MINDWORKS

Mini: Data! Data! And more data! (Jessica Lynch, Phil Wagner, and Angelica Smith)

June 15, 2021 Daniel Serfaty
MINDWORKS
Mini: Data! Data! And more data! (Jessica Lynch, Phil Wagner, and Angelica Smith)
Show Notes Transcript

Thanks to gadgets such as Apple Watch, Fitbit, Peloton, and other smart devices, we can track just about every aspect of our health and wellness. What do we with all this data?  Join MINDWORKS host Daniel Serfaty as he talks with Wishroute founder Jessica Lynch, Sparta Science CEO Dr. Phil Wagner, and Aptima’s Marine Corps fitness planner engineer Angelica Smith about possible solutions.  

Daniel Serfaty: …if people ask  us, so what's new here? At the end of the day, people have been in fitness for a long time, in different ways, at least in America. 

From a technology perspective, and your three companies that are actually using technology or science, or psychology to offer something to their customers. What is new here fundamentally in 2021, when we look at those technologies? Phil, can you take us there? You've been looking at this field for a while, but what is really, really new here? 

Phil Wagner: The big thing that people are now starting to realize is, what are we going to do with this data? Because I think what's happened over the last five, 10 years, there's been some great technologies that have collected data and that made it presentable in a nice way. But I think we're getting to the point where individuals are looking at it saying, "Yeah, I know I slept seven hours because if I went to bed at 10:00 and I got up at 5:00, I've spent money on this device that helps me do that math, right?

And so, now I think the challenge to technologies are now they have to deliver back. They're gathering information, now they have to leverage that in a ethical way to say, "Here's how you can use that data to add and change habits." Because just telling me, I slept seven hours is no longer enough. And I think the hard part is, we're all limited by time. So you can't just say, "Well, just sleep eight hours. What's the problem?" You can't make the day longer, so what things in your day should you not be doing to allow more time for other things? So technology should be individualizing what you need to strip away, so you can do more of what you need.

Daniel Serfaty: That's very interesting. So you're making the point that just collecting data with the Fitbit's of this world is necessary, but certainly not sufficient. We need to transform this data into useful and actionable information. 

Phil Wagner: Right. And just say you got to sleep eight hours, that's just the lazy insight. We all have that, right?

Jessica Lynch: We have these great recommendations now, we're starting to get better and better at individualized, personalized recommendations for actions people should take. But then how we pick up the problem from there is, we're human and most of us need external accountability to follow through something and break out of our current habits to form new ones, and take a detour from what we were doing yesterday to now do something different. And we don't feel accountable to things that aren't human, and caring, and knowing that someone cares about what you accomplished. 

So we're enabling that human heart and care to be delivered in a way that is based in behavioral science and motivational interviewing psychology to help people feel accountable and actually adopt those changes in an achievable way. So it's really that continuum of, "I completely agree follow data into more personalized recommendations, and then get those personal recommendations broken down and delivered in a way that actually helps people adopt them. 

Daniel Serfaty: It's amazing that it's not just about sets and reps, or [inaudible 00:18:07] prescription, but there is so much thought behind, as you say, accountability, but also the science of it. That basically it becomes more of a diagnosis and recommendation almost, dare I say, almost like a medical profession. 

Phil Wagner: Absolutely. Yeah. It's pharmacology at the end of the day, it's just in this case, the medicine is the exercise. You don't go to a physician and say, "Go take an antibiotic." It's like, "Well, which one, how often? How much, when do I stop? When do I change?" Whereas we've kind of looked at exercise like that, where we've said, "Well, just go walk for 20 minutes." Well, one of the biggest breakthroughs in pharmacology was the extended release once a day pill, because it reduced the barrier for thresholds. So if we say, "Hey, just go walk 20 minutes." And that person says, "I've got 10 minutes a day." They're going to choose option B, which is nothing. So how can we grade it much like medicine has done with pharmacology?

Daniel Serfaty: Angelica, on this data question, how do you see in your experience, I mean, after all, you're the one actually touching the data with your fingers. How do you see the relationship between us looking at data, making some recommendation for exercises and the ability of the actual trainers, or trainees for that matter to take those data and trust them and actually comply with the recommendation?

Angelica Smith: So one of the things that I'm seeing, at least for my end users, the FFI, they don't seem to be as interested in the data. It's the leadership that wants the data that I think the FFIs were simply looking for a tool that's going to allow them to do their job, create these plans easier, faster, and distribute them easier. And that's what the mobile application does. It delivers it to the end users. The FFIs they're responsible for hundreds and thousands of individual Marines physical fitness. And so I don't think they're looking at the data as much, it's not as important. They just want to get these programs out to these guys and try to reduce injury, whatever that means. 

But then you've got the leadership, they want to know how healthy the fleet is, how healthy the unit is. And they're looking at the data to better understand how effective is this plan, in fact? And so you've got these two different groups and what they care about. And that's what I gather from being boots on the ground. 

Daniel Serfaty: That's a very interesting observation. At the end of the day, the person who do the exercise wants to have reasonable recommendation, that's what Phil was saying earlier. It's not so much that your heart rate is X that matters, is what do you do about it? Or maybe as you say, as the leaders, or the managers, or the commanders are more interested to see, to have some statistic about the general health, the general fitness of their units. These are two different stakeholders in this particular case.

But that's a big lesson that despite the extraordinary enthusiasm for people to measure everything, it remains to see whether or not those measurements lead to improvement. You need an intermediate step in between. One, is making sense of those data, but also encouraging people to comply with the recommendation in order to be effective. So Jess, could you describe a day in the life of one of your user? You're the one that is addressing actually the most, all of us, at least with your tools and your services in a much wider population. These are not elite athletes or special forces soldiers, they are basically us. 

Jessica Lynch: We have worked with some pretty unique groups, including frontline healthcare workers, during COVID, which was extremely rewarding and challenging, because they were all being challenged emotionally, physically, mentally. But a day in the life of working with an individual, our business sort of has two key sides of it. Most of our business is working with other wellness companies, helping them increase compliance and engagement of their end users. But we also work directly with individuals as a testing ground for our partners to develop new programs and insights that we can bring to our partners. 

So I'll give a day in the life, it's a pretty similar the end user in both. But we help people focus on one healthy habit at a time. So trying to break things down into achievable, sustainable steps. So if someone's working on exercise with us at the beginning of the week, they pick a daily goal for each day, one thing, and then each day they're getting a reminder or something inspirational in the morning, maybe a suggested podcast to listen to if their goal is to walk that day or a inspirational message, 10 minutes out of your day is 1% of the time, something like that. 

And then at night, we check in for accountability and that's when we're asking about their daily goal, did you go for your walk? And when they text us back, there's always a Wishroute guide to personally respond to them. And we've created a judgment free coaching methodology, that's providing positive reinforcement, encouragement and the help to game plan if it wasn't a good day. It's really important to make people feel comfortable saying, "No, I didn't do it." Because that's when we can be most impactful. 

And I would say the biggest kind of aha is just every day we hear, "I wasn't going to do it, but I remembered you'd check in and I wanted to have something positive to report back. So even though I only had 10 minutes and my workout I was supposed to do was 20, I got out and made the most of that 10 minutes and I did a walk and some squats. And there it is." And so just knowing that someone's going to check in is incredibly powerful. 

Daniel Serfaty: So it's an actual person. The Wishroute guide is a person who calls the [crosstalk 00:24:07] and asks them-

Angelica Smith: [crosstlk 00:24:08] and text message. Yep, so we're texting people in the morning and at night and whenever they text us, they're getting a personal response back. 

Daniel Serfaty: But that sets of recommendation that you provide in the morning, given a particular fitness goal, "This is what we recommend. You watch these, you go walk, you do this exercise." Those are automated, or these are actual... you said they are texts? 

Jessica Lynch: Yep. It's a mix of automation and personalized recommendations, which are automated. I mean, it's a set of preset selection and a mix of personalized things based on someone their own goals. So we're not a prescriptive service saying, "You need to do X, Y, Z." We're giving people inspiration to follow through with the goals that they've set and with our partners, we're helping people follow through with the goal with the partners content. So if it's a fitness app, we're sharing, "Here's the live workout schedule in the morning," or, "You said your goal was to increase flexibility, here's a yoga workout we think you're going to enjoy." So it's personalized and related to a preset set of messages. 

Daniel Serfaty: So that personalization is an important theme today, because we are all different, we learn differently, we practice differently. And Phil, I know this is some of the key part of the technology that you're proposing. It's not only very precisely diagnosed, but it's also very personalizing the diagnosis is for that person. Can you tell us a little bit about how you use basically technology and machine learning to turn these measurement, these very precise measurement that you're doing with the machine learning plate for the athlete to the user?

Phil Wagner: There are two key, I guess, case studies we tend to see with folks that we work with, whether that's athletes or fighters, or even in the employer's face it's, "I only have so much time," and that's a piece and a big part of data's role that we see is to convince the user to let go of things. And that could be something that they found to be useful in the past, or that could be something they're clinging to because they're really good at it and want to keep doing it. A good example is, if we think about war fighters, soldiers, CrossFit's really cottoned on in that group. 

Why? Because it's hard and it makes you really sore, and it's really difficult and challenging. The question would be, does that group that has incredible grit, and strong and explosive, is that what they need, or do they need yoga to help promote flexibility and breathing techniques and recovery, or do they really just need to continue to endure more challenging circumstances? So I think technology's role should be to help aluminate some of these things to teach the individual and say, "Hey, this might be something that's not serving you. You may enjoy it. You're going to have to make a decision. Are you training to serve your country, are you training to be in the cross the competition?"

Both are okay goals, but ultimately you can't serve two masters. And we have this all the time. When we started in sports with football, offensive linemen, they squat for living, every play they squat to get in their stance. They go in the weight room and what do they do? They squat all the time. Best way to have an ACL injury is too much squatting, too much quad dominance. You got to make a choice. Do you want to be an offensive lineman that plays a 20 year NFL career, or do you want to be someone that's really good at squatting and a short career? You can't do both. And I think data helps educate the individual. So they come to that conclusion because ultimately that's what's going to make it stick.