JDRF’s Big Data Management

“Data can be overwhelming, and if you are not careful, it can be distracting,” she says. “Sometimes people focus on the nitty-gritty of the numbers and tackling exact numbers day by day instead of looking at the bigger picture of using data to inform strategy.”

Business process has a huge effect on data analysis. Due to the nature of silos and data entry, sometimes there is a lag time between different data sets. For instance, when an event sponsor registers vs. when the check actually gets recorded into the finance system can differ, which means the dashboards may not match due to this lag. And sometimes one department might pull reports once a week while another pulls reports once a month, leading to more lag.

“That wasn’t something we anticipated having to tackle. But in order to get people the data they wanted in the way they wanted, we had to look at our business process,” Martin says. “… We had to change some business processes to make sure the information is accurate.”

Have strong IT partnerships. “When you start to pull data in from all these different systems,” Martin says, “it’s a lot more technical than we expected. In reality, every system collects data differently.

“We have hundreds of locations,” she adds. “When you combine all those systems, you have to have the technological expertise and logic to make all the data the same.”

It’s still a work in progress for JDRF, but the organization has already seen significant improvements in efficiency in both donor data collection and utilizing such data. It’s allowed the organization to send stronger messaging to its donors and find supporters with a strong affinity for certain actions.

Now, JDRF has cleaner, richer data, which in turn has led to stronger fundraising for the organization.