Data Quality: The Hero or Villain in your Transformation Story?

By: Karen Menard

Have you ever had a week when everything seemed to be sending you signs? That happened to me last week.  

First, Christine Haskell’s article on the return on investment from data quality grabbed my attention, and it really resonated with me and the typical challenges faced by charities and not-for-profits as they attempt to grow and demonstrate their impact. If you haven’t seen Christine’s work, I recommend reading it. She’s a brilliant leader in this field whom I hold in high regard. Second, in a digital transformation planning meeting with senior leaders, one executive made a comment that nearly made me jump out of my seat with excitement. Instead of focusing on the technology or timelines, he emphasized the importance of data quality work for the project and the institution’s success. I’d like to think my well-designed graphic helped, but the real reason is that he understands the core issue. Data quality is the foundation. It’s not just an IT task or something to delay. Everything else depends on it. Like this executive, anyone leading change or operating with limited resources in the not-for-profit sector should begin by understanding the role their data plays in supporting or impeding their progress or transformation.

 Why This Matters? (Hint: It’s Costly) 

Poor data quality is expensive for organizations. A quick Google search shows a widely cited figure: $12.9 million in annual losses, according to Gartner. Despite this cost, only 24% of organizations say their data is high-quality. In the not-for-profit sector, where dollars are tight and resources are lean, this leads to real challenges. Universities and colleges have many systems (and I mean many!), but still struggle to answer basic questions about student outcomes or the true costs of a program. Charities with scattered client records struggle to demonstrate their impact and risk losing donor funding. Municipalities trying to modernize services often find that old, incomplete data slows everything down. 

The good news is that investing in data quality pays off. Organizations often see results quickly. For example, one university saw a 28% increase in alumni participation and a 70% increase in response to fundraising appeals after implementing data-driven targeting using clean alumni data. 

You don't need a $2M data platform or a large IT team. Start with one decision that matters.

Where Do You Start? 

People often ask me where to start, and it’s a great question. Data quality can seem overwhelming. My advice is simple: don’t try to fix everything at once. What you really need is clarity, focus, and the freedom to start small. 

If you’re not a data expert, and most leaders are not, here’s what you can do right now. Start by asking yourself: What is the one decision/issue we need to improve? It could be student retention, patient outcomes, or service delivery efficiency. Once you know, focus on improving the data for that decision and measure the results. 

First, ask your team how confident they are in the data used for the decision you’re focusing on. Listen closely, you’ll learn a lot. Second, start small. Pick two or three data points that support that decision and need some TLC. Focus on making those supporting data points as accurate as possible. Third, make data quality a leadership and organizational priority, not just an IT task. To keep it top of mind, try simple steps, such as starting each team meeting with a five-minute data check-in. Choose a practice that aligns with your culture and demonstrates why data quality matters. Make it a habit, and soon your team will treat data as an asset to nurture in their everyday work. 

Celebrate your first clean-data win as a team success. Share this achievement across your organization to build excitement and sustain momentum. 

It All Comes Back to Leadership 

Before your organization can focus on digital transformation, improve the client or student experience, or get ready for AI, it needs to address data quality first. This isn’t just an IT problem; it’s a leadership challenge. Clean up your data and see what changes it brings. 

Talk about it, ask about it, and show that it matters. 

Digital and organizational transformation doesn’t fail because of the wrong technology. It fails when the foundation is weak. Data quality is the foundation.