Understanding data governance best practices at DGIQ

So you convinced your business leadership that investing in a data governance program is in the best interest of the company. Now what? While embarking on a data governance program is an exciting time for any enterprise data management team, it can also be a big undertaking. With little example to follow, those beginning a data governance program, and even those who have implemented one recently, would be wise to follow industry best practices and learn from some of the cautionary tales out there. Knowing what works, and what doesn’t will help you get your program stood up faster and with greater efficiency. Here are the data governance best practices that we saw throughout the 2018 Data Governance and Information Quality (DGIQ) conference: 

1. Start with your culture
Data governance can be a tricky thing to get right because so much of it depends on creating policies and procedures that every person at the organization can abide by (or at least by those who interact with the data). However, anytime we’re asking employees to follow a set of processes, we should expect the opportunity for human error to be present. It’s just a reality that employees interpret rules differently, and, despite their best intentions, they can cherry-pick the rules that they will follow.

At the end of the day, your governance program is only as effective as the employees who abide by it. That’s why data governance should be embedded into the culture of a company. You can start by answering the following questions publicly and consistently: Why do these policies exist? Why should employees follow them? What are the consequences (to the business and to the employee) if they do not? Once the purpose of the program is made clear, further solidify understanding by making the program something every employee can understand. To many in the business, the term “data governance” can seem bureaucratic and harken back to failed attempts to launch a program, so consider using an alternative term that doesn’t evoke negative sentiments. Many in the industry have coined the phrase “data asset management” as a way to make governance a bit more relatable to the business.

2. Create a cross-departmental committee
The most effective data governance programs are not run in silos; they’re run by a collaborative committee made up of department-level stakeholders from across the business. This not only includes stakeholders from IT, but also sales, marketing, finance, customer service, and so on. The benefit of this approach is that it ensures data definitions, rules, and processes are relevant to all areas of the business. This committee should meet regularly to identify data governance projects and work systematically and collaboratively to accomplish them.

You will want to avoid creating a committee that is too large to get anything accomplished, however. The leadership team at retail giant Amazon has the two-pizza rule, which essentially says that an effective team is made up of no more members than can be fed by two pizzas. It’s a good rule to thumb to follow for creating effective teams, and it also applies to creating an effective data governance committee. In addition, we must also remember the unavoidable reality that people leave businesses fairly frequently, so your committee should be set up in a way that establishes a clear line of succession within each department, and document work to ease the transitions. That way, when a member leaves there is little ambiguity as to who will replace them on the committee, and knowledge is not lost with the departing employee.

3. Operationalize data governance
Lack of forward momentum is the natural-born enemy of your data governance program. How so? Many in our organizations, including business members and those in IT, tend to think in terms of projects that have a defined beginning and end. It’s just how we’re programmed to think. To that end, many will think about your data governance work as a means to end. What we need to do is to operationalize data governance so that it becomes an ongoing, business-critical effort.

When it comes to making your data governance program sticky, it’s important to stress the importance that data plays in our businesses today. Our 2018 global data management benchmark report finds that 95 percent of C-suite executives say that data is integral to forming their business strategy. With that much dependence on our data, we must ensure that it is managed and leveraged appropriately. And with the growing volumes, variety, and velocity of data, our challenges today will be different from our challenges tomorrow. Data governance must be seen as fundamental to our businesses. Just as no organization could do without accounting, data governance should be seen as an equally crucial piece to supporting overall success.

4. Tie to business metrics and report consistently
Those involved in data governance programs know just how impactful they can be. Having the right data definitions and accountable data stewards can really improve business efficiency and reduce information risk. With that said, there tends to be a disconnect when it comes to translating that value into terms executives can understand. That’s why you should always be thinking about metrics from the moment you begin your program. What projects can you undertake that tie back either to larger business objectives or can be measured in a quantifiable way?

While not every project you accomplish can (or should be) tied to a dollar amount, organizations that have successful data governance programs demonstrate the ability to report on business-related metrics. For instance, if your organization has a goal to increase customer retention to 90 percent over the next year, how can your data governance program support that initiative? How can you show that changes to the way you govern and manage customer data ultimately helped your organization achieve that milestone?

Securing buy-in for a data governance program is only half the battle. Actually implementing and maintaining a data governance program is the other half. While many organizations have recently jumped headlong into governance programs to improve their data processes (GDPR comes to mind), the path to a successful long-term program can be wrought with obstacles. The easiest path to success is by following in the footsteps from those who’ve done this before. By understanding data governance best practices such as these, we can all ensure we’re set up for success.

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