Research On Sales Forecast And Inventory Optimization Of Retail Pharmaceutical Enterprises

Product sales forecasting has always been an important issue for the retail industry.Accurately predicting the sales of single products can improve the stocking efficiency of stores,thereby reducing product losses,reducing inventory occupation,and better meeting market demand.The problem of drug inventory is an important part of the operation and management of retail chain drug stores.Solving the problem of inventory optimization can save corporate costs and reduce inventory waste.To ensure the normal use of medicines by residents around the chain pharmacy,reduce the consumption and waste of resources.According to the establishment of the model and the implementation of the algorithm to rationally optimize the inventory of the pharmaceutical chain enterprises,it has a positive significance for the development of the medical cause.This article mainly studies the problem of drug inventory optimization.The real sales data and inventory data of T pharmaceutical chain companies are taken as the research objects.Combined with the local temperature factors,a pharmaceutical sales forecast model is constructed to achieve the purpose of dynamically adjusting the company's inventory.The main research work of this paper is as follows:(1)Divide the importance of drugs based on their cumulative sales during the study period.The ABC classification of drugs is performed according to the traditional drug classification method combined with the analytic hierarchy process.According to the classification results,the drugs classified as Class A will be the subject of sales forecast analysis.(2)According to the characteristics of sales data,for drugs of a high degree of importance,extract drugs that do not contain special labels(ephedrine label,zero mark),and use the FP-growth algorithm to analyze the correlation between drugs in the research period.Relationships,mining frequent itemsets of medicines,and predicting drug sales in frequent itemsets,and optimize sales mix and enterprise inventory based on prediction results.(3)Based on time series analysis of drug attributes and temperature factors,study the impact of historical sales and temperature changes on future drug sales.Combine random forest algorithms to integrate local temperature factors to predict sales of Class A drugs.According to error analysis,non-similar Drugs will have different prediction accuracy rates.A more suitable prediction model can be selected according to the comparison of the correct rate,and the stock alert line and the upper and lower limits of the stock can be set according to the predicted results.(4)Analyze the causes of inventory waste.Based on the company's inventory data and the forecast value of drug sales in a certain period,continue to compare the remaining inventory with the inventory warning line,and calculate the drug safety stock based on the forecast results,and perform periodicity.Dynamic optimization of drug inventory.Finally,an inventory management index system is established to help enterprises more comprehensively monitor and adjust their inventory to achieve the purpose of optimizing their inventory.The experimental results prove that the model in this paper has good prediction effect and scalability,and can also be applied to the commodity forecast of other retail enterprises.The inventory control model obtained based on the prediction results can well realize the dynamic regulation and optimization of inventory.