The biggest gulf between for-profits and nonprofits is data.

 

Data fuels business. Global spending on big data analytics is projected to reach $1.1 trillion by 2032. Companies invest so much in technology and talent because they know that collecting, analyzing, and acting on data is a proven path to growing revenue. In data, they find better ways to anticipate customer needs, focus their operations, direct resources and spending, and more effectively fulfill their missions.

 

Not so in the social sector, where limited resources and fragmented data have left nonprofit organizations decades behind their for-profit counterparts. Like for-profit companies, the social sector wants to measure and scale the impact of its work and better realize its goals. That’s just much harder to do when you don’t have reliable sources of data or can’t scale the data you have.

 

But there is a way for nonprofits to overcome this data divide and build the systems they need to leverage data without spending budget they don’t have or hiring Ph.D.s in machine learning. Data refineries offer a path forward, and when done right, they can propel a new wave of impact across the social sector.

 

THE BIGGEST NONPROFIT DATA PROBLEM ISN’T A LACK OF BUDGET 

 

Nonprofits often lack the resources to convert raw data to useful insights, and certainly, that has contributed to the state of the data divide. But there’s an underlying problem that would hamper the industry even if nonprofits had the same budgets as massive businesses.

 

Across the nonprofit sector, data is fragmented and unstructured. It comes from case management systems, partner agencies, surveys, and other sources, and exists in all different formats.

 

Most nonprofits use data as it suits their own organization. It never leaves their walls, thereby limiting the opportunities to find broader insights. Few are working to aggregate data across organizations for analysis, but without access to shared data, it’s hard to measure impact or chart a strategic plan.

 

Sometimes, data is hard to come by, too. Because nonprofit staff are often overwhelmed and under-resourced, they focus their limited time on advancing their programs and serving their communities, and not on added tasks like data collection.

 

HOW A DATA REFINERY MAKES PROGRESS ON THE DATA DIVIDE

 

A data refinery is a system designed to transform raw, fragmented data into actionable insights. As much as it makes collecting new data more valuable, it also makes existing data more useful—but only if you approach its creation in the right way.

 

Here are four guiding principles to ensure the biggest impact for a data refinery.

 

1. Work With Constituents To Define The Problem And The Data You Need

 

There’s no use building a refinery of data that guides you in the wrong direction. To truly understand the problems you’re working to solve and the needs of the people you serve, you have to ask them. The communities you work with should be the origin of any data you collect, and data collection should be integrated with service delivery so that overburdened staff consistently gather data in the normal course of serving their communities.

 

For example, when we developed our Freedom Lifemap tool to track the needs of human trafficking survivors, we designed it so survivors can easily participate in identifying their needs and priorities for their recovery, ensuring we have the most accurate picture of their needs while supporting them.

 

2. Adapt Proven Methodologies

 

You don’t have to come up with your own system or framework for collecting and categorizing data. There are many methodologies available that you might adapt to your purposes.

 

The Poverty Spotlight, for example, is a proven model for tracking multidimensional poverty. It provides a structured way to evaluate various dimensions of need to ensure that interventions are targeted and measurable. Freedom Lifemap adapts this model to human trafficking, using a similar method to evaluate survivors’ needs. By using an established model, you can get results faster and avoid trial and error.

 

3. Focus On Visible, Tangible, Scalable Impact

 

When building a data refinery, make sure it’s visible, tangible, and scalable. 

 

Visible refineries ensure your data isn’t stuck in your organization, and invite partners and collaborators that can advance your mission.

 

Tangible solutions allow organizations to show clear progress in a way that’s measurable and comprehensible. For example, metrics around improved housing stability, better mental health outcomes, or increased employment opportunities provide concrete evidence of success.

 

Scalability is equally critical. Design a solution that works both in individual programs and across regions and organizations without losing effectiveness. For example, Freedom Lifemap tracks well-being across multiple dimensions that are universally applicable. This scalability ensures that lessons learned in one context can drive widespread impact, multiplying the benefits of the data refinery approach.

 

4. Prioritize Sharing And Collaboration

 

The value of data-driven insights is sharing them with others. By pooling data from across organizations around the globe, the entire sector can identify patterns, scale effective programs, and advocate for better policies and funding with clear evidence of the problem’s toll. 

 

Through sharing and collaboration, nonprofits can eliminate silos and work collectively to tackle systemic challenges with the most efficient and impactful solutions.

 

BRIDGING THE DIVIDE

 

Better data leads to better solutions. Just because nonprofits can’t afford to hire a team of engineers and data scientists or spend millions of dollars to better understand complex data doesn’t mean they can’t build effective systems. By rethinking how we approach data, we can ensure that every organization, no matter its size, has the tools it needs to make a measurable difference.

 

Data refineries maximize the impact of nonprofits’ existing resources and can create a virtuous cycle in which organizations are better able to drive meaningful change, make their impact visible and tangible, and, in turn, attract more support and resources. With more resources, nonprofits can move beyond solving problems case by case and scale their data refineries to better anticipate community needs and address systemic challenges.