Data Quality: Villain or Hero?

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Any fan of comic books knows that the beloved characters often fall into one of two camps: heroes or villains. Often, it seems to me that Data Quality is considered in a similar way. Historically, Data Quality programs have often been looked at as a villain in many organizations, so the question is…is there any hope of a villain becoming the hero?

Although she may not be the perfect example of the transition from villain to hero, Marvel’s Black Widow certainly overcame her evil past to contribute to good. As the story goes, Black Widow was raised to be a spy who worked for the bad guys. Through experience, growth, and perspective, she changed her ways and ultimately became a force for good. For those of you who still think of it as the antihero, I hope that you might give Data Quality the chance to redeem itself much like Black Widow did.

I can understand how many organizations see Data Quality as a greater evil than good. Many invest tens, if not hundreds, of thousands of dollars on trying to improve their Data Quality. Whether they are trying to match records across different systems to create a single customer view, or append additional attributes from a third-party, Data Quality can be a costly endeavor.

Even after these major investments, Data Quality is constantly in a state of flux. Since it’s so difficult to reach 100% quality data, it can be frustrating to see problems arising all the time. Even for organizations that have worked hard to achieve sophisticated levels of Data Quality, past perceptions of inaccurate data can come back to haunt them. When users across the organization are skeptical of what the data says, they are more likely to simply rely on gut feelings or educated guesses, potentially leading to poor decisions that can have dramatic impacts on the business.

While these potential issues might lead to the belief that the Data Quality program is a burden, with the right approach and the right expertise, Data Quality can redeem itself and become the hero of your organization. In virtually every industry, decision-makers are starting to look to data to inform important decisions and drive strategy. A strong Data Quality program can be the key to unlocking the many potential benefits that trusted, reliable data can bring to your business. Effective Data Quality practices can help you to establish trust in your data. When users trust the data and what it’s telling them, they start to look at it as a true asset. It’s not easy, but the efforts are well worth it.

Think for a moment of a marketing team at a large retailer trying to determine if it’s worth doing another promotional giveaway to boost sales. They look at the data and see an overall increase in revenue and margin from three of the last four giveaways they conducted. There is that one giveaway that resulted in a net loss, but even more troubling is the fact that there have been some reporting issues in the past, so they aren’t sure what data they can trust and what is inaccurate. What should they do? Though there are limited data points, based on the data alone, a giveaway seems as though it would have a good likelihood of generating good results. Without that trust, however, the team is paralyzed with doubt. They aren’t in a position to risk the profit loss, so they decide against a giveaway and miss out on the revenue gains.

Now think that the whole dilemma could have been avoided and the right decision could have been made quickly with a little help from that pesky (or is it?) Data Quality. It’s easy to see how putting in the work could add value to your organization.  In fact, through sophisticated Analytics, along with trusted data, companies are now seeing Data Quality not as the historical cost burden but as a revenue generating activity!

It’s always easy to hate the villain and to love the hero…but what happens when someone with a murky past manages to comeback and work for the side of good? Black Widow didn’t go from bad to good overnight, and your Data Quality program similarly may take time to turnaround. As with most things, it takes hard work, determination, and endurance to see big changes, but I have yet to work with a customer who wasn’t glad they put in the effort. With the many potential benefits of trusted, accurate information, Data Quality could certainly go from the villain to the hero of your organization.

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