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Grants Managers: How to Think Like a Data Scientist

Chances are, if you began your career as a grants manager 10 or 15 years ago, you didn’t consider yourself a tech pro, or a data wizard. You probably used a computer every day. And you became adept at office applications like Excel and Word. But still, there probably was a whole lot of paper in your life.

How times have changed.

In fact, not only are grants managers expected to comfortably navigate the digital world, they are increasingly embracing the role of “data expert” at their foundations. It turns out, grants managers are uniquely positioned to access and help make sense of the growing stream of data now available to grantmakers.

“The role is starting to require a better understanding of data – how you can use it and what you can do with it to inform decision-making and ultimately improve grantmaking,” says Anuar Juraidini, program officer, strategy and research at the Citi Foundation. A former grants manager at the foundation, Juraidini says that a natural shift is underway, from a role that used to be heavily administrative and operational, to one where data and strategic thinking is taking on larger prominence.

But how should a grants manager with very little expertise in data, data collection, or data analysis become more savvy – and even begin to think like a data scientist?

First, What Kinds of Data are Important to Grants Managers?

Nowadays, data is everywhere. And technology has made it easier than ever before to tap into the free flowing stream of data for insights into all levels of your grantmaking. It can be helpful to understand the different types of data available and how these can be used for increased efficiency and impact, says Adriana Jimenez, Director of Grants Management at the ASPCA. Jimenez breaks the data down into 3 categories: process data, grantmaking data, and evaluation data.

Process data helps you build efficiencies into your grantmaking processes. When you are able to understand the exact number of weeks it takes to make a grant or review a report – and identify bottlenecks – you can adjust your processes accordingly and validate your decisions with data.

Grantmaking data shows how a funder’s grants at the portfolio or program level roll up into organization-wide strategy and learning. Examples include type of support (unrestricted vs. project-based), grant duration, geographic location, and other contextual data that can help a foundation gain a deeper understanding of the who, what, and where of their funding. When examined in aggregate over time, such data can provide insights on the organization’s values and priorities, and offer opportunities for course-corrections.

Evaluation data helps the foundation gauge the impact of their funding. It’s important that grantmakers and grantees work together to determine which outcomes to examine within the funded grant. Then together, they can look to the data to assess their work.

How to Embrace Grants Managers’ Evolving Role and Begin to Think Like a Data Scientist

Understandably, not every grants manager feels ready for this evolution. It can be intimidating to grants managers who may not have experience with data – or see any additional time in their work day to analyze data. “You’ve got a lot of people at foundations who wear a lot of hats. You’re always looking for time to try to develop this stuff,” says Michael Castens, grants and operations manager at the Winthrop Rockefeller Foundation. But time is tight, expertise is at a premium.

No one would suggest that grants managers drop everything to get an advanced degree in data science. But with a little curiosity and the right guidance, any grants manager can begin to become more data savvy, incorporate data into their processes, and enhance their role in developing and implementing strategy for their foundation.

Be Prepared and Proactive
Talk to other grants managers that are doing this kind of work. Find out what works and what doesn’t. Get an idea about what would be meaningful and appropriate for you and your organization. Develop a plan for what data you need and why it would help your foundation. This is important because the inclusion of this work will likely include additional resources and time on the grants team. Get buy-in from staff and leadership. Lastly, don’t wait to be asked for data. You know your data. Think about the future implications of the data on the strategic direction of the foundation.

Be Collaborative
When you see something in the data, say something. Reach outside of the grants team to pull in relevant players, including grantees, to show the broader implications of the data. How is it impacting the process, decision-making, and assessment of the impact of your grantmaking? Make this a collaborative discussion. Encourage the rest of the staff to react to the data and suggest alternate analyses or data that would be important or relevant to them in the future.

Always Be Learning
Don’t be rigid about strategy. This should be an iterative and ongoing process. Course-correct along the way based on what the data is telling you and what your team and the broader foundation are reacting to. Also share with your network. Learn from other foundations that are doing similar work. Are they seeing similar trends? Are there ways to collaborate or coordinate funding?

Be the Ambassador
Be the point person at your foundation that other staff can come to to talk about data. Be the person at your foundation that advocates for bringing data to the rest of the sector. A data culture is not just turned on. It needs to be cultivated and nurtured. Everyone at your foundation needs to believe that it is worthy of their time and attention, not just for their own work but for the collective good of the philanthropic sector.

It’s true, data can be intimidating. But it also can be empowering. Adopting a few strategies that help you begin to think like a data scientist can not only help your foundation’s grantmaking, but can also elevate your position within the foundation. Why not take the first steps?

 

 

Fluxx has a mind for technology and a heart for philanthropy. Our vision and innovation are propelled by a deep commitment to transform the grant process and spark lasting good. Fluxx’s cloud-based products are differentiated by a unique, intuitive user interface that makes collaboration, clarity and organization of data effortless. Large and small foundations, nonprofits, government agencies and corporations are dramatically shortening their grant cycles and making more strategic decisions with Fluxx. Until there is no further need for philanthropy, we will continue to expand our mission-critical solutions to drive real change. For more information visit www.fluxx.io.

Aaron Lester

Aaron Lester is a writer and editor in the nonprofit space. In his role as content marketing manager at Fluxx, Aaron’s goal is to collect and share meaningful stories from the world of philanthropy.

  • David Goodman, PhD

    There are some great insights and recommendations here, Aaron. I’m curious what grant manager’s think is their biggest challenge(s) related to being a data “scientist”? Is it figuring out what are the best data or metrics for their organization? How to manage the data (reformat, recode, merge, etc)? How to analyze the data, or maybe how to visualize it – often for multiple audiences who want to see results differently? Or is it all of the above? Anyone willing to share their experience with data?

    • Traci

      All of the above. Take Daniel Bassill’s suggestion for GEO spatial analysis. I think I have the concept as theory but I have no idea what the next action would be to implement it beyond using the internet to search for the term. I know the information that is available on the IRS Form 990, but I don’t know what other sources for information are out there. Without knowing sources, choosing the best data or metrics “feels” like a shot in the dark. Now, recoding metrics. What is that? Do you mean adjusting the columns on my excel spreadsheet? A local nonprofit finally hired a data analyst and he is amazing! I’ve stopped telling him the numbers I need and now tell him the question I have. When he gets back to me, he pulls information that I didn’t know existed much less who to present it. He has to do his work at home because his job doesn’t have the data software he uses.

      As with most things, I can figure it out if I had enough time. However, the length of time it takes to create one data-rich presentation doesn’t have the return on investment that other activities have. Data science is like spring cleaning to me. You know everything will be better if you do it, but don’t stop the everyday tasks in order to get it done.

      I hope this helps.

  • Thanks for writing this. I think there are many other uses of data that can enhance foundation impact. For instance, not only can you understand where your grants are landing (GEO spatial analysis), but you can also build an understanding of what other grant makers are funding in the same area. Since few foundations fund more than a small percent of the overall general operating support of any non profit, multiple grant makers would need to be funding if 100% of NPO needs were to be met, thus enhancing the potential of success.

    This type of data analysis might be done using GEO spatial analysis, but also might range into social network analysis tools as well. Ultimately, if the grant maker is comfortable that a grantee is doing work valued by the foundation, in areas that the foundation considers a priority, this type of decision support data might eliminate the need for proposals and annual reports and result in proactive, on-going support of organizations doing work that needs to be done consistently over many years.

    Finally, the foundation may begin to invest more in creating content libraries, with links to web sites that s how how others are using data to support decision making, so that the learning and constant process improvement of their own efforts, and their sector, is enhanced.