Activating Data Governance
It was spring 2020 in the United Kingdom. COVID-19 was starting to upend life, business, and government across the country. Desperate to gain control of the situation, the government hoped its technocratic Government Digital Service (GDS) would enable the cutting-edge data analysis required to track and isolate positive cases of the virus, ultimately preventing a more virulent outbreak. However, the team ran into an issue: they were using Excel spreadsheets and staff were not versioning them properly.
According to an article in The Economist, it was estimated that this mismanagement of data resulted in more than 15,000 positive COVID-19 contact tracing cases to be lost, leading to further spread. This case alone illustrates the vital importance of data governance.
No data governance? Get ready for problems
In the case above, the UK government violated one of the principles of data governance: having a verified single source of truth for data. As described in an article in CIO, data governance is a program structure that “defines roles, responsibilities, and processes for ensuring accountability for and ownership of data assets across the enterprise.”
In other words, data governance establishes the rules of the game when it comes to owning, managing, and using data within organizations. If the GDS had a more mature data governance program, there would have been existing rules for how and where the case data was stored, who had access, and how it was reported.
So how do you get companies to practice data governance? And how do you get individuals to own data governance? These are questions that typically get thrown around after a business case for data governance is presented.
To get started, clients need to have a sense of ownership and organically work data governance into their organization. Slalom recently found a successful approach to ameliorate this through the crafting and execution of a data governance pilot — an approach that shared similar characteristics with other successful data governance projects managed by Slalom.
Setting the stage
We created a data governance pilot as part of our engagement with a medical device company in their rollout of a new customer relationship management (CRM) platform to replace a sluggish, over-customized CRM platform. Executives were concerned about repeating old mistakes and sabotaging the new CRM platform. The group coalesced around the concept of guardianship in communicating the necessity of data governance throughout the organization — the new platform had to be guarded from mismanagement.
To ensure success, Slalom and the client partnered to design and conduct a data governance pilot — a charge to start small, provide a degree of ownership, and lay the groundwork for future operations. With this green light, we embarked on our program.
Small decisions, big impact
To get a data governance pilot off the ground, five critical activities are required:
1. Establish and drive alignment around a charter.
The charter is the de facto legal document for data governance operations. It outlines your objectives, the operating model, and the timeline for operations.
2. Establish core, priority roles and responsibilities.
For best practice, we recommend a data governance manager, data owner, and data steward. The data governance manager is the most important role because this individual serves as the chief of staff for operations.
3. Secure and maintain executive sponsorship.
A data governance program needs executive sponsorship to succeed. It’s much easier to get business units supporting the program if senior executives are backing it.
4. Identify use cases influenced by real-world examples.
To make data governance feel real and organic, people need to see how it can impact their jobs. This can be accomplished by identifying and working use cases with these implications. In our engagement we selected use cases related to CRM platforms.
5. Schedule and maintain a cadence for operations.
All programs — especially data governance — require a cadence for management and completion of work. We recommend a weekly cadence, if possible.
In addition to having these core elements in place, it’s key not to discount the importance of a data governance manager. In many cases, this individual can make or break the program. Another Slalom consulting team had one of their resources act as an interim data governance manager for a similar effort at a financial institution, furthering the maturation of their data governance operations. For the best possible outcome, outside expertise and impartiality are required to execute data governance operations.
Even with having these foundational pieces in place, these initiatives still need strong leadership support. To earn this, you’ll need to take your work on a roadshow.
Getting buy-in
During the first month of the data governance pilot, we presented our work to various executive audiences across the organization. For a data governance program to be successful it needs to have the support of senior leadership within the organization, so making sure all senior executives across the organization knew and supported our work was an essential step.
In our engagement, we defined what data governance meant for them, what issues it would address, and the timeline for our work. We linked the cause of data governance with their expensive investment in the new CRM platform, demonstrating how data governance would protect and augment it.
This challenge of presenting the case for data governance has been faced in other Slalom projects. If you can get in front of leaders early on, seize the opportunity to build the necessary executive support.
Early wins
Scoring early wins in our data governance pilot was critical. We did this by tackling two important issues for the organization to show the value of data governance: data domain refinement and data rationalization.
Our pilot group advised on the refinement of the customer data domain definition — a critical step in implementing a new CRM platform. To use the new platform properly, the organization needed to be able to trust their customer data. To build this trust and increased confidence in the data, it was important to convince stakeholders that their input was needed.
The team crafted a methodology that outlined a five-step process for updating its customer data domain, ensuring only applicable and tangible customer data would be captured for analysis and management. Stakeholders were impressed and having a methodology that answered their concerns made them feel heard. The five-step process crafted in this pilot was also leveraged by other Slalom teams to advise clients on refining their data domains for governance purposes.
We advised the massive data rationalization effort occurring parallel to ours, lending our expertise in deciding the migration status of over 300,000 items of data to potentially be migrated to the new CRM platform. Data engineers and tech managers were skeptical but quickly appreciated the order and structure our management brought to the rationalization exercise. Our impact ensured that “junk data” wouldn’t litter the new CRM platform, reducing the propensity of technical debt to clog it.
Through these experiences and the work, individuals and business units experienced first-hand the value data governance could bring to their jobs. It also demonstrated the importance of scoring early victories when rolling out a data governance program in an organization.
Setting a tempo
Lastly, our pilot had a disciplined operations cadence. Our group met biweekly to discuss use cases, prioritization of work, and strategic issues. For maximum engagement, the interim data governance manager always prepared a standard meeting deck that captured these items and was socialized before the meeting.
Furthermore, our operational cadence had an element of flexibility. During the final few weeks of our pilot, we focused our efforts on crafting a refined process for accepting change requests by the CRM platform that was grounded in guardianship. This focus on a single use case was not planned, but our executive sponsors pressed for it due to their concerns with the new platform. Our ability to pivot and deliver a standardized change request process customized to their data governance environment further enhanced our credibility and demonstrated the value of data governance.
This approach — discipline tethered with flexibility — is required for successful data governance management. Participants in data governance programs need to be ready to pivot when needed — especially at the request of senior executives.
Best practices
In conclusion, organizations should explore designing, standing up, and executing data governance pilots to better enable their data governance strategies (or leveraging our experience to inform their program planning). The value of a pilot cannot be discounted, as it’s an opportunity for leaders to begin taking ownership of data governance and to do so in a safe environment.
As we reflect on our pilot experience, the following best practices for data governance emerge:
- Have a realistic focus and scope.
- Have an end goal in mind. What are we working toward and what are our outputs?
- Identify engaged and passionate stakeholders from both business and IT, then collaborate with them regularly.
- Identify a strong data governance manager who serves as a task master and coordinates all activities.
- Lastly, be flexible and nimble. Data governance is a test of your organization’s resiliency.
By carefully applying and executing these practices, many organizations — regardless of industry — can finally activate data governance and realize the benefits it brings to the business.
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