Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company as a whole. The data layer of an organization is a critical component because it is so easy to ignore the quality of that data or to make overly optimistic assumptions about its efficacy.

It is important to note that many benefits accrue from improving the data quality of an organization. Many of these benefits are intangible or unreasonable to measure. Benefits such as improved speed to solutions, a single version of the truth, improved customer satisfaction, improved morale, an enhanced corporate image, and consistency between systems accumulate, but an organization must selectively choose which benefits to perform further analysis on and convert to hard dollars. ROI must be measured on hard dollars.

This paper from Business Objects, an SAP company, examines an overall approach to data quality ROI including 6 key steps to put into process to help you realize tangible ROI on your data quality initiative.