Avoid These Data Governance Strategies at All Cost

Avoid These Data Governance Strategies

Over the past 10 years, I’ve witnessed how data governance has evolved and changed progressively over time. What I’ve learned is that there are definitely right and wrong ways of implementing an effective data governance program, and there are data governance strategies you should definitely avoid.

Data governance teams have really evolved over the years and you can see that from the development of new roles like Chief Data Officers and data scientists. At first, data governance was a grassroots initiative managed by small teams, but nowadays it’s much more strategically planned and enforced from the top level down.

Even processes have changed. From having only a single area of focus on customer master data, material master data and more, to now being able to focus on a single target across multiple systems.

The need for data governance is greater than ever, and the choice of tools and software to successfully implement a data governance strategy is ripe for the picking, but here are strategies you should avoid when possible.

  1. Executives Not Buying It – Data governance is not a project, it’s a program that will forever live in your ecosystem. So when planning, be sure to get your executives involved from the beginning. If your executives are not on board from the start, you will not be able to get the funding and support needed to get your initiative off the ground. Save your time and resources and get their approval first.
  2. Houston We Have Some Problems – Data governance is great because it can solve a lot of problems, but the issue is when everyone wants to solve each individual problem. Organizations know they have issues and want to jump into fixing the data quality and business process issues where they think they have the most inefficiencies. However, they haven’t put much thought into how they would capture the metrics of those processes. You have to identify where your problems exist and model the process you have and monitor the metrics. It’s a solve all, hard to measure strategy that you should avoid.  
  3. Too Many Chefs in the Kitchen – Sometimes the issues in your systems might not be the processes, but the actual people monitoring those processes. When developing your policies and processes, you need members from different levels in your organization, but too many members may cause problems. Problems can occur when incorrect or irrelevant personnel are chosen to make touch point decisions in systems they are not involved in, as well as the time spent on organizing and evaluating all suggestions and resources. Bring in people who have integration points from that system into other systems. Someone must own the process and this must include input from subject matter experts of each area of that process, but not ever individual in the process.
  4. If We Build It, They Will Come – For many organizations, analytics and monitoring are always part of the discussion, but when they become the focus, we often forget about the metrics needed to measure the success of the process once executed. Spending more time and money on the execution of the process will result in more time and money spent on measuring the success of the process if it is not pinpointed from the start.

We’ve progressed quite a lot as a software and services vendor over the past 10 years, but so has the industry. Organizations are more mature and understanding of what data governance is from what they used to think it was, but in order to take that next leap in execution and benefits, we need to recognize the “what has” and “what hasn’t” worked for organizations. 

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