Life, Measured: Mapping the Anatomy of a Moment

Speaker A: Welcome to the Tech People Podcast. My name is Ken Coyne. I'm your host and founder, as well as an ambassador for OPS Talent. I believe at the heart of any success story are the people who made it happen. Diversity, creativity, and innovation, where nurturing people can lead to an unbeatable formula. I created this podcast to share the experiences of some truly inspirational leaders on a journey to success.

Speaker B: Enjoy the show.

Speaker A: Hey, guys. Welcome back to the Tech People Podcast. Today we're diving into a conversation that sits right at the intersection of data, science, and the human soul. Talk a lot on the show about KPIs, metrics and optimization in business, but my guest today, Shanta Wilson Trace, asks a much bigger, bigger question. Can you measure life? Now, I'm not talking about your heart rate or your step count. Chantel is the author of Life Measured Mapping the Autonomy of a Moment. She's developed a formal mathematical framework for lived experience. That moment to moment reality we all wake up inside of every day. So whether you're a leader looking to make change or an entrepreneur trying to understand why a high stakes deal went sideways, or you're just someone who feels like you're stuck in a loop of the same old patterns this episode has for you. We're breaking down the three components of every human moment. The facts, the feelings, and the powerful inverse data of what didn't happen. You ready to stop guessing and start measuring? Let's get into the autonomy of the moment with Chantel.

Speaker B: Welcome back to the show, Chantel.

Speaker C: Thank you so much, Ken. It's great to be back.

Speaker B: No, when it's the last time we spoke, actually, do you remember, was it over a year ago?

Speaker C: I think it was over a year

Speaker B: when you wrote your last book.

Speaker C: It was, yeah. So it would have been about a year ago. Yeah.

Speaker B: Wow. Wow. Tell us, maybe just for the benefit of our audience, can you give us maybe a brief background about yourself?

Speaker C: Of course. So, hi, audience. Uh, my name is Chantal and I have spent a lifetime studying patterns, loving math, being engaged with data, and all things science. Ooh.

Speaker B: And you've wrote. You've written a second book?

Speaker C: I have, yes.

Speaker B: Tell us all. I mean, what made you go and go again?

Speaker C: What made me go again? This one was a little bit different for me. So I wrote this book because. So it's called Life Mapping the Anatomy of a Moment. Because we don't have a universally accepted equation for life and nothing that really helps us think clearly about moments we actually kind of live inside, I guess. So when I study biology, of course, there's equations. Physics has equations. Economics has equations. Math, of course, has equations. Ken. But when it comes to sort of this lived experience that really shapes our every decision, our, uh, every relationship, we have no shared framework. And without that structure, without that shared language, critical thinking is really hard. But this book I wrote because it gives us that shared language to talk about our lived experiences, and also because I had a deep, compelling desire for, since I was little, to map this out.

Speaker B: Life measured. Who is this targeted and why would they benefit?

Speaker C: So this really is targeted towards anyone who wants to get the most out of their life by using a critical thinking method. So leaders and organizations can use this formula to have an outstanding, quick corporate experience for their employees. We can use it in our own lives to break patterns and to have a better and enhanced life by using this formula. So it's really good because it gives us a nice critical way of thinking about our life and dissecting it in such a way that we can break patterns and we can recognize shortcomings and correct them more quickly.

Speaker B: Okay, cool, Chantal. So you define life, right, as lived experience. Now, that's distinct from biology, uh, religion, different things. But why is it necessary to step back and, you know, create a new definition to build this framework?

Speaker C: Okay, so this is kind of cool, Ken, because I. I don't feel like I redefined, like, to separate it from, you know, the biology, philosophy, religion. I originally, when I was little, defined it to include all of those without being constrained by any single one. And I simply never changed that working definition. So each of those fields that you mentioned, things like biology, of course, that explains cellular mechanics. Philosophy explores meaning. Religion offers us that moral, spiritual framework. But lived experiences, where all of those naturally converge. So life as lived experience became the most accurate starting point. And when I think about it, there's that saying, uh, how's it go? Like, I learned everything I needed to know in kindergarten, or it's something like that. But I feel like that's kind of true because I started thinking about life at a very, very, very early age. And I defined it in such a way that it included all of those disciplines, because, honestly, I didn't know I wasn't supposed to. There's something really beautiful about the unconstrained nature of children. They don't know what they don't know. So, for example, like, when I was little, I would play outside. So I'd meet a day in the life. I'd play outside, I'd meet my friends. We'd all meet in front of one of Our friends, houses. We would go hiking in the woods, running, playing, jumping. We'd build a fort, mixing mud. Mixing dirt into mud. Build the fort. And then we'd spend the entire day engaged in imaginary play and basically writing little stories for ourselves. And I did that all day long. And that's what I thought life was that, you know, these moments of lived experience. And it wasn't until I got to high school, when we started to separate out all the disciplines. And you learn to think, you learn to sort of silo your thinking. So if I go back to that, you know, day in the life, I would meet my friends, so that's some sort of coordination, right? I would run and jump in the woods and navigate. So I'm sure that counts as gym class in high school. I'd mix dirt and water to make mud. That's some form of compounding in science class. And I would put it all together with rocks to build. So that's got to be engineering and architecture. Of course, there's angles in the fort building, so that's trigonometry, mathematics, you know. And then we'd play all day, laughing, telling stories. So that's English and art. That's playwriting and acting. But when I was little, when I was a child, I didn't know I was supposed to separate it. That didn't happen till high school. So even when I was taught things like biology and they say this is life, it always seemed like it was just part of it, not the whole thing. So to answer your question, I think my definition of life, I intentionally learned or developed it at 7 years old, and I never received information that contradicted that definition. So the lived experience as life has been a guiding central thought for me.

Speaker B: Okay. And, um, I mean, since that young age and what you've learned, right, in this book, when you look back at those times now, I mean, does it make you think differently? Does it change your outlook in life? It really change how you lived?

Speaker C: The definition for me didn't change because, uh, as I learned more and I learned siloed thinking, you know, different subjects, different classes, I just continued to piece them all together. So I would, of course, change my definition if I had information that made me think differently. But it never did. It only cemented that lived experience is life.

Speaker B: Okay? So I thought really cool in the book is you spoke about the gold standard of equations, and you break this down with what it takes to truly make a great equation. So you mentioned things like simplicity, elegance, scalability, consistency, and practical utility. Right. Can you Talk us through a bit more about those qualities, you know, and how to help us understand whether an equation is actually useful or not.

Speaker C: Oh, I, I love this kind of stuff, Ken. So yeah, I think I do need to go through just maybe a couple examples that that's okay. And then I think that'll get everybody understand. So there are criteria for equations that make them useful, that make them good. There are these sort of standards we look for. So if I take for example Newton's second law, f equals ma m. So that's that force equals mass times acceleration 1. And it really is the backbone of how engineers design anything that moves. So if we're looking at those components, the simplicity, it's three variables, one equal sign, and a middle schooler can grasp it. It is really beautiful and simple. Another component for the equation is accuracy and predictive power. So if you know the mass of something and the force acting on it, you literally can predict exactly how it will move. It's astonishingly accurate. What were the other ones? Generalizability. It works for baseballs, rockets falling apples, orbiting satellites, anything with mass. So it's very generalizable scaling. It can work for grains of sand, it can work for planets. Um, I'm pretty sure it does kind of break down in the extreme. So when we're talking quantum scales or near light speeds, not so much. But within classical mechanics, it never contradicts itself. It fits everything. So that's that consistency piece. And it is elegant, it's useful. Every structure, every machine that you interact with owes something to this equation. So that's that utility. And I could do this again and again. I could do this with logistic growth equation or with Einstein's equal MC squared. And you can see how they fall into these accuracy, scalability, consistency, elegance. And they don't hit everyone exactly, but there is a requirement for all of them to do their very best within their discipline, and they do. So when you line up Newton or logistic curve, that S equation or Einstein, E equals mc squared side by side, you see these patterns of the equation. Simple enough to use, it's elegant enough to reveal something deep, profound. It's general enough to travel scalable across levels consistent within its domain. Doesn't break any rules. You know, E mc squared emerges naturally from math. It fits perfectly within special relativity. There's no contradictions and it's useful. So those are the qualities when I was building out this formula, this equation, those are the components I was using to help build a life formula. And while it's not any of Those equations. And I won't say that it is, it is trying to meet those same standards in spirit. So if this formula can describe lived experience accurately, it can travel across context, it can hold up at different scales, and it can actually help people make sense of their lives, then it is doing its job. And that's kind of the whole point of it. So we have these standards for formulas and for equations so that we can produce work that matters.

Speaker B: Yeah, love it. And talk to us about it. We move on then to three part autonomy, where you talk about the three components. And those three components you have operational, perceptional and the inverse, which is often, as you say, the most powerful force that we can see. How does that link in them next? Uh, Chantal.

Speaker C: Yeah. So thank you. Absolutely. That is the heart of the formula. So there are three components that I saw consistently. And once I saw these patterns emerging from every moment, whether it was a sad moment, a happy moment, an everyday moment, or a mission critical moment, they all had these three components. And once I saw the pattern, I couldn't unsee it. And that's when I started to believe this had the potential to be formulatable. And those three components in every single moment repeating where I can then if I can measure them accurately, I can get a really strong picture and understanding of that moment. So operational data is kind of what we think of, that is the facts. That's what we think of when we talk about data. It's verifiable. It's the who, what, when, where. It's the structural outline of the moment. So that would be if I were drawing a painting, I would first sketch it out, sketch the structure. And that's operational data. So it's generally secondary analysis. And I like to think of it as if I had access to and uh, clearance to all the world's databases. I could get this deep degree of structure where without ever having to talk to my subjects. And we already have really strong measurement models in this domain, essentially math books. The data we use would be, you know, how much order, you know, demographics, think of stuff like that. And the analysis components would be the typical math operations, addition, subtraction, multiplication, division, correlations and regressions, percentages, frequencies. So we have really strong measurement models and that's, you already have a really good, strong structure to your moment. The next piece of your moment is this perceptional, interpretive component data. And that's that internal interpretation. It's the meaning, the sentiment, the emotional truth. Again, back to that analogy with the painting. It would be the texture and the Shading that you're painting in the brush strokes. This data is generally primary data collection. And we do have really strong measurement models in this domain as well. And they're in the social sciences, behavioral sciences, and they include things like focus groups and guided interviews, surveys, that sort of thing. So we have really strong measurement models. The third piece, however, in every moment that rarely ever gets measured, is this inverse data. So when I was younger, I would take a lot of photographs and I would develop them on 35 millimeter. You get 35 millimeter negatives back. So you get this picture and you get the negative. The picture was. The portrait was the picture of you, and you're in the foreground and you're lit up and you're great. The negative actually, you recede to the background. And everything that was originally in the background, Ken becomes the foreground and becomes more noticeable. That was an aha moment because it is the. What didn't happen, what was prevented, what was possible but unrealized, what are we not looking at, not thinking about in that moment? But it is invisibly there. We just haven't focused on it. So it's almost the context that shapes the moment without appearing in it. Um, yeah.

Speaker B: And how difficult is it to identify that inverse data? I mean, is it quite straightforward now that you've seen it and you understand it? I know. It's still quite difficult.

Speaker C: It's still difficult. So there aren't any real measurement models in this domain like we have in operational data and perception data. We know how to collect those. So in the book I wrote of two measurement models I created one I call the Wald method, and the other is the Black method. And they help illuminate this inverse data because it can be the most powerful, because it does explain the forces that we can't see but. Or struck. It's like it's missed opportunity, avoided conflict, structural constraint. It shapes behavior without ever being named. So we don't have those measurement models for it. So I did create. To help me be able to illuminate it better.

Speaker B: Okay. With these two new models, maybe could you just explain maybe a bit more on that? Just expand on them.

Speaker C: Yeah. So basically what we're trying to do is get. We're trying to get to what we didn't focus on. So let's see if I can do this. I'll do one of them. I'll do the black hole method, because that's kind of. That's more. It's very interesting to me. So. So, uh, I studied physics and there's this thing called black holes in outer space and they basically are this collapsing thing that you can't see. There's nothing to them. But they're enormous and they're powerful and yet you can't kind of understand them fully. So I studied how physicists, astrophysicists measure black holes. And they do it a couple different ways. They do this thing called gravitational lensing, where remember in high school you would, you'd stick a pencil in a, in a glass of water and it looks like it's bending.

Speaker A: Yes, yes.

Speaker C: Right. So basically they measured things and I'm going to do. I'm, um, not doing this justice at all. So sorry to the astrophysicists who are listening to you, but they basically measure things far out in the distance. They see these like. And you see this warping that occurs and you measure the warping of these other planets far off in the distance. And then there's this other thing about. Or maybe that was the gravitational lensing. But then there's another way of measuring it where there's this orbiting gravitational pull around black holes and it's all this stardust sort of circling around it. And the gravitational pull tells us something, and that helps us understand the black hole. But when I took step back and there's another thing called like radiation something or other. But so when I take a step back, all of these methods have something in common, all of them. And that is they actually aren't measuring the black hole. And I was like, what is happening here? But they're telling us that they're measuring the black hole, but they're not measuring the black hole. So what they are measuring is the impact of those around. They're measuring the gravitational pull of the startup material around the black hole in order to understand the black hole. So this is an equation, a methodology to figure out how to measure that is if I want to know about you and I want to measure your moment, I measure the people around you that impact you the greatest. I measure the structural constraints you're in that impact you the greatest. You measure what's around and has this pull on the person and you get a clearer understanding of the measurement you're doing of the lived experience right there.

Speaker B: Okay.

Speaker C: I don't know. So far out.

Speaker B: Yeah, I know. That's good. Yeah, yeah, it is really good. I mean, it's definitely a lot to take in. I could just say it is, it is. I mean, a lot, but I'm getting it. But how would. I mean, you're not concerned that Measurement like, you know, potentially could flatten the human experience. How does your formula actually. I mean, address this or, you know, provide a language for the. You know, I don't, uh, know the blurry parts of life like you mentioned. They're like the black hole.

Speaker C: I know. So you're right. Measurement does flatten experience when you measure the wrong things. Right. And most frameworks do reduce life because they only capture visible parts. Generally, operational data is what we measure. So even if I just look up, and I did look up the definition of life earlier on, I looked at the definition of life in the dictionary, and it basically says, life is defined as the existence of an individual human being or animal. It also says it's a quality that distinguishes a vital and functional being from a dead body. And that feels flat. So I get it, because there is this reduction that happens when you measure things, but that's only one part of the moment. And I absolutely can guarantee this is true for you. And I haven't asked you this, but I already know that there are people in my life. People in your life. I don't even have to ask you this, but I absolutely know, Ken, that there are people in your life who are physically dead. Yet I am willing to state with absolute certainty, I know this, that they are very much a current part of your life.

Speaker B: True. Yeah, I agree with that. Definitely.

Speaker C: So biology is not the only thing that defines your life. So when we measure all three components, the facts, the perceptions, the negative space, inverse space, you're not flattening anything. You're illuminating it. It is a multidisciplinary approach incorporating all of the science, all of the art. And the formula gives us language to those, as you say, the blurry parts of life. It honors the complexity. I can't. There are multiple different methods, multiple different disciplinary approaches in here. There's philosophy and religion. There's physics included in this approach. So it's illuminating, not erasing any of it, and it's honoring it because we're honoring life with a definition that is incorporating all of those components.

Speaker B: So, please, Chantal. So going back to the whole point about, you know, people who would learn and get value from this. So what changes for a leader or maybe an individual or creative person the moment they, you know, to start using this formula for life?

Speaker C: I know. Yeah. It's such a cool question, Ken, because I think critical thinkers are critical thinkers. And if we want, you know, if I were a senior leader, so I'm running an organization, I can look at my operational data. I can make My company better. I can look at the operational data. So that's all the employee data, all the customer data, and that's that mathematics. That's the stuff we think of as data. The number of widgets sold and the tenure of your employees, that kind of thing. You look at that, you couple that with perception data, which is customer engagement surveys, employee engagement surveys, customer satisfaction surveys. And so now you already have a stronger picture. And then you use a third component that never, ever, ever gets measured. And that's the structure of the organization, when you incorporate that structure. So it could be the quarterly, uh, pressures, the financial pressures, it could be the backfill that was never filled. People leave and then they don't fill positions. So we have all of these interesting components that are just not included. We have invisible ceilings. We have all sorts of career path limitations, things that aren't really incorporated into the equation, but when you do incorporate them, it illuminates it. So the moment somebody starts actually using this formula, whether they're an individual or a company, because it does scale. And in my book, I go through how it scales, you gain authorship. You separate interpretive from factual. You see the invisible forces shaping your reactions. The patterns are starting to emerge. So you get clearer decisions, and you're not reacting in one big blur. You're responding to the right part of the moment because you've dissected the moment. So you communicate clearly. You break cycles faster. There's a sense of agency because we understand the architecture of our experiences, of our own experiences and those within our corporations and our families.

Speaker B: Fascinating. I mean, I know you sent me an early copy, but. Has been released already in terms of.

Speaker C: Oh, yes. So it has been released. It's on Amazon. Yeah. Paperback and hard copy are on Amazon. I'm working to get an audio version. So. Yes. Yeah. And I'm, um, always up for conversations about this because I think having critical conversations, having thoughtful conversations, contribute to our body of knowledge and help us move forward as society and as individuals.

Speaker B: Um, and in terms of life measured. Are you also helping companies and leaders with this formula and these new, this new skill set?

Speaker C: Well, I am. So I'm doing a few conferences where I'm speaking at the conferences and I also support the Women, uh, in Science, or Association for Women in Science. So plug to them. Women in STEM is really a wonderful organization to support, so advance. So the association for Women in Science, I speak there. I'm at the Data Summit in Boston this summer. So, yeah, I'm hoping that we add this to our Critical thinking conversations.

Speaker B: Fantastic, Chantal. Well, listen, a pleasure to have you on the show again today. And big congrats on the book. Fascinating read, guys. Life measured. Check it out on Amazon. And the audiobook is coming shortly. Chantal, as always, a pleasure. And we look forward to speaking again soon, hopefully.

Speaker C: Oh, uh, I look to forward. Forward to it. Thank you so much for your time, Ken, and thank you to your audience for their time. I really appreciate it.