It is exciting to publish the latest episode of our Getting It Right Podcast Series. This podcast focuses on those organizations that are doing a good job making an impact – and in different ways.
We feature leaders from brands and suppliers that have made a lot of these steps and missteps towards success. We will cover the definition of success, how you know if you are being successful, how to organize around that idea, and what the future holds among other topics.
The episode’s guest is Hunter Thurman, CEO of Alpha-Diver. Alpha-Diver is a neuroscience and psychology-based consultancy focused on strategy and innovation. Alpha-Diver uses a model-based approach to understanding the drivers and barriers of human behavior. This model-based approach is at the heart of their success. The approach allows for internal alignment of the organization, faster time to insights, alignment with client needs, and a structure to make clear recommendations.
Hunter makes a number of observations and recommendations about the application of a model-based research and consulting company. Take time to read or listen. You won’t be disappointed.
Read the podcast text…
Hi, everybody, and thanks for joining us again. This is Getting It Right: Achieving Success and Insights. I want to welcome everyone to this edition.
I’m Gregg Archibald with Gen2 Advisors and this is another, in our series of podcasts on how various organizations are achieving success within the insights world.
And we’ll be highlighting both brands and suppliers that are achieving success. We will discuss how it’s defined, what the path to success looks like, the trials and tribulations, relationships with clients, and what the future holds.
I’m very pleased to have my guest today. Hunter Thurman, the president of Alpha-Diver, formerly known as Thriveplan, he’s actively been involved in brand innovation for over 20 years, with companies like WPP and Brandery, he’s a mentor and an author of Brand Be Nimble available on Amazon.
Hunter, thank you very much for being here.
Absolutely. Yeah, Thanks for having me. I always take so much away from our conversations, so hopefully, I can do in kind today.
And we hope so, as well. So, if I’m not mistaken, this is the 10th anniversary of Alpha-Diver is that, right?
Yes, it is. We started out in 2011, so, we’re hitting that decade, mark.
Congratulations. That’s a hard mark to hit.
Yes, absolutely. One of my teammates said, Hey, isn’t today, the 10-year anniversary. I was like, Oh, my gosh! One of our core values is ‘celebrate success,’ and I almost breezed right through it.
And I’m glad you mentioned core values because. We’ll get to that in just a minute, but before we get there, I’d like for you to give everyone a little bit of a description of what Alpha-Diver does: kind of where you are in the market.
We are an insights and strategy consultancy, and at the core of our approach is that we use a lot of neuroscience and psychology. Really, it’s grounded primarily in neuroscience and with that, we’re measuring and then using this framework, applying it for our client objectives around these durable, predictable drivers and barriers of human behavior, So that’s really the foundational piece. I’m sure we’re going to talk a lot more about that, Gregg.
Ok, so you just mentioned one of your core values, and the first thing I want to talk about is how you define success, And I’m assuming some of that, it sits around those core values. Can you tell us what success is for your company?
Absolutely. And I will give a big disclaimer that you are going to get very tired of me saying the phrase ‘model-based.’
You’re looking for the secret of my success. At the core of what we consider to be a success, and really how we measure ourselves is that we work very model-based – and the contrary to model-based thinking is model-free.
That phrase is one that I was taught to me very early by my academic teammates, namely, our principal neuroscientist, Dr. T. Sigi Hale who we know as Sigi. As we started talking, and this goes back over 10 years, I was describing to him the vision that we had for the company and he very immediately said to me, ‘oh, so we’ll be working model based’, which I sort of reacted and said, oh, that’s a thing?
I thought I had this original idea, and essentially in the world of academia – in that neuroscience psychology academic world – he explained that there are two approaches: model-based and model-free.
Model-based is when you’re using an established model that you know to be reliable. And when you’re going out and doing research, you’re measuring and evaluating whatever context you’re studying relative to the model. You’re measuring it back to the model.
Model-free is actually what most market research, and still to this day, is driven by, meaning, you don’t really know what you’re looking for, and you’re going out and exploring.
You’re collecting exploratory data, then you bring it back, whether qualitative or quantitative, and bring it back to the ranch, and then you’re assessing it, and essentially trying to reveal the model from the data.
So it’s really a fundamental difference. And every firm is well advised to take a real sober look at whether their approach is model-based or model-free, and that’s really been the unlock for us in terms of creating this durable, repeatable metric approach and outputs that have really demonstrated to us over these 10 years the ability to drive the client’s business.
And this model-based approach has allowed you to do some things that model-free does not allow you to do from my understanding. So, you guys have developed some action items around the outcomes of a model in any particular scenario that’s kind of played out in front of you, correct?
That’s right. If you talk to neuroscientists (those on our team or elsewhere), I think we, in the research and strategy space, feel that human behavior, and why people do what they do, is quite a mystery. And it is, to a degree, and that’s why all of us have jobs, and why this industry exists. So that’s good. But when you talk to these academics, human behavior is actually pretty predictable.
We, as a species, have evolved to be pretty predictable, in the ways we will respond to threats or pleasure. We’re actually more of a known quantity than I think many researchers or market researchers might realize.
And so, there are these four predictable drivers that compel a person, these five predictable barriers that hinder them. And by applying that, in any context, whether we’re looking at a CPG category or financial services, or quick-serve restaurants, that same “software,” if you will, is still running and it’s still driving our behavior
An analogy that I use a lot when talking about model-based work, is the five senses: a really simple model everyone’s familiar with. But if you imagine you’re trying to create innovation or strategy for soda / CSD’s – whatever – if you went out and just started watching people and observing and talking to people, why did you choose one brand over another? Why did you choose this? What was your experience like? You would eventually find your way to the five senses.
If you didn’t know about the five senses and you’re out just doing model-free research, you very quickly get to taste and, maybe slightly less quickly, get to touch. Because they’d say, oh, the bubbles, the way it fizzes, etc. But it would take you a long time to start thinking about sound, to start thinking about, you know the olfactory, what is drinking a soda sound or smell like?
But, with a model-based approach, you’d get there right away. You’d short circuit your way to assessing the consumer experience through all five senses. And then when you bring it back to the C-suite and say, here’s what we’re going to do we’ve got this innovation opportunity that really amplifies the sound when you open the can and the fizzing. We’ve got, this new can design, that creates a little echo chamber and you really hear the fizz better.
The CEO is not going to say, “what do you mean? What do you mean by the five senses? How do you know that?” As always happens in the C-suite, they ask how’d you get here? And then they say, “how do you know you thought of everything?”
When you’re in a model-based approach, and you say, we use the five senses, the model’s established. Everybody says, “Oh, I know you covered everything, and I know it to be a true and valuable means of looking at a context.”
So, it’s a simple one. But it’s actually a good analogy that when one is looking for or his or her models to apply, finding something that’s existing out there, and that’s really what we’ve done in the neuroscience space. Find an existing repository of knowledge and translate and apply it and invent ways to measure it in the context that we’re interested in studying.
Ok, I’m going to shift gears a little bit, because you did bring up celebrating as being one of your core values. Can you talk a little bit about the core values and that’s been part of what’s led to your success, and how you think about and design an organization around those core values.
Yes, our approach or I guess my approach has always been to hire as reluctantly as possible; to not rely on headcount. I hate that phrase, What’s your headcount? I mean, it commoditizes human capital so passively.
So my approach has been to hire as reluctantly as possible, and then to obviously empower each of our team members to do her or his best work and, I told you, you’re going get sick of hearing about model-based work, that’s at the core of being model-based work. So, it’s not a new idea in business, to have fewer people performing more work. It’s a profitable approach to business. The question is, how do you do that.
And so, in our experience, using this approach, we’re confident that everybody uses this durable framework. And everybody knows how we’re looking at the world. Everybody in our organization, and then our clients understand this view.
So when a problem comes up, they know exactly the lens that they should be looking through.
That’s really the unlock that lets each person do his or her best work, and so, you know, me applying the model with 20 years experience, I will have more context, more experiential wisdom that I can apply but I will look at a problem and diagnose it in the same way that somebody who’s new to the organization or even new to the industry will look at it. There’s nothing worse than working in a model freeway and someone says, “well, how do we drive penetration among Gen Z where we’re struggling?” And you flip over a chart sheet and there’s a white page and it’s like, OK, let’s start thinking. There’s a lot of psychology that explains this but it’s the most paralyzing endeavor there is.
So, having a model, having something that everybody in the organization knows, “oh, here’s how I go about this, Here’s the first question I ask. Here’s the approach I’ll take.”
It really empowers each person, then, to tackle a problem in a model-based way, And that’s a big part of celebrating success, it’s not like we only celebrate when we get a big, new client or a big new project or whatever.
We have just published, this Omni-Pulse tracker study that we’re using. And it’s this predictive measure. It’s a big production we’ve been working towards. So obviously that is success to celebrate, but relative to the core value, it’s more of the daily success that hey somebody who has no experience in a given category brought a really unique insight based on applying the model, in your daily work for example.
That’s a success, you know, that we celebrate and so it all circulates around trusting the model using the model and knowing what to do at the personal level, I think that’s a big piece of it. Knowing what to do is very it’s very liberating in your daily work.
So I want to talk a little bit about where you’ve come from to where you are now. So, you guys just rebranded 3 or 4 months ago, I believe something along those lines from Thriveplan to Alpha-Diver. And I’m sure that that’s predicated in what you’re seeing with your company, how you guys have changed, the things that you need to change.
Can you talk about a little bit of the evolution that you’ve been through in the past 10 years of what you started out doing, one way that you felt like really wasn’t serving, where you wanted to go? What are the benefits of the changes that you’ve made along the way?
Yes, if you look at it, over the 10 years, there have been a lot of changes. I think the biggest is we’ve really evolved from a more qualitative approach to a more quantitative approach. I guess the irony of it is, we’re still tackling the exact same challenges we used to.
We’ve just have found a way to use quantitative studies to get to these deep diagnostics at the scale of quant. So that’s been kind of the biggest evolution, and that’s really been based on the invention and the evolution, and the vetting of this core measure, that we use in a quantitative fashion, that essentially, uses a lot of the neuroscience I’ve talked about – uses our model to go out and measure and attribute people’s perceptions.
It’s basically a series of questions, and activities that a person does in a survey, essentially, that’s a “tell” in that it reveals what’s going on with their psychology. And let’s link it back to those drivers and barriers at the core of our framework: in the beginning, we were doing these longitudinal ethnographies where we’d have 50 people over the course of a week. At one point, we did the whole first half of the NFL season; these longitudinal periods. And we were working a little more model-free than we are.
We had a framework. We had the basics, but we were watching a lot of behavior and then applying it to what was then a little more of a hypothesis of the model, or an initial articulation of it.
And, essentially, as we’ve grown, we’ve become less and less reliant on qualitative, and more, and more reliant on bigger data, because we’ve seen in this transition phase, that happened maybe five years ago, we’ve seen that we’re getting to the answers much more quickly, much more accurately on the quantitative side and, we’ve sort of evolved to feel less reliant on watching people – observing people in a more qualitative setting – which has let us build this database, that becomes this bigger asset, and this repository of knowledge that we can dip into, and use in our analysis, all of which is more on the quantitative space, albeit still answering very qualitative questions, or what would traditionally be qualitative questions like, “why are people doing what they do?”
So what was the instigation behind the movement or the rebranding between from Thriveplan to Alpha-Diver? What was the driving force there?
Part of it relates to what I just said. As one of my teammates said the other day, we’re a totally different company than we were five years ago, and I think that’s healthy that we’ve evolved. And we feel like we’re continually building, standing on the shoulders of what we learned in the past, and we kind of got to a new point… We’ve started moving in this direction, where we’re using much more longitudinal data. We’re using our database in a much more predictive way.
We’re striving to become more and more reliant on our pulse data versus being totally reliant on primary studies. And all of those changes, we really are trying to equip the company for the future.
We’ve got some pretty aggressive growth goals over the next four years and we all just kind of agreed the old brand, you know, Thriveplan served us well. But it’s not us anymore.
And so we wanted to really re-invent the company to bring forth a brand and an approach and a look and feel that better fit with the new direction and kind of who we are now.
And so, like anyone who has named a company or named a new product or named anything now, the first thing you do is go to GoDaddy and realize that basically every domain name that makes any sense whatsoever is already taken. And we had some churn thinking about, what are we why, words like ‘why’ neuroscience, all sorts of things, basis and origins around those. And one of our teammates said we should be looking at this as “what is a name that only we can call ourselves?”
And so, Alpha and Diver are two internal shorthand words that we’ve used for years that are part of these driver profiles. So, we have this sort of internal lingo around these drivers, and two of them are the Alpha and the Diver.
And as we’ve put that together and, in fact, those are the most subconscious of the drivers, the most system one, and my teammate, Mary, pondered how can we take alpha and diver and make that a name?
And we thought, that sounds pretty cool, and it’s really something that only we can talk about in a way that that, you know, means something.
And so, it’s really been a nice sort of refresh, like a fresh coat of paint in a way, like, on your house. I think put a little more vigor in everybody’s, you know, excitement about where we’re headed.
You mentioned that you’ve adapted a lot over the course of the past five years. You’re not the same company you were five years ago. What are your clients able to see from you today that they may not have been able to see five years ago?
There are two components of it. It’s what we measure and how we report it, and so storytelling has been a phrase that is now kind of a cliche. It’s been so well-tread over the last 5 or 10 years in the industry.
But we’ve evolved quite a bit, in terms of how we take these pretty sophisticated measures and communicate them in ways that translate back to – being another cliché: “actionable” – things that a team can “carry the water” and go and apply.
So storytelling has been a piece of it, but I think the bigger piece in terms of what we’re delivering is… I started my career 20 years ago, I was with an agency, and the kind of claim to fame at the time was that that, we had invented quali-quant, and that was the unicorn: “quali-quant.”
It was 80 people in a big focus group facility using, you know, dials to capture sentiments. So essentially, what we did is said, look, we’ve got to sort of a technology invention that can lead us to a really enormous focus group, and that was “quali-quant.” When I think, back on that’s really what we’re actually delivering now: all the diagnostic of qual (and, in fact, deeper than qual because we’re really getting to the subconscious factors that people don’t even realize in their own behavior) at statistical levels; at a quantitative level.
And, again, the reason we’re able to do that is because we’re working in this model-based way. We are not making this up as we go. We’re not having to write questionnaires.
Based on specific questions, we understand what durably drives people and we’re measuring that on behalf of the client context that we’re studying and bringing it back then in a way that that really clarifies and simplifies. We always kind of joke that our reports say: “if you have a dollar to spend, spend it here. If you have two, spend them here. And if you have three, don’t worry because nobody’s got $3 to spend.” That is the summary of it: nobody needs more, they actually need less (i.e. more focus). And that’s a little bit about the vision for the future.
I’m still hearing so much about big data and AI, and I know there’s a lot of value in it but, you know, time and time again, what we see with our client partners is they don’t need more, they need less, but it’s got to be the right “less” – it’s got to be focused. And I think that’s where those organizations where we’ve really fostered these partnerships, that’s the value they’re seeing that we’re bringing a much more focused read on the marketplace that lets them activate with much more focus.
One of the ways that I’ve described this industry is on a continuum, from data to consulting and data is the ingredients that go in and consulting is, answering the question, what do I do next? And you just talked about the idea of, if you have $1 spend it here, $2 spend it there, that’s fundamentally the way I describe consulting.
Earlier you said, we’re research and strategy, so how do you get to that place that says, here’s the next best dollar over time, because you can’t do that on day one. So, over time, how did you get to this place?
That said, we’re going to design our organization, our people, our systems, whatever that may be, to be able to do, “here’s your best dollar. Here’s your next best dollar.”
Part of it relates to data collection vs. consulting. They’re often considered differently, and I totally understand that. But part of it to me is like, how could you be consultants without data?
How could one be a good consultant without fodder, and we’ve studied the natural creative process quite a bit.
As humans, we use a lot of analogy in our thinking. That’s where, in the most conventional sense consulting, is based on lots of experience. Someone who’s been doing it a long time has a lot of experience to draw from. What you’ve done is built this dataset and established, some sort of a model in your own mind, albeit often informally, and that’s what makes one a good consultant.
So, when you have the ability, like that five senses example that I gave earlier, to apply a model, you have a starting place. A smart person, a talented team member will be really creative. If they’ve got more experience their ideas will be generally better, but anybody can have great ideas when they at least have a starting point through a model-based approach.
And, the way we get from a more emphatic data interpretation and coaching standpoint, to the point on, “spend $1 here, spend $2 here.” It’s because you have this framework, you have this ability to say, look, we’ve measured these data that we know we can rely on.
And when we’re interpreting them and communicating them on the consulting end of the spectrum, we know confidently that when we see this signal in the data, that means this is your best opportunity. 10 points below that we see this signal, that’s your second-best opportunity.
And so, it’s a much more objective, data-driven way of inspiring, focusing, advising than conventional consulting domains.
I want to come back to a sentence that you said a minute ago, which was, around, having these partner relationships.
And you and I spoke a week or so ago and talked about, you know, so, some relationships are strong, some not, but not quite as strong, and that’s the way with every company, what characterizes a strong client relationship for you guys?
I think it’s similar to what many would probably say, but there’s a couple of things maybe that have been a bit surprising to me. Like, we got some feedback the other day from a client, saying “we’re really enjoyed working with you, because you really listen.” Listening: that is still a unique attribute, you know, among, I guess, our competitors. It’s like, OK, I’m good, I’m glad to hear it but I would have thought that’s just table stakes.
I think another part of what’s happening is that the market is so hyper-competitive. There’s so much innovation and evolution in terms of the nature of data that the digital space has really democratized a company’s ability to reach potential clients. In my 20+ years, the space has become much noisier and much more competitive. And, I think, you talked to a lot of clients, and they’re overwhelmed; one would have to have it be their full-time job, to keep track of all the firms, all the capabilities, all the nuances.
So, I think where the true partnerships are coming in is the ability to listen and then, from some of the things you hear challenge them, don’t just take a brief and say “OK, we’ll, run off and measure that,” but rather saying “is that really what we’re going to measure? Or is it, you know actually measuring?” Even that simple challenge or question can actually be, you know, even that sort of consulting upfront.
And, again, the model-based approach is the reason you can do that. And I think the partners that we have really strong relationships with are those that value our thinking – it’s not just about reaching out saying, hey, any projects, any projects, any projects? I think everybody knows that.
That’s where having this model-based approach really helps me, in my daily work, is having something to talk about. Good partners in our space can add value. You bring ideas, contribute, basically, help a client get through their day and their workflow, versus adding more noise to the mix.
What’s really hard about that is, what are you supposed to do? Read an article, and connect with a client. Say, hey, I saw this article, and it made me think of this? That’s an approach many take.
The way our clients value hearing from us, on a regular basis is more of a partnership. And they think to pick up the phone and call us because we have, this unique take, or we have a very immediate take via our model-based approach on whatever the question is.
So, when they say, hey, I’m trying to figure out why this is happening in my business, or, we’re trying to figure out what’s going to come next, based on all these households we’ve added over the past year, we’re able to look at our framework and say, well, here’s how we go about solving that problem here are the questions, you need to ask. Here are the real questions that need to be answered, and it helps you clarify for them what it is they’re even trying to achieve.
So, that’s really where, in my mind, again, that model base piece really contributes to the partnership side because it does help you distill down to even what they should be thinking about.
I’m always surprised and pleased by how often we’re engaged within the RFP writing process, and really good clients call and say, hey, I’ve got a draft of an RFP, would you give it a look?
And I’ll go through it and respond with, here’s how I would characterize this, here’s how I would frame that, and obviously, that’s a very consultative, very partner based place where you’re actually helping to create the brief that’s going go out and I’m happy to do that, and I think that’s where our approach does let us play that role. Because we will have a very durable point of view on the way they should be even framing the challenges.
So we’ve talked a lot about model-based design. We’ve talked a lot about where you guys have come from more qualitative and transitioning the rebranding and some of the efforts behind that and the rationale behind that. So, can you tell us kind of what is on the near-term horizon?
For the next change, the next evolution, the next step, and that Alpha-Diver’s future?
I am reflecting on the continuum that you described from data collection, all the way to consulting and it really does describe our future. Of course, we’re still collecting data, but we really have evolved much more into this consulting space, and that’s kind of into the points we were just discussing on how to be a partner. You hear phrases in these big companies, like “what are the go-dos, what are my so what’s, what are my no what’s,” – what should I be doing?
Everybody, whether they are the C suite or they’re a fairly entry-level Insights Pro, is trying to figure out what to do. And this kind of goes back to the point I made a minute ago that that doesn’t mean go and collect more data. It means frame it, and focus it in a way that’s much more on that consulting end of the spectrum.
And so, I think that really does describe our evolution from being a research company to being much more of a Strategy Consultancy and the ability using this model-based approach to say, we know that because of what we see in our data, and because of what we see in our framework, we really confidently know that your best opportunity really is this…
And, in fact, when other companies that we’ve worked with have done that, they’ve driven 10% growth; they’ve achieved these really dramatic successes.
So, part of that, and part of the benefit of, the longevity of the company that you talked about at the top of the call is that track record. It’s a good selling point, it gives us a lot of confidence.
But then the frustrating part is if you’d have asked me seven years ago, how can you be successful, well, just be doing this seven more years, and you’ll have this track record. That’s what this model-based approach and having a unique worldview lets you confidently go and do, you know, so hopefully, somebody listening to this would be able to just sort of accelerate that more dramatically and drive into more of that consulting space, where you really have a real clear point of view. You know, very strong ability to focus, and frame thinking, versus reporting data.
And the model-based approach doesn’t necessarily need to be a proprietary approach by definition, you mentioned the five senses that it is certainly a component, and innovation, and a lot of product innovation.
Have you worked with models that aren’t necessarily proprietary, that can be, that have been successful?
Absolutely, and I think that’s the great irony, but if you’re looking for your model-based approach, do it in a model-based way. I told you, you’re going get sick of hearing me say this.
What I mean by that, when someone says, Well, of course, we want to have our own proprietary secret sauce models. Go and look for established frameworks, established datasets, third-party things that are in the public domain, and translate them.
My advice in a setting like this could be to go invent something incredible and sell it. It’s like, no, that’s not what I’m talking about, and that’s not what we’ve done. We do have some unique inventions, but they’re based on lots of established knowledge from the world of academia. The first step I did take sort of happened by accident. I met these neuroscientists and started talking with them and saying: my job is to understand why people do what they do and coach companies on how to, you know, bring them solutions to solve the problems they don’t even know they have.
The neuroscientists said, “that’s what we do, and there are terabytes of data about how to do this and that sounds like a lot more fun application of our knowledge than writing white papers and defending them.”
So, my point is, I very proudly in retrospect went in and said, my ability is to take all that stuff from the world of neuroscience and make it relevant. That was the core of the model-based approach, not inventing something, so, whatever domain a company’s in looking afield to find something established A. gives you a starting point for your model-based approach and B. gives you some shoulders to stand on you don’t have to do all the work yourself.
In our case, the fact that there’s so much known about human behavior, what a waste if that weren’t to be brought forward but sit in these round files and in academic databases and never be applied. There is work to doing that translation.
That is how I would coach somebody, to go and find something out there that exists, that can be translated and apply what you’ve found – that’s proprietary enough.
That’s where the consulting and the ability you’ve been asking about relate to our core values – we’re not as big on the rote “here are the core values and rank order,” but use a model-based approach.
We hire very diverse minds – a model-based approach lets you do that and lets us have very diverse mindsets because everybody is looking at it through the same lens and bringing very different perspectives through the model.
It lets you do some of these things that add a lot of value, not only to your clients but to your company, in a way that you don’t have to work so hard to try to differentiate.
And being very familiar with some of the work that you’ve done, and some very difficult industries. I’ll say that this approach has absolutely served clients well, and obviously served you well.
Hunter, I really want to thank you for your time today. I think we’ve covered everything, but I’m going to pull on my qualitative researcher hat; I’ll put that on and have the traditional last question:
Anything that we didn’t cover that we should have?
The only challenge I would throw out to the industry is to make sure, as we’re characterizing data, I’m hearing a lot of things around DIY and Agile, and to me, like was said on one of your previous podcasts, if somebody can go and find those data without engaging the team and it’s already there, great. I think that’s a great application.
What can be a risk though is fostering a “less thinking, More doing” mindset. As in, less thinking, more data collecting, and faster. And likewise, then, you look at the other end of the data spectrum. It’s big data and AI, huge potential there, huge opportunity, obviously.
Let’s all remember that just because we have a lot of data doesn’t necessarily mean that we have the answers, or that the nature of the data is really diagnostic. In other words, looking at these approaches, be sure to ponder whether they really tell us why people do what they do.
So, as we think about this as consultants and researchers, be really mindful, and I think that, in the coming years, being really mindful of the nature of the data – what it actually is telling us before we go about boiling it and collecting more of it – is a big opportunity that I’m not hearing talked about very much. That’s what I’m trying to kind of lead the charge on in our work, as we forge ahead.
So, really kind of a framework around the why, and the thinking into the why versus the thinking that goes into the what? Do you agree
Hunter, thank you so much for your time today, really appreciate it looking forward to seeing you in person someday soon.
Likewise, thank you, Gregg.
The post Getting It Right with Hunter Thurman of Alpha-Diver first appeared on GreenBook.
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