Keeping Humans in the (Feedback) Loop: Orangetheory Fitness’s Ameen Kazerouni

**Sam Ransbotham** (0:01)
Real-time data collection means organizations can make many more informed choices based on metrics.
But when do they still need humans? Find out on today's episode.

**Ameen Kazerouni** (0:13)
I'm Ameen Kazerouni from Orangetheory Fitness, and you're listening to Me, Myself, and AI.

**Sam Ransbotham** (0:19)
Welcome to Me, Myself, and AI, a podcast on artificial intelligence and business. Each episode, we introduce you to someone innovating with AI.
I'm Sam Ransbotham, Professor of Analytics at Boston College. I'm also the AI and Business Strategy guest editor at MIT Sloan Management Review.

**Shervin Khodabandeh** (0:38)
And I'm Shervin Khodabandeh, senior partner with BCG, and I co-lead BCG's AI practice in North America. Together, MIT SMR and BCG have been researching and publishing on AI for six years, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.

**Sam Ransbotham** (1:03)
Today, Shervin and I are excited to be joined by Ameen Kazerouni, chief data and analytics officer for Orangetheory Fitness.
Ameen, thanks for joining us. Welcome.

**Ameen Kazerouni** (1:11)
Thank you, Sam. It's great to be here. Excited for the conversation.

**Sam Ransbotham** (1:14)
Currently, you lead the data and analytics function at Orangetheory Fitness. Maybe tell us a little bit about the organization.

**Ameen Kazerouni** (1:21)
Absolutely.
Orangetheory Fitness is a heart rate-based total body group workout. It combines science, great coaching, technology, and it's designed to provide what we like to think of as a more vibrant life.
The workouts develop to motivate each individual member to achieve their desired results. And if you're starting on your wellness journey or you're a seasoned fitness enthusiast, each OTF workout creates a community of shared experience but also uses heart rate-based training to allow you to experience the workout in a way that's most comfortable for you. And that's honestly where my role comes in. There's a tremendous amount of second-by-second telemetry data from the fitness equipment, from the heart rate monitors that allow us to create the most curated, personalized kind of boutique fitness experience in the world. That's Orangetheory.

**Sam Ransbotham** (2:22)
All right. What do you do with all this? You've collected all this data. You've got this telemetry. You've got heart rate information, I assume, since you're heart rate-based.
How does the process work? Take us through the steps.

**Ameen Kazerouni** (2:33)
Most Orangetheory members in the studio will be wearing what we call a OT-beat heart rate monitor, which is a proprietary piece of wearable technology. There's two purposes to that. One is it gives you a real-life feedback loop as to how you're performing, what intensity level you're outputting in the studio. But it also allows the coach to see the intensity level that you're outputting in the studio and help effectively provide a kind of personalized fitness training experience in a studio, in a group setting.
My role is focused on kind of unlocking that telemetry data and helping personalize the experience even more. A really cool example is that we recently launched a personalized max heart rate algorithm, and members now experience a much more curated experience in the studio. And that's allowing us to use proprietary algorithms to determine what the max heart rate, which is a physiological term for the maximum output that your heart can beat at, is for an individual member.
And percentages of that max heart rate tell you which heart rate zone you're training in. So anaerobic training versus aerobic training have different physiological impacts. Time spent in different intensity zones have been proven to have varying effects on longevity and health in general. And being able to personalize that per member, we're able to make this experience even more curated in the studio, while most places that leverage max heart rate will rely on a generic age-based kind of equation. And you know that, as you can imagine, every 30-year-old or 40-year-old doesn't have the same heart. So things like that are an example of how we curate the experience for our members using this data.

**Shervin Khodabandeh** (4:27)
That is a super cool example, right? Not the average for your age and gender.
And then it goes by bands of 10 anyway, right?

**Ameen Kazerouni** (4:35)
Yeah, exactly.

**Shervin Khodabandeh** (4:37)
Like as if all 40- to 50-year-old males are like exactly have the same ability. So that's really super cool.

**Ameen Kazerouni** (4:43)
Yeah, it makes the experience safer. It makes you more aware of what you're doing, what your capability is, and you see that cardiorespiratory fitness climb over your time with the program.

**Shervin Khodabandeh** (4:56)
And I like what's sort of inherent in what you're saying, the rapid feedback, right? Within a few seconds, you get feedback. But also in a broader symbolic sense, what you've been proposing is more and more experimentation in general as you build AI algorithms. So it's not just the algorithm, but it's also experimentation because you get feedback.