How to Make Data More Manageable—and Trustworthy

eWEEK DATA POINTS: Whether dealing with a slew of errors or getting overwhelmed by an overload of information coming from a staggering number of sources, tech and business teams are struggling with data. The end result: data that never reaches its promise and is often untrusted. To address this, Experian recommends the following best practices.

data management

“The data is wrong. … We can’t format it with our existing tools. … There’s so much of it—coming from everywhere! We can’t keep up with it all!” Do these complaints sound familiar? If so, you and your organization are in good company. In its recent report, titled “2019 Global Data Management Research,” Experian reveals that virtually all businesses are dealing with poor data quality, while frequently encountering multiple challenges in attempting to manage it and maximize its value. In fact, many teams simply do not “trust” the data they have to work with.

With continuing frustrations and a lack of progress in addressing them, C-suite leaders may take notice and “pull the plug” on funding. Therefore, CIOs and their teams must work with their business counterparts to develop comprehensive strategies that, for starters, identify the root causes of issues, while getting the right tech solutions and talent in place to eliminate them. They also need to come up with a plan that secures both immediate and long-term “data wins.”

In this eWEEK Data Points, we present the problems with data, as well as best practices to effectively manage it while restoring the “trust factor.”

Data Point No. 1: Pain points abound for data management.

Nearly all organizations say poor data quality has negatively impacted them. Why? Because information often ends up being too incomplete. Or it’s too difficult to corral because it’s spread out among a large collection of sources. Or it’s too unwieldy to manipulate to gain meaningful insights. Or an abundance of human errors leads to inaccuracies. All of this combines to create a lack of trust in data. To resolve these and other obstacles, consider the following best practices.

Data Point No. 2: Conduct a thorough assessment of your data “landscape.”

To understand where your data oversight needs improvement, inventory and assess enterprise-wide where it originates, how it is used and which technologies are in place to manage it. Then, drive to the root cause of data quality problems to better recognize how to solve them.

Data Point No. 3: Develop a comprehensive strategy.

The strategy should focus on how to improve information management over time. It includes, of course, the acquisition of tech tools to do this. (And make sure those tools are user-friendly, so nontechnical business teams can readily and successfully put them to work.) It also covers the recruitment and retention of the talent required to not only command those tools, but to cultivate a “data centric” culture within processes throughout the organization, to help prevent issues such as human error.

Data Point No. 4: Build upon “small wins.”

If it takes months or even years to reap rewards from data initiatives, stakeholders and key influencers will grow frustrated, potentially endangering funding. To avoid this, target smaller, easier wins to start with—like the improvement of customer contact information, which is usually riddled with errors that teams can fix quickly. Once you’ve compiled a steady track record of these victories, you’ll be better positioned to justify resources for longer-term projects.

Data Point No. 5: Gain buy-in from the top.

Without support from the C-suite, your strategy will go nowhere. Sure, executive leaders may “talk” the data talk. But without their genuine commitment, there’s a good chance that effective investment in the right tools and people won’t hold up over time.

Data Point No. 6: Decentralize ownership

Most companies still operate with a centralized data ownership model in which IT runs everything. But these same IT teams frequently juggle other responsibilities, such as cyber-security, so they may be too preoccupied to give data the attention it deserves. In addition, many business-side managers and users feel that their lack of control keeps them from accomplishing data-focused goals. A decentralized approach will bring data ownership closer to those who must leverage it to make good business decisions.

Data Point No. 7: Appoint a chief data officer (CDO)

CDOs do not replace IT. Rather, they deliver the strategic direction needed to ensure the right people have the right tools, and understand what outcomes are sought. That’s why the CDO must bring strong business skills and vision to the table, as opposed to solely tech knowledge.