“What is data governance?” Having championed the importance of data governance quality throughout my 30-year career in financial services, its principles are second nature to me. That said, this question is still one I continue to encounter with alarming regularity in my day-to-day work.
It seems many people see or understand just one dimension of data governance. For example, the term is grossly misunderstood when considered a synonym for data security and privacy. The term is misleading when equated only with data quality and the term is sadly off-putting when interpreted as a tool for policing business and technology and ensuring compliance with rigid data policies.
These common misconceptions prompt frequent debates, even amongst my colleagues, about whether a new term for data governance is warranted—one that better describes its applicability for every stage of the data lifecycle and team doing data management. We need a term and role parallel to Human Resources and Chief Financial Officer to educate the masses on the broad scope of data governance and its decade old principles that ensure data is managed and invested in as effectively as a companies invest in their people and financial assets.
The latest favorite replacement term is “Data Enablement.”
Defining Data Governance Means Aligning Business and Technology Objectives
Understanding this modernized definition requires getting both business and technology professionals curious about data governance with a ‘hook’ — something data governance professionals continue to conceive, experiment, test, and revise.
With the tenure of Chief Data Officers averaging 2 years, we know we desperately need to help executives both measure the business value of data governance and quantify the value of an organization’s data to ensure they can optimize the investment in their data assets. These measurement methodologies are maturing, but they are still hard and more practice is needed. So, what to do in the meantime?
Working with 7 organizations in the last 5 years, I’ve had plenty of opportunities to answer the question, ‘What is data governance?’ and I’ve learned several things. First, there are as many ways to internally define data governance as there are companies practicing data governance. That’s the bad news and the good news. It means data governance can mean everything, nothing, and anything in between, so defining data governance must be done in the context of an organization’s vision, mission, and strategic objectives and must have meaning to all levels of the organization.
This is best defined in the context of a data governance maturity model.
Thought Exercise: Your Data as an Asset
At Hakkoda, my favorite of the company’s foundational values is ‘Stay Curious.’ This value, framed as an imperative, speaks to a commitment on behalf of every employee to reach beyond the current business or technology paradigm and interrogate basic assumptions about the way things are done. With that in mind, I encourage readers to imagine the following scenarios for the opening day of a new restaurant franchise.
- Scenario 1: The facility and technology is new and all the information about your products is at the fingertips of your employees, but there are no employees. What is the likelihood of success that day? Pretty low.
- Scenario 2: Now imagine a different opening day where the employees are well trained, they know the product and client needs inside and out, but there is no power in the facility, disabling the ability for customers and employees to use the facility. Again, very low likelihood of any success that day.
- Scenario 3: Finally, imagine the last scenario for a different opening day. The facility and technology is new and employees are trained and ready to go. As they open business for the day, they realize the menu board is missing prices and all of their systems and application databases are empty, void of any information. This situation, too, points to a low likelihood of success.
Can you imagine a day of your work with amazing employees and beautiful facilities, but no data — no client list or product information or history of transactions? The point of this speculative exercise is to illustrate the vastly important role that information provides in the success of your business. It is as critical as well trained, engaged employees and well functioning facilities and technology. But often, companies rely on their people and their technology to piece together fragments of information instead of treating data as its own asset, worthy of dedicated resources focused solely on its value.
Investing in Data Governance Quality and Measurement
Fortunately, people and technology are great enablers of high value data and usually they know exactly what their data and information needs to become more valuable. What is often missing then is the leaders and investors to recognize the importance of treating data as an independent asset worthy of strong management and investment.
How can a leader or an employee recognize when a dedicated focus on data enablement or data governance practices could make the difference between success and failure? Imagine asking the following subset of questions to answer this question.
- Does the success of the company or the product or the project require strong alignment and collaboration between the business and technology? If the answer is yes, data governance is a great enabler of collaboration because data sits at the intersection of business and technology and requires collaboration if data governance is included to facilitate clear data ownership, enablement of data stewards, prioritization and definition of critical data, and awareness, classification and protection of high risk data. Just like Human Resources ensures its business units have high performing, healthy employees, data governance ensures its business units have high performing and healthy data.
- Does the accuracy or completeness of the information coming into applications or coming out of solutions matter for the success of the company, product, or project? If the answer is yes, data governance is a great enabler of high quality data because data governance practices ensure data and information requirements are well defined and clearly articulated, provide visibility and monitoring to the current health of data, and ensure data issues are owned and remediated.
- Would a single source of truth or unified view of your most critical business information increase the efficiency of your operations, increase the ability of your employees to provide better customer service, increase sales, or reduce costs by eliminating the discrepancies caused by multiple? If the answer is yes, data governance professionals enable unified views and single sources of truth using the principles of master data management.
Guiding Questions for Data Governance and Enablement
Additional questions that should prompt leaders and employees to enable success by seeking data governance resources:
- Is it unclear who is responsible for fixing a data issue?
- Do you wish you knew the full breadth of information available across the company so you could improve your ability to make decisions?
- Is there information you wish you had but your technology or application does not have that information?
- Do your employees spend a lot of time reformatting, cleaning, or correcting data before they analyze or report it?
- Do the numbers of your report differ from other reports, causing distrust amongst leaders or time spent reconciling, debating, or explaining the differences?
- Does it take longer than you’d like for new employees to get up to speed on where data is, what data they should be using, or understanding what data means?
- Do you wish you knew where the data in your reports comes from? Or how reliable the source data is?
- Are you interested in data governance but hold off because you think it requires the purchase of a dedicated data governance tool?
Shoring Up Data Governance Quality with Hakkōda
Despite its lackluster and misleading name, data governance is a powerful capability because it sits at the crossroads of business and technology and provides the practices to enable unified, powerful, well understood organizational information that enables well informed, empowered employees and highly optimized technical solutions that directly contribute to your organization’s central mission.
For many enterprise leaders, however—especially those in complex, tightly-regulated industries like financial services and insurance—getting data governance initiatives off the ground can be a harrowing challenge. Indeed, according to findings from Hakkoda’s FSI State of Data report, 49% of industry data leaders identified ensuring data quality and governance as a major operational challenge for their organization.
The good news? These organizations don’t have to implement and enforce data governance quality measures alone. With 74% of FSI orgs reporting they will need a “moderate” to “large” amount of outside help in modernizing their data stack in 2024, data partners like Hakkoda are taking a more and more active role in helping businesses plan and implement data governance frameworks that align with their objectives and scale with their business.
Take, for instance, Hakkoda’s success in working with a large regional bank that had struggled to accelerate the adoption of an existing data governance program due to deep misalignments between business and technical teams. With the help of Hakkoda’s industry experts and scalable data teams, the bank was able to reconcile its business and technology goals, implement end-to-end data governance practices, and build a Snowflake Data Vault—all within a tight 5-month timeline.
The time has come to set data governance free from its long history of misunderstanding. Ready to see how a robust data governance framework can help your organization align its business and technology goals? Let’s talk today.