Importance of Data Quality: How to Explain it To Your Boss
As an IT professional, you know what data quality means and why it’s important. But does your boss? If not, it’s time to explain the importance of data quality to the higher-ups in your company, in order to ensure that you have the tools and support you need to manage data most effectively.
For the purposes of this article, we’ll assume that your boss lacks special technical expertise related to data management. We’ll also assume that his or her main goal is to drive business value and cut costs.
We know: Those may be somewhat stereotypical assumptions. To be sure, not all bosses are technical know-nothings, and not all of them see the world only in terms of dollars and cents.
Still, to a greater or lesser extent, these are the core challenges that many IT teams face when trying to gain support from management for the tools and processes they need to manage data quality effectively. Even if your boss has an above-average level of technical expertise, that skillset may or may not extend to the nuances of data quality.
Five tips for explaining data quality to your boss
That’s why it’s important to develop a strategy for communicating the importance of data quality to your boss. The following pointers can help.
1. Explain the importance of data quality in real-world terms
You might think of data quality issues in terms of database index problems or dirty disk partition tables. But unless your boss works alongside you in the IT trenches on a daily basis, he or she probably doesn’t understand these technical concepts
That’s why you should talk about the importance of data quality using real-life examples that are easy for someone without deep technical knowledge to understand. For instance, you might say that a data quality problem occurs when a database contains multiple entries for the same person. That’s a pretty simple problem to understand.
Similarly, you could discuss the example of foreign or special characters within words that are formatted incorrectly. Chances are that your boss has seen this problem in action, and can understand why this issue could cause data management challenges.
Assessing data quality on an ongoing basis is necessary to know how well the organization is doing at maximizing data quality. There are a variety of data and metrics that organizations can use to measure data quality. We review a few of them in this eBook.
2. Emphasize that data quality matters to customers, not just you
Bosses might be sympathetic when you tell them how data quality problems make your job harder. But if they think that the problem stops there, they are less likely to be sympathetic, because a harder job for you does not necessarily mean a problem for the business.
But when you explain that data quality problems can also impact customers — by, for example, leading to lost records or making it hard for support staff to reach clients — bosses are more likely to recognize the imperative of protecting data quality.
3. Explain that data quality management requires people, tools, and processes
You want your boss to understand that when you talk about the importance of data quality, you’re not just trying to get him or her to sign off on a purchase order for a new tool or server. You instead want holistic support for all of the people, tools, and processes that you need to get data quality right.
Depending on your circumstances, improving data quality may require hiring new IT staff. It may involve purchasing new tools. Or it might require implementing new company-wide data management best practices. No matter what you need, you want to ensure that your boss is ready to help you get it.
4. Present data quality assurance as a continuous process
For similar reasons, it’s important to convey that achieving data quality is not a one-and-done type of task. You don’t just set up a new tool or process and consider your data quality problems permanently solved.
Instead, data quality requires an ongoing commitment, as well as continuous monitoring and improvement. This means you’ll need your boss to be on board with data quality for the long haul. Revisiting the data quality conversation on a routine basis with your boss, and presenting data to show how data quality is improving over time — and could be improved further — is one way to help him or her appreciate the continuous nature of data quality.
5. Stress that data quality challenges are getting harder, not easier
Finally, you want to make sure that your boss understands that data quality problems are not something that will go away on their own, or that you’ll just learn to cope with. On the contrary, they tend to become greater in scope, due to the ever-increasing volume of data that companies collect, as well the need to integrate data across diverse IT infrastructures that are composed of different types of legacy and modern technologies.
To learn more, read our eBook: 4 Ways to Measure Data Quality