How do you measure the success of your BI & Analytics Programs/Capabilities?

Ability to translate the insights from the output of the program to drive value (revenue increase, cost optimization, market capitalization, innovation, policy changes, etc.)

first you cant control local user reporting.  Focus on the enterprise published reporting.  Second, I think somewhere in your success measures you should report technical debt elimination: 
 - ratio of actively consumed reports/dashboards vs. total enterprise report inventory.

Some suggestions:
*) Capability related:

-> Number of projects accepted and rejected due to existence / lack of capabilities and methodical background
-> Necessary time for understanding the business needs

-> Methodical variance of solutions (number of different BI & Analytics approaches applied, especially in the AI area)
*) Success related:
-> Number of projects / developments accepted by the Business Unit as digital extension to current product offers
-> Number of revoked BI / Analytics outcomes due to no use (after ensuring proper communication within the responsible people)
-> Contributions to risk mitigation or performance improvements by comparing before and after a BI & Analytics program been rolled-out

We have a Data Scorecard which is a combination of Business KPIs (for example, the % contribution of D&A to Commercial Uplift) and Data Management KPIs.  All of the KPIs are linked to our five Data Strategy Goals and measure the shifts we want to achieve and / or the capabilities we want to develop.  For example, for our Data Democratization goal, we measure the number of return users to the self-service section of the D&A Portal and the frequency of use of the different SSBI apps.