company P and its organizational structure,analyzes the current status of company P's procurement,production,sales,and warehousing links,and then analyzes many problems existing in company P's supply chain management and inventory management.At the root of the problem,the root cause of poor supply chain inventory management has been found to be two points: first,the unpredictable valuation when forecasting product demand;second,inventory management needs to be optimized in the entire supply chain.Therefore,to cope with the problem of inaccurate demand forecasting,this article divides P's sportswear products into similar new and old products.It focuses on the research and analysis of new products that are more difficult in demand forecasting,and proposes a method for forecasting demand for new products.: Using similarity principle,fuzzy clustering principle,similarity measurement and other methods to determine similarity weights,and combining market evaluation surveys and questionnaire survey methods to determine epidemic sensitivity factors,and then use expert scoring and fuzzy comprehensive evaluation methods to quantify epidemic sensitivity Factor;comprehensive popular sensitivity factor and seasonal factor improved the classic model of Bass prediction,skillfully transferred the characteristic points of the old product to the new product through the similarity principle,and finally accurately predicted the demand for the new product;for P Insufficient inventory management of the company,this article analyzes from the perspective of inventory cost management,takes such products with stable demand as research objects,proposes an economic order batch model,and uses the classic EOQ model to allow the improvement of shortages.EOQ model,improved EOQ model that allows price discounts as well as the comprehensive improvement of the EOQ model,targeted for P's inventory management is optimized by optimizing the results of the model given in order to save inventory costs provide a strong basis for the final optimization of the P supply chain inventory management.The research results of this paper have certain reference value for the supply chain inventory management of company P.The first chapter of this article is an overall introduction;the second chapter of this article is a review of relevant theories and literatures;the third chapter analyzes the current situation of supply chain management and inventory management of P company's sports brand products;the fourth chapter builds the Bass model of P company's sportswear products Optimize demand forecasting;Chapter 5 builds an economic order batch model to optimize inventory;Chapter 6 is a summary and outlook.