The Dangers of Poor Quality Data

The Dangers of Poor Quality Data

Many statistics demonstrate the high cost of poor quality data. The Data Warehousing Institute (TDWI) estimates that poor quality data costs US companies $611 billion per year due to revenue losses and productivity problems. Some examples of the issues that create this negative impact in enterprises include:

  • Wasted resources in manual data correction activities.
  • Customer dissatisfaction due to duplicate mailings, incorrect billings, and poor service.
  • Wasted marketing spend due to incorrect or incomplete customer information.
  • Missed business opportunities due to inaccurate customer intelligence.
  • Excess inventory.
  • Delays in deploying new systems.

In September 2005, QAS, a division of experian's Marketing Services Business, released the report, "The Impact Poor Data Management Has on Your Organization." Key findings of this study include:

  • Enterprises around the world lose 6% of annual revenue due to quality problems with their customer data alone.
  • In the US this figure is above the international average, with enterprises losing 7.3% of revenue as a result of poor quality data.
  • Over 70% of companies from all industries reported losing money due to data quality problems.
  • This figure is even more dramatic in the US, with 77% of companies reporting that such problems have negatively affected their bottom line. Figure 1 below summarizes these findings by country and Figure 2 does so by industry:

 

 

Here is a document on Step by Step Guide to  Data Quality Remediation. Hope you find it useful.

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