Inventory allocation decisions are all too critical for retailers, manufacturers or any organization with significant volumes of inventory in a variety of locations and distribution levels. Some of the decisions are time sensitive, and significant revenue loss and decreased customer satisfaction (“I’m leaving!”) can occur by not having the right item in the right place at the right time.
Organizations could get a handle on those decisions through high-performance analytics that will factor in point-of-sale (POS) data – in addition to historical information. While most demand forecast prediction is done on historical shipping data, the availability of POS data would make it possible to perform in-memory processing of historical plus time-latency-adjusted POS data on very large data sets.
What decisions make or break customer satisfaction in your organization? Follow the next article in this series to see how high-performance analytics can help the insurance industry. Or read more now in this white paper.