A decade has passed since “data-driven strategies” was lodged in the association industry’s consciousness by the ASAE bestseller 7 Measures of Success: What Remarkable Associations Do That Others Don’t.

Data analysis was nothing new then, of course, but the measure proved a handy roadmap for the years to come, as data-based decision-making grew in importance and was widely adopted in associations and businesses alike.

Simultaneously, American society has grown more diverse and more inclusive of previously marginalized groups. And the role of diversity and inclusion (D+I) in organizations has evolved from fighting discrimination to building a business case based on positive organizational development and bottom-line impact.

At the confluence of these trends, associations find a particular challenge: While data and D+I are vital pursuits, collecting data for D+I purposes—personal information about members’ age, ethnicity, or sexual orientation—is not an easy task.

Why D+I Needs Data

Diversity and inclusion efforts often arise “because there’s a problem,” says Vicki Deal-Williams, MA, CCC-SLP, FASAE, CAE, chief staff officer for multicultural affairs at the American Speech-Language-Hearing Association (ASHA). But opportunity lies in a more proactive approach.

“What organizations have to do is to recognize the long-term growth potential, the long-term advantage of having or addressing diversity and inclusion,” she says. It “is going to dictate their future success, to a large degree.”

That means getting a head start on data gathering for members’ age, gender, race, ethnicity, education, geographic location, and job type—plus whatever else an association deems relevant to its D+I goals.

We incorporate demographic collection in everything we do, or most everything we can. It's never just a one-time thing.—Debi Sutton, Entomological Society of America

In general, the more an association knows about its members, the better it can serve them. But data is especially necessary for making the case that particular groups are underrepresented or underserved, says Deal-Williams, and for tracking progress toward D+I goals.

And, to the extent that members are willing to be identified by their personal information, simply knowing who fits into relevant groups is valuable. The Association for Women in Science, for instance, asks members about their employment settings so it can highlight nontraditional career pathways.

“Being able to pinpoint who those people are more effectively, elicit those stories, and engage them in helping us to qualify the data in a way that makes it tangible is going to be an important part of our process of effecting change systemwide,” says Sheri Potter, director of community and stakeholder engagement at AWIS.

Why Personal Data Is Hard to Get

Data collection is tricky in general, but the personal information often sought for D+I goals carries added sensitivities, often shaped by how one’s identity intersects with societal forces.

For instance, a generation ago, some African-Americans hesitated to share their race on surveys for fear of discrimination, Deal-Williams says, but members of today’s younger generation often don’t provide it for the opposite reason: because they don’t see it as an important factor for segmentation.

“When you’ve got pockets of people that are responding to issues in society and the changes that we’re seeing there, that impacts people’s behavior, their confidence, their trust, their willingness to provide sensitive information, and their assumptions about what’s going to be done with it or what could happen to it and how well we can protect it,” she says.

That concern demands that the association provide both a strong case for the value of members sharing their personal information and clear assurances about its confidentiality and security. ASHA built a protocol for protecting members’ demographic information when it developed security policies and procedures for all forms of sensitive data, such as Social Security and credit card numbers. Data types are divided into tiers, and only some of ASHA’s 300 staff have access to each tier, Deal-Williams says. Requests to use members’ demographic information are reviewed by ASHA’s Office of Multicultural Affairs “to ensure that the business processes of the association support the promise that we’ve made to members.”

Language must also be carefully crafted in data-collection efforts, as use of outdated or indelicate terminology might convey a lack of attentiveness to the very audiences an association seeks to engage. Debi Sutton, director of membership and marketing at the Entomological Society of America, suggests researching appropriate language and seeking expert feedback. For instance, a review of ESA’s new diversity survey led it to change its wording about physical or mental “difficulties” to “limitations,” she says.

How to Get the Data

Persistence is crucial in collecting members’ demographic information, says Sutton. ESA deployed a full membership survey related to diversity last summer, but it also asks members to provide or update their information when they join or renew, when they register for an event, or anytime they visit their online member profiles.

“We incorporate demographic collection in everything we do, or most everything we can,” she says. “It’s never just a one-time thing.”

The messaging that accompanies D+I data gathering—the answer to the question, “Why do you want to know this about me?”—is paramount. An association can provide “good of the order” or “good for the individual” reasons, or both, but they all must resonate with the member.

AWIS, for instance, appeals to its members’ commitment to the pursuit of knowledge. “We want to align our membership to our research more robustly,” Potter says. AWIS developed a template email for chapter leaders to ask members to fill out a demographic questionnaire. The email “captures the fact that this is a strategic move forward for the organization, not just about demographic questions.”

ESA took a similar approach leading up to a future symposium on D+I in entomology, at which the results of ESA’s own diversity survey would be presented. “If they know that a symposium presented and reviewed this data from this study, they’re more likely going to want to make sure that our data is accurate,” Sutton says.

ASHA makes the case that demographic information allows it to better tailor its programs and services to members, but it also tries to show members how the greater good benefits them, says Deal-Williams.

“What’s in it for them is that their profession continues to grow and to maintain relevance where, without that increased diversity, it’s possible that we’re going to get to a point where we [speech-language therapists] are limited as a profession in who we can serve and the extent of the services that we would be able to provide,” she says.

A Long-Term Pursuit

If you’re hoping for a benchmark percentage of members to get demographic information from, beyond “as many as possible,” you may be disappointed. What an association can collect will vary based on the attitudes of its members, the quality of its data-collection practices, individual sensitivities about each type of data field, and regular membership churn.

“We have demographic data on probably 75 percent or so of our members, but we don’t have the same demographic data on all 75 percent of those members,” says Deal-Williams. “So, there might be members who’ve given us race or ethnicity. There are other members that have given us gender or age.”

Whatever you get, don’t forget to communicate the impact of your D+I data collection back to members. Deal-Williams says that, despite ASHA having formalized its D+I work under its Office of Multicultural Affairs, it still occasionally hears members call on ASHA to be more diverse.

“Some of it is making sure that, as we’re looking at the data, we’re not neglecting to communicate what we get, why we’re doing it, what we end up with, and what we develop as a result,” she says.

[This article was originally published in the Associations Now print edition, titled "Diversity Meets Data."]