281 Strategy in The Digital Age and Mastering Digital Transformation with Michael Lenox | Partnering Leadership Global Thought Leader

***DISCLAIMER: Please note that the following AI-generated transcript may not be 100% accurate and could contain misspellings or errors.***

[00:00:00] Mahan Tavakoli: Welcome to Partnering Leadership. I'm really excited to speak to welcoming Michael Lenox. Michael is an expert on strategic management and he's a professor at the University of Virginia's Darden School of Business. He studies the opportunities and competitive implications of newly emerging technologies.

Michael is also the author of the new book Strategy in the Digital Age: Mastering Digital Transformation, which provides a comprehensive roadmap for organizations to successfully leverage digital advances. I really enjoyed the conversation as Michael shared insights from companies and outlined an approach to digital strategy, covered key technologies, new competitive positions, critical human elements, and frameworks for planning transformation. 

I am sure you will enjoy the conversation and learn a lot from Michael as well. I also love hearing from you. Keep your comments coming. mahan@mahantavakoli.com. There's a microphone icon on partneringleadership.com. Really enjoy getting those voice messages. Don't forget to follow the podcast on your favorite platform, and when you get a chance, leave a rating and review that will help more people find and benefit from these conversations. Now here is my conversation with Michael Lennox.

Mike Lennox, welcome to Partnering Leadership. I'm thrilled to have you in this conversation with me.

[00:01:29] Mike Lenox: Thank you so much, Mahan for having me. 

[00:01:31] Mahan Tavakoli: Mike, I really enjoy Strategy in the Digital Age: Mastering Digital Transformation, and can't wait to talk about that because while for many years I've been talking about digital transformation and strategy, I am finding part as a result of AI and generative AI, more executives and CEOs are sitting up and paying attention.

I think your book has come at a great time for organizational leaders to think about their strategy. But before we get to that, we'd love to get to know you a little bit better. Whereabouts did you grow up and how did your upbringing impact the kind of person you've become? Mike? 

[00:02:10] Mike Lenox: Yeah, wonderful. I'm from a small steel mill town outside of Philadelphia, in Pennsylvania.

Definitely was very influential in my upbringing and even the research I do today. Just a quick little background. At one time it was the largest US steel plant in the country. And unfortunately, during the time I was, growing up and going through high school, it was on the decline and it eventually shuddered about five, 10 years after I had left off to college.

And you could see the devastating impact that had on the community. And it really got me interested in this kind of broader question about disruption. And the ways in which, technologies rise and fall, industries rise and fall and even cities and communities can rise and fall with the evolution of technology.

So it's always in the back of my mind as I study disruption and I'm a technologist, so I'm always interested in what technology can bring next. I try to always remember, what are those impacts it can have on local communities and local people's lives as we go through these disruptive periods.

[00:03:11] Mahan Tavakoli: Those disruptions, as you mentioned it. I also love Asima Harris's work and book, The Exponential Age, have been getting a lot faster. Why is it that you see digital transformation accelerating at this point causing even more disruption? 

[00:03:28] Mike Lenox: It's interesting, I almost have two minds of this. If you look at any age, go back any decade, and read, it's always the most intensive, hyper-competitive, innovative, time period in the history of the world, right? So it almost seems like it's human nature for us to view our time period as the most disruptive as there is, and as I put it on the book, in terms of digital technology. We can go back 50 years and have stories of disruption mentioned the old windup watches that we had back in the sixties and seventies, and of course, the personal computer disrupting the typewriter and the like.

But there is a palatable sense that things are accelerating and I think, generative AI is on the top of everyone's mind. AI is not new. This has also been discussed going back 50 years or so. But the time is ripe right now. I always went out, I was undergraduate. I did my degrees in systems engineering.

During that time, we were actually talking about AI, we were talking about things like neural networks and some of the backbone of what we see in our AI-enabled world. What's changed are two things. One we really just didn't have the volume of data that's needed to train algorithms. And now we live in a world of, data abundance.

And the second is we didn't have the processing power. We didn't have the storage and processing power to allow us to create something like a chat GPT and these other generative AI that we see now. 

So it does feel different at this point in time than it has in decades past.

[00:04:53] Mahan Tavakoli: And you also mentioned this in the book, that the lifespan of organizations, whether they stay on the Fortune 500 or survive, has continually become less. 

So one of the things I wonder about that though, Mike, is that by default is going to happen or it sounds like you're an optimist, that you believe organizations can survive for longer through digital transformation.

[00:05:21] Mike Lenox: That's right. Unfortunately, the list of examples I can give you of failed digital transformations is long for sure in companies that have faced these types of epics and changes in technology and have struggled. At the same time, I'm an optimist by nature and I think there are ways in which you can think through the problem in ways to position yourself for success moving forward.

And that's a large part of what the book is about, providing you with a set of frameworks. A way of thinking about how do you strategically position yourself in a digitally evolving industry and environment that you're likely operating in. Because honestly I've observed, and I think many have observed, I have yet to find an industry or sector that is not being impacted by digital technology at this point.

This is impacting just wide swaths of the economy. You ignore this at your peril. 

[00:06:07] Mahan Tavakoli: I totally agree with that, Mike. One of the challenges and frustrations that I've seen, I'm based in Washington, DC and many of my clients are in the region. In many instances, people that are not in the technology sector don't see themselves in as much of a threat as I believe they are under, without going through that digital transformation.

So we'd love to get your thoughts. Why should organizations whose core function is not technology, why are they at risk of being disrupted and why do they need to go through digital transformation? 

[00:06:49] Mike Lenox: I make the point in the book that if digital transformation is being led by your IT organization, you're probably in trouble already. You view this as just a technological problem and we've got a tech group over here and they'll handle it. And unfortunately, a lot of the digital transformation efforts I see in companies are really centered around, how do we improve some of our processes, do a better job with our data, and maybe create some data visuals.

And those are all fine and good activities and probably necessary, but you're missing the big picture. So what's the big picture? Fundamentally changing the ways in which you create customer value. Moving into worlds where your engagement with customers is going to be continuous and in real-time, and adjusting in that real-time leveraging data and analytics to create and customize products and services to your customers. 

You're seeing the ways in which the value chain is constructed being, as we call it, deconstructed here, ways in which different maybe entrepreneurial players might come in and take various parts of your value proposition in your value chain and disrupted.

That's happening. And then, probably last but not least, just simply what are the ways in which you capture the value that you create? And this gets the fundamental strategy question of how do you position yourself in a market to both create value, but also of course create some for your organization as well.

We're living in a world where data rules supreme. Some have said, data's the new oil in our economy. It has huge implications for as an economist, the underlying structure of the industry. So one thing we talk a lot about are these network externalities and these winner take all markets that we see probably best exemplified by platforms that are proliferating out there.

And so those can have just dramatic impacts on your business model who your competitors are and how you might position yourself. Just to give you one example we're all familiar with, think about Uber and the disruption it's had on the taxi cab market. Uber didn't build any taxi cabs. They didn't go into different cities and, build out stations, and like they used a piece of software installed on your phone to create what we call a two-sided market.

We're now. Those who wanna be drivers can connect with those who want rides, and they fundamentally disrupt that kind of old state industry there. That's what we're seeing in the digital world. It's not just these kinds of minor upgrades to how you do your thing. It is often much more fundamental to the nature of competition.

[00:09:16] Mahan Tavakoli: So that's where I wonder Uber is a great example of it where. , a disruption comes from outside of the traditional industry. And it drastically changed things. You also mentioned music streaming and music platforms. The music industry was not in the position necessarily to make that transition.

When streaming started, then all of a sudden they had to play catch up. Is it possible for organizations as they're doing their strategic planning to be able to view those external opportunities? I've done lots of strategic planning for organizations. I used to actually be the chief strategy officer for an organization.

We did brilliant competitive analysis, but the threats almost never come from the competition. They come from people that like an Airbnb all of a sudden pop up. Almost out of nowhere and redefine what the value proposition is. So how can organizations, as they're going through the strategic planning process, account for that and think about that?

[00:10:24] Mike Lenox: Yeah, and there's a number of tools that we have in the book that really try to help you along in trying to see that future that might exist. Obviously, you need to be thinking about not only your current competitors but who might be able to diversify into your industry. It comes up quite frequently in the book about the big tech companies.

They are moving into so many adjacent markets, healthcare, education, and financial services. You need to be, paying attention to what they are doing and how might they think about positioning themselves into your market. Talk a lot about industry life cycles, trying to really understand where are we in the nature of technology.

A lot of times incumbent firms miss out on technology 'cause they don't understand a fundamental concept of S-curves. And the idea here very simply is that early on in the lifestyle cycle of a technology, doesn't seem to be improving very much. It might not have much adoption. It might in some cases go on for decades before it really gets traction.

But if it's gonna be disruptive, you'll get to this kind of exponential improvement and growth part of the curve. How to pay attention to those when are we seeing that? I'll give you one example that I pay quite a bit of attention to is the electrification of vehicles. And I still see analyses out there that are making predictions like maybe by 2040 there'll be a significant percentage of electric vehicles.

The fact of the matter is, in the last five years, we've gone from 1% to 2% to 4%, to 8% to 16%. You don't have to be a mathematician to figure out what you just saw. We're seeing a doubling of new car sales per year as electric vehicles. If that trend continues for another two or three years.

We're talking about the vast majority of new car sales are going to be electric. That's exponential growth. A lot of people have been highlighting chat GPT, the fastest adoption rate seen on a piece of technology arguably maybe ever. Within a matter of months, hundreds of millions of users and subscribers were there.

That's exponential growth. That's the type of disruption you've gotta be looking for and preparing for in your various markets. 

[00:12:26] Mahan Tavakoli: We have a very hard time understanding that exponential growth. And I know you mentioned it briefly in your book, I had the joy and honor to speak with Steve Sasson, who is a person that invented digital photography at Kodak.

Yeah. And when he had done that in 1975, When the executives looked at the output, they're like, no one will ever want to use this thing. There's this big camera. You've got, the quality is not good. They will want to stick with the film. Part of what you're saying, and part of what happened there is that exponential growth curve in the technology that made it a lot better, a lot more efficient, and had serious impacts. 

Another question related to Kodak, they knew at a certain point, by the mid to late nineties that digital was going to take over. But until even 2003, introducing the film, they would make more money than through digital. 

So how can organizations, even if they understand the exponential growth of the technology, how can they rethink the business models, which become the biggest challenge and barrier to that change?

[00:13:41] Mike Lenox: And Kodak is one of my favorite examples. I start the book with it. At one level, it seems like the simplest digital disruption story, they made film, and the world goes to digital imaging. But as you pointed out, they were actually a pioneer in digital imaging. They saw this coming.

They hired a CEO away from Motorola. They did everything you could imagine to try to bring about this digital transformation and yet they still failed and they failed for the reasons we might see as obvious. Worries about cannibalization of existing revenue streams. Even things like the rock stars at Kodak historically were chemistry PhDs who knew how to work with film. What role do you have in a digitally engaged company there?

So, the internal politics even come to play. And these are all the reasons, again, why it's so hard for incumbents to make these changes. I go back to what I think is a fundamental principle of business strategy, what we call the strategist challenge, and the idea very simply. That valuable competitive positions emerge out of your values and mission organization is very critical. 

Who are you and what are you trying to achieve? The opportunities the market provides, including your competitors and the like, and then of course your capabilities as an organization. The reason it's a challenge is that in the digital age, that opportunity set that you might've been used to.

Shifting away from where it historically has been and it's rendering a lot of your existing capabilities worthless in many cases. The problem is, it's almost impossible, and I cannot think of an example of a company who just wholesale a Jettisons what they used to do in the past and reinvents themselves from scratch.

A new right like that is not likely to happen. And more likely than not, you'll be out-competed by some, new venture that comes into the market. So what you need to be thinking about is what do we have historically that can be an asset. In this digitally transforming world Mahan, I see too many companies come to me and they're like, we want to be the Google of X.

And my standard line is no. Google's gonna be the Google of X. They're actually much better positioned to you to take that position you've identified. You need to go back to the drawing board and rethink. Where can we leverage our existing capabilities to create a competitive advantage in this digitally transforming market and have a certain degree of humility and understanding that you can absolutely build and develop capabilities, but you're not gonna just completely reinvent the company from scratch?

[00:16:02] Mahan Tavakoli: That's a great point in terms of how leaders can think about their strategy and their organizations. So as they're doing that, Mike, I wanna marry that with. Part of my fascination in many of the conversations I've been having on artificial intelligence, part of what a lot of people aren't aware of is Open ai.

I think right now is about 300 employees. Mid Journey has about 10 employees. It's incredible how few people can get lots and lots of things done through being augmented with ai. Will this therefore require legacy organizations as they're thinking about digital transformation and that change to rethink how they get things done and be able to get it done through drastically reducing 

[00:16:55] Mike Lenox: headcount. I think increasingly this is what everyone is worried about. I do point out in the book that the Luddites, the original Luddites, we're worried that the industrial revolution and the machines that were coming online were gonna replace human labor and we would all be jobless. And over the course of the last 150 years or so that hasn't.

Proven true. And economists will quickly point out that almost always we create new sets of jobs, new sets of capabilities, and continue to have opportunities for employment. So maybe we, don't want to freak out too much. People who I really value their opinion feel that this is different.

That we are entering into a different epic where. This could be a really significant disruption to labor force participation. The way I've been thinking about this is I don't think necessarily whole job classifications will necessarily go away, but to your point, they're gonna be able to scale.

So think about a lawyer, a law firm has a bunch of senior lawyers, then they have a bunch of junior lawyers who are doing more routine work, maybe summarizing case law and man, that is a very easy activity for a chat, G p t generative AI to do. What you'll see is that same senior partner now doesn't need, five junior partners.

They can now have 10 x the amount of impact by leveraging ai. There's examples in the medical field when it comes to dermatology. There's examples where the AI is doing a better job of recognizing skin cancers than often. The doctor does. I don't think the dermatologist goes away.

You still need that human there for consultation and judgment and the like. But now that same doctor can do 10 x the amount of patients that they were able to do before. And of course, that ultimately will reduce the number of doctors that we need. We're gonna see that in industry sector after industry sector.

The scalability. We can talk about income inequality. That's gonna be accelerated because we're gonna go to even more of a winner take all market where those who position themselves in these aggregator positions are going to capture more economic value than the rest of us.

And we do need to be thinking about this and be prepared as a society for that type of acceleration. 

[00:18:59] Mahan Tavakoli: I totally agree with you on that. But with respect to organizational strategy, Mike, your book, is a handbook for the executive leadership team to sit down, fill out the frameworks, and that leads them to thinking through their digital transformation.

But one of the things that as I've been interacting with clients and lots of other leaders telling them about this transformation, which is accelerating in part because of ai. They tell me Mahan, it's overwhelming. They feel really overwhelmed. So where should companies start with their digital transformation?

Yeah. They come to Mike ai. Now you can train an AI with all of your previous content, Mike. They don't need to talk to you anymore. They say, okay, I get it. We need to go through digital transformation regardless of the industry size, all of those things.

Where should we start? 

[00:20:02] Mike Lenox: Yeah. And I talk about in the book this idea of the digital transformation stack. And there's four layers to it in my mind. I'm gonna start from the bottom, but this is not the order by which I think you should do this. In fact, it's gonna be the opposite. At the bottom layer of that stack is your digital infrastructure.

And this is unfortunately where a lot of companies think digital transformation. Wholly resides. This is building out maybe cloud storage or a data lake and, getting your data and your, it organized, very critical, but that's just the foundation layered on top of that are your data and analytics which includes people and skill sets to be able to use the data you have in hand to create.

Value added analyses or services and the like. And this is where having data scientists on hand and the like, becomes really critical. Layered on top of that is what we might call digital applications. This is where the rubber really hits the road, and you're saying, all right, we're gonna create an application to help our HR unit do a better job of processing employee requests and the work.

Maybe it's our marketing division and how they're gonna leverage digital to do a better job of customer engagement on the lifetime value. Those are all critical. But then the top layer, and maybe not surprising as a business strategist of saying this, but I. Resides your strategy.

And this is where kinda the first half of the book tries to lay out, where are you actually trying to go? What is your, position you're trying to achieve? And so I use this metaphor of the idea of if you're not careful, what you'll be doing is making the engines more efficient on the Titanic.

And all that's gonna do is run you into the iceberg quicker or more efficiently than you would've otherwise. So knowing where you're trying to go and steer the ship is gonna be critical then to informing the rest of the stack. And again, where I find companies failing is they run it the other way around.

They start with, Hey, what data do we have? Hey, wow, I can create this beautiful visualization with the data. More often than not, those visualizations then aren't used in the organization or people don't understand how they use them to influence their decision making. And that ends up being a lot of wasted time and effort and money as well.

And I think that's where a lot of frustration sets in that they're like, wait, we've already spent, x millions of dollars on our digital transformation and I don't see it filtering into our organization. So I really think having. The goal in mind, knowing where you're trying to go, and then have that influence and inform your actual application development, infrastructure development, just absolutely critical and surprisingly missed by a lot of companies.

[00:22:27] Mahan Tavakoli: I love that, Mike, and that is a golden statement right there in that many organizations I've seen have spent a lot of money. On the digital tools and technologies rather than letting the strategy guide the digital transformation 

[00:22:45] Mike Lenox: There's a lot of companies out there who are, scrounging around saying we need chat G P T, , let's make an application using generative ai.

And it begs the question, wait a minute. Why, how is this gonna add value? How are we going to benefit from this? And hopefully those questions are starting to be, asked. 

[00:23:03] Mahan Tavakoli: So in order to do that, as you are guiding leaders, having conversations with CEOs, How frequently does that strategy need to be revisited?

Yeah. For organizations to stay relevant because the pace of changes really fast. Yeah. But you also don't want to be changing your strategy every other week. Yeah. 

[00:23:25] Mike Lenox: I think that's right though. I always point out that I think there's a misnomer sometimes that as companies and organizations go through strategic planning exercises, that now it's a rigid, guidebook for us for the next five years, and that's not what strategy is in my mind.

Strategy needs to be dynamic. It needs to be constantly revisited. Your core assumptions need to be revisited as new data and the like are brought in. I'm a big believer in kind of a hypothesis testing approach to thinking about strategy. And you do need to pivot and there will be times where you are heading in direction A and you realize that a pivot to be is necessary.

I agree with you can't be pivoting all the time. And this is where I guess, You could say strategy is so important because it is that directionality that really matters. I quote in the book a quote from Eisenhower, where he talks about strategy is useless, but strategic planning is invaluable.

And what he meant by that is whatever strategy you put in place, the second you get on the battlefield it becomes irrelevant because conditions have changed. But that process of going through the strategic planning process was actually invaluable, so that you can understand now how to pivot move and respond to the conditions at hand.

 That's the way I think about your digital strategy is it's not set in stone. But you need to understand where you're trying to go and pivot when necessary. 

[00:24:42] Mahan Tavakoli: That's essential, and it's one of the challenges that I see in many organizations. However, an additional challenge to that, Mike, at least in my experience has been there have been times when the leadership team has been able to come up with a good or good enough strategy.

However, that's not what gets in the way of the digital transformation and the strategy execution. It's the ability to bring the organization along, because at the end of the day, it's not the 10 people that sit in a room and come up with a strategy. Yeah. So what is your advice to leadership teams in being able to bring the organization along toward that strategy?

[00:25:26] Mike Lenox: I a hundred percent agree with this. I think more often than not, it's the organizational change aspects that are the most critical. And so that does start with the senior leadership, setting a vision and setting, motivation for the organization. But it takes far more than that.

I I like this idea, and I'm stealing this from other colleagues, that what you really get, especially ai, but digital more broadly, are very good predictions. Hopefully more and more accurate predictions, but you also need judgment that's laid out on top of that. And judgment, I would argue, is distinctly human activity.

And to the extent they're compliments, if one is going down in its cost, 'cause you can do prediction very easily now it actually raises the demand for judgment. So we're moving into a world where managers and employees in general have to be able to understand what am I getting out of my ai or what am I getting outta my data and analytics?

What judgements do I layer on top of that? The problem I see, and this gets back to my point about just relying on your IT organization. Similarly, running out and hiring a bunch of data scientists might be necessary, but clearly not sufficient. And more often than not, sometimes those data scientists are very skilled, but maybe not skilled in translating what they do to those who are making the decisions and the judgments that are needed.

So I talk in the book about this idea of digital champions. You need to have people in the organization who are digitally sophisticated, but not necessarily, a data scientist or an IT expert but they understand the potential that digital brings and those really need to be populated throughout the units of the organization and your marketing group your HR group your finance group and your product development divisions and the like. Those digital champions who understand the world of possibility and can translate. How these technologies can actually be brought to bear in your organization. I think they are the true linchpin of connecting that strategy with the implementation 

[00:27:17] Mahan Tavakoli: side. And you addressed this in the book as well.

I truly believe that you should spend as much time, if not more time, thinking about the change initiatives and how to bring the organization along as you do on the actual strategy. The strategy can be brilliant and not succeed. Less than brilliant strategy can still be effective to move the organization forward. You mentioned it in the book, I had a conversation with AJ Agrawal outstanding books on artificial intelligence. 

[00:27:49] Mike Lenox: AJ was the one I was just stealing from with the 

[00:27:50] Mahan Tavakoli: prediction. Yeah. No, that's a great point. With respect to the power of prediction that comes from artificial intelligence, therefore, Placing greater emphasis and need for that judgment.

Now, part of what allows for that prediction Mike, is data. And you talk about the value of data in your book as well. Roger Martin has a lot of great thoughts and books on strategy and he says there is no data about the future. So he is very skeptical of leadership teams. Thinking too much about data and analyzing too much data to come up with strategy about the future.

How do you balance that? Yeah. Where there's value in the data, but you need to move way beyond that if you're having a strategy for the future. 

[00:28:42] Mike Lenox: The good news for us is that I don't think there's gonna be an AI who can do strategy effectively, in the near future for exactly this reason.

So that's good for us there. No, it's absolutely right. We're only able to train our AI on historical data that we've already collected. By definition that's the case. And I guess this goes back to what we were talking about with judgment being layered over top of those predictions and understanding that AI is very powerful and can do some amazing things, but it's not an oracle.

It's not able to totally foresee the future , and I talk about this in the book, about having humility, understanding the limits of technology and what it can and can't do, I think is absolutely critical as you approach these systems.

If you think of it as of a magical box that's going to, do everything, you're probably gonna be sorely disappointed even with the success and the fast pace of evolution of AI that we're seeing. It's still. Fairly limited in what it can do. Getting back to your earlier points about data I do think it's really becoming the critical source of competitive advantage.

A lot of the technology around ai. Is actually becoming commoditized by the likes of Amazon with a w s and Microsoft. With MA Azure they're providing these tools as just part of using their cloud services. So what's gonna differ one AI from the next is the access to data and what data sets are proprietary and can train your algorithm that others.

Aren't able to do. That I think is gonna be really critical. It's one of the reasons and I talk about this in the book, that I worry about big tech to the extent they are gobbling up, especially on individuals, just so much data about us. That they'll be able to, diversify into a wide number of industries here, leveraging that vast trove of personal data they have.

The critical question that I have with that is, , thinking about Esker. There clearly are increasing returns to data that we have seen, but , as an economist, you would expect there to be decreasing returns at some point in time. So how much data is good enough? To train your ai and when does data have these decreasing returns to it?

I think you look at these large language models. It's a fascinating question, like does, it require the internet, and all the data and all the writings out there. Or could the New York Times train a AI just based on New York Times content.

That's actually a pretty good large language model. I don't know the answer. I'm not sure anybody knows the answer to that. That's gonna have huge implications for the competitive outcomes. 'cause if it really is increasing returns for a long period of time, we're looking at an economy dominated by a handful of companies that's the world we're looking at.

If it's not that large. Now it gets a little more interesting from a competitive dynamic standpoint. 

[00:31:26] Mahan Tavakoli: I want underline a point that you made, Mike. That I agree with Roger Martin. I totally understand the point that he is making about the future, requiring judgment and not necessarily just being based on data.

In most of the strategic planning conversations I have been involved with, there has been a ton of judgment and very little data. The only data that has existed has been some of the financial data. One of the things AI can do. Is really tap into a lot of data within the organization and a lot of insights.

So judgments can be built on top of that data, not just based on the experience of the individuals in the room. So at least my experience has been an overreliance on the judgment the opinions and the experience of the individuals. Yeah, rather than real data driven insights.

[00:32:21] Mike Lenox: Tensions with this, like in the fashion industry where historically the fashion industry was dominated by those buyers who, had the eye for fashion and, had this innate ability to see where trends were going. And it's largely moved into this AI driven world where it's predictive algorithms based on TikTok and Instagram.

And you have this whole world now of fash fashion that's grown up on this that is completely based not even, yeah, probably completely based on data and algorithms and not a person sitting there deciding that, cargo pants are back or whatever. It might be. 

[00:32:56] Mahan Tavakoli: That's important to keep in mind for that strategic planning.

And one of the things that I mentioned to you, I sometimes get emails from listeners that say, I run the regional operation for an organization in the greater Washington, DC region. So I'm not the c e o. Yeah, I'm c e o of the region, but not c e o of the entire organization, or I am a manager in a division.

Or running a nonprofit organization, so people at different levels of the organization who are not necessarily the c e O and the C-suite, working on the strategic plan, how can they think about and play a role in this digital transformation of their team, group, or organization? 

[00:33:41] Mike Lenox: Maybe not surprising.

I have a really strong opinion on this as someone who's been teaching MBAs for the last 20 plus years, and obviously most of them don't at least immediately go out and become CEOs some occasionally do. I really believe strongly that strategy is not just the domain of the C-Suite. It strategy needs to be understood and appreciated, and everyone in the organization needs to be strategic.

Thinkers at the very least to see how their actions and decisions fit into the broader strategy of the organization. I always tell my students to think of strategy on three different levels. At the most base level is a typical strategic planning process or a strategy consulting engagement.

Maybe you're given a couple months and you can do some. Deep dives into competitor intelligence and other data to formulate an opinion and a strategy. Then you have the overnight, the boss calls at 5:00 PM and says, I want on my desk of report by tomorrow afternoon on, generative ai.

And how do you think through that? And then to me, the highest level order of strategy is what I call the elevator conversation. You get on the elevator with a client or a boss and she asks you a question, maybe again, about generative ai. You are trying in real time to give a cogent and powerful response to that question.

In all three of these scenarios, though, you're going through the same logic. You're still thinking about my strategist challenge again, what's happening in terms of the market opportunities. What are our competitors doing? What capabilities do we bring and what is that mission and value that's so central to who we are?

That level of strategic thinking applies again, doing a big planning process, but also that kind of in the moment. How do you respond to this situation? And so in many ways what I'm trying to do with the book is that bigger strategy question in strategic thinking, but with the nuance of what are the particular things in the digital age that you really need to be paying attention to data.

Platforms, network externalities, how this is, deconstructing value chains. These are things that need to be really top of mind as you think about, regardless of how small your unit might be, how your actions are gonna influence the direction of the company organization. 

[00:35:45] Mahan Tavakoli: Mike, one of the things I love is that you have great insights.

This is a framework in addition to teaching, you also have to practice this. You  have a strategy role at Darden. So how have you been implementing some of your thoughts in thinking through the strategy of the business school? Yeah, 

[00:36:09] Mike Lenox: and I share some of this in the book about how here I am, an academic, a strategy professor, and then suddenly I'm asked to run our strategy as a school, including our own digital transformation.

And I made all the mistakes that I've saw others make. I came in with high expectation. We're gonna run all these sophisticated analyses and I. Wow what we can do with data and analytics and immediately ran into, the politics of who owns and controls data. Just even building a data lake was like a heroic effort.

And then the real problem is you create these wonderful applications that then promptly sit on someone's computer, never to be referenced again when they're actually making decisions. So I've seen it all firsthand and the like. I think, you're probably interested more broadly of what's happening in higher ed and I'll tell you my thoughts there is I really do think there's a disruption facing higher ed.

And what I think's going to happen, at least what I'm betting on, is that there'll be a bifurcation. What you'll see is there will always be a set of elite selective residential based education opportunities. As much advancement as we've made on online and other forms of delivery.

It's not going to replace what we do, for example, in the Darden classroom with our case-based method. However, what's available now that's never been available really before is scalable educational opportunities. And there are certain universities, certain , profit players. That are going after this.

And once you leverage digital and online and you say, let's have a hundred thousand students, why not have a million students? Why not have 10 million students? And that's gonna fundamentally shift the marketplace there. And as I like to say it might seem like why would I ever choose this inferior online product to the residential base?

At some price point, people are gonna make the jump. So my standard joke about this is who sells more cars, Porsche or Kia? Which is the better car? Porsche or Kia? No offense to Kia owners. Most people say, oh, Porsche is great. Far more Kias are sold. Why is it? It's less expensive.

As much as that's hard to realize, that also could apply to higher ed if I can get a good quality online degree for $10,000. There's gonna be a lot of people who are gonna choose that. Now for a Darden, given who we are and what we do, we're gonna continue to play that elite selective game.

And for us, we talk about it is critical for us to stay in the top 10 of business schools because being in the secondary part of the market is going to be brutal. You're either gonna need to move up the rankings or you're gonna need to go for this scale play. And the scale play is only gonna be available to a handful of schools.

[00:38:37] Mahan Tavakoli:  I totally agree with you in that the value of the credentialing from certain schools, Having that name will be a big part of it. I know there is real value to being in person and interacting and going through the case method but the mid-tier schools will have a rough time, especially because I think the education will be drastically better.

Because I'm sure you've seen Sal Khan talk about Yeah. Incorporating generative AI and has been working with G P T four in a individualized tutor that interacts with you, which I would imagine at this, based on what I've seen, will be a heck of a lot better. Then being a student with an average professor in an average school with 20 other students.

So I imagine not only the price point would be lower, but the educational quality can be drastically higher as 

[00:39:34] Mike Lenox: well. No, and there's been companies working on this for a while. Newton comes to mind as one who observed early on that when you move to an online environment, that idea of a customized journey for you.

And there's been lots written about how the way, especially education in the United States works there could be people left behind in the classroom. And so with these types of online engagements, Let's say you're taking a module in math and then they realize, by the way, you're maybe getting some questions wrong.

You don't understand natural algorithms, bam. Now suddenly you get a module that's customized to your need for learnings on natural algorithms. And so it's an ability to really bring everybody up that. Arguably, sometimes that doesn't happen in like a lecture-based mass format there.

So I completely agree with you. There are ways in which technology can actually not only do a pretty good job, but actually be superior to what some of the things we do in a more traditional environment. I think for Darden, that has meant to us that, we're not forsaking technology though.

We're not running after that online, m b A market, for example. But we need to be able to leverage and enhance what we do. Through the use of technology. And that's something that's really where we're putting our investment. As it relates by the way, to generative ai. I think we're all seeing like this is transformational over a whole bunch of areas.

It's not just the worries about, testing and people cheating by using generative ai. As a faculty member, I can put in generative ai. Give me 10 questions, multiple choice quiz on industry structure. Does a pretty good job. Now would I just use that in a course? No. But could I use that to start to then refine and create a quiz bank?

Yeah, absolutely. And I think that idea of leveraging generative AI to enhance what we do, we're already seeing it, but I think that is gonna just really take off here probably next few months, but then next few years. 

[00:41:28] Mahan Tavakoli: As it's taking off Mike, I would love to get your thoughts on some of the societal impact of all of this.

Yeah, and I also had a conversation with Joe Fuller a couple of months back at Harvard, the future of work that the gap that exists in our communities. One of the things that I know had been done by a lot of organizations, Across the country, including integrated Washington DC region, for example, was to take underserved youth and train them in coding.

Yeah. Now, overnight coding is one of the things that there's very little need for vast majority of coders. Still, you need outstanding coders, but the types of coding that they were training people on, it's not needed anymore. That's right. So as technology causes these bigger gaps, Where do you think there are opportunities for training development in order to make sure that we don't have a bigger and bigger divide as a result of this technological transformation?

[00:42:34] Mike Lenox: Yeah, look to the bigger point about the impacts of digitization on society. Again, I spent a whole chapter on this in the book mainly from a managerial standpoint. And from that, companies need to get out ahead of this. And there are so many questions companies need to grapple with.

What do you feel comfortable with in terms of data privacy? How do you want to think about that? How do you think about cybersecurity bias and algorithms? Tons of really hard questions that companies are gonna need to grapple with. And you see it right now with generative ai, with both Microsoft and Google and others.

I think struggling with how much should we constrain the technology now, but man, if we constrain it and others don't, then how far behind are we gonna fall? And there's a lot of fraught discussions and decisions there. This gets back to our question about the future of work and income inequality and the like, that might be, created.

I do think, again, it's gonna put more and more value on those distinctly human characteristics like judgment. And how do you deal with ambiguity and uncertainty? How do you deal with simultaneously having too little data and too much data? Those types of higher order skill sets are gonna be.

More and more valued in society. 'cause anything that's routine, anything that is relatively applicable over and over again. The digital world AI in particular are gonna be able to replace that. I mentioned in the book you go back 10 years ago, we talked about something like truck drivers as being, at least they'll be okay, right?

There'll be a lot of truck drivers. And now that one is probably intimately being at least long haul trucking from autonomous vehicles. So it really is a brave new world. I think we're entering here and like I said, the implications could be vast. So as 

[00:44:12] Mahan Tavakoli: leaders of teams and organizations are looking to lead themselves, their teams, and organization through this digital transformation, in addition to your book, what resources or practices do you find yourself recommending?

[00:44:30] Mike Lenox: I think you've gotta be incredibly well read and you've gotta be a learner. Everyone needs, again, we live in an age where we're being expert at everything is impossible. There's just way too much happening. Being knowledgeable though is gonna be critical. And I think that means being a lifelong learner.

We talk about this at Darden because I think. Very hard for us to, if our goal is to give you the latest and greatest in like technology, because it's going to be dated almost instantly as you graduate. So we have to go to more core concepts of what are we actually teaching?

What is our learning objectives? I like to say, we like to teach a set of integrative skills. Again, how do you deal with ambiguity, uncertainty. How do you frame an argument? How are you persuasive? How do you manage people and lead them? Those are gonna be the skill sets that are gonna be the critical ones moving forward.

Because again, being an expert on the technology, you will probably be dated in, six months from now. I'm embarrassed to say that, the way the university presses work, there's a long lag time between the final book and when it appears in press. My version of the book had to be to Stanford University Press back in the fall.

I talk about generative AI in the book. I don't actually mention chat, g p t because again, it wasn't really a thing until November December of this past year. That's the way technology moves. The metaverse is a concept that's been out there for a while, but it really didn't enter into public consciousness until about two or three years ago and seeing kind of uptake because of what Facebook now met.

 Was pushing there. So how do you become a constant learner and then how do you develop these kind of higher order skills? I think those are gonna be absolutely critical for people moving 

[00:46:03] Mahan Tavakoli: forward. I totally agree, and in my view, that's one of the potential opportunities for certain Higher education institutions, whether Darden or I went to Georgetown and loved the school, because the alumni need to constantly learn and grow 

[00:46:22] Mike Lenox: totally agree. I think most universities realize this and are running after what we call lifelong learning. I can't claim that we do it, the best, but I think we do it fairly well here.

But I think that is a big goal of a lot of universities is this idea that you are admitted into a community that you are a part of for the rest of your life. And that includes, like you said, not just going to football games or being asked to make donations, but that there's actually an educational learning component that's part of that.

[00:46:48] Mahan Tavakoli: Outstanding. Mike, how can the audience find out more about you and your book? 

[00:46:53] Mike Lenox: Absolutely. The book is available in multiple, channels as you would know, Amazon and Barnes and Noble and the like. In terms of myself I'm easily found@www.michaellennox.com. That's Lennox with one n l e n o x.

And so thank you Mohan, for having me. I really appreciate the time and really have enjoyed this conversation. 

[00:47:11] Mahan Tavakoli: Same here. I really enjoyed the book. So thank you for your insights and really appreciate the conversation as well. Thank you so much, Mike Lennox. Thank you as well.