Measuring Success | Is Big Data Too Big for Non-Profits?
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Is Big Data Too Big for Non-Profits?

23 Jul Is Big Data Too Big for Non-Profits?

Why Big Data remains elusive for the non-profit sector and how collaboration can help

By Hannah Romick


The words are ubiquitous. Big. Data. Everyone wants it. The for-profit sector has flocked to Big Data like kids to an ice cream truck on a hot summer’s day. This should come as no surprise. For-profits rely on data to understand consumer behavior, justify strategic decision making, and ensure the best financial outcomes for shareholders. But what about the non-profit sector, the sector that makes up 5.5%—nearly $800 billion—of our economy? What role does Big Data play there? What role should Big Data play there?

First of all, we must frame why the word “big” could mean something different to non-profits than it does to for-profits. In the non-profit sector, Big Data is big not just in size but in complexi- ty due to the challenges inherent in applying data to social problems. After all, the social sector is not just concerned with bottom lines; it is concerned with the transformation of society. This transformation often occurs on the human, interpersonal, and emotional level—difficult areas to measure.

What we also find in the non-profit sector is that Big Data often includes big tactical difficulties. Gone are large corporations’ enormous servers with their computational fire-power. Missing is the financial and human resource capacity to perform robust data analysis. Instead, we find non-profits with passion for achieving audacious goals but lacking in- sights on how to start and ultimately direct their efforts.

Despite these many challenges, there is hope for the future of Big Data in non-profits. We have seen time and again that when organizations come together to combine databases, they achieve outcomes they never could on their own. In such situations, smaller organizations with fewer resources can leverage a larger institution’s ability to financially support the data collection and analysis.

Is more data really better than less? The irony is that as data gets bigger, and more complex, it gets significantly more precise. As we merge organizational datasets together, a clearer picture emerges of the unique attributes and pathways of an individual. Working together helps us understand people better and serve them. Is that not the whole point of non-profits in the first place?

In a project we are currently working on in Dallas, the merging of 45 datasets from school districts, social service groups, and non -profits is helping determine the drivers behind whether or not a child graduates from high school. It is the pooling of data from multiple organizations, not the data from one single entity, that helps provide a comprehensive picture of children’s academic performance. The project will provide analyzable data come this fall and we look forward to sharing the results.

There are many non-profits that are making inroads in bringing data together. The concept of undergoing these collective pro- jects is making its way around communities throughout the nation. Implementing these initiatives will prove to be the challenge. Despite the difficulties, though, we know that data collaboration offers us hope that we can achieve even greater things.

So, is Big Data too big a challenge for non-profits to tackle? The first step towards successful use of Big Data occurs when an or- ganization fundamentally acknowledges that more data is better for a community success than less. Only when organizations let go and share their data (in a responsible way) will Big Data deliver on its promise for the non-profit sector.