JDRF’s Big Data Management

Managing a donor database is difficult no matter the size of an organization or its donor base. However, when you are a large, international nonprofit organization, particularly one with chapters across the U.S. in addition to six international affiliates, managing data in a uniform, centralized fashion is even more complex.

JDRF, the leading global organization funding type 1 diabetes research, is one of those large, international nonprofits handling data across different chapters spanning the globe.

“We realized we had a ton of software systems,” says Megan Martin, former director of data analysis at JDRF. “We had lots of places to collect and manage data, but it was disjointed. It wasn’t efficient to use the data to answer the strategic questions we wanted to answer.”

Having so many systems in so many different places made it difficult to pull everything together. JDRF had reports everywhere, Martin says. Every system had its own report, staffers kept their own Excel files and some people were looking at different reports, leading to confusion. For instance, one person may have been looking at an older report that was filtered to show just U.S. donors, while her colleague was looking at an ­updated report that included international support.

All this played into turnaround times for reports spanning weeks and sometimes even months to get a question answered.

“By the time you got the data you needed to make a decision, you had moved on,” Martin says. “Time had passed, and it was too late. You already developed another strategy. We needed to have a way to more efficiently use all this data we were collecting.”

But before it could find a solution, JDRF needed buy-in from executive leadership.

Taking the lead — from the top
The biggest decision JDRF had to make when embarking on this data project was choosing who should drive this IT initiative. Should it be the IT side of the organization or the business side?

“A couple of years ago when we started this, our [chief operating officer], James Szmak, chose the business side to lead the program, and it was a little bit of a cultural shift,” Martin says.

JDRF’s staff already had a strong partnership with its IT department, but Szmak, coming from an IT background himself, tabbed two fundraisers to lead the initiative — one from major gifts and the other from prospect research. And Szmak championed the project himself.

“Having someone at such a high level championing this helped get executive buy-in,” Martin says.

However, that buy-in did not happen overnight. Adding another system is always a challenge, Martin says, and you have to account for training employees on using it, supporting them, getting them to adopt the system and getting full buy-in. It’s been an ongoing process for JDRF.

First, it started at the national level with the executives, showing them how adding a new data solution would make the data management process more efficient. It then went to the regional staff that oversees the individual chapters and then moved down to the individual chapter fundraisers and events staff.

“It was trickling down to prove this makes our lives easier. Getting peer support and recommendations helped get buy-in, in addition to it being championed by our COO,” Martin says.

Availability and access
The goals in adding a system to streamline the donor data process were pretty simple. JDRF wanted easy access to data, easy analysis of the data and easy answers from the data for its staff.

With that in mind, JDRF chose dashboard solutions with the help of wealth intelligence and data analysis company WealthEngine. It implemented six dashboards that address all of the organization’s major fundraising areas. Now fundraisers have one central place to see how they’re tracking against their goals and pull data, Martin says. It’s easier to navigate and see more interactively how the data works together, combining the information from different systems into one place.

Now Martin and her team are able to do a lot of quick analysis behind the scenes with the new software and explore the data to answer strategic questions both individually and for the organization as a whole. The data team can then publish the relevant data for everybody and bring it to the entire organization — information like how many weeks before an event participants register so the marketing can be more targeted.

“We’ve been able to segment and focus efforts and resources more rapidly. Instead of waiting until the end of the month for a report to come out, we can see it mid-month. We can monitor in real time,” Martin says.

The dashboard not only makes the data available and accessible for JDRF’s fundraisers, but it’s also shed light on how important data and data entry are. Just by putting these dashboards on a screen, visually seeing how data interacts, Martin says, people understand why the data team asks them to fill out all those data fields when entering donor data.

“They see that if they do it correctly, they get more return out of the data,” she adds. “It was an unintended consequence, not necessarily a goal, but we saw that the data wasn’t as clean as we thought. This helped encourage clean data.”

This has all led to a more efficient donor data process, which in turn has helped JDRF’s fundraisers learn more about their donors — and send them more relevant, more targeted messaging.

Lessons learned
Embarking on this process, JDRF has gleaned many things when it comes to managing and utilizing big data. Martin shares some of the major takeaways:

One size does not fit all. Not everyone is able to digest data the same way, and when you are a larger organization like JDRF, there are a lot of people looking at data. That means you must provide a balance between giving turnkey information to people who aren’t that data-savvy, Martin says, but then also giving analytic capabilities to those who want to dig deeper into the data.

“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.