FORECASTING DEMAND IMPROVEMENT FOR REPLENISHMENT IN A RETAIL PAINTING COMPANY

Abstract

This case study was developed in a retail painting company; the main objective is to reach a higher cash flow for assuring the fulfilment of the demand with a 95% service level. Currently, supply chain faces to multiples competitors so familiar business have to improve the logistics processes for remaining in local, national and international markets. Through the ABC-classification, the product portfolio was classified for choosing the products with more significative impact. Forecasts techniques may obtain data with higher accuracy in the order preparation. For this research, a seasonal model is functional, since the demand tends to have a similar behaviour year by year and month by month. Seasonal demand model was used to find specific products that might not fit for ordering minimum quantities which might exceed the forecasted demand. On the other hand, classic EOQ model considers the value of the inventory and demand forecast, which demonstrates that the performance of the supply chain could improve considerably. Therefore, an accurate estimate can reduce inventory costs in each of the periods, satisfying customer demand, by at least 14%. EOQ model should apply to all products for reducing the investment in slow-moving stock and improving the inventory for those highly demanded products which can generate flexibility to embrace market complexity and meet customer expectations. As a future study, the company can develop a strategy to reduce non-rotating inventory with more accurately, what and when they will sell specific products.

Keywords

• forecast
• mape
• service level
• economic order quantity
• inventory management