This blog post is Human-Centered Content: Written by humans for humans.
Now that we’ve laid out the framework for what strong Data Governance strategies look like and the steps to achieve them, let’s round out this series by briefly going over a few common challenges you’re likely to face when you embark on your data governance journey.
The Big Four
We most commonly see four big hurdles to get over with data governance:
- Chasing Perfection
- Over-engineering
- Internal reluctance
- Clashing with current procedures
We’ll define the problems below and pitch a few ideas on how to get around them.
Chasing Perfection
“Perfect” is the enemy of “good enough.” It is easy to become consumed with the never-ending challenge of precisely defining every KPI, having every director agree with said definition, then deploying the most perfectly optimized data stack that will solve all your problems and be widely adopted.
You can’t. It’s a fool’s errand.
All chasing perfection will get you is adoption paralysis. Clearly lay out the requirements for your data governance changes, do your research, find a good option and get to work. Iterate on your changes at a set cadence with standard reviews to see how things are going. If your “good enough” choices aren’t being good enough, swap them out. There’s no shame in that.
The most important thing, always, is moving forward and making progress.
Over-Engineering
This one tends to be related to the chasing perfection roadblock. When developing your data governance strategy, be mindful to avoid over complicating the situation at hand. Follow prior guidance to focus on base level needs first, while tackling additional capabilities as your practice matures. Additionally, make a habit of self-evaluating your plans to ensure you’re in the goldilocks zone of being able to keep up with your needs without over-investing. It helps to lay out a roadmap for the future to adequately pace your scaling. You can opt for a phased approach, but continue to make sure you’re not neglecting your base needs. Finally, make sure you’re right-sizing your path with accurate forecasting on a realistic growth path forward.
Internal Reluctance
Sometimes, change is a scary thing. Sometimes, there are budgeting concerns. Sometimes, decision makers are risk averse. There are any number of reasons that internal stakeholders might not wish to implement additional policies and procedures within their data stack.
That’s why our biggest recommendation for overcoming internal reluctance is to be open about your progress and to have the research on your side. Lay out the benefits clearly in ways that show stakeholders how implementing your framework accomplishes your organization’s goals. Maintain proper trainings so users are empowered, and be consistent with what the end goal is and your teams progress towards achieving.
The whole point is to alleviate any concerns as they arise and leave no room for questioning whether the project is worthwhile or not.
Clashing With Current Procedures
Organizations should perpetually evaluate the way teams are functioning in order to maintain an optimal operating state. Now, of course, that’s not to say that you should throw the baby out with the bath water, but you have to break a few eggs to make an omelet, to borrow two conflicting turns of phrase.
Have a rock-solid proof of concept that clearly demonstrates the value your strategy will deliver. Identify opportunities to combine the old and the new in effective ways to not completely do away with solutions or experiences users are familiar with. Manage expectations about needed changes with clear lines communication. Ultimately, be sure to own your strategy, be consistent, flexible and stay the course!
Wrapping Up
If you find that you’re facing down too many red flags to adequately address yourself, reach out to our team here so we can help you build a stronger data governance strategy. Many hands make light work, and we’re willing to have your back
