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Business Impact of Data Validation - Volume or Economic Value

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Aug 30 2010

On a recent project, I was involved with running data validation tests to ensure that each constituent in the marketing database is accurate.  The tests were designed to validate that each record has correct contact information, relationships to dependents, products, etc.  In that effort, we took a holistic approach to testing the data; we validated information in the database, validated the output of campaigns, mail file quality checks, etc.

As expected upon reviewing the validation results, we found data that needed to be fixed. And it was clear that certain things needed to be fixed immediately. At that point, we began the process of prioritizing items and developing an action plan to fix them.  It can be tricky to define the priority and it depends upon the factors you are considering. Should you look at the number of records impacted, or look at it from economic value perspective? I think the answer may be obvious - it makes the most sense to focus on maximum economic value.

The economic value depends on where you will get a higher return from the data. As an example,  if you have 100k records from an online source that have incomplete information vs. 10k records from a reliable source, it's worth considering data from the reliable source. Focusing on this group could lead to a higher success rate in reaching out to those contacts as well as response rate. If each response translates to selling products/services with a direct impact to revenue, focusing on the smaller, effective, data source first makes a lot of sense. Sometimes, it can be misleading if you just focus your energy on the record volume.

What do think? Is there another dimension we should consider?

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