Normalizing Data

Equilar is now the leading provider of executive compensation data. Everyone from fortune 500 companies. So leading media organizations are your customers. You've also branched out into other categories, including board diversity, a very important topic right now. What creativity practices or tools do you use to generate new ideas of this nature and product lines with your team?

When I started the company, we made a very conscious effort when collecting the data is to normalize the people in our data set. So if Thuy Vu shows up in our dataset, is that the same Thuy Vu that's over there. And as we built our dataset, we would capture all that information about Thuy and others. So now, as we've built and collected our data, we had a database now we're up to about over a million profiles of executive.

Oh, wow. I didn’t realize it's so big.

Yeah, yeah. No, been we've been busy Thuy! But just organically, we've been able to capture that. And the reason we did this is that when I was back in investment banking, we would see emails going around all the time. Hey, we're meeting with this company, does anybody knows somebody who's affiliated with that company. So not only have we captured this information about these executives and where they've been, but we've also been able to infer who they would know because who was on the board with them at the same time? Who was an executive with them at the same time? And so we built it as kind of LinkedIn, like Rolodex. The two primary use cases. One is as you pointed out is around recruiting and specifically around board recruiting.

And so we've been in this space for at least five, six years now. And in the last couple years we've been building out the Equilar diversity network given all the attention around the lack of diversity on corporate boards. And so we already had this database ready to go because we were collecting it as part of what we're doing. But also people are using the same data set on the business development side. Like, hey, I'm trying to get to so and so. Is there anybody in our network that may know this person? Like, oh, they were on the HPE board together five years ago. So hey, maybe so and so can reach out to that person.