Sometimes it is easier to see why something fails than why something is successful. As many wise people have said:

• “Failure is success in progress.” Albert Einstein
• “Failure is simply an opportunity to begin again, this time more intelligently.” Henry Ford
• “You an’t let your failures define you. You have to let your failures teach you.” Barack Obama

Since Data Governance in facilitated through the often-complicated alignment of people, process and technology, you are bound to see a number of hurdles as you implement a program. Change is hard, and these hurdles often mean your program is on the right track, or a success in progress. See the hurdle as part of the process and do not be deterred to keep going.

Hurdles

There are many reasons why data governance fails or is a success in progress. But the cause is more often than not one of the following:

• Data governance is not well-defined (What is data governance anyway and why should I care?)
• Healthcare executives and managers consider data “an IT issue.” (IT maintains systems, databases and reporting, so they should own the data in each of those things)
• The business units and IT don’t work together, or when they do, they throw things over a fence instead of collaborating (IT implemented and knows the system. Why do I need to be involved?)
• Organizational units or domains are disparate and independent. The organization supports little to no centralized decision making (Why should I care what the ED or OR is doing? I can manage my own data and resources.)
• The return on investment (ROI) isn’t clear (Why should I care that 300 metrics have been standardized? Does it make anything I do better or easier?)
• The business use case for data governance isn’t defined, so the work effort doesn’t seem worth the time (Why should I join a meeting to standardize length of stay? It isn’t my project. Just tell me what happens.)
• Key subject matter experts are already overscheduled and can’t take on governance activities (I already have meetings from 8-5, so when am I supposed to join a monthly call or validate a definition?)
• Data governance is viewed and managed like a project with a go-live (3 more months until we have Data Governance and then we can stop meeting)
• Execution is lacking, and progress is not tangible (I can’t see what we have spent 40 hours doing related to resolving case volume discrepancies).

Guidelines

If any of the hurdles above sound familiar, just remember that they do not mean failure, rather your data governance journey is still a success in progress. To overcome these hurdles, keep in mind the following principles as you rollout data governance in your organization:

Break out of Silos

Don’t just implement a top down model of committees, charters and policies. You need to create a data governance network by promoting data and analytics community building. This means providing education for all staff to really understand and interact with the data, and see how their involvement is meaningful to them and the organization.

Make Data Actionable

The value of data comes from your actions. If you want business adoption you need to include the business metadata of requirements, usage, benchmarks, goals, thresholds, etc. and not just focus on data definitions. This will make the data meaningful to your business and help them use it to drive decision-making.

Facilitate Don’t Police

We need to focus our energy on creating the right environment for people to do more with data, instead of focusing that energy on policing and enforcing. That means making:

• data easier for people to use.
• it easier to understand what the data means.
• it easier to reuse and align.

Prominence specializes in doing more with data.  Reach out to us to talk about Analytics or Data Governance!