Demand Segmentation and Inventory Optimization

 

One of the biggest sources of variability in the supply chain is demand, and demand can be highly unpredictable. Despite the fact that there are many widely varyingdemand patterns, most inventory optimization tools assume that alldemand is “normal”, leading to either too much inventory or stock-outs and lostsales. Multi-echelon inventory optimization determines how much inventory must be kept at each level and location in the supply chain to deliver the desired service level at the lowestcost. This analysis includes the inherent supply chain variability on both the demand side and the supply side to identify the lowest total cost inventory stocking solution that meets the

service requirements for each product/site combination.

 

Case Example: Demand Segmentation

An automotive manufacturer has over 20 regional DCs to supply service parts to their dealer and repair part network of over 2,000 locations. The number of parts supplied throughout this network was over 120,000, with widely varying demand behaviors. The company used demand segmentation technology to analyze and automatically classify the demand patterns into 10 unique categories such as smooth, erratic, lumpy, unit-sized, etc. They then applied

the proper inventory policies to recommend the appropriate stocking levels required to achieve their service level targets. The result was a total on-hand inventory reduction of nearly 20 percent, and better-fitting policies for the items with irregular demand.

 

Case Example: Inventory Optimization

A grocery store chain has seven regional distribution centers that stock product for, anddeliver to, over 500 stores throughout the country. The top 2,500 SKUs are stocked at all DCs. These represent more than 70 percent of the overall sales volume. The company established seven service-level categories between 85 percent and 99 percent, based on product characteristics. Multi-echelon inventory optimization analyzed the demand andlead-time variability for each product/site combination and recommended a $5M reduction in overall inventory, even though numerous locations required a higher level of inventory. In specific cases, inventory for a product was increased in three or four sites and decreased in others. The result was the “right-size” inventory for the organization. Savings are achieved by actualizing  the lowest total landed-costs and not incurring excessive supply chain costs due

to buying improper quantities.

 


Case Study