Data governance: the key to building consistent, outstanding digital experiences

The investment required for data governance is the price organizations must pay for their teams to have access to the right data at the right time

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For modern marketers, data is the most abundant resource of all. Every team collects its own data, using its own preferred tools and methods for organizing that data. In fact, more often than not, marketers have more data than they know what to do with—and that just might be their biggest problem.

Data governance should be top of mind for organizations focused on customer experience. They cannot afford to neglect how they set up their data and what rules they put in place around managing that data. They need to consider reorganizing how departments work together to facilitate better data governance—which is no easy feat.

As difficult as this effort may seem, however, case studies make it clear: Improving your organization’s data governance to increase the availability of data will ultimately result in organizational efficiencies and unparalleled customer experiences. Here are a few ideas for how to make that happen as seamlessly as possible.

Keep analytics at the center of your data governance

Having worked with a number of organizations to establish solid data governance practices, I’ve seen a variety of successes and failures. The best predictor of success is whether there is an analytics-focused individual guiding the effort to consolidate data from various silos into one centralized group. This centralized group—often called a “center of excellence”—then defines everything from implementation and analysis to reporting, dashboard design, and optimization.

Southwest Airlines, implemented a tag management system to track and analyze its data points. Planning was key to Southwest Airlines success. After several process meetings, they decided a phased rollout would be best—which included eliminating duplicate codes and using shared code language. To achieve this task, Southwest Airlines reallocated resources from its IT department to its marketing department. Dedicating a team of analytics-minded individuals to this task ensures that Southwest Airlines always has a standard version of the truth that the business can rally around.

Invest in products, definition and processes

Successful data governance requires more than just getting a bunch of analytics folks together in a room. It takes real investment in time, money, and resources. Budget needs to be set aside for the right software, of course. Then it also takes time to create the level of definition—attributes of data—that will make the effort successful. That definition must include things like templates, data layers, and ownership of the tag management system. The more definition the governance team is able to create, the more successful they are going to be.

These definitions are often housed in a measurement plan, a list of business requirements, and a solution design reference, the technical specifications for how those business requirements are captured and who owns them. Without those simple definitions in place, even if a company has smart analysts, it will inevitably find itself in trouble, and lose those analysts to companies that have processes that are better defined. Having a well-governed data strategy leads to a happier workforce—because nobody wants to spend 80 percent of the day fixing broken data. Instead, analysts prefer to spend 80 percent of their time analyzing and presenting!

When Zebra Technologies acquired Motorola Solutions, it inherited 15,000 digital content assets, the data for which could have quickly gotten out of hand. Fortunately, Zebra went to work, immediately laying down processes and definitions by which it would bring all that data together in a consistent fashion, and in sync with its existing assets. The result: Zebra can now analyze data across all its assets, old and new, to deliver superior experiences for its customers.

Train your team for success

Once your department’s data is flowing accurately, training should absolutely be your next priority. Analytics training should be built so anyone from the center of excellence can present the training to any team. Using a “train-the-trainer” format also allows anyone to teach it to new employees or team members at any time.

This can be done in one of two ways. First, structured classroom-type sessions where anyone is welcome to attend and learn can be a great way to introduce people to analytics in an organized manner. Then, second, unstructured sessions—which can be an opportunity to show off cool new features, answer questions, or discuss future plans—are an equally powerful way to improve understanding around the need for and benefits of data. Be sure to include all aspects of the governance process in your training sessions too: understanding metrics, aligning them with proper dimensions, creating performance scorecards, performing ad hoc analyses, and even the processes and techniques for ensuring high-quality data.

Paying the price for better digital experiences

While data governance definitions and processes may seem rigid, the benefits are worth the effort. Sarah Bryowsky, digital marketing director for Zebra’s Global Demand Center, sees the benefits—and results—from implementing data governance:

“We’re already seeing returns from improving our digital experiences,” Sarah says. “Organic keyword rankings have gone up 300 percent year-over-year, on average, while our global website traffic is up about 13 percent year-over-year. We’ve also seen the time spent on site rise for high-value pages—a key indicator we’re delivering more valuable content.”

The investment required for data governance is the price organizations must pay for their teams to have access to the right data at the right time. But the benefit is being able to consistently deliver the outstanding customer experiences that will keep them far ahead of their competition.

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