#89 – Living on a farm while working at Levels (Ben Grynol & Chris Jones)

Living in a technology-driven world makes it difficult to take a step back and recharge. But you need to be able to disconnect from work and responsibilities once in while if you want to live your best life. In this episode, Levels employees Ben Grynol and Chris Jones discussed Chris’ jump from big tech to a startup, the perks of an asynchronous work culture, and how to treat customers’ data with respect.

12:03 – The power of disconnection Chris said disconnecting from work is hard when you’re surrounded by technology 24/7. So when he moved to Montana, he relearned how to take time for himself.

In the Bay Area, you’re connected all the time. And I’m like, all right, I’m in an area where there is no cell phone reception and I’m going to be here for three to four hours, enjoying whatever activity I’m doing. It helps me be in the moment as opposed to the, well, what didn’t I get done today? Like what’s that next to do item, the next dashboard. If I’m like, hey, I’m completely disconnected, you need to recharge by really turning work off. And that’s what’s hard to do in this hyper-connected world where everyone’s got 5G phones that can do everything on it. It’s like you never turned work off. So some of the functions of things like, all right, I have to go out and mow the lawn. And for some people that might say, “Oh, that’s like a half hour.” For me, it’s a six hour chore and I need to sometimes break it up over two days. I’m like, all right, I’m going to be on the tractor for six hours, I better make sure I’ve got a good audiobook downloaded because I’m going to be here a while. And it’s liberating to make sure you are taking time for yourself.

18:55 – Treat people like adults Ben said that environments where you’re expected to check in constantly are taxing and don’t allow employees to be treated as adults.

If people are in a synchronous environment, maybe not synchronous, but one where there’s an expectation as far as having a high response cadence, then even if you have the time booked off, like cross-country skiing and it was an hour. The whole time you’re like, okay, I have to get back to my phone. What if somebody… if they’re trying to reach me and I’m not responding, people are going to question where I am and what I’m doing. And it’s such an odd thing to think about. One of the things that we always talk about is treat people like adults, and the opposite of that is treating people almost like children. Like, okay, you do exactly what we’re going to say right now and it’s odd having that prescriptive environment for people to work in.

21:09 – The perks of asynchronous work Chris enjoys working asynchronously because it allows him to take time off when he needs to and he doesn’t feel the need to check in all the time.

I can enjoy Montana more just because of the asynchronous way of Levels of, yeah, I know I’ll be checking all my threads tonight, looking for anything I need to respond to or tomorrow and that’s okay and people can wait. There’s nothing so urgent that they need in my response within an hour and I’ve missed the entire thread. And that’s really, I won’t say powered, but really relaxing of like, I can enjoy the time that I want to take to do what I need to, whether it be mowing the lawn or doing yoga or going for a bike ride versus this constant, you’re right, like every time your phone buzzes, you feel like you have to stop your bike, pull your phone out, look at it and then check, I’m like, “Is that emergency? Yes or no? Like let me get going.” Which is what I faced when I was in the Bay Area for a lot of high tech companies. I would be on a bike ride and all of a sudden my phone would ring and I have to stop and take the call and people are like, “Are you walking up steps, breathing heavy, what is it?” I’m like, “Yeah, I’m on my bike right now but you called and you need answer, what is it?” And that is really hard to get into a zone of mentally I need to go and disconnect when you’re constantly waiting for that game of Whack-A-Mole.

26:30 – Startups have a culture of innovation Chris enjoys the culture of innovation that startups have. The predictability of larger companies is boring in comparison to the constant problem-solving a startup requires.

I love the challenges where I don’t know what it looks like, I have no idea and the heavier it is, the more fun I have. Where the answer isn’t the, “Hey, there is a right way and a wrong way to do this and if you follow all the best practices in someone’s playbook, you should have a good outcome.” Like that’s the boring stuff. It’s all about the, we have no idea how we’re going to do this, but we’re just going to keep trying and throwing spaghetti against the wall. Like that’s where I have fun. So what I realize is even within big companies, I navigate towards the startup environments within those companies. And as Google gets… it got bigger and bigger, the number of opportunities that you could jump onto became less and less. They used to have a lot of culture for just tons of innovation and tons of ideas. And over time, they realized like, “Well, we can only launch so many products and to scale them and put marketing effort behind it.” So they really over time reduced the amount of these random ideas of two engineers going to town to build that next new app. It still happens a lot but much, much less, and it’s much, much harder to find. So to some degree, I’ve always found myself to thrive or to love the startup environment.

32:20 – Handling high stakes Chris said there’s a certain pressure that comes along with being in a startup that bigger companies just don’t have to deal with.

When you’re doing your version of a Kickstarter and you’re spending your own money funding those Facebook ads or those Google ads and it doesn’t deliver on the ROI or the Return On Ads spend that you hope, that’s a scary moment where you literally have your own money in it. And when it doesn’t materialize, you’re just like, I’m just lighting dollars on fire. And I have to pull these things back in a hurry. That’s the scary time when you’ve got your own hard earned cash in it versus when you’re at Google or some big company like, “Hey, what’s going to happen if this test doesn’t work?” You’re not going to get fired. Maybe there’s really low… you have no skin in the game or very little other than your boss saying, “Hey, good job on that project.” So when we were launching new products at Nest and the team was all getting super excited and, or nervous, they’re like, “Chris, why are you cool as a cucumber?” I’m like, “Because this isn’t pressure. Pressure is when you’ve got a startup where if this doesn’t work, we’re going to turn around and fire 75% of the company, that’s pressure.”

35:21 – The challenges of acquisitions Ben said there are a lot of challenges around acquisition and integration, and you have to be very intentional if you want to properly integrate two companies.

If you look at the stats of acquisitions, so many acquisitions don’t work out for different reasons or they don’t provide the value that they thought they would, neither here nor there. And there’s good HBR articles, there’s a really old one. I can’t remember when it’s from. It’s probably very old now probably 20 years old. But where there’s a lot of challenges is around integration. And if companies don’t set up the expectation around what a great integration looks like, that’s where things can be very, very challenging because of maybe misaligned expectations around what the acquisition or decision making might be. And we saw this, again, this is from an outsider’s perspective, everything is anecdotal because you can read what you read in books, but none of us, if we’re actually there, you don’t know what it’s actually like. You hear about this with the Facebook, Instagram acquisition, where there was maybe misaligned expectations around what the next steps for execution would look like. You can see it with what it sounds like when you went through an integration, even though you were part of Google, you weren’t integrated into Google. And so that becomes challenging. Even with Skip, we saw it where integrating with different companies is really hard and you have to be intentional about it. And it’s not something that is comfortable nor easy, but a lot changes. And I think the larger the organization, the more challenging it becomes.

41:43 – The democratization of data Chris said the democratization of data allows information to be shared among as many people as possible and prevents silos from forming.

Their view was we want data in as many hands, answering as many questions as possible to scale it. So they invested tons in terms of making their data set open to the entire company. Versus like, “Oh well, you’re not an analyst. You don’t belong to this part of the org. You’re not in IT, you’re not in this team. Therefore, you don’t get access.” Which is typically what most companies do. They kind of lock it down behind like only the DBAs have access and to get access, you have to make a request and then request it, which is why eventually business users give up and go around and use things like Google Sheets or Excel because they can’t get access to the data. So for me, a big one is getting as many people on the system, using the data as quickly and learning as fast as we can.

45:52 – Treat your customers’ data with respect Chris said it’s important to protect the anonymity of clients’ personal data, even when you use that data for the business as a whole.

There is an absolute requirement of the treating your customer’s data with respect. And what can you do to still enable the business, but to say, “All right, I don’t need to know that John Doe, what his glucose reading was for yesterday,” but I am trying to figure out like, “Hey, we just rolled out this new feature in the app, are our members finding that new feature useful? And do they like it? Do they not like it?” And that level of log file data around the product and in their experience is super powerful to say, “Are we helping people in their journey? Yes or no?” But you’re right. I can’t think of any reason where I would need to know who that person is or to tie it back to their personal health data. It’s much more an aggregated do not or anonymized standpoint of just how many people, how many members are using this? How many people are not? And feeding that to the product team to say, “Hey, people really like the blue button versus a green button. They like this feature, but not that feature.” To really inform the roadmap versus us just making wild guesses at it.

52:29 – Data offers people personalized insight Ben said that while Levels can give generalized food guidelines, personal data is a much more powerful resource for living a healthy lifestyle.

We can just look at data and say, on average, food X gives people a metabolic response of whatever the number ends up being. That is, having that data gives people more assurance to know where they stand as it relates to the mean. And I think that that’s really important too, so people can say, “Great, I don’t don’t do well with this, but when Billy said, ‘Never eat that thing again, it gives you a spike.’ It’s like, we want to avoid that.” And that’s where data can become really important to provide people with personalized insight. And that’s also part of product, but we can only surface these insights in product if we’ve got the data. And so that’s the important thing is saying, “Cool, here is the data, here is your personalized data or here’s the way you can look at this.” And then people can make decisions around having those insights.

57:22 – There’s no universal approach Chris said personalized data is great for helping individuals, but it also makes it harder to scale because data isn’t universal.

It’s really powerful, the personalized data, but it also makes it much harder to scale because now on the support standpoint, we get people riding into us all the time, going, “What foods should I eat?” Or, “I had a spike, what else…” “I can’t eat this type of food, what else should I eat?” And because of what you just mentioned, it’s all personal. Just because I might say, “Hey. Yeah, I got really bad spikes from that Chicago Deep Dish Pizza, but at New York thin crust, I get great scores.” Doesn’t mean everyone else is going to have the same response. Some people might say, “Wow, I got awful scores with any type of pizza, like thin, thick, whatever.” So me recommending a thin crust to someone could be absolutely the wrong thing for them to do because I might say, “Hey, that was the point of that mix of fat and cheese and carbs of the thin crust was good enough that my system says, ‘Yep, I can handle this.’” Where other people might say, “Uh-uh, I really can’t have any pizza, I just need to stick to salads and things with a lot less carbs.” That makes it hard to scale when you’re like, hey, we have all these insights from people because it’s more of like a, N equals one, you’re like, “How do I apply these aggregate insights to an individual without them experiencing it for themselves of like, what are they eating and their reactions to it?” So it just becomes harder for a member because they want all this data.

Chris Jones (00:00):

One of the benefits of kind of living where we are is call it lack of cell phone coverage, or lack of coverage where if I’m out hiking or doing the chores, and I’m like, all right, I’m in an area where there is no cell phone reception and I’m going to be here for three to four hours, enjoying whatever activity I’m doing, it helps me be in the moment as opposed to the, well, what didn’t I get done today? What’s that next to do item, the next dashboard. I’m like, hey, I’m just completely disconnected. Like you need to recharge by really turning work off. And that’s what’s hard to do in this kind of hyper-connected world where everyone’s got 5G phones that can do everything on it. It’s like you never turned work off.

Ben Grynol (00:52):

I’m Ben Grynol part of the early startup team here at Levels. We’re building tech that helps people to understand their metabolic health and this is your front row seat to everything we do. This is A Whole New Level. From small companies to big companies, that startups to large tech codes like the FAANGs, the Facebook, Apple, Amazon, Netflix and Googles, well, they both have very different ways of working. We’re very much a startup and we have people who’ve worked at all different types of companies. Well, for Chris Jones, Head of Member Experience, Chris has been part of the small scrappy startups. And he’s been part of some of the worlds largest tech companies. That’s companies like Google, companies like Nest, companies like Zynga, he’s very much done it all.

Ben Grynol (01:50):

In early 2021, Chris made the move from the Bay Area, San Francisco, all the way to Montana. Chris and his wife, well, they decided they wanted to change, they wanted something different. They made the move, they got an acreage and now he lives on a farm. Yes, Levels is made up of team members with all different backgrounds. Chris has a full farm, he has horses, he has a tractor. He has it all. It’s not exactly what you think of when you think of people working in tech. He’s unbelievable at member experience, member support, analytics. He’s so well versed in all these things that he’s had this life experience and built his career around. But now that remote work is a thing now that it is ingrained in many companies way of working.

Ben Grynol (02:38):

With levels, remote is our default mode. And that is what allowed Chris to take this move. Chris moved to the farm before he started with Levels, but it was very much a decision that he and his wife made together. Being on a farm was about living and having a life experience. Not about living in a city, because that’s where your work is, but working in a place that you really want to be. So Chris and I, we sat down and we discussed this idea of what it’s like to live on a farm and work at a tech company at the same time. It was a really fun conversation and our team always loves hearing stories from Chris. He has such a cool way of going about his days and here’s where we kick things off. Where exactly are you? You are not in a closet.

Chris Jones (03:32):

I’m in my office or AKA my bike room, my office and my tool shed. It’s the trifecta.

Ben Grynol (03:40):

Ah, you sort of have these like three areas that I can think of. This is a viewer’s lens, bike room is 90%, then you’ve got, it looks like your kitchen or something like that with green cupboards and then there’s one where it’s like the windows behind you, but that’s probably not as frequent because the sun blazing from behind.

Chris Jones (04:01):

That’s our living room out overlooking the mountain range, which is maybe 30 miles behind us. And it’s beau… Like every day when I get up and I come out by the bedroom, I look through those windows, seeing the mountains and especially if it’s a sunny day, I’d be like, “Wow, I’m so lucky to live here.” And it’s just the way I love to start my day, is kind of looking out at nature in this kind of grand vastness and just be like, so what am I going to do to get out there today or to get some vitamin D or to go hiking or mountain biking? So it’s been an adjustment moving to Montana, but if you embrace the outdoors, like it is just Disneyland for the outdoor person.

Ben Grynol (04:50):

What was that decision like? I know we talked about it before, but you and your wife were thinking about it before pandemic. Correct?

Chris Jones (05:00):

So we’ve been thinking, we knew the Bay Area for us had a timeline on it. And it always felt a little bit romantic of the, oh, within five years we’re going to leave the Bay Area. And it starts opening up the whole, well, what’s next? What’s our next chapter? What’s our next job? What are we going to be doing? But it always had been kind of five years out. Because Nicole’s parents live up in Whitefish, we’re here twice a year. And every time we would come or really every time we would travel, whether we’re going to Europe for my wife’s work or taking a vacation, every time we’re out enjoying, we’re like, “Wow, like where do we want to live next?” And just kind of having that conversation around, “Is it France? Is it Dublin? Is it Germany? Is it Vienna? Is it Montana? Is it Bend, Oregon?”

Chris Jones (05:57):

It was just so much fun to kind of play through the what if game. And there was a number of times where through my wife’s work, that she was offered to move to Europe and it made me think like, “Wow, what would it be like to live in Europe for five years and see all the countries, not just on a weekend or like once every couple years, but like every weekend?” So as we got closer and closer, kind of, and this is pre still pre-pandemic, we realized that we wanted to shorten the timeline of like let’s buy land and build. So it then brought it in from a five year window to a two to three year window, just because of how long that takes. So in typical analytic fashion, I built a spreadsheet.

Ben Grynol (06:43):

Of course.

Chris Jones (06:45):

A research in all these cities, mostly in the US, but a couple international things like average number of inches of rain, number of inches of snow, number of sunny days a year, average cost of living, distance from a major airport, types of activities. It was just, I was scraping data from city data and just building my own sheet and thinking to myself going, I really need to build an app for this for other people try to do this exact same thing of like, what are the things you care about and how do you pull it into something locally? And it was fun because I’d love that type of the research phase. But what was hard was maybe two thirds of the places on our list, we had never been to. Places like Maryland or North Carolina, we’d been on the west coast for over 20 years and there’s a lot of the, “Oh wow, like what would it be like to live on the east coast and to only drive an hour to see these major cities?”

Chris Jones (07:52):

But in the end we realized, a lot of these places, we would be completely starting over. We would have no friends, no family, and in a remote environment, we would have no coworkers really. And that felt a little isolating. So as we continued to narrow in on it, a big draw for us was, hey, like we love Montana, but we were a little bit afraid of the winter. Me growing up in a small town, Iowa, Nicole growing up in Whitefish, we got used to the California sunny days and lack of cold and we didn’t know if we could go back to it. But there was something for, time is short and being able to spend it with your friends and family and for us family of, let’s go back and enjoy time with Nicole’s parents, her aunts, her uncles, her brother, her nephew, while we can watch him play football games or basketball or grow up or… and also while my wife can ride horses with her mom while she’s still young enough to do it.

Chris Jones (08:59):

Like let’s not wait until we’re at, say their caregivers and we’re coming back here to take care of them because they can’t take care of themselves. Like let’s actually enjoy the time we have together to go fishing, to go hunting, to do the things that… as opposed to just once a year, but every weekend. So for us, the decision really came down to her family and it’s been absolutely great. I love her family, they’re a lot of fun. We were over at their place last night watching the Super Bowl and it just reminds us, especially in times of COVID, of how much family matters and we’ve all… a lot of us from places like the Midwest, as soon as we get out of college, we run away to the biggest city we can and move as far away from home. But I’d say coming back to home, for Nicole’s home, is really peaceful and it’s really puts things in perspective and been a lot of fun.

Ben Grynol (09:58):

Yeah. So it’s a wild journey that you took because we didn’t set it up. But you went from living in the Bay Area, which you mentioned for 20 ish years. So living on the West Coast to living on a farm, which is a complete juxtaposition, if you think about the world of a tech startups and farming. And we also have to go one layer deeper, you’re not actually farming or a farmer, but you live on a farm and you do have horses and you have the responsibilities of owning an acreage, which is to say that you’re not farming, you’re not farming from an agriculture perspective or you’re not farming things like livestock.

Ben Grynol (10:40):

But there’s a ton of responsibility that comes with that and it’s not a mental model that I think a lot of people would have when they think somebody works in a high growth, high paced, fast startup, but the life they live is very much this life of being in the open country and it’s very freeing and it’s very different in outlook. So it’s an interesting life move to have made and it’s almost like starting over again, like the way that you’ve framed it previously, where you’re resetting your lens and learning new things that were so far outside your comfort zone, but it’s almost this challenge of saying, “Hey, I’m exposing myself to new things that I didn’t really know would even be part of my lived experience.” And from what it seems, you really seem to be enjoying it.

Chris Jones (11:29):

For the most part, it’s been a lot of fun to… One of the benefits of kind of living where we are is, call it lack of cell phone coverage or lack of coverage, where if I’m out hiking or doing the chores, I have to force myself to turn work off and agree, it’s because if I don’t have any my phones not connected anymore, I have to embrace myself in the moment of versus like the phone of like, let me just check my email, let me just check my email, let me just check my email, because in the Bay Area, you’re connected all the time. And I’m like, all right, I’m in an area where there is no cell phone reception and I’m going to be here for three to four hours, enjoying whatever activity I’m doing. It helps me be in the moment as opposed to the, well, what didn’t I get done today? Like what’s that next to do item, the next dashboard. If I’m like, hey, I’m completely disconnected like you need to recharge by really turning work off.

Chris Jones (12:27):

And that’s what’s hard to do in this kind of hyper-connected world where everyone’s got 5G phones that can do everything on it. It’s like you never turned work off. So some of the functions of things like, all right, I have to go out and mow the lawn. And for some people that might say, “Oh, that’s like a half hour.” For me, it’s a six hour chore and I need to dedicate like sometimes break it up over two days. I’m like, all right, I’m going to be on the tractor for six hours, I better have make sure I’ve got a good audiobook downloaded because I’m going to be here a while. And it’s liberating to kind of make sure you are taking time for yourself and also some people meditate, some people… I ride a lot of bites or go for running. And for me, a lot of the chores on the farm or just another form of meditation of I’m out there mowing, moving dirt around and you get the sense of accomplishment. Plus a little bit of, I need to turn my brain off from work otherwise I’ll just get sucked in.

Ben Grynol (13:27):

What do you think it would be like if you were working, so let’s also frame it. Past experience, I had to do the laundry list because I knew, let’s say, 70% of them off the top of my head, but there were a couple companies that I didn’t know as well, even though we’ve talked about it. So Google, Nest, Beartooth, Zynga, Adobe, Intuit, CNET, Ernst and Young. It’s a very strong stack of companies that you’ve been part of. And the most recent one was Google. So that was sequential as far as the way that they were listed out, but some companies, so not all but many companies, you hear about this challenge that people have, where the expectation for response times, and this has to do with communicating as a remote team, communicating in a synchronous fashion and creating unrealistic expectations as far as, “Well, I emailed you and you haven’t responded within six and a half minutes.”

Ben Grynol (14:28):

When you have this expectation from team members, it could make it really challenging if you were in an area where you’ve got lower reception. How do you think it would change, like let’s make the assumption that you moved to Montana and we communicate very much asynchronously. So if you don’t respond to something for 15 hours and no one’s like, “Man, why is Chris not responding?” It’s just like, he’s going to respond when it fits into his day. And you know, like you’re prioritizing according to how time sensitive something or how urgent something is, it’s not that you’re ignoring everything for 15 hours. But what do you think it would look like if you moved to Montana and there was this expectation for like being constantly connected. Do you think that your outlook on it would change or it’s like, “Ah, I don’t know if I like this as much,” or is it just sort of like neutral?

Chris Jones (15:23):

It’s a great question. I would say because having the asynchronous nature, being in a place Montana, in my opinion, really allows me to enjoy it at a level much higher than my wife who is still at Google. So for example, I might say, oh, for lunch, I’m going to have my lunch and then go for a walk because one, I want to get outside, two, Levels tells me it’s a good thing to control my glucose levels and three, to get the dogs exercise. And I realize I can almost plan to do that every day and move work around it where my wife will lock herself in her office from 8:00 until 6:00 and she may emerge for 15 minutes just to grab a bite to eat and go right back to beat on Meet calls, they’re equivalent of Zoom, all day long.

Chris Jones (16:18):

And she it’s like, I almost never open her office to give her a coffee or check in on her. And she doesn’t have some live synchronous meeting going on all the time and it looks exhausting. And usually at the end of the day, she looks exhausted. Like she gets done and she like, “All right. Wow, like that was a challenge,” and I’m like, “Wow,” I’m like, “That’s got to suck.” Like where you just feel like you’re reacting to the emergency all day long versus saying, “Hey, I’d say, you want to go take some time off during the middle of the day when it’s sunny nice and do yoga or go for a bike ride or go for a walk and take the dogs?” And realizing in that, yeah, so I’ll get done when I need to. But I mean, if I might be doing it while I’m watching the Olympics at night versus during the best hours of the day is when it’s sunny and warm out.

Ben Grynol (17:10):

Like there’s no riding horses in the middle of the day for her. Like she can be like, “I’m going to do it for, even if it was an hour.”

Chris Jones (17:18):

She’s made that… There is for her, but it was really hard for her to do. Where she basically said, “Hey, life’s too short, I’ve been here 10 years, I’m going to take every Wednesday afternoon and I’m just going to like put that in block on my calendar and go ride the horses.” So because otherwise her day will fill up. If she plans for it, she might be able to do it. But she can’t react of like, “Hey, it’s sunny out right now, I’m going to ride the horses.” Where I can.

Chris Jones (17:49):

Like I can kind of more opportunistically say, “Okay, I’m a fair weather person when it comes to exercise, I’d rather be outside when it’s nice and sunny and warmer than cold and dark.” So I’ll be staring out outside all the day, all of a sudden the sun will pop up and I’ll like quickly look down and going, oh, I’ve got no meetings for the next four hours, you know what? This is a good time for me to take a break for me to take the dogs out and enjoy the beauty of Montana. Where she has to basically say, “I’m going to take work off every Wednesday afternoon and that’s the day I’m going to ride horses to make sure I’m getting it in.” So she has to plan for it, I can react to it.

Ben Grynol (18:26):

Yeah. And I would imagine like when you do that, so let’s say, I think it was like last week or the week before, when you’re like, “Oh, I went cross country skiing today because we got a big dump and it was really enjoyable.” And it was like a, I don’t know, it might have been three hours. But I would assume you’re not like checking your phone all the time out of hyper anxiety of like, what if somebody’s trying to reach me and they are like, why isn’t Chris getting back to me?

Ben Grynol (18:53):

Whereas it’s like, if people are in a synchronous environment, maybe not synchronous, but one where there’s an expectation as far as having a high response cadence, then even if you have the time booked off, like cross-country skiing and it was an hour. The whole time you’re like, okay, I have to get back to my phone. What if somebody… if they’re trying to reach me and I’m not responding, people are going to question where I am and what I’m doing. And it’s such an odd thing to think about when… Like one of the things that we always talk about is treat people like adults and the opposite of that is treating people almost like children. Like, okay, you do exactly what we’re going to say right now and it’s odd having that prescriptive environment for people to work in.

Chris Jones (19:44):

Yeah, I totally agree. And there’ll be times I’ll go and I won’t even take my phone with me or if I’m doing it, I’m only doing it because I want to listen to a podcast or listen to music or kind of do something multitask, but I’m never doing it with the intention of, I need to be connected for work where, when my wife is out or writing, she has two phones on her, she has her personal phone and her work phone. And she is much more reactive to like, if it buzzes or rings, she may stop writing her horse and take it out and check on it. So she’s probably likely not as present as I would hope that she would be where it’s like, “Hey, I’m just going to leave my phone at home and…”

Chris Jones (20:24):

But when I went skiing the other day for three hours, it was an area where there was no cell phone coverage and the half hour drive in there and out of there, no coverage. And it wasn’t until I stopped for lunch afterwards and got on their WiFi and I was like, okay, let me see if there’s any thing urgent to respond to. And of course there wasn’t because Levels doesn’t really work that way. There’s like urgent like, “Get back to me right now, right now,” where her world does. Like she gets involved in if there’s a data breach or someone tried to hack Google and she’s providing kind of legal defense. So she does have this little bit more of like she can’t fully let go. So she tries by scheduling it.

Chris Jones (21:07):

But for me, I can actually kind of… I feel like I can enjoy Montana more just because of the asynchronous way of Levels of, yeah, I know I’ll be checking all my threads tonight, looking for anything I need to respond to or tomorrow and that’s okay and people can wait. There’s nothing so urgent that they need in my response within an hour and I’ve missed the entire thread. And that’s really, I won’t say powered, but really relaxing of like, I can enjoy the time that I want to take to do what I need to, whether it be mowing the lawn or doing yoga or going for a bike ride versus this constant, you’re right, like every time your phone buzzes, you feel like you have to stop your bike, pull your phone out, look at it and then check, I’m like, “Is that emergency? Yes or no? Like let me get going.”

Chris Jones (21:52):

Which is what I faced when I was in the Bay Area for a lot of high tech companies. I would be on a bike ride and all of a sudden my phone would ring and I have to stop and take the call and people are like, “Are you walking up steps, breathing heavy, what is it?” I’m like, “Yeah, I’m on my bike right now but you called and you need answer, what is it?” And that is really hard to get into zone of mentally I need to go on kind of disconnect when you’re kind of constantly waiting for that game of Whac-A-Mole, which I think I talked to Sam about when I first joined Levels. My experience kind of being at places like Google was they’re using chat all the time and having run a lot of large call center supports and people doing concurrent chat, agents will tell, one chat simple, two is a little bit hard, but three is just like, it’s unmanageable. You can’t do three or even four, it’s just crazy talk.

Chris Jones (22:46):

And I’m looking at going, wait a minute, any a given day, I have eight to 10 chat windows going on all day long with people across different teams. And it’s just constantly like instant text messaging on all fronts and I’m just multitasking across 10 or more chat windows, like a game of Whac-A-Mole of just like, someone chatted me, how quickly can I get back to them? And it does build this, people expect instantaneous response back for not just urgent things, but like any like, “Hey, I got a quick question,” and you’re like, those quick questions take you out of whatever focus you’re doing, which is why when I would work for places like Nest or Google, I would usually do most of my work at night when I’m not getting pinged with 100 chats all day long of like, all right, I need to do some deep thought. And it would come at the hours of 7:00 PM to midnight because that’s the only time I could free up myself mentally to focus on the problem and make progress. Otherwise, I’m reacting to things all day long and I just couldn’t get anything done.

Ben Grynol (23:46):

Yeah. When you’re trying to get into a zone of deep work and it’s just constant notifications, it’s impossible. And even if you’re not doing something that is work related such as Nicole riding horses, like if she’s mid canter and she’s like, “Okay, hold up, hold up. We got to stop. There’s somebody that is Google Meeting me. Like somebody is just cold calling me on Google Meet.” Like what do you do? Like you can’t… It’s just, it’s not something that’s easy to do. So you can’t immerse yourself in that experience where you’re trying to ride a horse. You’re just trying to canter. And it’s like… Like constantly going-

Chris Jones (24:25):

Ben, I’m impressed you know what cantering is. Like that’s more knowledge than most people. That’s…

Ben Grynol (24:31):

Oh, come on, Chris. I’ve been on a horse once or twice in my day.

Chris Jones (24:35):

Good, nice.

Ben Grynol (24:37):

But yeah, I mean, it’s one of those things where it’s really hard to immerse yourself in that experience and feel deeply connected to it. And the same thing goes with deep work, but I’m curious, like you’ve worked across startups, the scrappiest stage of startups, and you’ve worked with the largest techs companies. So you’ve seen the execution and the outlook on both. And what was it when you… so you made the decision to leave Google to move on. And the way that we operate is completely different in not only in execution, but we’re at the opposite end of the spectrum as far as stage goes. What did that feel like as far as when you made that decision and you’re like, oh, we’re like really deep in the weeds?

Chris Jones (25:23):

Pure joy. What I found is, as I look back at my career, even regardless of kind of who my employer was, the times that I was the most happy was when I was on the scrappiest teams, whether that was at TurboTax or Nest or Adobe, like in these large well established companies, I always found myself navigating towards what skunk team is out there that I can kind of attach myself to, because they’re trying to be innovative. At Google, the equivalents is kind of Google X, where you kind of have true innovation as opposed to being slowed down by the big machine. And I always found myself just navigating towards the teams that were trying to say, “Hey, let’s get five or 10 people together and let’s come up with some crazy and see if we can get it off the ground and then pitch it to kind of management or how do we scale it?”

Chris Jones (26:17):

Or things I was doing myself within operations or support. So by nature of it, like if the processes is fine that I can do in my sleep, I’m going to get bored and I’m going to leave. Like, I love the challenges where I don’t know what it looks like, I have no idea and the heavier it is, the more fun I have. Where the answer isn’t the, “Hey, there is a right way and a wrong way to do this and if you follow all the best practices in someone’s playbook, you should have a good outcome. Like that’s the boring stuff. It’s all about the, we have no idea how we’re going to do this, but we’re just going to keep trying and throwing spaghetti against the wall. Like that’s where I have fun. So what I realize is even within big companies, I navigate towards the startup environments within those companies. And as Google gets… it got bigger and bigger, the number of opportunities that you could kind of jump onto became less and less. They used to have a lot of culture for just tons of innovation and tons of ideas.

Chris Jones (27:17):

And over time, they realized like, “Well, we can only launch so many products and to scale them and put marketing effort behind it.” So they really over time reduced the amount of these random ideas of two engineers going to town to build that next new app. Like it still happens a lot but much, much less, and it’s much, much harder to find. So to some degree, I’ve always found myself to thrive or to love the startup environment, whether I was of the fourth employee at a Beartooth or the 900th employee at Nest or the maybe 24th at Levels. Like the more that we are just completely experimenting and trying and I’m taking big swings, are where I have the most amount of fun. Which gives some people the most amount of anxiety, like it just scares them to that. So like, “Oh my God, what’s going to happen if this goes wrong?” Like, “Well, we’re going to learn and we’re going to keep iterating. We’re going to keep going.” So that’s where I have fun and that’s where I get my energy from.

Ben Grynol (28:17):

Yeah. When you came in and I think we probably frame this all the time is whether it’s member episodes, that people come in through the Levels Community or team member, when we have team member conversations, there are a number of people that came in through the community first. And so I think that was a first connection point is that you started using Levels, like everybody on the team became obsessed with the problem space and all the things that were being done and went really deep on documentation, participated in some of things like the UX journaling experiment that we ran and then that led down the path of coming in.

Ben Grynol (28:57):

But when we started having conversations, I think when you’re talking with a number of members of the team, as well as doing the documentation for like just your general interest, you’re like, “I just love building things,” and that’s essentially what you’ve come in and done is you’ve just been building, building, building against all of our member experience and analytics initiatives, but really taking the reins. And it’s like, no one’s stopping you like you. I mean, all the bureaucracy that exists in larger organizations is gone. It’s like, if you want to do something, everyone’s like, “Sweet. That’s like one less thing for any of us to think about.” And so it’s so cool to watch different team members come in and just take on certain areas and go really deep in them.

Chris Jones (29:44):

The journey to join Levels was one where I had no aspirations about joining the company full time. I just, I ran into an old coworker of mine who was an early investor in Levels, who I worked with that Nest, who I you know, huge respect for. And we were walking our dogs down Ocean Beach, outside San Francisco, and he’s like, “Chris, you’re a data guy, you’re an athlete, you have probably five trackers on you right now between like a Whoop, a Fitbit and a Garmin Tracker.” He’s like, “I think you really enjoy this. And he put me in contact with Sam who got me kind of past the waiting list. And a new set of data for things that just made… Helped me explain things that were happening to my body and system that I had no other answers for and it just… within the first two dates.

Chris Jones (30:39):

That, aha moment, I was in and I was hooked of like, this is absolutely incredible and realizing some people don’t always have the, aha moment, and everyone’s kind of different, but for me, I was like, I was in and as I did the 35 page write up of my every day, the unboxing, the feedback, the journaling, the community calls, I’ve realized, I sat back for a while going in. I’m doing all this for Levels just because I want to be helpful. Like I’m not advocating for a job, I’m not trying to do the best homework, I did it because I had passion for the product and I wanted it to be successful. And I said, “Hey, if any of my knowledge or any of my ideas is helpful, great, here you go. If it’s not and you hit delete and you want to block me, I’m not going to be offended.”

Chris Jones (31:26):

And I just felt bad sometimes for Sam, because it was, at least after every other Friday forum, I’d be emailing him about some idea like, “Oh, you guys talked about doing voice of the member. You guys talked about doing text analytics. You talked about doing surveys, like have you tried these 500 things?” And when I realized I was doing a lot of this work for free and I would continue to do it like, yeah, that’s the type of company I want to be at where you don’t have to pay me. Like I enjoy this so much, whether it be the mission, the team, the product or the work that… I’m like, “Wow, I actually get to do this and be able to be part of the team.”

Chris Jones (32:03):

And then like the salary and any equity become pure gravy and a bonus. But I mean, I felt the same way when I was at Beartooth. Like, I mean, they were a much smaller startup and not only did I not get paid, but I had to pay for the luxury to work there. So when you’re doing your version of a Kickstarter and you’re spending your own money funding those Facebook ads or those Google ads and it doesn’t deliver on the ROI or the Return On Ads spend that you hope, that’s a scary moment where you literally have with your own money in it. And when it doesn’t materialize, you’re just like, I’m just lighting dollars on fire.

Chris Jones (32:43):

And I have to pull these things back in a hurry. That’s the scary time when you’ve got your own kind of hard earned cash in it versus like when you’re at Google or some big company like, “Hey, what’s going to happen if this test doesn’t work?” Like you’re not going to get fired. Like maybe there’s really low… you have no skin in the game or very little other than your boss saying, “Hey, good job on that project.” So when we were launching new products at Nest and the team was all getting super excited and, or nervous, they’re like, “Chris, why are you cool as a cucumber?” I’m like, “Because this isn’t pressure. Pressure is when you’ve got a startup where if this doesn’t work, we’re going to turn around and fire 75% of the company, that’s pressure.”

Ben Grynol (33:26):

And you were at Nest post acquisition?

Chris Jones (33:29):

Yeah. So post acquisition, but when they were still part of what alphabet would call in other bets. So they were still treated like a separate company. We were on our own campus, other than Google writing my paychecks and getting the benefits and kind of like the comp, it felt like I was working for Nest. But then I also worked kind of as that conversion from Nest merged into Google hardware. And that’s really when I saw the big behemoth of the machine that is Google. Where at Nest, it was maybe 800 people, but we were still pretty scrappy. We could have our own stack of Salesforce or Tableau or whatever database and then all of a sudden within Google it’s like, “Nope, you all have to be on the same tech stack. I don’t care how cool your innovation is or how much it’s empowering agents or how insightful it is.”

Chris Jones (34:21):

Like we scale by getting everyone on the same tech stack and it’s took them, I think, three years to get Nest onto Google’s tech stack. So think about as a company where you’re no longer really innovating at the speed you were, you’re doing all your work to port your tech over from one product to another product. And you’re really not making steps forward from a customer or a member standpoint around that new feature, you’re not making your agents better by arming them with better data, you’re just porting it from one database to another because that’s what Google uses versus what Nest. So that’s it. It was painful to kind of watch those large acquisitions by larger tech companies where you’re like, “Oh yeah, we’re going to get synergies by merging these two huge companies.” They’re like, “Maybe in 10 years, but the next three to five are going to be pretty bumpy.”

Ben Grynol (35:16):

Yeah. Integration’s such a hard thing. I mean, if you look at the stats of acquisitions, so many acquisitions don’t work out for different reasons or they don’t provide the value that they thought they would, neither here nor there. And there’s good HBR articles, there’s a really old one. I can’t remember when it’s from. It’s probably very old now probably 20 years old. But where there’s a lot of challenges is around integration. And if companies don’t set up the expectation around what a great integration looks like, that’s where things can be very, very challenging because of maybe misaligned expect around what the acquisition or decision making might be. And we saw this, again, this is from an outsider’s perspective, everything is anecdotal because you can read what you read in books, but none of us, if we’re actually there, you don’t know what it’s actually like.

Ben Grynol (36:11):

You hear about this with the Facebook, Instagram acquisition, where there was maybe misaligned expectations around what the next steps for execution would look like. You can see it with what it sounds like when you went through an integration, even though you were part of Google, you weren’t integrated into Google. And so that becomes challenging. Even with Skip, we saw it where integrating with different companies is really hard and you have to be intentional about it. And it’s not something that is comfortable nor easy, but a lot changes. And I think the larger the organization, the more challenging it becomes.

Chris Jones (36:51):

It’s true. But looking at… talking to a lot of the M&A teams at places like Google or large companies, a lot of them will say, “Hey, we realize,” there might be company X, Y, Z, that they’ve got their eyes on to acquire and they realize it could be easier to integrate it when they’re rather small, but they also realize that the company’s going to move a lot slower after the acquisition. So they kind of say, “Hey, let’s more…” Maybe an example, Google will do this with their Google Ventures of like, “Hey, this is a company we actually like, instead of acquiring them, let’s just give them more money to accelerate them,” that way when they kind of really get to critical mess, they really get kind of stuck, now they’re actually a better acquisition target. Not from an integration, because we get more tech stack to kind of unwind.

Chris Jones (37:41):

But from a, they’ve really kind of achieve product market fit. They’ve really have got a large audience and they’re starting to run into problems that they just don’t have the cash to kind of get to the next step. So it was interesting to me where you have a lot of companies that say, “Yeah, we would like to have acquired Instagram or WhatsApp or whatever, five, seven years ago, but we realize that by doing that, we slowed down their innovation just by being part of this larger company and they would’ve taken their eye off the ball. So instead, we’ll kind of fund them from the outside to continue to let them accelerate when they’re scrappy, they can take bigger risks versus when you’re part of a large company like Google.”

Chris Jones (38:23):

And I even saw the difference with Nest, even though they were owned by Alphabet, the moment the product went from having the Nest brand on it to the Google product, everyone like, “Oh well, now you have to get approval from 10 different marketing BPS because it’s a brand, you’re now tied to the Google brand, as opposed to like this sidearm.” And that slowed things down of just how people had to approve anything just because the brand itself is so big and kind of designed to kind of keep people from doing all this wild stuff onside.

Ben Grynol (38:55):

That’s when things start to slow down, that’s when things change. But with big companies and with small companies, there’s a lot of opportunity to learn with both and in different ways.

Chris Jones (39:07):

Totally, totally. Yeah.

Ben Grynol (39:08):

With some of the things that you saw, like you’ve seen analytics, so everything that you do currently and everything you’ve done in your past around analytics, what are some of the things that you saw work really well, which you’re like, “Okay, yes. We’re going to implement that. We need to build upon that for what we’re working on,” or what are some of the things where you were like, “Okay, we’re avoiding that at all costs.” Like are there certain things when it comes to analytics where you have strong opinions, loosely held, we’ll call them that, because of experience, right? Like you’ve seen things that work and seen things that don’t work, where you might say like before we even go down a rabbit hole, you might be like, “No, we’re not doing that. Like I’ve seen this movie, I know the ending.” What does that look like when you start to think about the way we should think? Because we have the opportunity to build from the ground up. Like what’s your outlook on that?

Chris Jones (39:58):

The theme I would say is a democratization of data. And the place I saw this that shocked me, but I thought it was really well done was when I joined Zynga. And so I was coming in with an analytics background. I was there to build their text analytics and kind of voice of the customer program or voice of the player program at scale using surveys and text mining and just basic analytics for member insights. So I’d heard about this very large vertical database that they had, all these log file data and could get all these great insights from all the data scientists that had joined the company before me. So I said how, week went on, like how do I get access to the database? And they said, “Oh, just show up at this room every Monday. There’s a class from like 12:00 to 1:00.”

Chris Jones (40:49):

So I show up in this room and it’s standing room only just packed with new hires. And the person asked the question, “Hey, all right. So this is the meeting. At the end of this meeting, you’re all going to get access to the production database for analytics. How many people in this room have ever written SQL, which is the language you write against databases to do things like how many members download the app yesterday or last week or clicked on this feature?” Less than 25% of that room raised their hand. Which was just shocking to me of you have a room of people not to see, “Hey, I’ve done some analytics, I’ve done it here,” but people that have claimed of I’ve never written SQL in my life and you’re going to give them access to the production system that all games run on.

Chris Jones (41:42):

And their view was we want data in as many hands, answering as many questions as possible to scale it. So they invested tons in terms of making their data set open to the entire company. Versus like, “Oh well, you’re not an analyst. You don’t belong to this part of the org. You’re not in IT, you’re not in this team. Therefore, you don’t get access.” Which is typically what most companies do. They kind of lock it down behind like only the DBAs have access and to get access, you have to make a request and then request it, which is why eventually business users give up and go around and use things like Google Sheets or Excel because they can’t kind of get access to the data. So for me, a big one is getting as many people on the system, using the data as quickly and learning as fast as we can. Which has been great.

Chris Jones (42:30):

I mean, [Gin Lu 00:42:33] and Helena have done an incredible job to get Snowflake up and running, which is super powerful, but you’ll get myself or J.M on the data and we are just throwing spaghetti against a wall and probably sometimes giving Gin Lu a heart attack, what we’re doing with the data. But it’s in the spirit of like, all right, like how do we learn? How do we grow? How do we have fast things? It’s not the… So Ben, if I think about the example gave me this weekend of, “Hey Chris, could I get this dashboard to do X, Y, and Z?” Like I probably turned around something scrappy within about an hour’s worth of work. It’s like, Hey, all this data doesn’t belong in… isn’t in our data warehouse today, but what can I give you and kind of stitch it together quick? Just to see like, are we in the right direction?

Chris Jones (43:14):

Versus the, “Oh Ben, that’s a great request, but I can’t do any of that until I make a request of the data or M&A team to source all this data, to build you that one metric and it’s going to take six to nine months to do.” It’s more about like, well, what data do you have? What analysis can you get? How close can you get and iterate? And then that feeds the, well, what should we be building and what should be the next source? So I’m very comfortable living in kind of that gray land of like, well, let me just randomly pull data from things by hand and stitch it together, just like, is this right? Does this help? And if so, then great.

Chris Jones (43:49):

Then how do we make that more efficient and put that into a system like a Snowflake, make it more productionalized versus the, a lot of company’s like, “Well, let’s go, we take all the requirements. Let’s get all the business needs. Let’s go source all the data into a warehouse, let’s normalize it. And then we’re going to start slowly building dashboards, and it takes three years to get them off the ground.” By which time, all the requirements are no longer valid, all the people that ask for those requirements, no longer work there, the company has 17 new products and it’s just, it’s waterfall approach to kind of building analytics and kind of data warehousing and dashboards is just, it just pains me when I see companies going down that route.

Chris Jones (44:30):

And I did one of the… Everyone on content, I did an article talking a little bit about that with my Kantian team. And the day that article got published, one of my old bosses from Intuit called me up asking for help with one of his clients who wanted to do that very waterfall approach. “Hey Chris, do you know any people in the analytics space who would help my client with interviewing all the stakeholders, coming up with a list of every KPI and requirements documented and a data dictionary and this like three year plan to build a new data mark?” I’m like, “Oh, this just makes me cringe.” I’m like, “Run, runway, run away now.”

Ben Grynol (45:08):

But it’s important what you’re doing, how you’re saying and we should drill down on one part of it, which is when you say the democratization of data, it’s still very much anonymized and it’s still macro data. So when talking about people having access to data, it is not personalized data where we are able to see everybody’s individual data, but we’re looking at macro data aggregated so we can say, “Cool, how many food logs were there yesterday at between like 2:30 PM and 4:30 PM?” Like that type of data, if we wanted to.

Chris Jones (45:43):

You’re absolutely correct. Whether it’s encrypted or anonymized or yeah. There is a certain… In that world, there is a absolute requirement of the treating your customer’s data with respect. And what can you do to still kind of enable the business, but to say, “All right, I don’t need to know that John [Doe 00:46:06], what his glucose reading for yesterday,” but I am trying to figure out like, “Hey, we just rolled out this new feature in the app, are our members finding that new each are useful? And do they like it? Do they not like it?” And that level of kind of log file data around kind of the product and in their experience is super powerful to kind of say, “Are we helping people in their journey? Yes or no?”

Chris Jones (46:27):

But you’re right. I can’t think of any reason where I would need to know who that person is or to tie it back to kind of their personal health data. It’s much more at a aggregated do not or anonymized standpoint of just how many people, how many members are using this? How people are not? And feeding that to the product team to say, “Hey, people really like the blue button versus a green button. They like this feature, but not that feature.” To really inform the roadmap versus us just making kind of wild guesses at it.

Ben Grynol (46:58):

And that’s something that a number of people on the team, everyone on the team has the lens on the importance of privacy. It’s not something that we’re trying to pay lip service to. It’s something that everyone believes is inherently important to our mission because, not only should people own their data, but it’s health related data. It’s very personal and it’s data that people should have ownership over what is done with their exact data. What we can do with a large data set that being, “Gosh, what are we at now?” We’re at, as of yesterday, we’ll just call it, one eight, 1.8 million food logs. What we can do with that, as soon as we drill down and we can start to look at what is the response to Skittles, things like that. We know Skittles is objectively the, I was going to say food, can you call it food? [inaudible 00:47:51]

Chris Jones (47:53):

I mean, it has calories, I guess. It’s a form of energy.

Ben Grynol (47:57):

That’s a Robert Lustig discussion, a deeper discussion, but I almost called it food. We’ll call it food for the sake of it right now. But we know objectively, Skittles give the poorest overall metabolic response in our dataset. So we can start to surface certain things, certain insights and say, “This is something that people should avoid.” I think anecdotally people should probably know that they should avoid Skittles. I think we give Josh a nudge on this one, I think he… is either Josh or his pops love the Skittles, but yeah, it’s one of those things where being able to see this data and then surface these insights for members across the community and say, “Instead of this, try that.” And that’s one of the areas where we’re trying to get to with personalization, but you absolutely can’t get there without A, the analytics and B, access to data across the company and C, a very strong data set so that you could start to glean these insights from it.

Chris Jones (48:57):

Yeah. You bring up a great point with the, how we’re trying to unlock our data set to really be a key feature of the product. And it gets back to working with a lot of maybe the, what not to do, is I see a lot of analysts that will like, well, either from an engineering standpoint, you’ll have an engineer at company ABC that says, “Well, I technically can collect all this data and I don’t know what I’m going to do with it, but someday, I’ll think of something. So let me just log it all, that way we have it in case someday we want to do something with it.” Which is absolutely the not right, the wrong approach. Like you want to be only collecting the data that either one, you can glean insights of things like are people using this feature, yes or no, do they like it? Or it’s your point of like, we are going to be using this kind of Levels’ database to basically allow people to see like what does the average Levels’ member get with Skittles? Like what are the best foods at Chipotle or whole foods?

Chris Jones (49:55):

Like that’s where it’s now a feature of the product and the membership where we’re using this database, not to just kind of collect a bunch of random like, “Oh, I wonder what people eat today,” but where I’d say using it to be like, this is the offering, this is part of the education around like, well, we may not always know like what the best or worst foods are, but as we collect it, we can now surface that back to individual people when we see them logging against it. If like, “Hey, you just ate Skittles and here’s how your Skittles compares to everyone else,” or just giving them help of like, “Hey, I’m going to go to McDonald’s, what are some of the best foods I should be thinking about when I go to McDonald’s or not? I mean, I don’t want to say the answer is to not ever go to McDonald’s because it is convenient and people go there all the time and it’s affordable.

Chris Jones (50:39):

But when you’re making the decisions like, “okay, can I make a slightly better decision? Like let me not go for the big Mac and fries and Coke, but let me make something that’s going to be relatively more healthy.” So you should always have a purpose in the data you collect. And what are you planning to learn? How is that going to benefit your members or your community in some way? Not just see, well, just because I collected and this data is exposed, let me go store it someplace. Like that’s the absolute wrong idea, well, wrong way to take it. And I’ve seen companies go down that route. They’re like, “Well, one day we may have an answer for it so let’s collect everything because data storage is cheap.” That’s where you’re getting yourself into trouble.

Ben Grynol (51:16):

Yeah. The hard thing is so the larger the scale of a company or a community we’ll call it that, customer base, we call the members, but the larger the scale, the more challenging things can become without data. The example is when things become qualitative and word spreads, so we’ll say, things become qualitative and there’s a large enough community of people communicating. And where people unintentionally can start to have misinformation is, “Food X will give you a spike.” And it’s like, that’s not entirely true. It could be something like, let’s use chickpeas. We know chickpeas have a higher load of carbohydrates or peanuts like a legume. They do have a higher number of carbohydrates than something like a Walnut. But somebody’s baseline reac… or the way that they had a metabolic response from a baseline level as it compares to somebody else, they can be totally different.

Ben Grynol (52:20):

And then if you start to think about, was that eaten with some type of other fat or some type of fiber some type of protein and go down the list, down the list, we can just look at data and say, on average, food X gives people a glyc… or it gives people a metabolic response of whatever the number ends up being. That is having that data gives people more assurance to know where they stand as it relates to the mean. And I think that that’s really important too, so people can say, “Great, I don’t don’t do well with this, but when Billy said, ‘Never eat that thing again, it gives you a spike.’ It’s like, we want to avoid that.” And that’s where data can become really important to provide people with personalized insight. And that’s also part of product, but we can only surface these insights in product if we’ve got the data. And so that’s the important thing is saying, “Cool, here is the data, here is your personalized data or here’s the way you can look at this.” And then people can make decisions around having those insights.

Chris Jones (53:22):

Or what to do before or after having that food. So if I used myself and my wife as an example, I am much more sensitive to food than my wife is and less from a measuring our glucose response, but just in terms of how I feel. So one of the learnings I had when I was in the beta program was, every weekday maybe I might make a breakfast sandwich and we both eat it. Then have coffee, read the paper and then go take the dogs for a walk. And because of my prior knowledge being in the beta, I knew that that muffin had enough carbs in it that it would spike me and it would drop me like a hammer about an hour later. And I would go hypoglycemic.

Chris Jones (54:08):

Because I actually had been watching my levels through Level and I knew if I ate something rich in carbs and then didn’t go for a walk immediately, I was setting myself up for a little bit of pain. So we’d go for a walk with the dogs and all of a sudden I’m start to drag behind and my wife’s looking at me going, “What’s wrong with you? Like why…” We’re not even hiking up a hill, like we’re walking on a flat. Because I know it’d been an hour that had gone by since I ate something rich in carbohydrates and I’m, without even pull out my phone, I know I’m going hypoglycemic and it’s going to last about 10 to 15 minutes and then I’m going to come back out of it, I’m going to feel fine.

Chris Jones (54:51):

So I know I can make decisions like go for a walk earlier. If I eat, immediately go for a walk and I’ll be fine. But if I wait that hour, go back, have another cup of coffee or read the paper, I’m setting myself up for a little bit of pain. But it’s a decision I’m making around, but it’s one that I’ve kind of known of like, “Okay, I still want to have that breakfast sandwich. Okay, great. That just means pull up the walk faster and don’t wait it out because it’s going to… then it’s going to hit you.”

Ben Grynol (55:17):

Mm-hmm (affirmative). And that’s where you’re getting your… your data is giving you that insight also the way that you… The cool thing is being able to link the feelings that people have and be like, “Oh wait, now the data reinforces that the…” We’ll call it, “That odd feeling.” Like I think that is a thing. When you start to connect the dots between data and just these subjective feelings that people have had of like, “I feel,” we’ll call it groggy, like brain fog, “I feel this way. I feel the nod, like the head nod where you’re trying to do work and you like trying to stay awake.” As soon as you see data and then you go, “Cool, now I can make decisions around that because I understand what is physically happening in my body.” The important thing is not being prescriptive and extrapolating that to other people’s life experiences, right? As you said, you and Nicole will make metabolize food, the same food, the same, we’ll say, the exact same food in the exact same quantity, just for scientific accuracy, but you might metabolize-

Chris Jones (56:23):

Are you implying I eat three times as much breakfast sandwiches as my wife?

Ben Grynol (56:27):

Potentially. Potentially. No, but Pam and I are the same way where things that she can eat, she’ll be flat and things that I’ll eat, and these would be foods that maybe don’t have a high glycemic index, it’s something that I just know now, again, let’s use like peanuts versus walnuts, that’s a pretty easy one. I can see like there’s a drastic difference for me, whereas Pam can be the exact same with both of them. So that’s where the data gives you that feedback to be like, “Cool, make decisions around what is working for you. And you can only do that when you start to surface things. And then when you can provide this to your point of democratizing data. When you can start to do it across a company where more people can get deeper into a data set and start to design products and features and content and all the great things around it,” that is a very interesting thing.

Chris Jones (57:21):

Yeah. And that it’s really powerful, the personalized data, but it also makes it much harder to scale because now, like on the support standpoint, we get people riding into us all the time, going, “What foods should I eat?” Or, “I had a spike, what else…” “I can’t eat this type of food, like what else should I eat?” And because of what you just mentioned, it’s all personal. Just because I might say, “Hey. Yeah, I got really bad spikes from that Chicago Deep Dish Pizza, but at New York thin crust, I get great scores. Doesn’t mean everyone else is going to have the same response. Some people might say, “Wow, I got awful scores with any type of pizza, like thin, thick, whatever.”

Chris Jones (58:03):

So me recommending a thin crust to someone could be absolutely the wrong thing for them to do because I might say, “Hey, that was the point of that mix of fat and cheese and carbs of the thin crust was good enough that my system says, ‘Yep, I can handle this.’” Where other people might say, “Uh-uh (negative), I need a… I really can’t have any pizza, I just need to stick to salads and things was a lot less carbs.” That makes it hard to scale when you’re like, hey, we have all these insights from people because it’s more of like a, N equals one, you’re like, “How do I apply these aggregate insights to an individual without them experiencing it for themselves of like, what are they eating and their reactions to it?”

Chris Jones (58:44):

So it just becomes harder from a member because they want all this data. They want all the… Well, what’s good for everyone else and what did everyone else learn? But it’s harder when you’re like, “Well, it is all personalized and just because most members get this score, doesn’t mean it’s going to work for you. So you kind of have to experiment on your own.” Like that can sometimes be a hard delivery because it’s saying, “Hey, you have to kind of put the work in. You can’t just like benefit from all the people before you and say, ‘Oh, this is the perfect diet because other people have figured it out.’” You’re like, “Well, that’s why a lot of diets don’t work, because they kind of take that approach of the one size fits all. Like let’s go keto or low carb or South Beach or low sugar or like…” There’s might be a lot of people worked for and other people that sleep doesn’t work at all.