Forming, Storming, Norming, Performing – Getting Data Governance Off The Ground
Getting a data governance program up and running can seem like an enormous task. At a November Meetup in Detroit, two data governance teams gave the audience their advice, wrapped under the three traditional project stages to achieve top performance:
Don’t boil the ocean – When beginning a data governance program, it can be tempting to load as much data into a data lake as possible. However, it’s much better to be selective and pick meaty projects to load – it can be easier to demonstrate business value this way.
Set standards early – Having standards early on will result in a smoother roll-out and less time-consuming debate about terms, processes, and customization.
Focus on data quality – Enthusiasm for a data lake may, early on, lead to the posting of data without much focus on data lineage or metadata. Be sure all data posted is well documented from the beginning.
One size does not fit all – Don’t import processes, taxonomies, or other practices from other companies without first checking to see how well the approach will work within the particular circumstances of the organization. Does the solution fit the existing data governance approach, culture, and business needs?
Collaborate – Reach out to business partners and get them on board with the data governance project early on. Help them to understand the value of it to their teams. Look for ways in which data governance will make their lives easier – for example, reporting.
Educate the business – Business users will be facing quite a lot of change all at once, from learning new ways to think about data assets to the collaboration across the business that this new approach generates. Educate business users to help them better understand how to engage with this new ecosystem.
Keep it simple – As the data governance project evolves, maintain a focus on keeping things simple for the business user. Complexity will lower adoption rates.
Establish internal processes – Documenting helps to standardize processes, ensuring users engage in the same way. Having documentation also helps to provide solutions, as well as narrow down the scope of work for the support team.
Determine the business value of a potential customization – When the business comes in with a customization, look at what the business value of the request is. If the business value is low, then consider alternative approaches.
Think globally, apply locally with customization – When considering a customization to solve a specific challenge, step back and explore how that customization might solve other challenges across the business. Then create a customization that will solve the larger group of use cases.
Internal alignment of the team – As the team grows, be sure to maintain alignment within the data governance team. For example, it can be a good idea to have data stewards who report to the business side, but it’s important to empower them by meeting regularly and gathering feedback.
Learn how to tell the story – When talking about the value that data governance brings to the organization, be sure to describe the “before” state of how business users worked with the data, and the work that the data governance team performed, as well as the end result.
Build for your audience – When the data governance team encounters an issue, it’s important to consider the points of view of both the data governance team and the business when seeking a solution. Additionally, look to solve specific challenges for the business’s use of data to show how data governance delivers value.
Automation enables scalability – Look to see where automation is possible within data governance processes. Getting automation programs underway should be a part of the second phase of Collibra adoption, if it was not part of the first phase. Automation makes it easier to achieve scale.
Create a change management process – Having a regular process to manage change in data governance can make it easier for the team to implement new programs and for the business to remain engaged because they will know what to expect from the change process.
Communication – Create a regular pattern of communication with the business. For example, create a templated monthly newsletter that updates the business on the data governance team’s activities, and indicates future progress timelines. Circulating information helps improve the dialogue with the business.
Getting to Performing
Launching a data governance program is a significant undertaking that the entire organization will need to engage with. These insights from data governance teams that have gone some way on their journey underscore just how important effective collaboration – within the team and across the organization – is for success. To learn more about best practices within data governance programs, explore the communities, solutions, and services Collibra can offer.
Miss our NYC Meetup? Check out our recap here.