270 How to Lead Your Organization Through Digital Disruption with Eric Lamarre, McKinsey Senior Partner & Coauthor of REWIRED: The McKinsey Guide to Outcompeting in the Age of Digital and AI | Partnering Leadership AI 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: Eric Lamar, welcome to Partnering Leadership. I am thrilled to have you in this conversation with me. Thank you for 

[00:00:05] Eric Lamarre: having me. Mahan. 

[00:00:07] Mahan Tavakoli: Really excited. I love the book, the McKinsey Guide. To out competing in the age of digital and ai. Before we get to that though, Eric, we'd love to know whereabouts you grew up and how your upbringing impacted the kind of person you've become.

[00:00:21] Eric Lamarre: Awesome. So I'm Canadian. I come from Quebec. My training is in engineering. I'm a civil engineer and oceanographic engineer. I studied actually ocean engineering and underwater acoustic in grad school at mit. And this is where I got a lot into Large volume data analysis because that's what you do in acoustics.

So I guess my first initial foray. In this field of data. And it certainly was not AI when I was doing this 30 years ago. It was brute force data and building out acoustic sensors and doing experiments in the ocean. And that was a fun part of my early career. And I got a little bit of a, a handle 

on analytics and the science behind. And after that I joined McKinsey even though I had done many years of studies in engineering and I've been at McKinsey for 29 years and I've loved my job, I still do. And quite frankly, my worlds have become, what I trained for and what I do as a living.

I've gotten closer than when I started 30 years ago. And I'm at a good place. So I'm enjoying what I do. And the fact that it's even more rich in AI data and analytics is for the best. 

[00:01:44] Mahan Tavakoli: That's an outstanding background, Eric, and we could spend an entire episode talking about your studies, now, Eric, I've been involved in many organizations where we've gone through digital transformations, and in most instances, they started out with incredible hope aspirations and goals, and they fizzled out. What do you see as the reason for those failures in digital transformations and how should we approach it differently now?

[00:02:16] Eric Lamarre: Yes. You're right. They don't all turn out successes. We survey companies all the time on this question. So the first thing that's interesting is everybody's got digital transformation of some sort going on. 90% tell us, yeah. 

And then we asked them, how successful were you with your revenue benefit or cost productivity? Benefit that you were hoping for. And in general, it's 30% of what they were expecting. And so it's falling short of expectations. We all know that this is not new news. The root causes behind are not multiple, but there are a few big ones in my opinion.

The very first one is the alignment of the top team on the prize. So if we approach this as it's gonna be a set of experiments versus we are really going after a big rock that's gonna make a difference to our performance as a top team, then we tend to have a lot of fizzling out because the day to day, hey, we gotta deliver the quarter it takes over.

 So that's the number one and most important reason why they fail. The other one is an underinvestment in the capabilities for the journey. And so there's a bit of this belief that, hey, it's a transformation.

We start now and a couple of years it'll be done. We can move on to something else. No, we'll get some consultants to help some third parties. We'll do what we gotta do and then in two years it's done versus it's a journey. We're gonna be doing this for the rest of our careers to actually inject more data and more analytics in everything we do in marketing, in product development, in operations, in our contact center, in sales, every aspect of our business will be infused with this, so we need a capability set. So they're short-changing the building out of that capability set. And so they find themselves that after the first year, all of a sudden they're running out of breath because they're running stuff in special project mode with a bunch of consultants. And it's okay we don't have the machine to keep going.

And so then it comes down, WA air comes out of the balloon and the whole thing comes down. There are other reasons, but let me just cap these two as being the primary ones. 

[00:04:38] Mahan Tavakoli: You said alignment. At the top team level, that lack of alignment is a lot of times a contributor to the failure of a lot of initiatives, including digital transformation. 

How should they approach it in order to be better aligned? 

[00:04:54] Eric Lamarre: To some extent, part of your question is why is alignment so much more important for digital transformation than it may be for other kind of transformations? Let's just take a straight cost cutting effort. Mahan, you got 5%.

Go get 5%. Eric, you've got 7%. Go get 7%. You can come back, but this is not for debate. Just get it out. Everybody goes, there's their job. We don't need to align so much. The boss has decided we go on and we do our thing. I'm exaggerating, obviously, but for effect in a digital transformation, everybody's got a role to play.

And so let's say that we decide we're gonna transform how we do. Supply chain and how we do sales and we start with these two areas, supply, chain, and sales. Okay. If I start to transform, I'm gonna do supply chain, I'm probably going to impact how I order stuff. I'm probably gonna impact how I manufacture stuff.

I'm probably gonna impact how I do. Ordering how I do demand forecasting, and now all of a sudden I'm finding out, oh my God, this is actually touching the end-to-end process. And whatever little piece that I touch, I end up actually impacting somebody else. And then back to my point on capabilities, I'm gonna need to hire new people.

Oh, head of hr, you gotta do something. I'm gonna need to change my funding. I can no longer be doing project funding as it's called. We're doing persistent funding, which is I'm standing up teams that are gonna be persistent over time. Finance. We're gonna need to change how we do funding. By the way, risk management.

All of these teams that are not developing technology, they may infringe on data privacy. They may infringe on cybersecurity. How will the control functions do their job? So we don't actually incur more risk? Every player has a game to play to actually capture the value. And let me give an example. I was doing work for an airline once and we had constructed, they had constructed.

 With our help, phenomenal technology to actually be able to do extra loading of the cargo space on passenger airlines. Basically, you may not show up for your flight. That gives me more space to put in cargo. That is a yield optimization problem that you can solve with ai. And so we said, beautiful.

This is working. We could see it on the analytics. And then we said, huh, the planes are not flying with the cargo that we said they were supposed to sell and fly with. Why is that? Then we show up at Heathrow airport. Guess what? The palletizing procedures were wrong.

They weren't palletizing wrong, they weren't able to maximize the actual palletizing procedure, so it doesn't matter how much good I do on ai. The operational procedures are not where they need to be. If I don't align the head of operations to say, we're gonna need to palletize with best practice, otherwise, doesn't matter what the AI does, then you don't get the value.

Another example, in banking. If you and I start to do more banking online, that's beautiful. Okay, great. That means I don't show up in the branches anymore. I should be able to reduce branch staffing. I should perhaps even be able to close down branches and reap the productivity benefit from the fact that they go online.

If the head of branches is not aligned with that, cuz the head of branches is probably saying, Hey, my job is to sell. I need all the people to sell. I need to keep my branch open. Don't tell me about your app. It doesn't work with me if you don't align them right at the top. In saying, Hey, I know we're gonna change your incentives because as the volume comes down in the branches, we gotta be able to take people out.

And so I'm not gonna incentivize you on sales anymore. I'll incentivize you of a more total optimization. It won't work. So this is why AI digital more than any other transformation is the ultimate corporate team sport. 

[00:08:55] Mahan Tavakoli: I love that, Eric. As you were giving the examples, especially on the banking one, because I have some experience there, I could relate very well to it, having seen initiatives fail. One of the main points that I got from reading your book, is that a lot of times organizations try to do digital.

They initiate a digital strategy as opposed to being digital. There needs to be a rethinking of how to be digital, not to initiate a digital strategy. Oh, yes. We have one of those as well.

[00:09:32] Eric Lamarre: Great point. And digital strategy is almost a dangerous word because the strategy is not digital or ai. These are. Things that will augment the effectiveness of our strategy. The strategy has to be about differentiation in your service or in your product, or in your unit costs.

And so it's coming in to actually accentuate your competitive differentiation. So it cannot be the strategy in and of itself, and that's why the starting point always has to be, what are you trying to do with your customers? What are you trying to do with your unit cost? And then at that point you can say, okay, if that's what you're trying to do, then this is where you could imagine technology coming in and making a difference and accelerating where you're trying to get to and making it even more effective.

So the starting point has to be clear strategically. Otherwise it's the chase for the use case. Here's a use case. Here's another use case. You don't like that one? What about that one? I got three of those. Would you like those instead? And it becomes, let's just chase use cases and we're forgetting why are we doing all of this?

There's a strategy here that we need to be supporting. That's what this stuff is supposed to be doing for us. 

[00:10:53] Mahan Tavakoli: Actually one of the things I'm saying, Eric, is most specifically over the past few months in terms of some ai implementation or strategies, that's exactly the approach people are taking.

Rather than thinking about what is the real use case, what is the customer impact that we want to have, they want to also have an AI initiative. So where in the organization can we implement ai? 

[00:11:20] Eric Lamarre: Yes. And section one of the book and there's a specific chapter, I think it's chapter three, on getting the bite size right.

So when you actually start, we recommend don't focus so much on the plethora of use cases that you could be chasing. Take a step back and organize your company in whatever is logical in a bank, it would be a long customer journey. So the journey for onboarding, the journey for buying a credit card, the journey for getting servicing and the contact center.

These are logical journeys and figure out what's wrong with them today. Why are they not serving the customer the way they should? Why are they too expensive on a unit cost basis? And then overlay technology to go solve these business problems. So don't start with, I got a shiny toy. Where can I use the toy?

Start with the business problem to be solved and back into technology solutions. Some of these solutions, maybe ai, some of them may not be, they may just be good old simple analytics. They may not even be technology mahan. They could be just a simple process fix. Or a fixed to your risk management processes or are fixed to something else.

So start with the business problem. Put your business hat on and say, I'm not just gonna be chasing tech for tech's sake. I'm going to be chasing the most effective lever to solve my business problem. And you will find out that some of them are quite technology intensive and AI intensive, but not all of them will be.

And I think that creates a more effective transformation roadmap at the end and gets you to more impact coming out of that. And so there is a danger. You are right in just chasing where can we shine the new toy? And that comes with a whole bunch of dangers.

[00:13:18] Mahan Tavakoli: And one of the challenges that I know you go into in the book as well, Eric, is the need to have. And build the right leadership team. I go back to the Jim Collins analogy of having the right people on the bus, and in many instances what I have seen is one person in the team at most is the tech person, c i o, or whoever else you want to call it, and the makeup of the leadership team doesn't enable it to do the kind of thinking that you are talking about.

How can organizations think about having the right leadership team with the skills needed to embark on this digital transformation? 

[00:14:03] Eric Lamarre: It is one of the most important aspect to eventually succeed. Any leadership team today, there are some exceptions of course, but most leadership team today, I have a set of leaders that have grown with a pattern recognition for how to drive the business that is not necessarily aligned with ai.

And with digital, they're aligned with a set of levers that they have pulled in the past that were not technology leavers. Leavers are good leavers and they're gonna continue to pull them. It can be levers around. Customer selection, it can be leavers around how to optimize deployment of a Salesforce.

It can be believers around how to optimize a production environment. Those are all good leavers. They're gonna continue to pull, but the pattern recognition for how could technology do even more is not there. So how do you build that pattern recognition? Because you're not gonna change your entire leadership team.

You're gonna keep them. So building that pattern recognition is what I call going slow to go fast. So going slow to go fast works like this. You take your top team, you level set their knowledge of technology and I call it out in the book, we call it out in the book, as being something around those six to 10 hours of investments to at least have a common mental model.

What is agile? What does the data engineer do? What is gen ai? Is that the same as the old ai? Is that different? What is data architecture? What is it used for? And it's not that complicated. Okay? So six to 10 hours, you level set, step one, step two, you go visit companies that have been ahead, that have done transformation on their own.

How did they approach it? What did they do? And you start to align people on, okay, that's how it works at these other companies. This is how we can do it here as well. And step three, You align on where you're going to start. And so if I take back my analogies of journey, are we gonna start in onboarding or are we gonna start in customer servicing or in credit card?

To continue with my bank analogy, what you don't wanna do is spread your investment too thin to please everybody, so everybody can get something. That's the wrong approach. Everybody gets something is the wrong approach because you will fall back in shiny toys. So you said no. We as a top team need to decide where strategically it's gonna make the biggest difference.

Guess what? It's onboarding. Great. We put all our eggs there in onboarding or in a couple of areas, and now we create the talent teams that are needed. We create the data environment that's needed to be successful. And it's not gonna take a long time. It's not like a five year journey here. In onboarding, it's gonna be 12 months, 24 months, you're gonna see material difference in the investment you're gonna make.

And when you're gonna decide it's onboarding, you're gonna do what we just talked about, which is, it's not just tech leavers. It can be something else. Be open to that. What's the problem back into that roadmap. And so those would be the three. Learn. Level set on basic language, learn from others and decide where you're gonna focus.

[00:17:21] Mahan Tavakoli: I love that. And part of what I see is initially that level setting not happening. Therefore, the understanding of the potential applications implications isn't there, and therefore it becomes a who gets the shiny toy, okay? Each one of you get a little shiny toy to play with. So that lack of initial understanding then contributes.

To what will end up resulting failure of the digital implementation and transformation. 

[00:17:51] Eric Lamarre: Yes, exactly. And so couple of questions maybe to test for if you're part of one of those management teams. Question number one that I love to toss in there. How is your digital transformation going? Watch who's answering the question?

If it's the head of it, who answers the question? Nothing wrong with the head of it, but you know that there hasn't been enough empowerment of the business. The business is not owning this, so that will be a failure mode. Second question is what you are working on going to make the performance in two or three or four quarters from now or not?

And if the answer is not, Then you know that no one in the C-suite is actually going to be rolling out of bed to drive that digital transformation because something else is more important. And question number three, and that one usually goes to the ceo. Which of the shiny do story that you have currently ongoing, you're gonna showcase at the investor meeting.

And if it's none, then you know it's shiny toys. And if he says that one or she says that one. You go, okay, maybe there's something there that is really gonna be material. So just some little, you'll have your own set of questions, but I like to toss those in to just reflect, basically play the mirror back.

For us, the top team, we need to be working on big things that we're aligned on and things are gonna be material to our performance in a year from now. 

[00:19:19] Mahan Tavakoli: Those are great questions to ask , as you said also to level set ourselves on whether these are real priorities or shiny toys we're playing with.

So you mentioned the business case, which is essential, the leadership team alignment. And then another thing that you mentioned in the book is the fact that the core of every digital transformation is people transformation. Yeah. And that's such big challenge that I've seen even when leadership teams are aligned around the business case, which is a lot of times not the case.

 Bringing the people along fails. So what are some of your thoughts with respect to what it takes to make it a people transformation along with the digital transformation? 

[00:20:03] Eric Lamarre: So there's a reason why it is section two in the book on talent, because after section one, which is where's the value and are we aligned, where are we gonna go after, the very first thing is not tech.

It's not data, it's people. And that's because when you got that next piece right, things tend to go well. It's easier to get that piece right when you have all line on where's the value and how we're gonna capture it. Because from there comes a pretty natural roadmap of what kind of talent we're gonna need to actually be able to realize this opportunity.

And so now talent is no longer. In a theoretical vacuum, it's actually anchored on a specific opportunity that you're gonna go after if you're just starting the journey. The talent equation is gonna be by the dozens, not hundreds, not thousands. And so by the dozens it becomes a feasible problem to address, and HR is gonna be at the table and HR will need to change their approach.

Recruiting digital talent. You gotta be faster. You gotta demonstrate that you are really committed to technology. You gotta be asking the right questions to get the right talent in. So there is a bit of a retooling of how HR manages that talent pool. But then, so HR is at the table. You know what you need by a few dozens, and then you get that mission going.

And after a few months, you may get a little bit of third party help to start with. But the point is that you want to have these people as part of your team over time. And so we say something in the book that has been quite important, at least in my approach to this, is you cannot outsource your way to digital excellence.

You need to own that bench. So while you may get a little bit of help, at some point you need to have those people in house. And we can go into, why that's fundamental. You build that bench, you will be able to build, a dozen, a few dozens, a hundred, a couple hundred, and then becomes a very important turning point, which is okay, I've been able to rescale selectively.

I've been able to hire on the outside, but now I need to move in the hundreds. I need to move into maybe even thousands if you're a large company, oh where am I gonna get those folks? And now you need to look at your IT and tech organization, and that organization now needs to be modernized. The skillset set that you had in there, which was appropriate for perhaps an IT environment of 10 years ago, also needs to progress.

And that becomes the next bigger surgery, which is how do I transform my IT organization to start to supply? The additional talent pool that I need because I need a data AI analytics everywhere in the company. 

[00:22:59] Mahan Tavakoli: Eric, in doing that, one of the challenges I've seen is a lot of times the immune system of the organization goes to work and The antibodies try to reject the new entrance in part because HR has had to make modifications, whether it is to compensation or flexibility practices in part because this is where the in investment is going.

So these are the golden girls and the golden boys who are coming in. So the antibody goes to work getting in the way of. These new entrants into the organization, what has been your experience and what are best practices in approaching it? So it becomes something that everyone is vested in making succeed rather than people making sure this doesn't succeed.

So they continue the way things were in the past? 

[00:23:53] Eric Lamarre: At the most senior level of your tech talent. Organization you need as a CEO and as a cfo and as a C H R O, you need to be protective of that talent that you're bringing in. You need to give them time to absorb the context of the company they're working in.

They're coming in with great digital talent, but they don't have the context. They don't know the problems to be solved. They may not understand your industry, they may not understand your customers. They may not understand your products, and so that requires a certain customization on theirs. They need to get they need to understand that, and that takes a little bit of time.

You also need to give them a chance to show you a little bit what their magic is about. And so put them to use, put them on a problem and be willing to learn on your side, what is it that they're bringing new to the organization? Protecting for a little bit of time. That doesn't mean everybody's perfect, that comes from the outside.

So of course you'll apply judgment. But sometimes that reaction from the organization tends to be quick, ah, we don't like this. We don't like this. And then you see the whole organ rejection at work. So the leadership team needs to offer a little bit that protection for some time.

Point number one And point number two, you have to be building careers for the technologies that are gonna be attractive. Attractive from a compensation standpoint, and attractive from the standing they have in the organization. And that takes us to creating that technology career path where I can continue to grow in my roles and in my compensation and in my stature in the company on the basis of the excellence of my craft, not on the basis of how many people report to me.

So it's the difference between a technical career and a managerial career. And if you don't build a technical career in the organization and HR has work to do to build that, then people will go. That's a, foundational aspects. Any good technologists will expect to be rewarded on the back of excellency in their craft.

And so those would be the two things. Mohan Establishing that protection for the first few years, at least giving them a chance and having career tracks that keeps them motivated and sends them the signal that you value craftsmanship in technology. 

[00:26:20] Mahan Tavakoli: Which is why it's the holistic approach that you also address.

This is being digital. This is fully part of the organization. It's not just an initiative. 

[00:26:30] Eric Lamarre: Correct. It becomes business as usual. And so the way we do strategy every year, there's not a digital strategy that runs on the side. There's a strategy that runs and we are embedding technology.

 Same old way we used to do strategy, but now we're embedding technology levers in it, how we do career tracks. Now we need to accommodate for that. It's not a special project. That's how we actually handle technologies in our company. So on and so forth. And that's eventually, how the culture changes.

But it cannot be special project mode all the time. It may start in a special project mode for six months, for 12 months, but you have to know that at some point it needs to become business as usual and it doesn't stop. We're gonna be doing this for the rest of our careers, not, it will stop after we're done with special project mode that gets forgotten and it takes us also to.

The operating model of all this, we know how it's gonna run in special project, how is it gonna run in business as usual? That's a bit the, section three in this book, which is how do we actually start to organize business technologists operations into a mode where everybody now can be productive using technology to help our customers and help our productivity.

 So 

[00:27:42] Mahan Tavakoli: it actually impacts that organizational structure. Yes. That needs to be set up for the digital transformation as well. 

[00:27:50] Eric Lamarre: It does. Absolutely. With the view that structure will evolve. It may start a little bit as a special project. At first, this big organization here, that special project digital stuff is starting, but soon.

There's gotta be a view that note, the goal here is to embed every aspects of our business with digital, with ai, with data and business leaders need to actually be pulling versus, let me call it it's no longer, let me call it, to get some technology stuff done. It's, ah, I have teams that know how to develop this stuff.

Report to me, head of supply chain or report to me head of sales, and I can guide them in developing solutions that are gonna make me better at selling or make me better at actually meeting my supply chain needs. And that is not so straightforward to do. And because now I have a responsibility for guiding the development of technology.

I'm not gonna write code, but I'm the one who's saying, these are the problems to solve. And I have learned enough that I know the kind of team that can solve a problem like this, and I know the goals that I'm gonna put for that team for the next three months or the three months after. And three months after.

So every manager is becoming a little bit of a product manager. They're able to guide that management effort, and that's when you are rewired when your business leaders across your different functions and businesses. No. The counter problems to be solved, how they're gonna get solved and guide that development effort.

When you have achieved that state, you're rewired. 

[00:29:36] Mahan Tavakoli: And for that rewiring, Erica, I was laughing because it requires giving up turf issues that exist in organizations and territorial issues. And I go back to your point about the transformation and the people is an essential part of it.

This requires a different thinking all throughout. 

[00:29:58] Eric Lamarre: It does. And it does call on a higher level of collaboration than in maybe the organizational construct that we have been used to in the past. In the past. If I can make things simple, that's my p and l, those are my resources, those are my objective.

This is what I'm going to deliver. And of course, there's nothing wrong with that because the accountability model in this is so strong. But in digital and ai, because you have that end-to-end effect that we spoke about earlier, which is, I may do digital here, but guess what? I have to reduce headcount in the branches there.

 That alignment requires a higher level of collaboration than is typically noted. Actually, that's an important tray that people recruit for the collaborativeness of folks and the ability to say, I'm working to optimize the greater good. You know what, my incentives may not be a hundred percent aligned, but I know what the greater good is, so I'm gonna go do what's right for the company.

So collaboration's a very important aspect of this. And the second one is everybody now has a role to play in technology, as we spoke about earlier. What it means now is I have to view my role as I'm finding the problems to be solved, and I'm actually willing to fund and guide development team.

So I'm putting my money where my mouth is as a head of sales. You know what? I would like three agile pods to come and work in my unit to develop technology to do this. I know the problems to put them on. I will guide them and I will fund them. I will fund them. To actually achieve a better sales performance.

And so now it's no longer it's freebies. Let's call in it. It's free until it's not anymore. No, actually the businesses, the functions, the leaders, this is where they, accountability comes in. You wanna do digital and ai? Great. You pay for it. And so now they're your pods. And of course they work within a construct that makes sense and we avoid duplication and all of that.

We can get into this, but at the end of the day, , I believe that this is where I should be deploying that lever. This is the return I think I'm gonna get, and that's the investment I'm willing to put in. When that flywheel starts to work different business leaders have that accountability for the performance of digital and ai.

Then the flywheel becomes a lot easier to turn. It's no longer a push. You're in a pull, they're pulling for it and you've set in the right conditions. But it has to start with prompt to solve how much is it worth solving that problem? What investment or why am I willing to put in, what resources will I need?

Who's gonna be accountable for that, how do we realign the people end 10? It's heavy work that we skip at the beginning because we're in so much of a rush to go do the shiny toy and to show an app. Because we think success is to show the app as quickly as possible. This is what the app can do.

Okay, how much money have we made? That's the final metric. Or how much happier is the customer versus, three months ago. That's the final metric. And those metrics don't move because you say ai. They move because people have been taught. And frankly, that's always been true in business. A good problem, a good plan, good resourcing a good business case.

That still is true with AI and digital. 

[00:33:25] Mahan Tavakoli: That's what, at least in my experience, is the contributor to some of those failed digital transformation initiatives of the past. In many instances, the end result has been the app or the product or whatever it is, the shiny toy, rather than the digital transformation.

Now, I imagine as what we are experiencing, Eric, all organizations need to go through. This digital transformation, but do you see certain industries, sectors, types of organizations where this is even a bigger urgency for them to consider going through the process? 

[00:34:04] Eric Lamarre: Yes. We run this survey instrument called digital coaching at McKinsey.

It's basically something like 60 questions that get asked to measure maturity level in digital. And we've been running this now for. Seven, eight years. So we have a decent data set. We can clearly see industries. You can see public sector is still in the very, very early stage of that.

You can see banks, much more advanced but what's interesting is within a given industry, take consumer package goods, you take banking, you will find a very widespread. So yes, on average industries position themselves on a maturity curve, but within an industry we see very wide spreads.

And so the question is, does it matter if I'm late, if I'm a laggard? Does it really matter at the end of the day? Because frankly, 10 years ago we used to hear, I want to invest less in technology because it's proven and it's cheaper. So maybe that's still true today. So here's what we did. Here's what's interesting.

This is gonna come out, I think next week in Harvard. Business review. We took banking. Banking has been at this for 10 years, and so we have a pretty decent data set by now, and it happens that we benchmark 80 banks around the world. On very detailed, granular benchmarking. So how many people are using the app?

How much are their sales online? How many people they have in their contact center? How many branches do they have? How many people in the branches do they have 50 parameters like this? They give it to us every year on a very normalized benchmark. And then we know their financial performance of course.

And so we have that for the last five years. Every year we take that group of 80, we split them 20 top quartile digital. 20 bottom quarter are digital, so you know, digital being adoption of the app, how many of their sales are online. And so now we track these two groups over time, over five years. Guess what?

The digital leaders in that group, those that have higher level of adoption of the app by their customers, but also much higher sales online, lower people in their contact centers because they've been better at call deflection. Lower number of people in their branches because they've had that integrated problem that we talked about earlier.

Guess what? Total return to shareholders growth productivity, number of new customers. The metrics are all very differentiated for the leaders. Not marginal, substantially different. Here's what I'm concluding from this. Oh, one more interesting fact. If you take the leaders over these five years, none of them become laggers.

Sometimes they fall in the middle. They don't become laggers. And if you look at the laggers, none of them become leaders in that five year journey. They improve. They can be in the middle, but they don't change position. It's persistent. I think the game is starting to be played in retail banking. If you are sitting in the laggard category.

And you are not making massive changes now to get yourself out of that box, the game will be played out. That's not true in all industries. Some are way back. The game is not played out. But in the industries where the game has been played for a decade already, it is starting to be played out. Why?

Because rewired capabilities are hard to build, but they're also hard to copy. And so everything we've been talking about, leadership that leads new talent. We haven't even spoken about data and all of these other things, but all of these capabilities are hard to build. But once you have them every day, everywhere in all aspects of your businesses, you have a little bit better.

You don't see it in a month. You may not see it in a quarter, but over five years you see it. And that's what we saw in banking and that performance trajectory is just. Total return to shareholders almost twice as good for the leaders than the laggers. And so yes, if you lead, you get rewarded. And if you lead, it's actually starting to create some distance and it's hard to catch up that distance.

[00:38:25] Mahan Tavakoli: That's outstanding data, Eric. And it goes to the point of the flywheel effect in this digital transformation as well, where those. Small contributors over months and years at the beginning in an industry, people might not see that much of a difference, but that flywheel takes place and then it's almost impossible to catch up for the other organizations.

[00:38:53] Eric Lamarre: That's exactly right. That's where I'm at as well. When I look at the data, which is the flywheel momentum. It is starting to take a hold. It takes a little bit of time to turn. It's not overnight. It's not, oh, we're gonna do this for a year, and then, we're gonna be good. No, it takes time to build, but when it's building, it's really hard to replicate and catch up with.

[00:39:12] Mahan Tavakoli: The good news is the framework for the flywheel is right here in the book rewired. You've done an outstanding job with your co-authors both documenting the entire process. Great visuals, great. Data supporting how leaders can approach this before finding out more on how the audience can connect with you and find out about the book.

Would love to know. Eric, you work with CEOs and leadership teams in addition to. Your book and work with McKinsey, are there certain resources or practices you recommend to them in order for them to become more capable at leading this digital transformation? Yes, 

[00:40:01] Eric Lamarre: so there's certainly a few that I would recommend.

So one is this notion of visiting others and learning from others I think is very important. I don't know exactly what's the right frequency getting on a plane and going and spending, I did that with a client recently. The co, took the entire team and went to Seattle for three days.

And visited some big tech and visited some startup and visited some companies that had been down their journey for some time, even if it's not in their industry, preferably if it's not in their industry, and listen to their stories. And take stock and talk as a management team, at dinner in the evening and start to immerse yourself into this.

 All these executives are smart people. If you actually start to build their patent recognition, they have the context for the company. They know the problems to be solved, they will be able to start to project back. That is probably. The most important investment to make as a management team.

And so get your top team exposed to what others are doing and then decide what you're gonna do. 

[00:41:06] Mahan Tavakoli: Outstanding. I talked to the c m O of chick-Fil-A from early on until a few years back and one of the first things that they did was to benchmark b m w Benchmark Amazon organizations like that for their operations at Chick-fil-A.

So part of what you are saying is that it's not necessarily a bank going to another bank, there are a whole host of issues. No. With respect to that, you can learn from the best in other industries. 

[00:41:34] Eric Lamarre: Exactly and a lot of what we're talking about in this book is industry agnostic, how you recruit a data engineer and build a career for data engineer.

That is true in tech, as it is in banking, as it in consumer. Packaged good is the same thing. How you prioritize the domains and where you gonna go. That approach is the same. Of course, the domains are different, the journeys are different, but. The approach is the same. And so visiting other companies, especially in other industries, is particularly good.

And it's interesting if you read some of the last cases the one I was inspired with I got inspired by all three that are there, but the one on d b s bank the case that's written up, I think it's chapter 33 or 34, I forget. Takes you on a 10 year journey that DBS has been on at the very beginning of their journey.

They go and they decide they're gonna visit Big Tech. And so they visit Google and Netflix and LinkedIn and Apples and the Amazons and then they get back home and they said, ah, we gotta be a lot more like a tech company cuz that's the banking of the future. And so they have this new motto

they said Gandalf become their new rallying cry because, Gandalf is Google and Apple and Netflix, except for the D. The D is d b s, they want to be like a tech company. And Gandalf is gonna be the new approach. And they got totally inspired by how software gets developed.

And people will get inspired by other stories, but for them it was the stories of the tech companies. Some companies don't like that. They prefer to be inspired by, different peers, but in any case, the fundamental of visiting and opening up your eyes and learning and your language and new way of seeing things that's a small investment.

It's not a big investment. And frankly, you could always say at the end of it, you know what, that's not for us. At least you would've given it a fair shot. 

[00:43:30] Mahan Tavakoli: I love that. And I would urge people not to say it's not for us because the smartest ideas jump industries they are for you. Find ways that they are for you now, Eric, how can the audience find out more about your book and follow your work?

[00:43:48] Eric Lamarre: So the book is out on Amazon and bars and nobles. And it can be found in Bookstores of course, and purchased online. We publish a huge amount at McKinsey. So on mckinsey.com, you take any of the topic of interest. For example, you take Gen ai, you wanna find out more about Gen ai, like many others.

We've published a huge amount. I think there's a richness. On mckinsey.com. And then, at some point if anybody was to say, Hey, you know what, we'd like to engage a bit more with a professional that's been down this path, I'm here for you.

The two co-authors are here for you as well. And of course we'll make ourself available. But there's a lot out there to consult and what I'm hoping the book will do is, Have in one place, in one coherent framework with one coherent language, with the holistic approach, the whole story told, versus I need to read 200 different articles.

And then after that I'm still confused because everybody's been using a different language, a different framework. So it should be a good foundational aspects, hopefully. 

[00:44:51] Mahan Tavakoli: It really is, and you do a beautiful job in the book, as I mentioned, taking everyone through the entire journey and entire cycle.

 It's a comprehensive look add what it takes to lead the organization through this digital transformation. And we were chatting before we started recording the conversation. I do encourage and obviously podcast listeners are people who like learning.

I do encourage all of the listeners and the CEOs that I interact and work with. It is essential. We are living through the speed of the exponential curve of many of these technologies that will transform how we live and our organizations. And it is our responsibility and opportunity as leaders to lead our organizations forward.

So this book, does an outstanding job with respect to that. I loved the wording on the inside cover jacket how companies navigate the technology world to achieve competitive advantage is the defining business challenge of our time.

It's not a simple journey. As one c e o said, we can find digital everywhere in our company, but the bottom line for digital and AI to deliver on its potential executives need to be ready and willing to undertake the organizational surgery required to become a digitally capable enterprise. Thank you so much.

Eric Lamar for the guidebook in helping leaders take on this surgery and leading their organizations to the digital transformation of the future. Thank you so much for the conversation, Eric 

[00:46:37] Eric Lamarre: Mahan, it's been fantastic to be with you during this hour and thank you for the time.