System and method for inventory management

In an inventory management environment having inventory statistics, the inventory statistics specific to each day of the week, a method of computing target inventory levels comprising:

• gathering, for each day of the week, inventory level statistics from previous sales;
• computing, based on the inventory level statistics, a safety stock for each day of the week, the safety stock independent of a safety stock for other days of the week such that the computed safety stock accommodates variations in inventory between the different days of the week;
• and
• rendering, for each of a plurality of SKUs, a stocking level indicative of the target the safety stock for each day of the week.

A computer program product having instructions stored on a non-transitory computer readable storage medium for performing, in an ordering environment having at least one SKU, each SKU denoting an item at a location, a method for computing an inventory quantity for each SKU, the method comprising:

• gathering, for each SKU, a history of inventory sold
• computing an expected bias, the bias based on the history;
• identifying, for each SKU, a deviation range of the expected quantity for each period;
• aggregating, for the periods remaining until a replenishment of inventory, the deviation range;
• and
• computing the safety stock based on the bias and an aggregation of the deviation range.

An inventory management server, comprising:

• a user interface device responsive to an ordering environment having at least one SKU, the SKU denoting an item for sale at a location;
• a processor for computing a safety stock for each SKU;
• a storage repository for gathering, for each SKU, a history of inventory sold;
• the processor configured to, for each SKU,
• compute an expected bias, the bias based on the history;
• identify for each SKU, a deviation range of the expected quantity for each period;
• aggregate, for the periods remaining until a replenishment of inventory, the deviation range;
• and
• compute the safety stock based on the bias and an aggregation of the deviation range.