Thought Leaders in Big Data: Greg Moran, CEO of OutMatch (Part 2)

Sramana Mitra: You described the outcome but you haven’t described how you do it.

Greg Moran: The way that we would work with organisations like that is, we would go in and basically collect data around job and culture fit, and to help determine why somebody is successful in a given role in an organisation. What is it about the personality? What is it about the skills? What is it about their cultural match to the organisation? Once we have that profile built, we can then install that at a very early stage of the screening process and work with candidates applying against that profile by having them fill out a very simple questionnaire.

We are able to provide the hiring manager a score, way past the point of application. That score basically represents that candidate’s fit to the job and the culture of the organisation. You’re matching that candidate against that profile, and that’s how you really predict the performance of that hire. It also accelerates the hiring process as well. It really makes the job of the manager much easier. That’s a typical use case for us.

Sramana Mitra: I’d like to double-click on that. When you parametrise culture of an organisation, what kinds of things are you modelling?

Greg Moran: What we’re looking for are things like the tempo of the organisation—how fast-moving it is, the relative stability of the organisation—is it a rapidly changing organisation or one that has their business process down and executing on a very known playbook? We are also looking at the collaborative nature of the organisation. Is it a team-driven environment, or is it an individual-performer environment? It’s factors like that that help us to engage how the candidate will mesh with their colleagues.

Sramana Mitra: When you’re determining the parameters of the candidate, what kinds of things are you modelling?

Greg Moran: Candidates are actually completing situational type of questions that they would encounter on the job. That provides us that background information that we need. They’re basically answering a series of structured questions around specific situations that they would encounter on the job. That’s actually what we use to match against that underlying profile that we had built.

Sramana Mitra: It sounds like it’s a pretty horizontal process. It really doesn’t have much difference from one vertical to another.

Greg Moran: From one vertical to another, no. What really is very calibrated to the company are those underlying profiles. What makes someone successful at Aspen Dental is very different from what makes somebody successful at Subway restaurants. That’s really what we’re looking at, it’s not so much about the vertical differences.

This segment is part 2 in the series : Thought Leaders in Big Data: Greg Moran, CEO of OutMatch
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