Innovating Leadership:
Co-Creating Our Future

Resources:

Learn more about Greg Moran on his LinkedIn page at https://www.linkedin.com/in/gsmoran/. Information on Pyx Health is on their website at https://www.pyxhealth.com/.

Our host Maureen Metcalf posts a newsletter every week on LinkedIn. You can subscribe here.

Maureen’s latest book is Innovative Leadership & Followership in the Age of AI. You’ll find details about it at https://bit.ly/LeaderInAI, or check out the Kindle version at https://amzn.to/44buVz8. The audiobook version is now available at  https://amzn.to/4dTCleZ.

Her other 10 books are available on Amazon here.

Other episodes you’ll enjoy:

– The End of Stability: Leading in a Disrupted World with Bob Bush, Jr.

– Are You Disrupting or Being Disrupted with Mark Kvamme

– Facing Uncertainty: It’s VUCA with Chris Nolan

Guest(s):

Guest(s) Bio:

Greg Moran is the CTO of Pyx Health, the female-led and LGBTQI+ founded, working with national health insurance plans to improve access to quality care. Through his extensive career, Greg has been a director, founder, advisor and operating executive with extensive global operations experience (U.S., Europe and Asia). He holds a strong market focus with deep technology experience, including start-up, scaling, restructuring, sales, finance, and operations.

Transcript
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[00:00:00]  

Maureen: Welcome to Innovating Leadership co-Creating our Future, where we explore the practices, mindsets, and systems that help leaders navigate complexity and create sustainable impact. I’m Maureen Metcalf, CEO of the Innovative Leadership Institute. I work with senior leaders and organizations to strengthen strategy to execution, build leadership capability and design continuity, so results endure through disruption. Today’s guest is Greg Moran. Greg’s a regular voice on this podcast and a trusted thought leader in the technology and AI space. We hear constantly that change is accelerating, but leaders are still responsible for making real decisions, reallocating resources, and building systems that keep pace. Today we will move beyond abstraction and explore what speed actually demands from leaders, teams and governance structures [00:01:00] right now. Greg, welcome back. 

Greg: It’s great to be back and thanks for having me. I currently a CTO for an early stage mid stage startup in the healthcare services arena called Pix Health. focus on serving the needs of members of health plans that need the most help and are the hardest to reach out to. 

Maureen: The pace of change, you said is only 5% of what it’s going to be. Can you elaborate on that? ‘Cause that is a terrifying number. 

Greg: If you spend time following technical leaders in social media on X or wherever you choose to consume your information, the entire tech world is basically in a sky is falling moment, right? Like the language is very extreme. 

Every single day, people whose name you recognize will say, “This is the end of software. This is the end of [00:02:00] engineering as we know it, not the end of engineering. This is the end of product management. This is the end of most business models that we’ve taken for granted for 50 or a hundred years.” It’s that kind of language and so far, the reason I would say 5% is I’m not seeing that really reflected in mainstream business people certainly acknowledging the relevance of AI, but most of them are interacting with LLMs as a thought partner and are using it as a minor productivity tool, but they’re not yet stepping back and saying what are the midterm, and I say midterm, next five years impact of AI on my underlying business model and how it’s not a matter of whether it will be disrupted, it’s like how dramatically will it be disrupted and how fast. 

Maureen: I just published a paper in Forbes, just a short article, [00:03:00] and I looked at AI implementation and looked at all the practical pieces, just foundational stuff. And the last one, is once I have some of the foundation, now let’s think about what business should I be in? I think some of the folks we’re talking to a year from now will be in a different business. 

Greg: I completely agree. At one level, I think there are a lot of businesses that will continue to operate, but the mechanism by which they create value and the how of what they do is going to change entirely, right? Like, the concept of, for example, if you’re wanting to do a startup of some kind that relies on technology or software — as recently as a year and a half ago, you would go raise a seed round so that you had enough capital to pay engineers to build your working prototype or your, MVP, your minimum viable product. And then [00:04:00] that would be the basis on which you would go seek funding for an A round from a VC who would then help you establish product market fit. 

You don’t need a seed round. The barrier to software development is essentially zero, and so building MVP is a matter of refining your context so that you get the MVP that you wanted, which is probably the work of a week of a single founder who understands what problem they’re trying to solve. You don’t need a seed round for that. So that’s one example on the extreme end, on the other end, you’ve got large corporations who have buildings full of people who are doing things a certain way, and the unit of productivity is those people. And it doesn’t mean that business will go away, all those people may well go away because you won’t be able to compete if your unit of [00:05:00] productivity is still a person when your competitor or one of those startups comes in with a model that’s economically 10 times more efficient and a hundred times smarter. 

That’s a different game. And so it’s not that the business goes away, it’s just that you could be disrupted quite rapidly out of existence. 

Maureen: We haven’t addressed the idea of things like the optimist robots. We will have human-like robots who have specifically the manual dexterity to do things that we used to have to build machines to do a repetitive action. Now it looks like some of that will change as well. 

Greg: Yeah it’s interesting because so many of these things are, continuums and when you’re old like me, like I can see the threads of all this technology  

Maureen: Mm-hmm.  

Greg: going back years and years and years. It’s always amusing to me when a young technologist will be talking [00:06:00] to me and go, “Well, you know, back in your day you guys dealt with mainframes and you dealt with data centers, and now we’re all using virtual machines.” 

And I’m like, “Yeah, you mean virtual machines that are sitting in data centers? Those ones?” They’re like, “Yeah, like the whole virtual technology may be new to you.” And I’m like, “Do you know the name of the operating system from the mid sixties on an IBM mainframe? It was called VM. It stood for virtual machine.” That’s just an easy example of where there’s threads of technology and robotics is another example. And I was at a tech conference, this would’ve been probably in the 20 17, 18 timeframe. And a very prominent VC was interviewing the head of a robotics company. And he asked the question, “When are robots gonna be better than humans?” 

And the CEO of the robotics company said “I’m confused by the question. [00:07:00] Robots are better than humans at everything right now. stronger, they’re faster, they’re, all the things.” He said, “If your question is, ‘when will they be better than humans at everything at the same time?’ that’s a different question, and that’s an integration question and it’s an intelligence question.” And I bring that up to say, what’s happening with autonomous robots today is a function of injecting intelligence and integration, not some step function in our conception of what we would like to do with robots. 

Right, and the rest are just engineering problems. You know, dexterity is one problem, but that can be solved by intelligence. If you’ve got enough horsepower like a human does. You can, turn a nut onto fairly easily without even having to think about it. You can even be having a conversation at the same time. 

That’s intelligence, right? The [00:08:00] dexterity component of it is really just an engineering problem. What materials do you put on the end of the digits of the robot so it can do that reliably? Those sorts of things, right? So to me. What you’re seeing in robotics is really an extension of a known problem, which is we didn’t have enough intelligence that we could put on board the robot for it to be autonomously useful. 

And now we do. 

Maureen: So it won’t just vacuum my house. It will do any number of things that frankly, I don’t know how to do. 

Greg: absolutely. Or you won’t be able to do. You’ve already got robots that will vacuum your house. We’ve had those for a decade or more. It’s now a robot that can vacuum the house, can take out the trash, can lift up the car if you want to change the tire; it can do a lot of things that you could not normally do. 

But that’s a function of intelligence and integration and the two kind of go hand in hand ’cause integration requires a lot of [00:09:00] horsepower. That’s one of the great things about what a human is, is we’re integrated with a lot of horsepower. And we’re really vulnerable. 

Like we always forget that. I could have not been wearing a helmet when I was mountain biking and I’d be dead. I’m very vulnerable. But we overcome that vulnerability with intelligence. And, decision making that comes from that intelligence, that takes this very fragile body and somehow manages to navigate it through life for 70, 80, or 90 years, right? 

That’s the game. And we don’t all succeed, but most of us do. And we do. So as a function of our intelligence, not our inherent protections as a biological being. We’re very vulnerable. 

Maureen: We are now approaching a point where synthetic beings, robots have the dexterity that we as humans do, and are now being integrated with the intelligence that is, what did you [00:10:00] say a hundred times what we have. 

Greg: Back to the core theme, which is: what are leaders to do and what are companies to do? The first thing that I would point out is that traditional management training, both formal and informal, at most companies, and I say most companies, it’s not every company, but most companies of any scale, the training is all about maintaining the status quo. 

The reality is that any mature company that’s been operating for a significant period of time, particularly public companies, have already established a business model that they believe works and they believe that business model is based on a set of proven algorithms, whether you’re talking about McDonald’s or whether you’re talking about a big insurance company or a big bank, or a big manufacturing company, they’re all operating [00:11:00] based on algorithms that they think work for their business model and are the basis of their value, and then they’re held accountable on a quarterly basis when they do an analyst meeting as to whether or not they’re returning value to the shareholders at a rate that people expect for a business of that maturity and based on their historical track record. And that’s what gets CEOs fired and hired is this perception that they would manage the existing business proposition effectively, and if they don’t, they’ll lose their job. 

The problem with that is: All of the managers in that organization are not only trained, but incented to maintain that status quo, vociferously, like you’re aggressively incented to make sure that certain things don’t happen. One, you wanna deploy capital only very carefully. And that gets a lot of scrutiny. 

You go to most big companies, there’s a whole business case process [00:12:00] you’ve gotta go through. There’s a certain internal rate of return hurdle that you’ve gotta hit. And if you don’t hit those, you don’t get the capital to do your project, whatever your project is. And the point there is we’re only going to deploy capital where it enhances our existing business model in some meaningful way. 

And that’s most of the capital that gets deployed inside of large companies. There may be an efficiency gain, may be a new product idea based on an existing product line that you can very carefully expand the product line, et cetera. So capital is scarce, should be deployed very carefully. 

Second of all, you gotta make sure nothing breaks. So the other job of a manager, most managers at most companies, is to make sure the process continues to operate effectively. And in a lot of cases, the unit of productivity is a person a team of people, or a team of people working with machines, whatever the mix is. 

The [00:13:00] manager is there to make sure that quote unquote machine made up of people and machines works well. If they don’t, their job is to diagnose the problem, remove the offending part and replace it. Could be a person, could be a machine, whatever it is, but that’s their job. Make sure the system runs and and doesn’t break. 

And then the last thing is efficiency is prized. Unless it’s a business model where there’s no accountability, right? So most businesses, because of the scrutiny that they get from the marketplace, particularly public companies are constantly focused on efficiency efficiency is easier to control than the market. 

And so there’s a constant focus on how do I find another basis point of efficiency in this mega process that is producing cars or producing widgets or producing loans or producing whatever. And so efficiency is highly prized. And if you can come along with a [00:14:00] project that everybody agrees through the business case process will produce some level of savings that goes directly to margin. 

So you can produce the same product at a lower cost, you’re gonna make more money. It’s all goodness and light  

Maureen: Mm-hmm.  

Greg: Is highly prized. I would say that is different in businesses that don’t have that type of accountability. And I’ve seen those type of business models. There are certainly privately held companies… there are companies like mutual companies where they don’t have that external accountability and the market they control, they can control pricing to a much greater degree than other business models. And in those organizations, there’s still something that’s highly valued and it’s called stability. 

Don’t rock the boat. And that’s very typical as well. But either way, like those are the pillars of modern management inside of large organizations. How likely is that system of managers to [00:15:00] produce kind of innovation that you need deal with an industrial revolution compressed to five years or 10 years? 

So what’s on my mind from a leadership standpoint is, boy, we gotta really step back and rethink the mental models, the training, all of the mechanisms, the incentives around what leadership looks like, if we want to be able to survive the ult a highly compressed industrial revolution type impact on the economy. 

Maureen: I was listening to something yesterday about the change in warfare that we’re shifting from conventional missiles at about 4 million a pop to drones that can be produced as cheaply as $2,000. So the shift in how we deploy or engage in a wartime scenario is completely [00:16:00] upended. If I’m running a military facility or Lockheed Martin or any one of the large defense contractors, how am I recalibrating my system? How do you do that quickly? 

Greg: Military technology is a good place… I say military technology writ large. It’s not just the stuff, it’s the leadership, it’s the training techniques. Everything is morphing . What’s cool about it and why it’s worth studying is because when life and death is on the line, we tend to innovate at a rapider pace than when we don’t necessarily see the stakes as life and death.  

Maureen: Mm-hmm.  

Greg: There’s something to be learned. We all do that on an individual level, right? There are a lot of sort of values you hold dear that when your life threatened go the window. I may hold close to the value that I would never [00:17:00] fight with somebody, but if somebody’s threatening my life or my family’s life, I’ll fight. 

And I’ll innovate rapidly. Particularly if I’m losing. So I bring that up to say I do think that there is something to be learned from seeing where the change is being forced because so much is on the line. What’s changed? We look at the Iran conflict that’s going on right now, you pointed out that the nature of warfare changed and Iran was one of the leaders in innovating very inexpensive drones that could then do damage at a distance. It did not take us very long to adapt our existing weaponry and techniques to combat that threat, So what happened, right? 

They’ve got these drone farms underground. They’re launching these drones rapidly and in masses, [00:18:00] and what did we do? We sent the A 10 over there on which we can strap really inexpensive missiles that can just blow up in an area and take out a lot of drones at one time. So suddenly this ancient technology that’s really good at circling on station for long periods of time and really good at carrying a whole bunch of inexpensive armaments that can take out inexpensive drones efficiently is suddenly of the most valuable assets in a war that’s happening in 2026. So I do think there’s a little bit to be learned from that in that sometimes the answer that you’re looking for isn’t something new. something that’s old, that’s being repurposed in a way that was never intended to be used. 

The A 10 is a close air support weapon. It was supposed to protect troops on the ground that were engaged with the enemy. It’s now got this whole different [00:19:00] purpose. We don’t even have troops on the ground yet over there, and we’re using A-10s like crazy, and they have a completely different purpose. So that’s innovation forced by something where there’s an imminent threat. 

Threats have a tendency to drive innovation rapidly. The point I was making earlier about the pace of change is that I’m not yet seeing mainstream businesses really project a deep enough understanding of how significant the threat is, right? And so therefore, they’re not adapting as fast as they ought to be adapting. 

On the leadership front, if you’re the head of HR and training and development for a large company, you should be spending your time contemplating how do you change everything about how you have incented people and how you’ve trained and developed [00:20:00] people to manage through this period of substantial change. 

What does your model look like after the fact? What does HR look like for a system of 2000 agents that are running your company? Right? It’s not HR anymore, it’s R, but there’s an H component and there’s an M component. What does machine resources look like? What does performance management look like? 

What’s the role of the human in that model? What type of person and what capabilities, what competency maps have to exist for somebody who is managing 2000 agents versus somebody who’s managing 2000 people? 

Maureen: And how do you build evolution into that machine? Because how it changes for 2027 is gonna be entirely different than it will be for 2029. 

Greg: Yes, and I think similar to the industrial revolution, just more time compressed, you’re gonna have a period of extreme [00:21:00] change that’s gonna be very volatile and the competencies that work for that period of time are gonna look really different than the competencies that will eventually emerge and be more stable in kind of the next, call it generation of the economy. 

Maureen: One of the things we focused on, and we’ve done this for a while, is mindsets, specifically because competencies change. So how I think about a difficult conversation is potentially more important to allowing me to do that thing. Talk to a client in one setting, talk to a colleague in a setting, talk to a supplier in a different setting. If I have a mindset that supports my ability to be fluid, then I can be more agile than if somebody teaches me the formula for conversations. 

Greg: Yeah. I think we all have [00:22:00] had examples over the course of our lives where we get confronted with a truth that shatters something that we thought was a truth. And I think we’re in a time period where what you want to do, this is gonna sound cliche, but question everything, but there it’s a very real point, right? If you accept any constraint in your business model as truth, what happens in your brain is you ignore that variable; it becomes an independent variable in your equation instead of a dependent variable. And so you don’t think about it. 

You don’t get up in the morning wondering if the sun will come up. That’s an independent variable. The sun’s definitely coming up. Might be cloudy, might not be cloudy. That’s a variable that may be important, but sun coming up? Not a thing we spend time thinking about cause it’s gonna come up, right? Every business is based on [00:23:00] an understanding and an a set of assumptions around what the variables are, 

dependent and independent. if I were running a, large company now, I would be looking at every single one of those assumptions; back off, build a picture of the system, and then go and understand whether or not any of those constraints or independent variables are, questionable. ‘Cause they probably are. 

I read a post the other day. It was by a, prominent, tech, CEO, who was on a visit to Japan. And he met with 10 or 12, founders and innovators in Japan, and upon his return he was working with AI. He said, he tasked his AI agent with “help me discover the network of those 10 people so that I can get more benefit from this visit and expand my network in Japan. To the people that THESE known prominent people are [00:24:00] networking with in Japan.” 

And he and the agent got to going back and forth on it and the agent came back and said, “Would you like me to just build you a CRM so that you have a networking tool that you can use for managing your network?” And this founder was like, ” Now I do. I’m curious about that.” Within 10 minutes, the agent had coded a CRM fit for purpose for this person managing their network. 

That’s a constraint that you wouldn’t have considered violating even three months ago, most likely. It wouldn’t have occurred to you that the easiest way to solve this problem of expanding your network based on a visit somewhere where you met some people was to get a custom coded CRM. 

Turns out that’s not a constraint. 

It’s actually really easy and takes less time than it [00:25:00] would to jump in your car and drive to Starbucks and wait for a $10 coffee. That’s an example. It’s a relatively small one, but all of the constraints that you think you have in your business should be questioned explicitly. 

Is that still a constraint? Because so often we make decisions based on our assumptions about those constraints. 

Maureen: What do I do? I’m running a company, I’m an executive. Either I’m a founder and I am running a software company and now this Claude agent’s gonna put me out of business, or I’m running an insurance company and people will still require insurance, but how it’s delivered to your earlier point, may look entirely different. How does all of this as an individual leader or leader of an enterprise, how do I make sense of, and then act on what’s [00:26:00] happening? 

Greg: I think the first thing is you gotta spend time on it. It’s very real. And I think the senior leadership teams of large companies, or even small companies, ought to be dedicating some meaningful portion of their time to figuring out what this means, right? You already have people who are maintaining your business model as it exists. 

You already have mechanisms that you use for your annual planning cycle. You already do things like hold senior leadership retreats when a new competitor enters the market. And you gotta figure out what that means. Use those same tools that you have to burn energy on this problem. One of the more notorious case studies that had huge impact on business for decades was what Shell Oil Company did with scenario planning during  

Maureen: Hmm.  

Greg: oil crisis in the [00:27:00] early seventies. And Shell Oil was able to navigate that storm better than all of their competitors because they had spent time prior to the oil crisis of the early seventies, figuring out what they would do if there was an oil crisis, and they already had a binder that had the action plan for what they would do if that type of an economic impact came along. 

How many companies have a binder action plan or a technological one that will give them the playbook for what to do if their business is dependent on energy and $175 barrels of oil are a problem. If you don’t, you probably should. Are companies putting time and energy into scenario planning for what has emerged as a whole new set of scenarios that for [00:28:00] sure you don’t have a plan for yet. 

Even if you’ve been super disciplined about it and you already have playbooks for a bunch of scenarios, they probably don’t include the ones that are gonna be occurring in the next five years. So you gotta go update that. And when you do that thinking, it’s gonna force you to deal with the fact that, oh my goodness, none of our leaders are equipped to participate in this playbook. 

We gotta fix that. So now you’ve got another thing to go do, which is go retrain your leaders on how to manage in this emerging economy. And then you’re gonna realize we incent all the wrong behaviors in  

Maureen: Hmm.  

Greg: “Oh wow. We gotta start paying them differently.” So everything starts getting questioned because you did the work of looking at the scenario and saying, you know what? What would we do if this happened? 

Maureen: If the pace of change is accelerating, then the pace of decision making has to [00:29:00] accelerate. 

Greg: And the biggest lever you have on that is training in shared context. You cannot achieve faster decision making by simply having a small number of senior leaders making all the decisions faster. That won’t work. What you need is to have autonomous decision making happening as close to the action as possible. 

But with the full context and competence required to do; that’s decision velocity. And there’s so many analogies for that. That’s the manufacturing line worker that can stop  

Maureen: Mm-hmm.  

Greg: the entire assembly line, That’s autonomous decision making. But you don’t let that happen unless that person is trained and has the competencies to make the decision. 

But then you want them to make that decision. You don’t want them to escalate that, if somebody’s injured or there’s a quality problem or something like that. You want them to have the [00:30:00] context to make the immediate decision to do that thing. That’s what fast decision making looks like; not I’m gonna equip my senior most leaders to make better decisions faster, because you’ve still got: the real wasted time is the decision getting presented to them with the appropriate information in the first place. That’s the problem. 

Maureen: And so all of that requires not just chain training the operators, but building the entire ecosystem that supports decision velocity and sense making. That we need the employee on the line to be able to interpret the signal and make a good decision 

consistently. The context piece:, context and competency. they need to understand. And then they need to understand the context, right? And most companies are really bad at that. The big companies I’ve worked for information and context is a management weapon [00:31:00] to preserve superiority.  

Greg: And it’s such a mistake, A lot of companies don’t share their financials. Every employee in your company ought to understand your financials sufficiently to make decisions that are relevant to them. You want that, right? They should understand how, what they’re doing and their decision authority relates to the outcomes the company values most.  

Maureen: that a  

Greg: of us have been in a conversation with a manager where the manager says, I know something that you don’t, so it’s really important that you take my word on this, right? We’ve all been in that conversation and it’s undermines that whole concept of shared context and decision velocity. 

Maureen: And we’ve probably all been that manager because the context expected us to keep things quote secret. 

Greg: there are real reasons why information can’t be shared, and I would say as a manager, I I always tell my team, “Anything I know that I think is relevant to your job, I’m going to [00:32:00] tell you unless I absolutely can’t.” Insider trading is not a pretend thing. Quiet periods are not a pretend thing and they’re regulatory and you can go to jail if you violate ’em. So I think everybody gets those constraints, but way more information could be shared than is shared. 

Maureen: What is the one leadership choice you believe senior leaders or boards should make in the next 30 days? And what systems or practices must be put in place so that choice actually sticks? 

Greg: I’ll go back to if you are running a company today and it’s a successful company with a track record, a senior leader, you should be stepping back, examining your system at a macro level and questioning all of the constraints to see if those constraints are vulnerable. technology innovation that is coming at us at a rapid pace. 

Maureen: Not just technology [00:33:00] changes, but context changes. What does the price of oil do? What does the difference in climate do? There are so many variables at play that are surfacing more rapidly than have happened in the past. 

Greg: I think that can get baked into your scenario planning if you assume that certain variables that you have held true are going to change, Mm-hmm, some of those may be related to technological change, some of them may be environmental. And then you make assumptions  

Maureen: Mm-hmm.  

Greg: about the environmental things ’cause the thing about the environmental changes is they are independent variables. It’s not that they  

Maureen: Mm-hmm.  

Greg: you, you can’t control them. There’s circle of concern, not circle of control. So you should build scenarios around your assumptions about those independent variables, and then focus on the pieces that you can control, some of which you thought you couldn’t control, but [00:34:00] now you probably need to question that. 

Maureen: And then to extend that: Put into action, how do I get my leaders ready? How do I change my systems? Because one of the scenarios may or may not happen, but something aligned with that will. 

Greg: Yes. And it wasn’t that, back to the Shell example, it  

Maureen: Mm-hmm.  

Greg: that, it played out exactly as one of Shell’s scenarios predicted it would. It was close enough that it gave them the playbook and they had already trained their managers, and the training part is really important. Back to the point we were just making, you want the people who are close to the action to be able to make really good decisions in real time. 

That’s decision velocity: not escalate the problem as fast as possible so somebody important can make the decision; you’ve already lost. Yeah. 

Maureen: Yeah, agreed. 

Greg: That’d be like calling 9 1 1 when you’re having a car accident. It’s [00:35:00] not gonna be helpful. 

Maureen: You may get an ambulance after you get crushed, but yeah, not helpful. 

Greg: If I had one, one more thing to mention, I would say that the pace of change is gonna be such that you’re probably not gonna have the luxury of redoing your scenario plan every three months. But that then hunts back to then, great. How do I equip my managers to deal with volatility in the near term when I don’t have the luxury of having a management retreat every month because the world’s changing so fast? 

 the easiest analogy is what you see. Back to your point about like we learn a lot from the military because life and death is on the line, and so you have to innovate rapidly. I look at like how a SEAL Team operates versus how a large deployed army unit operates. 

SEAL teams achieve their flex, their mission flexibility, and their mission [00:36:00] success by training on the technology, training on teamwork, training on techniques around how to solve problems. And then experimenting with that tool set together, and 90% of their time is spent doing those four things. 

10% of their time is being deployed into the world to leverage all of that capability in a very specific and volatile mission. The question is, how do you bring the lessons from that inside of your corporate environment where you don’t have the luxury of practicing 90% of the time, but you certainly can take some of those pillars of making sure people are current on technology, making sure that you’re focused on teamwork and how people work together effectively. And then training on problem solving with context, and then experimenting together. Try things, iterate right on things that you [00:37:00] think could be disruptive to your business if you’re not doing it, somebody is. So hopefully that, that’s a good parting thought in terms of a way to approach the problem with an existing business that still has to run. 

Maureen: Thank you. I find these conversations incredibly insightful and I trust our listeners do, too. So to our listeners, thank you for engaging. Thank you for taking the time to listen to us, listen to Greg as he synthesizes and shares. Please continue to listen, follow and share, and like this content as we navigate the changes we’re experiencing. Part of how we make sense of it is the collective wisdom and so listening and sharing and talking to others about what you’re listening helps all of us live in a better world.