Ajilitee’s newly-released “Ultimate Guide to Data Governance Metrics for Health Payers” dives into 30+ data governance metrics from a quantitative and qualitative vantage point. But today, I’m exploring a subset topic, which is how to measure the success of a Data Governance Council initiative.
We’ve said this often, but it bears repeating: data governance programs tend to fall short of expectations because they wind up as tactical data quality initiatives that address accuracy and consistency in silos. They also lack an effective governing body to manage data ownership, lineage and accountability across the enterprise.
We believe that establishing a Data Governance Council is the key to transforming a data governance program into real business value. An informed and active Data Governance Council will tackle inaccurate, inconsistent and incomplete data holistically through policies and cultural change at the leadership level. And just as a data governance program establishes metrics on its data quality and performance measurements on the data stewards, it’s equally as important to set performance goals for the Data Governance Council.
In the Health Payer space, metrics are driven by corporate drivers and key performance indicators. Typical drivers include the following:
- Cost avoidance and cost containment
- HIPAA, Privacy and/or regulatory compliance
- Fraud detection
- Constraints management
- Products and Plans time-to-market
A Data Governance Council composed of upper management will be engaged and committed if they are presented with demonstrated successes that address these drivers. This includes continuous data quality that the governance program helps ensure is embedded upstream rather than performed sporadically downstream. Also realized are the benefits of improved transparency, audit-ability and data lineage, which are essential to compliance with government regulations such as HIPAA.
During its instantiation, the Data Governance Council should be reminded that they are part of this group to serve as proactive change agents. Therefore, this ability to be change agents should be measured. To that end, we recommend these five key metrics to measure the Data Governance Council and its members:
- METRIC 1: Advocacy success measure.
- Getting each Council member to recognize that their role is not a passive one. To remain on the Council, they are expected to be “data integrity proselytizers” – e.g., identifying a steward for their line of business, and speaking at their team meetings about the new policies, progress and changes, and so forth.
- METRIC 2: Meeting success measure.
- Demonstration of commitment. This can be accomplished by an early vote to have a policy that a Council member could and would be “disinvited” for lack of attendance.
- METRIC 3: Each Council Member must bring a Data or Process Issue request to the Council.
- Demonstration that the Council member understands what is an appropriate process and/or data issue that warrants attention from the DG Council. They must be willing to push skeletons in their own business areas in front of their peers for resolution.
- METRIC 4: Number of Policies Established.
- Enterprise Policies serve as the basis for prying systemic data issues away from the silo-minded lines of business. In the first years, typical policies include defining the list of governed data elements; approving Unique Identifier data elements (e.g., Unique Provider, Unique Institution, Unique Member); establishing USPS Address Standardization; conforming Provider Specialty Taxonomy to CMS labels.
- METRIC 5: Maturity Model measure.
- The Data Governance Council should demonstrate proficiency in their role before tackling the more complex topic of a Data Governance 5-Year Maturity Model. But by the end of Year 1, the level of progress on the Maturity Model should be set and tracked for each succeeding year.
At each Council meeting, we advocate reviewing each of these Scorecard metrics. Everyone sees the contributions of their colleagues. It’s important to have this level of visibility and openness – peer pressure works wonders! And we stress not to be “locked-in” to a particular set of members. It’s not uncommon to realize that another representative needs to be added or someone cannot make the necessary commitment and should be replaced.
Finally, measure the business impact of a Data Governance Council and then publish results on an enterprise data governance internal website or Sharepoint. This demonstrates the commitment to improved data integrity at the highest executive ranks.