Where McKinsey—and Consulting—Go From Here

Summary

HBR IdeaCast – Where McKinsey—and Consulting—Go From Here

Date: January 6, 2026
Host: Adi Ignatius (A), Alison Beard (B)
Guest: Bob Sternfels (C), Global Managing Partner at McKinsey & Company

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Overview

This episode explores the transformation of management consulting in the age of AI, with a special focus on how McKinsey & Company is evolving as it celebrates its 100th anniversary. Host Adi Ignatius interviews McKinsey's global managing partner, Bob Sternfels, covering the firm’s legacy, the impact of AI, changing consulting skillsets, dealing with reputational crises, and what the next decade at McKinsey may look like.

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Key Discussion Points & Insights

1. McKinsey’s 100-Year Legacy: Creation vs. Best Practices

• Co-Creation as a Model:
  Bob frames McKinsey’s work as a co-creation partnership with clients, involving both novel innovation and global best practice sharing.

  “Maybe the way we frame is we're co-creating with clients to help them come up with things that they may not have come up with themselves…” (03:01)

• Investment in Thought Leadership:
  Significant investments in proprietary IP and institutes (e.g., McKinsey Global Institute, McKinsey Health Institute) exemplify a commitment to novel thinking, not just best practices.

2. AI and Consulting’s Business Model

• AI Shifts Both Client Solutions and Internal Operations:
  AI is driving monumental changes inside McKinsey and for its clients, requiring rewiring of both.

  “There's a unique moment to help all our clients reimagine themselves leveraging this technology. And to be able to do that, we have to rewire ourselves.” (05:17)

• Economic & Organizational Change:

  “What we're finding is half, if not more of the secret sauce is organizational change as opposed to technology implementation.” (07:06) Using AI as an impetus for organizational flattening and cross-departmental work.

• Growing Role of AI Agents:
  McKinsey’s workforce includes 20,000 AI agents alongside 40,000 humans—up from 3,000 agents 18 months ago.

  “I now update this almost every month, but my latest answer to you would be 60,000. But it's 40,000 humans and 20,000 agents.” (08:46)

• Shift Toward Outcomes-Based Consulting:
  The traditional fee-for-service advisory model is being replaced by outcome-based partnerships.

  “It's moving to much more of an outcomes-based model where we say…we will underwrite the outcomes of that business case.” (09:25)

3. Evolving Skills: What Makes a Modern Consultant?

• Shift in Talent Assessment:
  Analytics revealed overemphasis on credentials, not enough focus on resilience, teamwork, or learning agility.

  “We were too focused on did you have perfect marks versus did you have a setback and recover?” (13:03)
  "The applicant who had a setback and recovered was more resilient and more likely to be a higher probability of making partner in McKinsey." (13:13)

• Emphasis on Liberal Arts and Creativity:
  AI’s limitations (judgment, creativity, aspiration-setting) are ironic drivers for the resurgence of liberal arts profiles.

  “We're going back to liberal arts degrees and kind of saying, hey, let's come back to some of the things that might have been deprioritized in the past to see if we can get a little bit more creativity.” (15:57)

• Key Skills for the Future:
  • Resilience
  • Teamwork
  • Ability to learn
  • Leadership (setting aspiration)
  • Judgment
  • Creative, discontinuous thinking

4. Addressing Scandals and Public Image

• Learning from Failures:
  Humility and courage are both necessary: learning from mistakes (e.g., opioid crisis, South Africa controversies) while sometimes courageously pushing back on misperceptions.

  “Some of the ones that you mentioned fall clearly in the humble camp…. what we learned is that we have to have a higher diligence around client selection.” (18:43)

• Stronger Compliance & Risk Oversight:
  McKinsey invested heavily in compliance staff and systems, borrowing leadership from companies like Apple and Walmart, aiming to meet or exceed public company standards.

  “We invested about a billion dollars. I brought in the head of internal audit from Apple, the head of compliance from Walmart, to basically kind of modernize us.” (19:31)

• Maintaining Integrity:
  Controls and compliance considered necessary for preserving the firm’s professional ethos.

  “It's painful for a partnership to give up some of that autonomy, but I think… it's worth giving up that autonomy to actually preserve the integrity of the enterprise.” (23:06)

• Pushing Back on Reputation Issues:
  McKinsey is willing to disagree publicly about work in controversial sectors when aligned with their principles.

  “If you're going to be committed to climate transition, you have to work with the hardest to abate sectors.” (21:41)

5. From PowerPoint to Impact: Shifting Client Value

• Beyond Presentations:
  Aim to tie McKinsey’s compensation to the long-term outcomes, not just advice.

  “We’re on a change journey of moving, quite frankly, from a model that was advisory to one that underwrites outcomes.” (24:19)

6. Where Leaders Go Wrong and Future Management Paradigms

• Common Leadership Missteps:
  • Overconfidence and stasis
  • Lack of information-seeking from all levels
  • Failure to collaborate
  • Insufficient speed in decision-making

  “Whenever you get too confident, too overconfident, I think change for the negative is going to come...faster organizations outperform slower organizations.” (25:24, 26:39)

• Paradigm Shifts for Today’s Environment:
  • Navigating AI and technology transformation
  • Building institutional resilience (“playing offense and defense at the same time”)
  • Rethinking organizational structures, especially the matrix model

  “There’s going to be a world of continuous shocks. And so in a world of continuous shocks, do I have enough institutional resilience…?” (27:37)

7. McKinsey’s Aspiration for the Next Decade

• Leadership Factory:
  Continuing to develop leaders who go on to make an impact elsewhere.

  “We produce more CEOs than any other institution in the world. And I hope that's still the case in 10 years.” (30:26)

• From Advisor to Impact Partner:
  Becoming known for co-owning and achieving outcomes with clients, not just for giving advice.

  “We designed a business case together, and these guys underwrote the same outcomes that I took to the board. And we went on this journey and we kept at it until we got to someplace I didn't think I could get to.” (31:25)

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Notable Quotes & Moments

• On adapting to AI internally:

  "I originally thought it was going to take us to 2030 to get to one agent per human. I think we're going to be there in 18 months." — Bob Sternfels (08:53)

• On hiring for resilience:

  “It turned out we had some bias in our system...the applicant who had a setback and recovered was more likely to be a higher probability of making partner in McKinsey.” — Bob Sternfels (13:13)

• On liberal arts:

  “We’re going back to liberal arts degrees and kind of saying, hey, let's come back to some of the things that might have been deprioritized in the past.” — Bob Sternfels (15:57)

• On addressing high-profile controversies:

  “I brought in the head of internal audit from Apple, the head of compliance from Walmart, to basically kind of modernize us around these processes.” — Bob Sternfels (19:31)

• On the future of consulting:

  “We're on a change journey of moving, quite frankly, from a model that was advisory to one that underwrites outcomes.” — Bob Sternfels (24:19)

• On speed in organizations:

  “Faster organizations outperform slower organizations, even if they make more mistakes.” — Bob Sternfels (26:40)

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Timestamps for Major Segments

• [03:01] McKinsey’s methods—co-creation, innovation, global best practices
• [05:17] Internal impact and opportunities of AI
• [08:46] Rise of AI agents at McKinsey; productivity and workforce evolution
• [09:25] Shift to outcomes-based consulting
• [11:28] Changing consultant skill profiles and talent analytics overhaul
• [15:57] The resurgence of creativity and liberal arts backgrounds
• [18:26] Addressing high-profile ethical and reputational crises
• [21:26] Firm growth, compliance, and preserving professional ethos
• [24:15] From PowerPoint to impact: ensuring lasting client value
• [25:24] What leaders get wrong—learning, collaboration, and speed
• [27:10] Institutional resilience and future organizational models
• [30:09] McKinsey’s aspirational future

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Summary Table: Evolution of Consulting at McKinsey

| Aspect | Past Model | Present/Future Model | |--------------------------|-------------------|---------------------------------------------| | Service Focus | Advisory, best practices | Impact co-creation, outcomes-based | | Workforce | Elite, credentialed, often technical | Diverse, resilient, creative, adaptive | | Use of AI | Minimal | Integrated, both client-facing and internal | | Engagement Structure | Fee-for-service | Joint business cases, risk-sharing | | Ethics Compliance | Traditional partnership model | Public-company standards, robust oversight| | Leadership Development | Implicit outcome | Explicit mission (“leadership factory”) | | Thought Leadership | Proprietary IP | Broader, cross-disciplinary, creative |

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Conclusion

This episode delivers a dynamic look at the pressures and opportunities facing management consulting, particularly for firms as large and influential as McKinsey. AI is not just automating work—it’s reshaping the very skills, models, and mindsets required to stay relevant. Sternfels is candid about mistakes and proactive about changing both internal culture and business practices, with a clear focus on resilience, creativity, and partnership for impact. Listeners are left with a sense that consulting’s future will look very different—and uniquely human—despite, and perhaps because of, the rise of powerful AI.

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Transcript

[A]

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[B]

I'm adi ignatius.

[A]

I'm alison beard and this is the hbr ideacast.

[B]

All right, Allison, this question is going to seem random, but I promise you it's not. What was your major in college?

[A]

I was a double major in journalism and politics at Washington and Lee University.

[B]

Okay. I was history at Haverford, another liberal arts college. If you're like me, you probably figured that your majors equipped you well for something like journalism, but maybe not so well for something like management consulting, which has tended to recruit people who studied economics or engineering, you know, or business.

[A]

Yeah, I always thought of consulting and finance as the place where sort of all the most ambitious, highest achievers, most capitalistic students wanted to go. And those firms definitely focused on the Ivy League and the big universe space.

[B]

The world is changing. We know that AI is remaking everything, including the world of management. And my guest today, McKinsey's global managing partner, has a lot to say about how it is rethinking its business in this era. So McKinsey already views its first AI agents as very much part of its workforce and is rapidly expanding that part of its team. But while AI is really good at linear problem solving, it's not so good at out of the box thinking. Which means McKinsey is rethinking its talent needs. I'm not going to spoil it, but your journalism politics double major might line up well with what the consulting giant is increasingly looking for. So here's my interview with Bob Sternfels, global managing partner at McKinsey, which is celebrating its 100th anniversary this year. So I want to start. McKinsey is turning, maybe has turned 100 HBR. By the way, we're 103, so welcome to the Century Club. How would you summarize the company's 100 year legacy? To what extent has McKinsey created the ideas that have shaped the business world? Or to what extent is it about identifying and suggesting best practices that come from elsewhere?

[C]

I guess I would start with the nature of how we do our work. And the idea is, look, we co create with our clients and when we're at our best, it is figuring out how do we help clients get to places they can't get to themselves. The whole notion in some ways of credit of did you create something novel or did you best practice? Maybe the way we frame is we're co creating with clients to help them come up with things that they may not have come up with themselves or we might not have come up with themselves. And we clearly invest a boatload in proprietary ip. We invest over a billion dollars a year in innovation. New thought, new ideas. Our McKinsey Global Institute, for example, which is a bit of our independent research tank, but We've now created McKinsey Health Institute. I think if you do look at their history, a lot of that is novel thinking. You know, the most recent looking at a global balance sheet and kind of saying how's the world? When you look at assets and liabilities, that's not a best practice, that's new thought. But equally part of the reason we stay global as an operating model is then at the more micro levels, the clients that we serve don't want to understand what the leading edge innovation is in their particular country. They want to understand innovation around the world and perhaps even cross sector. And that is part of our model. So I'd probably say it's, if I had to guess, it's probably half, half on this around where are there truly novel co creation and where is this idea of figuring out how do you bring innovation around the world to clients who may not have access to that innovation based on their, you know, the reality that they're in?

[B]

So one area of innovation obviously is AI and I'm sure you're advising companies all the time on how to adapt to an AI driven world. I want to talk about that, but I' interested in the internal discussions that are happening at McKinsey about this. To what extent is AI shifting the economics of your industry? Headcount pricing, productivity, are margins improving? Are they under stress? What are the internal conversations about AI for your business?

[C]

AI? We haven't talked about that at all. No, I'm just.

[B]

We should. It's really cool.

[C]

I mean it's hard to have a conversation in any context right now that doesn't link back to some form of AI. You know, I think this question around AI and how it impacts McKinsey, there's kind of two sides of that coin. There's a client facing side and then there's a what are the implications on McKinsey There's a unique moment to help all of our clients reimagine themselves leveraging this technology. And to be able to do that, we have to rewire ourselves to be able to deliver that. I may adi just start with a bit of what I'm actually hearing from clients around the world, across all industries and across all geographies. And I really hear in the truth room maybe two things. On the one hand, an enormous belief in the potential for this wave of technological change. And that's everything from enormous productivity gains in areas like customer care or, you know, back office processes, but also to growth things. You know, if you think about radically shortening the time of drug discovery and what that actually means for longevity and life, and that's top line growth. So folks are excited and they're believers, but at the same time, from the conversations that I have with CEOs, you know, they'll often say, hey Bob, so do I listen to my CFO or my CIO right now? You know, my CFO is in my ear that we're spending a lot of money on technology, but we're not yet seeing enterprise level value from this. And so do we really need to be at the cutting edge or why can't we be a fast follower, let other folks figure out where this is and then we'll adopt quickly because it's a lot more efficient to be a follower than a, than a leader. CIO's saying, are you crazy? This is one of those moments and if we're not in the lead, we're going to get disrupted. You know, we've spent a lot of time looking at at least what we think the answer is here. And I know we spend a lot of time talking about technology, but what we're finding is half, if not more of the secret sauce is organizational change as opposed to technology implementation. This is for large, large enterprise. And you know, it's things like, well, what does your look like after you're implementing these? Could you have, for example, a much flatter organization that cuts out a lot of middle layers and makes your organization faster? When you think about really complicated workflows, think about a mortgage process. You got all these steps, you know, origination, credit scoring, collection, after service, etc. Those are all departments in a bank. Well, why do you have four or five departments in a process? If you can really enable this through AI, can't you break those walls down? And so we're spending a lot of time thinking through not only what's the strategy and how do you implement, but how do you change the organization, how do you Rewire the organization to realize the value. And if you can get that right, all of a sudden the CFO and the CIO are actually on the same page. But we're finding that's harder and it's taking longer than people thought. And so I do think we're going to be in this period where really, enterprise fundamentally changing themselves. Yes, enormous potential. It's going to take a little while to get there. So then you kind of say, okay, what does that mean for McKinsey? We're applying this to ourselves. I often get asked, how big is McKinsey? How many people do you employ? I now update this almost every month, but my latest answer to you would be 60,000. But it's 40,000 humans and 20,000 agents. Little over a year and a half ago, that was 3,000 agents. And I originally thought it was going to take us to 20, 30 to get to one agent per human. I think we're going to be there in 18 months and we'll have every employee enabled by at least one or more agents. That's kind of one piece of what are the assets and technologies that we're building in ourselves. The other big piece is how does it change our model? We're coming around to the conviction that we're migrating pretty quickly away from, call it pure advisory work, which was a lot of the origins of our firm and kind of a fee for service model, et cetera. And what's it moving to? It's moving to much more of an outcomes based model where we say, look, let's identify a joint business case together and we will underwrite the outcomes of that business case. And it aligns our interests with our clients a lot more and I think will be the way of the future now.

[B]

I mean, AI is going to get better, right? We're still in the early phases of generative AI. If technology can continue to commoditize even the kinds of analysis and insight that a McKinsey has long provided, what will clients actually be paying for when they could probably do a lot of that themselves?

[C]

The kind of problems that we have tackled with our clients over 100 years has not been static. It has changed radically. I'm now considered a dinosaur in our firm because I'm a little over 30 years with us. But the stuff that I did when I joined as an associate 32 years ago, we wouldn't consider even doing right now. Why? Because clients do that stuff themselves. And we are solving much more complicated, interconnected questions with our clients. And I think what this is going to then mean is this is just going to be that next evolution of there'll be a whole bunch of things that a couple years ago we did for our clients that our clients will do for themselves. And the imperative will then be to move to the even more complicated questions. And to your point, what are clients going to pay us for? They're going to play us to find ways to double their market cap. And until we get to CEOs who say, I don't want to double my market cap, I think there'll always be a more complicated set of questions and opportunities out there.

[B]

What is the evolving skills profile then of a management consultant? Do you even know yet? I mean, what are you looking for in new hires? And that must be evolving pretty quickly.

[C]

I might frame it in what are some things we're confident about now and then what are some things we're exploring? When I came into this role, and it was a little over four years ago, I asked our talent attraction team how we doing on attracting talent? And I got a, we're doing great, Bob, we're doing great. I said, why? And so, well, you know, we, we get over a million applications a year and we, we hire anywhere between 8 and 10,000 people. And, and even the million aren't a normal distribution, right? It's, there's some of the brightest minds in the world that are applying so effectively. What's the problem? Why are you asking me? Let me, let me go back and do my job. And I kind of kept asking the question, but, well, how many profiles are we really looking for? What are we systematically screening out? And, and it turned out that really, when you boiled it down worldwide, there was only 500 pathways that would lead you to McKinsey. And that wasn't tying with what our own organizational research was saying, that the half life on skills was getting shorter, that people were too focused on paper sealing because you have the right credentials. And so we, we actually applied analytics on ourselves and took the last 20 years of data and said, what are the skills and characteristics that are most likely to make partner in McKinsey? Because that's, it's not perfect, but it's kind of a marker of success. You know, only one in six hires make partner. And it turned out we had some bias in our system. We had like 50 different implications. But I'll give you the biggest three. One was that we were too focused on did you have perfect marks versus did you have a setback and recover? And the applicant who had a setback and recovered was more resilient and more likely to be a higher probability of making partner in McKinsey. And we weren't screening for that. So we've changed the process to look for resilience in the application process. You know, it may sound shocking, but we weren't indexing enough on had you had real experience in a significant way working with others. You know, fundamentally we're about helping our clients change. And if you'd done a team sport or if you've worked in retail, you know, working your way through college, you've had to engage with others. And it's built a skill, human to human skill that we're now indexing a lot more on. And, and then the last one was, did you have the aptitude to learn new stuff versus had you mastered the subject that you chose to study? My youngest guy used this one against me, actually, when he was changing his major for the third time. And I was a little frustrated with him. And he's like, but dad, you published a paper that said, you know, if you have the aptitude to learn new stuff. And I'm like, yeah, but you have to do well in the subject that you go to.

[B]

This kid's smart. Yeah, well, send his resume to me.

[C]

It's the only time he quoted me.

[B]

I'm like, really?

[C]

But it did get us to then change our assessment techniques where we purposely create an environment where no human in the world will have any pattern recognition in this environment, and we figure out, how well do you do in an environment where you have no pattern recognition? You just have to go figure things out. So those are some of the skills now we know we're moving to. We've launched more of an exploratory look. Now, going forward, where you say, okay, but if everyone gets superhuman with these AI tools, what do you want to add on top of this? Resilience, teamwork, ability to learn new stuff. That part I just told you I feel pretty solid about, this part I'm going to tell you, is places we're more in exploration mode. One of them is, well, what do the models not do? Well, they don't aspire. They're not good at setting the right aspiration level. When you think about what great leaders do, they help an organization set the right ask, what should we aspire to? And so how do we start to look for and develop the skills of leadership? Leadership is going to be durable in a post AI world because one of the great things leaders do is they help set an aspiration and get people to stretch. The second is judgment. And you've seen time and time again these models, there's not truth in the model, there's not judgment in the model. Humans need to impose those parameters. So how do you build judgment and how do you build that capability? And then maybe the last one we're spending a lot of time on is the models are inference models. They're great at a linear approach to problem solving, which is kind of what we've been teaching for the last hundred years. What they're not great as discontinuous leaps, truly novel thinking. And so we're starting to figure out where are backgrounds that are going to be more creative to come up with things that aren't about the next logical step but are about a discontinuity. And so we're going back to liberal arts degrees and kind of saying, hey, let's come back to some of the things that might have been deprioritized in the past to see if we can get a little bit more creativity.

[B]

Yeah, we had a piece from the chief technology officer of Goldman Sachs who had wanted his child to be a coder and then thought, nope, I think she should be a philosophy major. That that's kind of what this world calls for, maybe.

[C]

Right? You.

[A]

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[B]

You know, we sort of looked back, we've looked forward. You've talked about the some of the celebratory stuff that's going on. I need to ask though, you've also had, you know, your share of unwelcome publicity in recent years. And I'm talking about OxyContin bribery charges in South Africa, conflict of interest accusations in the US and elsewhere. How do you account for all of that? How do you look at what happened and why?

[C]

Well, I'm glad you asked. And, you know, this has been. I think it's been a real soul searching for us starting about four or five years ago of really two questions. I On the one hand, where should we be more humble and learn from our mistakes? And at the same time, where should we be more courageous and just say, look, we disagree with you, and even though we'll face criticism, we're going to push back because that's what we believe in. And let me kind of parse each of those. You know, some of the ones that you mentioned fall clearly in the humble camp. And I think some of the great learnings that we had, if I just take two in particular, opioids, the work with opioids and our partnerships in South Africa, you know, what we learned is that we have to have a higher diligence around client selection. And we've put in place a framework that is a really robust assessment now that looks across every aspect from the country, the topic, the institution, the individuals, and the operating environment to say, is this a client that we actually want to bring in to the firm? And so one of the languages that I've used with our partners, and, you know, it's hard to drive change in a partnership, is you all grew up with the idea that one of the privileges of a partner, partner is to commit the firm. And I'm not saying that's not the case anymore, but you don't do it alone. You do it with risk professionals. And, and we invested about a billion dollars. I brought in the head of internal audit from Apple, the head of compliance from Walmart, to basically kind of modernize us around these processes. And that's why I also said, look, we apologize, we got those wrong. And. But we don't want to set out just to remediate the problem. We want to set out to try and set the standard for professionalism for our industry. So I think that is an important lesson of how do you learn from your mistakes, stay humble, but not seek to just repair them, but seek to actually make yourself better.

[B]

Yeah.

[C]

And we've had a lot of learnings around that. McKinsey has learned a ton from this, and we're setting out to make ourselves better. And one of the things that I've tried to open myself up to, both to regulators and to clients, is, look, these are the new protocols we put in place. Do you have any ideas on how we can make them better? Because even what we've put in place, I'm not sure we're ever going to be done on this front. So I just wanted to close the loop on that. Like, I'm obsessed with we got to be a journey to try and aspire to set the standard for professionalism, the lifeblood of what we do. And it's why so many great talent from around the world come is the kind of impact that they can have with clients.

[B]

I mean, from the outside, you know, it looked like McKinsey was committed to growing as quickly as possible in markets all over the world. By design, relatively little centralized oversight, and again, from the outside, that sounds like a recipe for trouble. Is that a fair analysis?

[C]

No, not really. It's easy to kind of say that from the outside, but, you know, the truth of the matter is you have three or four forces that are going on here. You know, on the one hand, there's an increasing scrutiny on the side of media, governments, for all institutions. And so one of the things that we learned through this process is there are some things that we're going to be criticized for that we're just going to push back on. We got heavily criticized for our work in hard to abate sectors on their transition issues. And it was McKinsey's accelerating climate change degradation, et cetera. And we pushed back and said, no, look, if you're going to be committed to climate transition, you have to work with the hardest to abate sectors. It's just naive to say that you're going to solve this problem without that. So there's a portion of this that was rooted in just more transparency, more criticism. And I'm trying to build a bit of thicker skin. There's a portion which was an evolution in our organization model that said, look, as we do get bigger and as the world gets more complicated and more requirements are thrown in, we do need tighter compliance standards. This is where the idea that we should have the same compliance and accountability standards as a publicly traded company, even though we're not publicly traded, was, I think, one of the greatest changes that we've been through in the last six years. And growth has never been our objective function. We're privately traded, we don't have quarterly earnings. You don't see McKinsey talking about, oh, we had revenue growth of this or that, because the ethos internally is that we're a profession, not a business, meaning that we want to put our clients interests ahead of ourselves. And the objective should Be are we doing distinctive work versus, you know, any kind of work, but without the right controls, you can't guarantee that. And so one of the things I think we learned is even though we had that as our ethos and the objective function was never grow at all costs, if you don't put in place compliance, you're not going to actually be able to enforce those standards. It's painful for a partnership to give up some of that autonomy, but I think it's one that we now have Pretty Amelia, you never get 100% uniformity in a partnership, but I think there's pretty good agreement that these things have made us better. And it's worth giving up that autonomy to actually preserve the integrity of the enterprise.

[B]

People would say consultants prescribe frameworks but don't have to live with the consequences. How do you ensure that McKinsey's advice is more than a PowerPoint strategy? You know, that it creates real lasting, long term impact.

[C]

I hope we get out of PowerPoint entirely at someday, and I say that with love to Microsoft. But it's, it isn't about providing a unique insight. It goes back to this notion of what we really aspire to be is to be impact partners with our clients. We're on a change journey of moving, quite frankly, from a model that was advisory to one that underwrites outcomes. And today, Adi, about a third of our revenues total are underwriting outcomes. So it's not, hey, you handed me a PowerPoint great. It's we collectively signed up for this outcome together, and we're tied on this journey all the way through until that impact is delivered. My hope is that that crosses a majority of the revenues by the time I'm done being the global managing partner.

[B]

We've been around 100 years, you've been around 100 years. We're all presenting important ideas. There are others as well. And yet this is hard, right? Running a business is hard. Nobody really has cracked the code forever. Where do you think leaders most consistently get things wrong?

[C]

I think there is some mix of a couple things that are, at least in my mind, increasingly important. You know, one is this hunger and thirst to acquire new information. And whenever you get too confident, too overconfident, I think change for the negative is going to come. And so how do you have this almost ruthless quest for let me continue to question new things and maybe also from all levels in the organization, often the best ideas are embedded somewhere, lowered out the second. And Adi, you kind of linked it when you talked about both of our organizations. Is how much do you do this yourself versus do you think about partnerships? And I think increasingly we're seeing when people collaborate across the value chain, et cetera, you find disproportionate gain. And yet our organizations aren't geared to collaborate well. Right. We're just not. And so thirst for new focus on collaboration. And then finally, I would say, and maybe this is kind of a sign of the times, maybe not speed matters. You know, one of the things that we've studied to death is faster organizations outperform slower organizations, even if they make more mistakes. And yet we're not wired to do that. There's such risk aversion in large enterprise. If we could lean in a bit more to that, I think great things happen.

[B]

So on the issue of management, what seems to be fundamentally different today versus how companies have to adapt to jolts in geopolitics or with technology, what are you seeing in terms of new management paradigms that are taking shape today?

[C]

I kind of look at it from the lens of the discussions that I have, which is what are CEOs focused on? What are some big topics right now that are occupying the minds of senior management teams and their discussions both amongst themselves and with boards. And as you can imagine, that varies based on where you sit in the world. But there are some themes to your question, Adi, that seem to be transversal. I'd be lying if one of the themes wasn't one of the ones that we talked about, which is how do I get value from this technology, you know, and what is everyone else doing? Because this is hard. And so I would put that as one of the themes of how do I transform my enterprise through this revolution in technology that we're seeing right before our eyes? It is a big theme. The second big theme is how do I build more institutional resilience? Because I'm increasingly, I'm talking now in the. In the guise of a CEO of the mine that unfortunately it's not. Things will never go back to how they were. There's going to be a world of continuous shocks. And so in a world of continuous shocks, do I have enough institutional resilience in my organization? And when you burrow under that, what folks often say is, I like sports. So I'll give you a sports analogy. I need to play offense and defense at the same time. So I need defense that I need enough buffer, enough cushion to be able to withstand something that I don't see coming. And have I built that margin into my system to be able to take the next blow that I may not see coming. But I also can't just play defense. I need some capacity to take some bold bets even when I may be getting hit with exogenous shocks. So can I play offense and defense at the same time? Is my simple version of how do you build institutional resilience? And then maybe the last one if I were to just give you three. I haven't met a CEO yet that thinks that their organization model is perfect. Haven't met one. And you know, a lot of the. The seminal thinking actually comes from some stuff. A 1959 paper in HBR by Gil Klee. This was before he became a GMP. He was one of my predecessors, but it was about creating a global organization and it was the precursor thinking to the matrixed organization. And if you kind of look at almost every large enterprise today, there is some version of a matrix organization. And I hear different tension points from CEOs about why their org is one of the bottlenecks in getting done what they need to get done. It's too slow, it's too cumbersome. I can't resource reallocate. It doesn't help me with complicated geography decisions, whatever it may be. Adi, I hear a lot of questions about what should my future organization model be?

[B]

So in 10 years time, what would you like McKinsey to be known for that it is not known for today?

[C]

I think it's gotta be a mix of what do I hope we're still known for and then what might be some new things. Because it's not going to be just stuff that McKinsey isn't known for today. I hope the part that it's continued to be known for is leadership factory of the world. And one of the things that's been very exciting is no matter how long folks stay with us, they tend to do pretty well wherever they go. You know, we produce more CEOs than any other institution in the world. And I hope that's still the case in 10 years. Our folks coming to us and you know, sorry, this is just my direct language. You know, maybe the experience isn't easy, maybe it's pretty hard and they got a lot of tough feedback. But do we make you a better leader no matter how long you're in McKinsey? Two years, 30 years. But do you leave McKinsey a better. I hope that remains. I hope the part that is new to your point is something that's in flight today, but I think not really well known, which is we complete this journey from being an advisor to an impact partner and that McKinsey is not known for. Hey, they gave me great advice, but, you know, if it worked, that was because they were smart. And if it didn't work, it's because I didn't implement. Which is the joke, right? But as it moved to, you know what, we designed a business case together, and these guys underwrote the same outcomes that I took to the board. And we went on this journey and we kept at it until we got to someplace I didn't think I could get to. I think that's the part that I'd love to land fully in this next decade.

[B]

Bob, thank you very much for being here. That was a great discussion and congratulations on turning 100.

[C]

Thank you. I enjoyed it.

[B]

That was Bob Sternfels, global managing partner at McKinsey & Company. Next week, Alison looks into the latest research on what it takes to really be ready for the C Suite. If you found this episode helpful, share it with a colleague and be sure to subscribe and rate IdeaCast in Apple Podcasts, Spotify, or wherever you listen. If you want to help leaders move the world forward, please consider subscribing to Harvard Business Review. You'll get access to the HBR mobile app, the weekly exclusive Insider newsletter, and unlimited access to HBR Online. Just head to hbr.org subscribe and thanks to our team, Senior producer Mary Dew, Audio Production Manager Ian Fox, and senior Production specialist Rob Eckhart. And thanks to you for listening to the HBR IdeaCast. We'll be back with a new episode on Tuesday. I'm Adi.