Everyone agrees that the result your data management efforts should be measured and the way to do that should be to define some Key Performance Indicators that can be tracked.
But what should those KPIs be? This has been a key question (so to speak) in almost all data management initiatives I have been involved with. You can with the tools available today easily define some technical indicators close to the raw data such as percentage of duplicate data records and completeness of data attributes. The harder thing to do is to relate data management efforts to business terms and quantify the expected and achieved results in business value.
A recent Gartner study points out five areas where such KPIs can be defined and measured. The aim is that data / information become a monetizable asset. The KPIs revolves around business impact, time to action, data quality, data literacy and risk.
Get a free copy of the Gartner report on 5 Data and Analytics KPIs Every Executive Should Track from the parsionate site here.
Liliendahl on Data Quality 
Henrik, this is a great topic. Can you share a little bit about how you help your clients decide which measures to track? What process do you use to quantify the business value?
Sure, Gino. Ususally the starting point is the pains and gains identified for the selection of the components to be involved in the data management initiative. In best cases these are quantified for the prioritization. As exemplified in the Gartner paper this may be in money amounts but also in time reduced (for insight to action, automation) or percentage covered (eg data literacy).