Data Science, a Critical Tool in the Nonprofit World in 2015

In Viewpoints by Brian LangeLeave a Comment


In 2015, the social sector is changing. Nonprofit organizations are realizing the many benefits of utilizing data to effectively assess the impact and value of their work. However, many of these organizations, particularly the smaller ones, can feel intimidated by the many methods, products, and sources at their disposal. What many nonprofits don’t realize is that they can focus on small pieces of this collected data and organize it into ways that are both simple to understand and useful.

“What many nonprofits don’t realize is that they can focus on small pieces of this collected data and organize it into ways that are both simple to understand and useful.”

Thanks to falling costs of storage and computation and new methods of collecting and analyzing data, there’s never been more opportunity for nonprofits and foundations to adopt evidence-based practices in their work. This could help them drive new fundraising opportunities, grow membership and uncover potential problems ahead of time.


Every organization out there—nonprofit or otherwise—can become more efficient and forward-thinking by incorporating some data-driven approaches, tools and methodologies into their workflow.


Nonprofits tend to focus on “measuring their effectiveness” so that they can raise more money for their organization. To do this, they tend to be sold on the age-old mantra of building and buying a data warehouse and then buying business intelligence tools to make sense of this data. This is the same trap that for-profit companies face, except that nonprofits tend to operate on a slimmer budget and often with a smaller “data team,” if any at all. Paying for big name products and services out of the gate is a daunting upfront investment in which the returns are far from certain.


Non-profits can get started with data science by taking inspiration from the lean startup, human centered design and agile programming movements. They should begin the process by finding a real problem within their organizations that can be solved with data, and then work backwards to figure out what data should be stored and how it needs to be analyzed. The idea behind these movements is to build fast and build cheaply to test ideas and deliver value early in a project lifecycle. These early tests become a base to iterate towards greater things.

“A totally different way of using data as a nonprofit is by using data to drive your own organization. “

Here are a few real-life examples of how nonprofit organizations utilized data science to better themselves:


  • Research Corporation for Scientific Advancement (RCSA) is the oldest scientific funding group in the US. They recently started a conference called “Scialog” to help scientists connect to create innovative solutions to the world’s most pressing challenges. However, measuring the impact of a conference is tricky. How could RCSA quantify the success of the Scialog program? To solve this, our team ended up doing a number of small analyses over the years to help them better understand (i) how much Scialog was fostering connections between conference attendees, (ii) which components of the conference had the most substantive impact, and (iii) to create environments at the conference that most effectively enable the most innovative connections.


  • IssueLab is an organization that is devoted to cataloging the world’s “gray literature”. They collate thousands of insightful white papers from non-profits around the world and put it all in one place in order to make these documents as accessible as peer-reviewed research. The challenge was getting people to engage with the content. For instance, a 200-page manifesto from the World Wildlife Foundation can be very intimidating; is it worth it to read the document? To determine the answer, we developed a suite of analysis techniques that summarize the content of the various manuscripts that IssueLab collects to help the organization’s users more quickly find and filter relevant gray literature.


  • A totally different way of using data as a nonprofit is by using data to drive your own organization. For example, the Red Cross responds to thousands of fires around Chicago. So, how can they best use their resources to most effectively meet the community’s need? We brainstormed with the Chicago Red Cross to help them evaluate how they could use data to better meet these needs of the Chicago community.


Whether it is to better quantify the success of your organization or to improve your organization’s workflow, data science can be a useful tool for all nonprofit organizations. “Big data” seems daunting and many of the tools sound expensive. Rather than investing in tools, develop a core competency around “problem solving with data” (for more, see this 15 minute video clip) and you will make enormous strides, even when you’re on a tight budget.

Many thanks to Brian Lange for his contribution! Be sure to follow Datascope Analytics on Twitter at @DsATweet, and Brian at @bjlange

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