Why the future of nonprofit data interoperability depends on shared meaning, not standardized systems. 

By 2018, many of us had spent years helping nonprofit organizations connect systems and use technology better. Yet the same challenge kept surfacing. 

The grant report is due on Friday. Everyone is working hard to show impact. Yet by Thursday, each team may be telling a different version of the same story. This isn’t about effort or skill; each group is measuring something different, e.g., outcomes, service delivery, evidence of impact, stewardship, sustainability. All departments describe the same organization, but the meaning behind their data is not always the same.  

Paper, the original operating system

Nonprofits are, without question, among the most resourceful organizations I know. Before dedicated nonprofit platforms, they ran on paper, spreadsheets, borrowed tools, and institutional memory. Information lived in filing cabinets, inboxes, and, most of all, in people’s heads. Processes depended on individuals who understood the work because they were closest to it.  

Technology existed, but almost none of it was built for nonprofits. Most systems were designed for businesses and later adapted to nonprofit organizations. What nonprofits lacked was technology that reflected the realities of their work. 

When nonprofit software finally arrived, it centered on fundraising

Fundraising was not the most important function, but it was the bottleneck. Without the ability to raise money, an organization could not deliver on its mission. As digital giving grew, donor data became a priceless asset, and technology focused there first. Blackbaud was a turning point. For the first time, organizations could see themselves in their software. That success shaped what came next. Data was built around donors, because donor data was the most mature, measurable, and accessible. Fundraising became the sector’s first shared language. 

Then, the cloud changed the way nonprofits build 

Cloud platforms shifted organizations from buying fixed applications to configuring systems for unique needs. Platforms like Salesforce took capabilities once reserved for the giants and put them in the hands of many.  

For nonprofits, this was liberating. Technology could finally adapt to each mission rather than forcing the mission to adapt to the technology. Organizations built systems that reflected their own priorities and ways of working.  

Everything worked, but nothing connected

What came next looked like progress, and in many ways, it was. Organizations adopted fundraising platforms, marketing automation, grant management systems, volunteer solutions, advocacy platforms, finance systems, and program applications. Most made the best choices they could with the information and constraints they had. Development teams built one way. Program teams built another, and so on. Each system solved a real problem but described the world in its own language. A donor became a constituent. A constituent became a contact. A contact became a participant. A participant became a volunteer. The words changed from system to system, even when the underlying reality stayed the same.  

One integration became two. Two became ten. Data moved from platform to platform. New consultants, middleware, and integration practices appeared to bridge the gaps. The integrations worked, but the connections were expensive, fragile, and depended on the people who built them. Moving information was only half of the challenge. Preserving meaning as data moved was just as hard. A technical connection did not guarantee shared understanding. Even as technology improved, a familiar challenge remained.  

Even when data moved seamlessly between systems could work perfectly, organizations still struggled to function as a connected whole. Nothing broke badly enough or visibly enough to force real change so the work continued. Organizations kept serving communities, raising funds, managing programs, and reporting outcomes. Beneath that progress, a deeper question remained: how do we preserve and enrich the meaning of data while information moves from one system and team to another? 

The consequences became most visible where misunderstanding carried the highest cost. In disaster preparedness and response, dozens of organizations, each with its own systems, funders, and processes, must coordinate under intense time pressure, where lives are saved or lost in minutes. 

The humanitarians got there first

That urgency pushed people across the sector to build something different. Through NetHope and other sector-led gatherings, the NGO Reference Model emerged - a shared framework for describing how an NGO operates. It was not software, but a way to understand the work itself, in the words of those who do it. Contributors brought perspectives shaped by decades of on-the-ground service, managing global operations, partnerships, finance, and programs. The NGO Reference Model proved that when the challenge is urgent enough, the sector can collaborate on shared solutions. But while it described the work, it did not solve how meaning could remain consistent as information moved between people, teams, and systems. 

The problem, beneath the problem

The problem beneath the problem comes into focus: moving information between systems was never enough. The real challenge is understanding what that information means in context.  

After more than twenty years working alongside nonprofit leaders, technologists, fundraisers, and frontline staff, I’ve seen some version of this challenge in organizations of every size and mission. The biggest technology challenge in our sector has never really been about technology. I've come to believe the challenge is not moving data between systems but preserving meaning as it moves. This was our thinking in 2018, and things were about to change. What mattered then was finding a way for people and technology to understand the same work, in the same way. The question was no longer “can we connect our systems?” it was “can we create shared meaning?” 

-Dan