Defining data is table stakes—owning and understanding it is what matters

The onset of the pandemic in 2020 brought an acceleration of digital transformation that no one was entirely prepared for, sending us years ahead of where many originally predicted we’d be by now. Companies are more dependent on data than ever before, and we are all (understandably) still adjusting to this new data-driven normal.

However, before we barrel ahead into even more innovation, it’s essential that we pause to ensure we understand and take ownership of the data assets we have been implementing thus far. As leaders, it is imperative that we examine our old technologies, take responsibility for the new, and create a democratized and streamlined system of data that will sustain us for years to come.

WHAT MAKES DATA VALUABLE

In the modern era, no business can thrive without utilizing data. In a survey, MIT Sloan School of Management faculty members Andrew McAfee and Erik Brynjolfsson found that companies using primarily data-driven strategies benefited from 4% higher productivity and 6% higher profits.

But data is only as valuable as the number of people who know how to use it. For our data-driven strategies to be effective, the data needs to be accessible and legible to all involved in the company, not just IT. It is democratized data that is valuable and enables every member of the company, from operations to finance and marketing, to speak the same language.

Data democratization across the company improves traditionally siloed structures, creating more organizational agility and streamlined processes. But it can only work if the data can be trusted and is properly governed to minimize discrepancies. “Bad data” often leads to poorly informed decisions that can cost significant time and money in the future.

I’ve seen cases where projects have experienced significant delays because the assumptions and expectations around the data output were wrong. These projects were then forced to go back and identify at what point the misunderstanding occurred, causing extensive (and avoidable) delays.

To truly take advantage of the advancements in data collection, it will not be enough to merely go through the motions, receiving spreadsheets without understanding how the data assets were achieved or how they will be governed at our companies. We have to take our data assets seriously and put in the time to govern our data responsibly to achieve optimal performance.

DEALING WITH DATA DISCREPANCIES

Though data is often collected through artificial intelligence, it is not a simple “set it and forget it” task. Without dedicated digital governance, data discrepancies and “bad data” will thwart our continued success.

Suppose your finance team thinks about and utilizes a particular data asset differently than the operations team. In that case, you are likely to face data discrepancies across the two functions, potentially causing the company to make ill-advised or uninformed decisions. In these cases, you may end up with multiple sources of the same data and will be sent down the rabbit hole of attempting to reconcile each source. To avoid this, you can implement robust governance and systems of record for each set of data, working together as teams to understand exactly how and why each data asset is used.

Data governance is a collaborative effort. The majority of data assets have cross-functional implications, which means they also need to be understood cross-functionally. If each team refers to the same set of data in different ways, you will encounter frustration and discrepancies when you go to build reports or do analytics.

So before you march forward with a new and exciting data tool, take the time upfront to understand your data assets and how you govern decisions around them. If you separate your technology understanding from your general business understanding, you risk running into roadblocks, potholes, and detours that could have been avoided.

TAKE CONTROL OF YOUR DATA QUALITY

Many business leaders fail to understand that IT alone does not own the data. They may collect it, but the business as a whole owns the data, and as such, business leaders need to take full responsibility for its quality, both internally and externally.

Internally, this means taking actions such as defining a clear data framework and establishing robust measures and controls. Externally, this may look like establishing a shared understanding of the data systems in place as soon as you begin onboarding new clients or collaborating with them to help them improve their own data quality.

When business leaders don’t take ownership of and fully understand the value of their data, it becomes that much harder to ensure data quality remains at a sufficient level to provide accurate, actionable, and consistent signals to inform data-based decisions for both the company itself and the clients they serve.

DATA IS THE ENGINE

In this new normal, business leaders can improve the utility of their data by fully understanding its value and taking steps to ensure its quality is protected. The longer you go without taking responsibility for your data and implementing data governance strategies, the more discrepancies and bad data will arise, with each compounding on the others. Every time you plug one hole, a new one will appear, and the whole pipe will burst before you know it.

In utilizing data, we have to slow down to speed up. If we work to establish a deep understanding of our data systems from the beginning, the data can become our engine rather than a roadblock, allowing us to move seamlessly from project to project and propelling us into an exciting future.

Jeanine L. Charlton serves as Senior Vice President & Chief Technology & Digital Officer at Merchants Fleet.