Unit Fill Rate (UFR)

The unit fill rate (UFR) for an item is the portion of the total number of units...


Warehouse Occupancy Percentage

Optimal storage utilization helps enforce healthy inventory management. In our early work with Honda their...


Efficient Procurement Inventory

Efficient procurement inventory (EPI) is often required to realize steep discounts when a special opportunity...


Inventory Activity Profiling & Data Mining

Suppose you were sick and went to the doctor for a diagnosis and prescription.  When...


Inventory Performance Measures

Inventory performance measures include financial, productivity , quality, and response time indicators for evaluating the efficiency and...

Customer Data Cleansing

Unfortunately, as is the case with most data sets, an important part of customer activity profiling is data cleansing (or data scrubbing). More often than not customers are referenced by many names and aliases. For example, a common set of representations for Wal-Mart is WM, WMart, W-Mart, W-M , W_Mart, Wal_Mart, WMrt, etc. In addition, bill-to vs. ship-to locations and customers need to be carefully distinguished to insure that an accurate representation of customer activity is portrayed.


The ultimate goal of any data cleansing initiative is high data integrity or high data quality. High quality data sets are characterized by completeness, accuracy, consistency, de-duplification, and uniformity. Clean data is contrasted with dirty data.


Customer data is continuously cleansed to insure that truly unique, consistent, and accurate references to customers bill-tos, and customer ship-tos are maintained.



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