Talk Data to Me
There’s a phrase that gets used a lot in the nonprofit world: data driven. We put it in grant applications, strategic plans, and board presentations. But how many of us have actually paused to ask, what does that really mean? And more importantly, how do we actually get there?
Data isn’t just for researchers or evaluators. It’s for every organization doing meaningful work alongside organizations, communities, and systems. Here’s what every nonprofit leader needs to understand about data: why it matters, what it actually is, and how to start sharing it in ways that move the needle.
Why Data Matters — More Than You Think
At its core, data serves three essential functions. It informs our thinking by helping us challenge assumptions and making sense of what’s happening in the communities we serve. Data also shapes our decisions by giving us a foundation that goes beyond gut instinct or best guesses. And it drives our action by ensuring that what we do is purposeful and accountable to the people we serve.
When organizations don’t have a data infrastructure in place, leaders don’t stop making decisions. Those decisions, however, are just made on shakier ground. Leaders lean on intuition, historical patterns, anecdotes, or the loudest voice in the room. Sometimes those instincts are right. But when we’re talking about programs that affect vulnerable populations — young people experiencing maltreatment, families in crisis, communities navigating systemic barriers — we owe them more than our best guess.
Data, when used well, is how we redistribute power from assumptions to evidence.
So… What Even Is Data?
If we are pulling straight from the dictionary data is factual information. In another frame, data is qualitative or quantitative information that we use for research and evaluation. Both of these are true, and neither are enough. Data is what we use for critical thinking, deliberate decision-making, and strategic action.
Notice what that definition includes: qualitative information. That means the story a young person shares in an interview. The patterns a case manager notices in weekly check-ins. The feedback captured in a community listening session. These are data.
And notice what it requires: that the information actually be used. Data sitting in a spreadsheet or a file cabinet isn’t doing anything for anyone. Data earns its value when it informs a program adjustment, a funding ask, a policy recommendation, a conversation with a partner.
This is especially important for organizations working within larger systems or collaboratives. The data your organization holds doesn’t just tell your story — it can be part of a collective story that demonstrates impact at a scale no single organization can achieve alone.
Getting Started With Data Sharing
If the phrase “data sharing” makes you nervous, you’re not alone. Many organizations worry about privacy, losing autonomy, or not having the “right” data to contribute. Data sharing doesn’t have to be all-or-nothing, and it doesn’t require perfection to begin.
A useful framework for getting started breaks the work into six interconnected areas:
Purpose: Before anything else, get clear on why you’re sharing data. Is it to track outcomes across a continuum of services? To make the case for collective impact to funders? To improve service coordination? The purpose shapes every other decision including what data you share, with whom, and how.
Ecosystem: Who is at the table? Data sharing is a form of collective decision-making, and that means every voice within the impacted ecosystem matters (i.e., not just organizations, but the people you serve). A critical question worth sitting with: Who is in our collective ecosystem but doesn’t currently have a voice or a seat at the table?
Data Points: Once you know your purpose and your ecosystem, you can map what data already exists across organizations and identify any gaps. The goal is to find the intersection of what’s available, what’s meaningful, and what’s ethically shareable.
Legal Landscape and Governance: Some data sharing is straightforward. Other types require consent forms, data use agreements, or compliance with federal privacy regulations. Governance also means developing shared protocols about who can access data, how it can be used, and how it gets reported. This sounds complicated, but it’s really just setting rules of the road so that everyone is protected and knows the boundaries.
Tools, Resources, and Services: You need the right infrastructure to store, access, and analyze shared data. This might mean a shared case management system, a joint database, or even a shared data team. The right tools depend on your purpose and resources, but the key is not to let perfect be the enemy of the good.
Roles, Responsibilities, and Communication: This is the piece that often gets overlooked — the who behind the data. Who is responsible for entering data? Who analyzes it? Who presents it to decision-makers? Who communicates it to the community? Purposeful, clearly assigned roles are what turn data infrastructure from a plan into a practice.
Building a Data Infrastructure That Lasts
For nonprofits doing systems-level work, such as building coalitions, coordinating across providers, or advocating for policy change, data infrastructure is a core part of the work. It’s the connective tissue that holds system level work together.
The organizations making the biggest difference aren’t necessarily the ones with the most resources. They’re the ones who know what’s working, can prove it, and can adapt when it’s not. That capacity starts with data and with the relationships and infrastructure to share it.
You don’t have to have it all figured out to get started. You just need a clear purpose, the right people at the table, and a shared commitment to learning together.
That’s what it means to talk data.
