Wednesday, March 30, 2011

Inventory Control and Business Analytics

In this age of cost cutting measures, every aspect of business operations must be considered.  It is in business functions that have a high degree of variability that cost control can be a difficult endeavor, but yet provide a tremendous opportunity for savings.  One of these business functions is the management of inventory.  Inventory can be a physical or abstract concept.  It can represent real raw materials or products ready for sale.  It can also represent intellectual property or data that may have storage costs and a limited shelf life.  The general management of inventory, however, comes down to this trade off: If you have more than you can use, then there are storage or disposal costs.  If you don't have enough when a customer comes knocking, then there is lost revenue.  In rare cases inventory has low storage and disposal costs so excess quantities are kept on hand for future use.  In  most cases though, whether due to fads, styles, age, or market forces, inventory perishes and has a carrying cost.

Managing a complex base of inventory is difficult and costly.  One tool that can support this effort, however, is business analytics.   Business analytics offers a  framework for lending insight to trends, inefficiencies and and opportunities for the  management of inventory.  Since inventory control is a highly variable activity, analytics can help understand the drivers and magnitude of this variation.

Several different analytic methods are available to provide this insight.  The most simple and straightforward method for understanding inventory levels is historical reporting and analysis.  This will illustrate periods when inventory was either deficient or in excess, and will clearly show seasonal or business cycle variation.  It can also identify poor or successful inventory decisions that have been made in the past; these can inform better future decisions.

A historical perspective does not necessarily give full insight to current inventory decisions, however.  Real-time monitoring of current inventory levels with key metrics such as Current Inventory, Working Capital, Backlog and End of Life Inventory provide an illustration of where inventory may by actively lacking, in excess or at risk.  Through regular review of these metrics, real-time inventory control decisions may be made to mitigate potential future waste or lost opportunity.

Without insight into future needs, however, current inventory monitoring has limited benefit.  In order to truly stay ahead of demand for inventory, a reliable and accurate inventory forecast is essential for proactive decision making.  The nature of forecasts, however, is that they become less certain the further into the future they predict.  As such regular update and review of forecasts is required to allow for re-alignment of future inventory requirements.  Proactive inventory management is effectively a bet on future needs.  This bet needs to be balanced with the variability inherent in the inventory forecast: The bigger the forecast uncertainty, the smaller the bet, and visa versa.  The net effect is an optimized inventory program.

This article just begins to touch on the analytic methods that could support the management of inventory.  The actual techniques will vary depending on business needs and business objectives.  It is these analytic techniques allow for the control of uncertainty and variation that is so present in inventory management.

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