Inventory Optimization at Proctor & Gamble

Inventory Management in a company of P&G’s size, scale and complexity requires leveraging the right people, organization and tools. By marrying the appropriate operations research (OR) techniques with a unique planning-organization structure, P&G has achieved two step-change improvements in inventory levels. The first improvement came from the broad application of spreadsheet-based inventory models; this work produced four tools that locally optimize different portions of the supply chain. The second improvement integrated multi-echelon inventory software in P&G’s more-complex supply chains. In 2009, these tools, implemented through a well-coordinated planning community, were instrumental in driving $1.5 billion in cash savings, while maintaining or increasing service levels. This work produced 4 tools that locally optimize different portions of the supply chain.

The first step of inventory optimization led to the development of the following 4 spread-sheet based tools:

  • FIM: Finished goods Inventory Model for the optimization of the finished goods inventory held at P&G plant locations

  • XIM: Extended Inventory Model for the optimization of inventory held at distribution centers with several remote stocking locations

  • RIM: Retail Inventory Models developed for retail level inventory optimization by incorporating customer variations

  • MIM: Materials Inventory Model meant for optimizing raw material inventory at plant locations

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These Single-Stage Inventory models provide benefits to the business as statistical inventory models avoid supply chain planner bias towards excessively high levels of stock. Safety stock at too low a level would quickly result in customer service incidents and the planner would choose higher safety stock targets. However, when a planner manually sets a high safety stock target, no automatic correction mechanism is available to adjust the safety stock levels downward.

 

 

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