Inventory Management Analytics for Catalog Companies

Catalog companies need to maximize their inventory management while maintaining the complicated balance between having enough inventory to ensure customer satisfaction and yet running lean enough to effectively minimize corporate risk. One approach to achieving this balance is to create an expert system that leverages the knowledge base of senior inventory managers and distributes that knowledge to the entire staff.

Such a system naturally lends itself to alert-based analysis where inventory levels outside the realm of acceptable deviation are flagged for remediation. Given that each inventory manager at a catalog company is assigned numerous styles and SKUs, the process of management by exception is critical to the success of in-season forecast and trend management. 

The methodology of expert inventory management revolves around three functions: fill, overstock and forecast.  The action levers that experts have at their disposal are adjusting supply and/or adjusting demand.  Listed below are three snapshots of these analytics in action:    

Incorporate analytics that address in-season fill analysis – a service metric

• Business Benefit – These analytic alerts act to improve the inventory position relative to demand.  They identify when initial fill is projected to fall below acceptable levels.  Fill for the week = demand quantity – backorders taken – lost sales / demand quantity.

Expert System Action Levers:

Demand: pull style and or color, adjust availability e.g. “men’s only”

Supply: shipping method change, manufacture sequence change, adjust timing of Purchase Order (PO)

Incorporate analytics that address in-season overstock – a financial metric

• Business Benefit – These analytic alerts act to increase demand.  They identify when overstock is projected to exceed acceptable levels. Overstock cost = overstock quantity * SKU cost.

Expert System Action Levers:

Demand: add appearances, red line (discount) future appearances, carryover to following season

Supply: cancel future PO’s

Incorporate analytics that address in-season forecast – a leading indicator

• Business Benefit – These analytic alerts act to adjust future forecasts to reflect revised trends.  They identify when actual demand has varied from plan by more than an acceptable amount.  Forecast Variance = 1 – (sum of actual demand / sum of preseason demand) * 100.

Expert System Action Levers:

Demand: adjust appearance forecasts

Supply: adjust receipts timing

Conclusion:

The development of a rules-based system which leverages the subject matter expertise of expert practitioners can lay the foundation for effective and efficient inventory management in the catalog industry.