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A predictive model to determine the causes of safety stock requirements: An analytical approach to reduce working capital

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  • Rahman, Fazlur

Abstract

Safety stock is an important component of a company’s total inventory. Safety stocks, cycle stocks and seasonal builds drive the overall inventory position of the business, which has a direct impact on its cash flow and financial statements. For any company, it is important to service customers at the right level without getting stock-outs and, at the same time, carry optimal levels of inventory. It is often hard to find the right balance between inventory cost, customer service level and operational efficiency, as these three integral components of the supply chain go hand-in-hand and are prioritised over each other based upon the needs of the business. To achieve the optimum balance of service and cost, there is a need for a predictive working model which determines the causes of safety stock requirements for the current state of any business. This paper discusses a predictive model which can be used for any time horizon and enables an organisation to focus on the right variables to reduce safety stock requirements, thereby reducing inventory levels while meeting customer service level targets.

Suggested Citation

  • Rahman, Fazlur, 2018. "A predictive model to determine the causes of safety stock requirements: An analytical approach to reduce working capital," Journal of Supply Chain Management, Logistics and Procurement, Henry Stewart Publications, vol. 1(2), pages 114-124, September.
  • Handle: RePEc:aza:jscm00:y:2018:v:1:i:2:p:114-124
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    More about this item

    Keywords

    safety stock; service level; working capital; predictive analytics; regression analysis;
    All these keywords.

    JEL classification:

    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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