A Process-Based Dead Stock Management Framework for Retail Chain Store Systems

Abstract

All supply chain levels experience the dead stock problem. However, the impact is felt more in the retail level due to the volume and diversity of products handled especially when chain stores are involved. Causes of dead stock accumulation in the retail level of the supply chain include inventory policies, forecast inaccuracy, sudden change in demand, product expiration, product damages, etc. Literature is divided into strategy-based and management-based approaches in handling the dead stock problem. Strategy-based approaches build upon a single strategy to provide better solutions while management-based approaches identify root causes and provide solutions for a specific problem situation. Proactive and reactive strategies were proposed in literature to either prevent the accumulation of dead stocks or manage dead stock accumulation as it happens. This paper examines the causes of dead stocks and the different dead stock management strategies developed through the years to conceptualize a framework for a solution process that can effectively control the accumulation of dead stocks in retail chain store systems. The result is an end-to-end process-based dead stock management framework that starts from problem recognition and ends with selection of strategies in reducing the dead stocks of retail chain stores. The proposed framework minimizes dead stock costs of the retail chain store system through timely recognition of dead stocks and an optimal balance among dead stock warehouse costs, strategy-related costs, and stockout costs across all retain chain stores.