As an IT manager, you find yourself in a difficult predicament. Senior management wants the organization to become data-driven, but you know that data quality leaves much to be desired in many areas. And that’s where the classic chicken-and-egg problem comes in—the one that causes many data projects to stall:

• The Chicken: You need high-quality data to truly work in a data-driven way. Without reliable data, no one will dare to make decisions based on a dashboard.
• The egg: You have to start working in a data-driven way to truly feel the pain and consequences of poor data quality, so that the organization recognizes the urgency of investing in it.

As long as you remain stuck in this vicious cycle, nothing will happen. You’ll keep talking about the abstract importance of data quality, but because the pain isn’t immediately felt, it never gets the priority it deserves. It remains an “IT problem” that gets put on the back burner.

The breakthrough: Stop talking, start feeling

The solution to this dilemma might not be what you'd expect. Stop trying to get the data quality perfect right away. Stop talking about the abstract concept. The breakthrough lies in making the pain of poor data visible and tangible.

How? By consciously initiating an important, data-driven process—even with the imperfect data you have right now.

Choose a process that is critical to a department—for example, the process related to housing changes. Automate this process and base it entirely on data from the source systems. Then see what happens.

• When a new property can’t be rented out for weeks because the data is incomplete, the pain of poor data quality suddenly becomes very real. It’s no longer an abstract percentage in an IT report; it’s immediately tangible, lost rental income.
• When an employee spends three times as much time on a transaction because he has to correct data manually, the hassle turns into operational frustration.