The automobile industry got the message in the 1960s and 70s: the cost of low quality is too high. It makes sense to make sure that your processes deliver top quality rather than fixing errors after they occur.
Modern retail institutions are coming to this realization as well, however, in their case the raw material is not steel and glass, but rather information. A high percentage of the headcount of a typical retail institution is dedicated to data entry, updating and processing. The cost of errors are not only the cost of rework when fixing the error, but also the cost of erroneous decisions, the cost of campaigns with low contactability, and the cost of reputational risk.
In many cases, the issue of data quality is that the initiative is not connected to business results nor to the business case. ABC’s approach is just the opposite as it is built on understanding data quality implications as they occur in risk management as well as in CVM areas. The resulting evaluation and roadmap of subsequent steps are designed so that they lead directly to achieving quick returns on the initial investment.