Problems with the data

Every database has flaws: idiosyncrasies, missing data, etc. The worst problem is wrong data that looks believable. How are you going to handle these flaws? First, check your data carefully for missing or obviously wrong values. Then estimate how large each problem is. Missing data on one sku out of 10,000 may be safely ignored; missing data on half of those sku's means the project is dead.

Here are some things to note about the SPR data.

Copyright © John J. Bartholdi, III and Steven T. Hackman. All Rights Reserved.

This is material to supplement our textbook Warehousing & Distribution Science. See

Last revised: 27 February 2003

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