On the Fast Track to Fast Data

Associations have found ways to get more business intelligence out of their data and use it to inform their decision making. Now the next challenge is to do it faster.

“Fast data”—identified by the ASAE ForesightWorks research initiative as one of 46 drivers of change that are likely to have a significant impact on associations in the future—involves real-time decision making, based on the idea that the greatest value from data comes when the analytics can be used immediately. Fast data allows associations to be nimble and responsive to what members are talking about, registering for, or purchasing.

For example, if your data is telling you that lots of members are discussing a particular topic in your online community, your organization might respond by creating a webinar, which would take place in a week or two. “That’s something that’s different for associations. You’re not planning a year in advance—you’re really pivoting based on fast data,” says Julie Sciullo, CEO of Association Analytics.

While associations have always had this data, “it was a mountain, and they couldn’t necessarily tackle it,” Sciullo says. Fast data breaks up the mountain into digestible pieces and makes them actionable.

Ultimately, associations should see fast data as a way to better engage members and tailor offerings to them.

“The immediate benefit is true engagement—giving people what they care about when they care about it,” Sciullo says. “It’s paying attention to what your community is talking about and then serving that back to them.”

Internally, associations can harness fast data to make their operations and processes more efficient—or to decide when to sunset a product. Externally, they can better target their marketing efforts. “Everybody is trying to figure out: How do we remain relevant? How do we drive engagement? Some of the answers are right there with existing data,” Sciullo says. “You might be overlooking something right in front of you.”

Associations can also use real-time data to gain insights into their meetings. Data can help staff determine “where their audience is underperforming or overperforming across a number of different metrics,” says Joe Colangelo, cofounder and CEO of Bear Analytics. For example, if the data shows an association is doing a good job bringing back previous attendees, it can quickly shift resources and attention to increasing first-timer registration rates. “It’s an exercise in agility and resource allocation,” Colangelo says.

Bear Analytics also encourages association clients to set more short-term goals and to plan without knowing all the pieces of the puzzle beforehand. Because “they’re looking at [data] in a much more consumable manner, that’s allowing them to deploy their resources smarter than ever,” Colangelo says.

Where Associations Are Using It

While the Society for Neuroscience’s business intelligence program has been in place for several years, SfN started acting on data more quickly in the last year and a half. Staff across the organization can access dashboards and reports through Microsoft’s Power BI, says Liz Rumsey, director of information strategy and business analysis.

As a result, SfN was able to make its marketing strategy more flexible and responsive, including better targeting members and personalizing messaging. They have moved away from setting a rigid marketing calendar at the beginning of the year and sending registration reminders to prospects every August. Instead, in August, staffers go to a report on member engagement, segment members by their behavior and their likelihood to register for the meeting, and then build a marketing campaign based on what they find. “There’s more creativity in how we market things,” Rumsey says.

Some associations also offer fast data to members. For decades, the Association of Schools and Programs of Public Health has been sharing data from its data center with its member institutions annually. In 2012, ASPPH moved to a more efficient online system of data reporting, and a year later, it started making that data accessible to members.

“We did it in response to their needs to have data for decision making and to have it quickly,” says Emily Burke, director of data analytics.

ASPPH uses near-real-time data on the current admissions cycle. This year, as applications have come in, the association has shared with members the number of applications they’ve received and how that number compares with other schools and programs.

“They can kind of benchmark themselves against that national average during the cycle,” Burke says. “Being able to see where they stand during the middle of an admissions cycle has turned out to be pretty valuable to them.”

Higher education always sees some ebb and flow, “but when we’re able to experience that ebb and flow in real time, we are better positioned to adjust to it on behalf of our members,” Burke says. Until a couple of years ago, ASPPH didn’t know what was happening in the admissions cycle until a year later.

Many types of data have proved useful to members. “Our experience has been, ‘If you build it, they will come,’” Burke says. “If you make it available to them, they’re going to find a way to use it to drive their decision making.”

How to Get Started

For associations looking to dip their toes into fast data, Bear Analytics’ Colangelo says it’s important to “get a handle on the data you already have.” This includes making a list of the vendors you use, when you started using them, and when you stopped, if applicable—because former vendors might not be retaining the data. Then, make sure someone on your staff is getting all the data delivered back to the association. “There’s always that stewardship to be done,” he says.

Sciullo says a starting point “might be as simple as taking a couple of assumptions that you’ve known for years and validating them by data,” or zeroing in on your pain points and how data might help.

Once SfN ramped up its business intelligence efforts, it immediately debunked a couple of longstanding myths. One was an assumption that more neuroscientists from Europe came to their meetings in Washington, DC, and more neuroscientists from Asia came to their San Francisco meetings.

“We could see within seconds that that was not the case,” Rumsey says. “We had to change our marketing strategy, because we were marketing to the wrong people.”

The organization intends to keep building its data warehouse. “This is a journey,” she says. “Even though the data is fast, getting here does take some time and investment and commitment, but it’s totally worth it.”

But there’s good news in this trend for association leaders.

“Sometimes it feels like the wind is kind of in your face,” Colangelo says, “But data analytics—in particular, some of the advancements in fast data—allows the wind to be at your back sometimes.”

(Shuoshu/Getty Images)