Why grantmakers should embrace the power of predictive analytics

Predictive analytics is used to calculate your insurance rates. It even tells retailers how to design their stores. Whether you realize it or not, the uses for predictive analytics aren’t only expanding but becoming more and more ingrained in our daily lives. The world of grants management is no different.

Tim Daciuk, Director, Data Analytics at SmartSimple

What is Predictive Analytics?

The term “predictive analytics” means different things to different people depending on the context. So what does it mean for grantmakers?

Basically, predictive analytics takes historical information and combines it with data science and math to comment on future events. For granters, that makes it the ideal tool to leverage in order to increase the impact of funding and improve outcomes. How? By using prediction and segmentation.


Forecasting outcomes is an important part of what predictive analytics does. By looking at your past granting activities, it can help you make better-informed funding decisions in the future.

Let’s suppose you’re unsure that the $500,000 you allot in annual granting for animal rescue group support across your region is being used effectively. By creating a predictive analytics model, you can see how funds were used, and evaluate if you should commit more funding or less, or create different criteria for the grants you offer.


Simply put, segmentation is the ability to group people, places, or things that have common traits, like applicants, donors, or funding sources (government support, endowments, etc.). For example, applicants seeking grants to improve primary education could be one segment. Those seeking grants to improve middle school education would be another, and so on.
Read more about the challenge of extracting data from text, what the next steps are for granters exploring predictive analytics, and information on an upcoming series of webinars with Tim Daciuk, Director, Data Analytics at SmartSimple on the Peak Grantmaking blog.

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