Best of LinkedIn: Strategy & Consulting CW 04/ 05

00:00:00: provided by Thomas Elguyer and Frennus, based on the most relevant LinkedIn posts about strategy and consulting from CW four and five.

00:00:08: Frennus specializes in B to B market research for strategy and consulting teams with a focus on tech and ICT.

00:00:15: Okay, so we've got a massive stack of research on the desk today.

00:00:19: And looking through these posts from the last two weeks, Honestly, it feels a little bit like the hangover after the party.

00:00:26: That

00:00:26: is the perfect way to put it.

00:00:27: You know, for the last year, LinkedIn has been this breathless echo chamber of AI is magic and everything is changing forever.

00:00:34: Right, lots of rocket ship emojis.

00:00:36: Exactly,

00:00:36: and now the lights are on, the music stopped, and well, the bill has arrived.

00:00:41: If I had to put a bumper sticker on the mood for weeks four and five, it would be, the party is over, the real work.

00:00:47: Which sounds a bit depressing, but that's actually where the money is made, right?

00:00:50: Precisely.

00:00:51: We are shifting from ambition, what we could do, to execution.

00:00:55: How do we actually govern this stuff, pay for it, and, you know, fix it?

00:00:59: We're seeing a huge pivot to financial accountability, the gritty reality of operationalizing AI, and some very, very serious geopolitical headwinds.

00:01:07: And we're going to talk about the token economy, which blew my mind, by the way.

00:01:12: We've got a potential breakup of the big four consulting firms and we need to talk about why your personal strategy is probably failing you.

00:01:19: It's a dense landscape, no doubt.

00:01:21: Let's dive in.

00:01:22: Let's start with that real work theme.

00:01:24: For so long, AI was the shiny toy for the CIO or, you know, the CTO.

00:01:29: But looking at the sources, particularly a post from Kristach Heiser at BCG, he is waiting a huge red flag here.

00:01:36: He's basically saying that area is over.

00:01:39: It's completely dead.

00:01:40: Weiser's point is that AI has graduated.

00:01:44: It's no longer just a tech initiative.

00:01:46: It is now a core pillar of corporate strategy.

00:01:48: And that means the leadership of AI is moving decisively to the CEO.

00:01:53: Which

00:01:53: makes sense in theory, but practically CEOs are already swamped.

00:01:56: Can they actually own this?

00:01:57: They have to.

00:01:58: They have to own it because the differentiator is no longer who is experimenting.

00:02:01: Everyone is running a pilot program somewhere.

00:02:03: The real winner is the company that scales with discipline.

00:02:06: And you just can't scale across silos, across marketing, supply chain, HR without a mandate from the very top.

00:02:12: But Mike Evans raised a counterpoint that I thought was really sharp.

00:02:16: He argues that ownership right now is a complete mess.

00:02:19: You've got the CIO, the CDO, the CTO.

00:02:22: It's like a game of musical chairs.

00:02:24: Right.

00:02:24: And when everyone owns it, nobody owns it.

00:02:27: Evan suggests we might see the rise of a chief AI transformation officer.

00:02:32: Someone whose sole job is to bridge that gap between the technical ambition and the business reality.

00:02:38: Because right now, those two things are just not talking to each other.

00:02:42: Speaking of that gap, I have to bring up this analogy from Valentino Koster.

00:02:46: I think this explains why so many boards are frustrated.

00:02:48: The

00:02:48: orchestra analogy?

00:02:49: Yes.

00:02:50: He says, everyone bought into AI expecting a symphony.

00:02:53: They thought they'd flip a switch and have this fully formed orchestra playing perfect harmony.

00:02:57: And instead?

00:02:58: Instead they got a guy with a tuba.

00:02:59: Right.

00:02:59: They got one strong instrument.

00:03:01: Maybe it's a great chatbot or a great coding assistant, but it is not a symphony.

00:03:06: And the natural reaction is disappointment.

00:03:09: Yeah, you know, you fired up the program expecting Beethoven and you got a solo.

00:03:13: But Coaster's advice is don't fire the tuba player because he isn't an orchestra.

00:03:18: That's such a crucial mindset shift.

00:03:20: You have to build the section first.

00:03:21: You start with the one use case, the one player, and you perfect that before you try to conduct the whole show.

00:03:27: It's about patience and execution, which is... pretty rare these days.

00:03:31: And it connects to the infrastructure question too.

00:03:33: Vikas Ghul had a very sharp analysis of the Apple and Google Gemini partnership.

00:03:38: Oh,

00:03:38: this is the debate about tracks versus rails.

00:03:40: Okay.

00:03:41: Break that down for me, because to me, tracks and rails, they sound like the same thing.

00:03:45: So

00:03:45: think of the tracks as the heavy infrastructure, the massive foundational models, the billions of dollars in data centers.

00:03:53: That's becoming a public utility.

00:03:55: Goal argues that for most companies, trying to build your own track, your own foundational brain, is just an unjustifiable expense.

00:04:03: So don't build your own LLM from scratch.

00:04:05: Exactly.

00:04:06: The value is in the rails.

00:04:07: The rails are the user experience, the sensors, the customer.

00:04:11: That's where Apple lives.

00:04:12: The advice is to focus on the experience layer, not the plumbing.

00:04:16: But, and there's always a but, you can't build a great experience on a shaky foundation.

00:04:22: So Rashidi had a post that really resonated.

00:04:25: She argues that companies are buying furniture before building the house.

00:04:29: That is a classic problem in digital transformation, but it's just so much worse with AI.

00:04:35: So the furniture is the flashy AI use case.

00:04:38: the chatbot.

00:04:38: Right.

00:04:39: Look at our cool generative design tool.

00:04:41: But the

00:04:42: house,

00:04:43: the data architecture underneath is a mess.

00:04:46: Full of termites.

00:04:47: Exactly.

00:04:47: The data is siloed.

00:04:49: It's dirty.

00:04:49: It's unstructured.

00:04:50: So you buy this expensive furniture, you put it on a rotting floor, and then you wonder why the initiative collapses.

00:04:56: Rashidi is saying, stop buying furniture.

00:04:58: Fix the floor.

00:05:00: And even if the floor is solid, the people walking on it might not be ready.

00:05:04: Kabil Beraja shared some takeaways from Davos, and he noted that the bottleneck isn't the technology anymore.

00:05:09: It's speed and talent adaptation.

00:05:11: We are just moving faster than our people can learn, and that leaves to friction.

00:05:15: Which is a perfect segue to the economics of all this.

00:05:18: Because if we are scaling, we need to know what it costs.

00:05:21: And this is where it gets really interesting.

00:05:23: We are seeing a whole new economic unit emerge.

00:05:26: The token.

00:05:27: Right.

00:05:27: Stuart Scott is from Deloitte is calling the token the new unit of economic value.

00:05:32: It's a fundamental shift.

00:05:34: We really need to understand this.

00:05:36: The last twenty years we've lived in the sauce era.

00:05:39: you pay a flat fee per user say fifty bucks a month for a seat and that person can use the software as much as they want.

00:05:46: It's predictable.

00:05:47: It's a buffer.

00:05:48: The CFO knows exactly what the bill will be in December.

00:05:50: Exactly.

00:05:51: But AI is moving us to a consumption model.

00:05:54: You pay for the compute.

00:05:55: You pay per token generated.

00:05:57: It's like your water bill or your electric bill.

00:06:00: The more you leave the tap running, the more you pay.

00:06:02: And this is where SCOTUS brings up.

00:06:04: Jeven's Paradox.

00:06:05: Can we just unpack that for a second?

00:06:07: Because it sounds really counterintuitive.

00:06:09: It is.

00:06:09: Jeven's Paradox is an economic theory from the nineteenth century.

00:06:13: It was originally about coal.

00:06:14: That says, as technology becomes more efficient and cheaper, you don't actually save resources, you end up consuming

00:06:20: more.

00:06:21: Because it's cheaper, so you just stop worrying about using it.

00:06:24: Precisely.

00:06:25: Think about LED light bulbs.

00:06:26: They're incredibly efficient compared to the old incandescent bulbs.

00:06:30: Did our electricity bills go down?

00:06:32: No.

00:06:32: We just started putting lights everywhere.

00:06:34: So as AI gets cheaper per token, we aren't going to save budget.

00:06:38: We're just going to inject AI into every single email, report, and meeting.

00:06:42: And the bill will skyrocket.

00:06:44: That is what is keeping CFOs up at night, because suddenly your IT cost isn't fixed.

00:06:49: It's variable, and it can scale infinitely.

00:06:52: Evan Benjamin asked the million dollar question.

00:06:55: Is there such a thing as predictable AI ROI?

00:06:58: I'm guessing the answer is not yet.

00:07:00: It's difficult.

00:07:01: Benjamin highlights the need for AI fine ops.

00:07:04: You need a dedicated function just to track cost per million tokens.

00:07:08: You have to ensure that every dollar spent actually translates to business impact.

00:07:12: And Nicholas Fundrini took that even higher, right?

00:07:15: to the board level.

00:07:16: Yes.

00:07:16: So Andrea argues that fine ops isn't just about operational cost control anymore.

00:07:20: It's about economic governance and strategic risk.

00:07:24: Strategic

00:07:25: risk.

00:07:25: Think about it.

00:07:26: If your operational costs are variable based on how chatty your AI agent is, that is a board level risk issue.

00:07:33: If an agent goes rogue and starts having million token conversations with customers, you could blow your quarterly budget in a week.

00:07:40: Wow.

00:07:41: It's wild to think that a chatty agent could be a budget risk.

00:07:45: Okay, but let's pivot to the people running these budgets.

00:07:48: theme three is about the human element Because with all this automation people are asking so what is my job now?

00:07:55: Neha Cabra shared some really striking data from McKinsey.

00:07:59: They found that two-thirds of U.S.

00:08:00: work hours require non-physical capabilities.

00:08:03: Those are exactly the hours ripe for AI agents.

00:08:06: That

00:08:06: sounds terrifying.

00:08:07: Two-thirds.

00:08:08: That's basically the entire white-collar workforce.

00:08:10: It does sound scary, but Cabra asks the so-what question.

00:08:13: If the AI does the processing, what stays stubbornly human?

00:08:16: And her answer is trust.

00:08:18: judgment, escalation, care, and orchestration.

00:08:21: The

00:08:21: human backbone.

00:08:22: That's it.

00:08:22: The AI can generate the report, but a human has to decide if it's true, if it matters, and who needs to see it.

00:08:28: That judgment layer becomes more valuable, not less.

00:08:31: But you have to pivot your skills toward it.

00:08:33: I think this connects to a post by Reshma Ramachandran that I absolutely loved.

00:08:37: She flipped the script.

00:08:38: She said companies spend billions on strategy market signals, positioning portfolios, but individuals.

00:08:45: We rarely have a strategy for our own lives.

00:08:48: That is such a powerful insight.

00:08:49: Most people just drift.

00:08:50: They take the next job that comes along.

00:08:52: And she advises treating your life like an organization.

00:08:56: What is your product?

00:08:57: How diversified is your portfolio?

00:09:00: If you lose your main client, your employer, Do you have a backup plan?

00:09:05: It's about viewing yourself as a business of one.

00:09:07: And Maidiz Derivik added a really practical note to that, specifically about job searching.

00:09:12: He says burnout comes from a lack of strategy, not just effort.

00:09:15: Oh, the sprinting into a brick wall feeling.

00:09:18: Precisely.

00:09:18: You see candidates sending out hundreds of applications.

00:09:21: That's effort.

00:09:23: But if you don't have feedback loops, if you don't know why you aren't getting hired, you just keep trying harder at the wrong thing.

00:09:29: That's a failure of personal strategy.

00:09:31: So don't just work hard.

00:09:32: Optimize.

00:09:33: Build a feedback loop.

00:09:35: Exactly.

00:09:36: And even for those who have jobs, Mark D. Orlick warns leaders not to get complacent.

00:09:41: He says low turnover does not equal engagement.

00:09:44: Right.

00:09:44: Just because nobody is quitting doesn't mean everyone is happy.

00:09:47: That's the paralysis factor.

00:09:49: People might stay because the market is tough, not because they're inspired.

00:09:53: The risk isn't the person who leaves, it's the person who stays but has stopped caring.

00:09:57: That zombie workforce can just kill a company's execution speed.

00:10:01: That is a silent killer.

00:10:04: Okay, zooming out from the individual to a global stage, we really can't ignore the geopolitical landscape.

00:10:10: It feels like every week there's a new complication.

00:10:12: It's the age of competition, as Shoaib Yusuf from BCG calls it.

00:10:16: He argues that geopolitics is no longer just a backdrop.

00:10:19: It's not something you watch on the news.

00:10:20: It has to be a core corporate capability.

00:10:23: A muscle you have to build.

00:10:24: Yes,

00:10:25: you need to be able to sense and interpret these shifts.

00:10:28: Andreas Pireschek mentioned the WEF global risks report, twenty twenty six.

00:10:32: And the takeaway there is that compliance is no longer just defensive.

00:10:35: It's a strategic asset for stability.

00:10:38: And there's a specific blind spot that Christian A. Rodriguez Schiffel pointed out that scared me a little bit.

00:10:44: Everyone is watching tariffs on goods, steel, cars, that sort of thing.

00:10:48: Right.

00:10:48: The physical stuff we can see on a container ship.

00:10:51: But he says the bigger threat is restrictions on cross-border services.

00:10:54: This is huge for the digital economy.

00:10:56: We are seeing data localization rules and market access limits growing twice as fast as trade restrictions on goods.

00:11:04: Can you give me a concrete example?

00:11:05: Who does this hurt?

00:11:06: Well, imagine you are a global bank or a massive HR consultancy.

00:11:12: You run a centralized model where your data sits in the cloud in the US, but you serve clients in Europe and Asia.

00:11:19: Suddenly, a new regulation says German data cannot leave Germany.

00:11:23: And your entire centralized business model just breaks.

00:11:27: Oh, overnight.

00:11:28: Exactly.

00:11:28: You have to duplicate your infrastructure, duplicate your data governance.

00:11:32: It becomes incredibly expensive and complex.

00:11:34: If you aren't watching services trade restrictions, you are just flying blind.

00:11:39: Speaking of business models breaking, let's talk about the consulting industry itself.

00:11:44: James O'Dowd dropped a bit of a bombshell prediction regarding the Big Four.

00:11:48: Yes, the potential separation of audit and consulting.

00:11:51: We've heard rumors of this for years.

00:11:53: Why does O'Dowd think it's actually inevitable now?

00:11:57: His reasoning is quite sound.

00:11:59: He argues they are essentially incompatible operating systems.

00:12:03: I mean, think about it.

00:12:04: What is the job of an auditor?

00:12:06: Verification, safety, saying no.

00:12:08: Exactly.

00:12:09: Audit requires restriction.

00:12:11: You have to be conservative.

00:12:12: You have to minimize risk.

00:12:13: Now, what does a strategy consultant do?

00:12:15: They sell, yes, they sell innovation, speed, taking risks.

00:12:19: Right.

00:12:19: Audit sells trust, consulting sells optionality.

00:12:23: Odoud argues that trying to house those two mindsets under one roof and under one conflict of interest policy is becoming impossible.

00:12:31: So the separation isn't a retreat, though.

00:12:32: No.

00:12:33: Odoud says it's a refocus for survival.

00:12:35: Audit becomes simpler and safer.

00:12:37: Consulting becomes faster and more meritocratic.

00:12:39: It allows both sides to actually do their jobs.

00:12:42: It'll be fascinating to see if that happens.

00:12:44: Okay, moving on to our final theme.

00:12:46: Sustainability, energy, and ESG.

00:12:49: And this is another area where optics are giving way to strategy.

00:12:53: Calm Divine noted that sustainability is moving from being a PR exercise to the strategic backbone of value creation.

00:13:01: But Patrick Schmucky had a critique of how we report on this.

00:13:05: He says current reporting describes programs well.

00:13:07: Look at our nice solar panels, but it's terrible at describing fragility.

00:13:11: That's the systemic risk.

00:13:13: You can have a great sustainability report and still be incredibly vulnerable to a supply chain shock or a climate event.

00:13:20: We just aren't measuring resilience well enough yet.

00:13:23: In talking about resilience, we have to talk about the grid.

00:13:26: Because all those tokens we talked about earlier, they run on electricity.

00:13:29: A

00:13:29: lot of electricity.

00:13:30: Joseph Nogle had some insights from PowerGen, in twenty twenty six, connecting AI to energy.

00:13:35: He is a metaphor I loved.

00:13:36: He said we're trying to fit a gallon of water into a pint glass.

00:13:39: The gallon is the AI power demand.

00:13:41: The pint glass is our current grid capacity.

00:13:44: So what do we do?

00:13:44: Do we just stop building data centers?

00:13:46: We can't.

00:13:47: The demand is exploding.

00:13:49: Nogel suggests the solution isn't one magic technology.

00:13:52: It involves hyperscale data centers, next-gen nuclear and sodium ion batteries.

00:13:57: We need it all.

00:13:58: It's in all of the above strategy.

00:14:00: It

00:14:00: has to be, and I liked his framing.

00:14:01: Extraordinary loads is extraordinary opportunity.

00:14:04: This is forcing an industrialization of our infrastructure at a speed we haven't seen in decades.

00:14:09: It's terrifying, but it's also a huge investment boom.

00:14:13: So... Bringing this all together.

00:14:15: We've covered a huge amount of ground from the CEO's office to the power grid from the token economy to our own resumes.

00:14:22: if you had to pull one thread that connects all of this, what would it be?

00:14:26: If I connect the dots, the theme is really about discipline.

00:14:29: Whether it's Sol Rashidi telling you to fix your data foundation before buying AI furniture, or Maid Distarovich telling you to have a strategy for your job search, or the energy sector facing the physics of the grid.

00:14:40: The

00:14:40: height is over.

00:14:41: The era of move fast and break things seems to be transitioning into move intentionally and build things that last.

00:14:47: It's about governance, resilience, and owning the outcome, not just the ambition.

00:14:52: I love that.

00:14:52: Move intentionally and build things at last.

00:14:54: That's a great note to end on.

00:14:56: If you enjoyed this episode, new episodes drop every two weeks.

00:14:59: Also check out our other editions on Private Equity, Venture Capital, and M&A.

00:15:04: Thanks for listening and don't forget to subscribe.