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Grants Managers: How to Think Like a Data Scientist
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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.
1. 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.
2. 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.
3. 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?
4. 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?