Developing quantitative benefit estimates
As explained in Chapter 1, one of the most difficult challenges when getting a data quality initiative “off the ground” is quantifying the benefits. I have already said that it is not possible to identify a comprehensive set of benefits.
At the business case stage of an initiative, there are usually few (or no) data quality rules in place to measure a full population of data. This means the size of the problem is not known and therefore the benefits of fixing the problem are also not known.
On top of this, “fixing” the data quality issue does not in itself provide business benefits. The benefit is “one step removed” because the corrected data only provides benefit at the point that it is used in a successful business process or in a meeting where a better decision is made based on more complete reporting.
For anyone thinking that calculating the benefits of data quality improvement cannot be...
