Best of LinkedIn: Strategy & Consulting CW 24/ 25

00:00:00: Provided by Thomas Allgaier and Frennus, based on the most relevant LinkedIn post about strategy in consulting from CW-TwentyFour and TwentyFive.

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00:00:33: so welcome everyone to The Deep Dive.

00:00:35: today we are looking at the top strategy and consulting trends that have popped up across LinkedIn over last two weeks.

00:00:40: yes specifically calendar Weeks.

00:00:42: Twenty Four and Twenty Five yeah And We're curating this directly for those of you working an M&A private equity venture capital and general consulting .The goal here is a really smart No fluff look at where the industry is actually heading.

00:00:53: Exactly, no fluff just pulling insights straight from The French's to understand how value Is actually being created and destroyed right now.

00:01:01: so To kick things off I want you to imagine a scenario

00:01:04: okay?

00:01:05: i'm listening.

00:01:05: You are sitting in A data room Right And you Are about to sign Off on this massive hundred million dollar acquisition of A fast-growing software company.

00:01:14: sounds like A pretty standard Tuesday.

00:01:16: honestly

00:01:16: great but you have audited their code, checked customer retention and everything looks incredibly solid.

00:01:23: But what if a specialized team of engineers using advanced AI could perfectly replicate that target company's core software from scratch by next week?

00:01:33: Oh wow!

00:01:34: Yeah like... If the fundamental product can just be cloned in few days is that companies' code actually competitive moat

00:01:41: anymore?!

00:01:42: I mean, that is the exact question we are tackling first.

00:01:45: This whole theme of AI strategy and how it's totally flipping traditional operating model for investors.

00:01:51: Yeah because scenario just laid out It isn't a science fiction anymore but rapidly becoming baseline reality.

00:01:58: No really not.

00:01:59: Hugo Reimaker has shared this explosive insight on LinkedIn about how Bain adapting their approach to private equity due diligence right now

00:02:07: Right!

00:02:07: And massive shift in how they evaluate target.

00:02:11: It really is.

00:02:11: They aren't just validating a target's financials or architecture anymore.

00:02:15: During the diligence phase itself, they are literally using AI to try and recreate the Target company software products

00:02:23: Which if you think about it completely changes how we calculate risk.

00:02:27: I mean, for decades the basic investor equation was figuring out how much time and capital it took the founders to build that specific architecture.

00:02:35: Right because that formed a barrier of entry

00:02:37: Exactly.

00:02:38: And now these diligence teams are just feeding public documentation API structures and feature specs into large language models To see just how fast a hypothetical competitor could spin up a clone.

00:02:50: It is wild.

00:02:51: It forces investors to ruthlessly separate what is genuinely hard-to-build from what has basically become commoditized.

00:03:00: Imagine tweeting a software company like a physical manufacturing plant?

00:03:03: Okay, a factory!

00:03:04: Yeah

00:03:04: if an AI native team can digitally three D print and exact replica of your factory in seventy two hours well the bricks and mortar over your factory are essentially worthless now

00:03:13: yeah but value as to live somewhere else

00:03:15: Exactly.

00:03:16: If the code itself is replaceable, we are basically forced back to old school business fundamentals.

00:03:22: The actual moat becomes proprietary data deeply entrenched distribution networks and you know institutional brand trust.

00:03:29: Which perfectly tees up this analysis from Antrix Gupta.

00:03:33: He made this point that the single biggest mistake Business leaders are making right now Is trying to copy AI use cases When they really should be copying AI operating models.

00:03:43: Okay so wait breaking that down a use case would be like dropping an AI co-pilot into a legacy workflow.

00:03:50: Yeah, exactly!

00:03:50: Like giving your marketing team a text generator so they can write the exact same email campaigns They always wrote just ten percent faster.

00:03:57: It is an automation play but it doesn't change The actual structure of the business right?

00:04:01: So he doesn't really move the needle on transformation.

00:04:03: precisely Goop does point Is that real Transformation isn't about deploying shiny new tools to speed up old habits made across the whole enterprise.

00:04:15: So you can't just plug AI into random departments and hope for

00:04:36: Well, Neha Khabar shared a really good framework for this recently.

00:04:39: She argues that the redesign has to happen at fun level now because let's face it… The macro reality is firmly behind

00:04:49: us.

00:04:49: Yeah, you can't just buy a company ride the rising tide of cheap financing and flip it for a higher multiple without actually changing how it runs?

00:04:57: Exactly!

00:04:57: The margin-for-operational error has completely evaporated.

00:05:01: so CobraRU's new edge for PE sponsors is building a highly repeatable value creation engine at firm level rather than treating every asset like a blank canvas.

00:05:11: You don't want to reinvent a bespoke operating plan And she laid out four specific moves to standardize this across a portfolio.

00:05:19: The first one is standardizing the core technology calls,

00:05:22: which is huge for avoiding technical debt.

00:05:25: it Is like every time affirm buys an asset that asset faces the same fundamental IT choice.

00:05:32: Do we patch our legacy systems try?

00:05:34: To simplify them or do we just rip them out and modernize.

00:05:37: And if a firm reinvents its methodology for making that choice with every single deal, they just accumulate massive technical fragmentation across their portfolio.

00:05:46: Exactly!

00:05:47: Standardizing those plays means the diligence and integration teams move with significantly higher velocity.

00:05:53: Her second point focuses on building a shared interpretation layer across the portfolio.

00:05:58: Yeah, and she points to EQT Group's mother brain as the gold standard for this fund-level capability.

00:06:04: Oh right they're a proprietary AI engine.

00:06:07: yeah it is essentially an Engine that ingests vast amounts of historical deal data And market signals To spot new investment patterns before human analysts do.

00:06:16: That

00:06:16: makes a lot of sense.

00:06:17: if a fund owns five different financial services companies They shouldn't be paying to build five completely separate data intelligence platforms from scratch

00:06:26: Exactly.

00:06:27: The underlying intelligence layer should travel across the entire portfolio.

00:06:30: So Cabra's

00:06:31: third and fourth points really focus on the human element, right?

00:06:35: Like backing operating partners who actually build the systems.

00:06:38: Yes

00:06:39: not just high-level advisors who parachute in for a steering committee meeting once a quarter.

00:06:44: You need technologists who get deep into the operational friction and make the painful trade-offs.

00:06:49: Right, And making this value creation a day one discipline it has to be baked in to the original investment thesis before they ink on deals even dry.

00:06:58: But you know we really needed transition from boardroom whiteboard to factory floor here.

00:07:02: Oh absolutely!

00:07:03: The messy reality of execution.

00:07:05: Because redesigning an AI native operating model sounds brilliant in an investment memo But the moment you attempt to execute that transformation inside a legacy organization with thousands of employees, The organizational immune system just

00:07:18: attacks it.

00:07:19: Yeah...the friction is immense!

00:07:21: And this brings us to our second theme A reality check on functional and enterprise transformation.

00:07:26: Christian Rouch recently published a very blunt assessment Of large-scale SAP software transformations

00:07:32: Right like as forehand on migration.

00:07:34: Just exactly Replacing the digital central nervous system That runs accompanies finances in supply chain.

00:07:40: Raj highlights that an astonishing seventy-five percent of these ERP projects failed to meet their objectives.

00:07:47: Seventy five percent?

00:07:48: That is a staggering failure

00:07:50: rate!

00:07:50: It IS, but his core argument is the failure has nothing do with software's technical capabilities... it fails because organizations chronically miscalculate impact on culture.

00:08:02: Okay I have challenge this narrative slightly though.

00:08:05: in consulting circles culture often used as really convenient scapegoat

00:08:09: You mean when a project goes over budget?

00:08:11: Leadership just blames culture.

00:08:13: Right, isn't this usually just the symptom of poor software training?

00:08:16: The enterprise buys one hundred million dollar tool does two-hour webinar on which buttons to click and then wonders why productivity plummets!

00:08:23: I think that is very common perspective.

00:08:26: But Rauch makes structural distinction here.

00:08:28: that separates training from psychology.

00:08:30: A training program addresses skill gap but organizational resistance doesn't usually stem form lack of skills.

00:08:37: So what it actually stems from?

00:08:39: It stems from a profound sense of loss.

00:08:42: Loss, like the fear of impending layoffs?

00:08:45: Sometimes it is headcount reduction sure but more insidiously...it's the loss status influence and professional identity.

00:08:53: Oh interesting

00:08:54: Yeah imagine mid-level supply chain manager who has spent fifteen years mastering this highly convoluted manual excel macro that keeps the warehouse running.

00:09:04: That macro makes them indispensable.

00:09:06: Uh, I see.

00:09:08: And if a new ERP system automates that process they lose their edge?

00:09:12: Exactly!

00:09:13: If it makes it transparent to the entire executive team That manager hasn't just lost a task They have lost their leverage and unique value To the company...that creates active entrenched resistance.

00:09:24: Wow

00:09:25: Yeah i can see how that derails a project.

00:09:27: Organizations typically deploy ninety-five percent of Their transformation budget on software licenses Leaving maybe five percent for change management.

00:09:34: They treat technology as hard infrastructure and the human element,as a soft metric.

00:09:39: When really Ratch's point is that The psychology of the workforce Is the hardest infrastructure Of all.

00:09:44: exactly.

00:09:46: And to see what happens when you systematically clear out?

00:09:48: The operational debris blocking That infrastructure.

00:09:51: Nadine charlon detailed A highly revealing case study of a swiss industrial company.

00:09:56: Oh

00:09:56: I read this one.

00:09:57: the financials tell the whole story.

00:09:58: they

00:09:58: Really do.

00:09:59: they were generating roughly thirty four million Swiss francs in revenue But their IT costs had inexplicably spiked by thirty-five percent over four years.

00:10:09: And the board basically mandated immediate cost reductions?

00:10:12: Yep,

00:10:13: and the operations team naturally panicked.

00:10:15: assuming a mandate like that meant severe disruption to their daily workflows.

00:10:19: It is classic standoff between CFO looking at spreadsheet and COO trying keep lights on

00:10:26: Exactly.

00:10:27: But when they actually audited the systems, They didn't need a massive restructuring.

00:10:30: It just needed to untangle unchecked complexity!

00:10:34: They recovered over half a million Swiss francs annually simply by cleaning house.

00:10:38: Just by removing legacy servers and shadow IT?

00:10:41: Right...they

00:10:42: found eleven on-premise legacy servers operating at incredibly low utilization.

00:10:47: Migrating those saved a hundred and forty-eight thousand francs.

00:10:51: They found rampant shadow IT with individual departments just swiping credit cards for redundant sauce tools,

00:10:57: which is so common in large companies

00:10:59: it Is centralizing.

00:11:01: those contracts received another seventy four thousand.

00:11:04: They even found that forty-two percent of their expensive IT help desk tickets were just employees asking for manual password resets,

00:11:11: which they obviously automated.

00:11:13: It is funny the COO had an epiphany That really encapsulates this entire theme?

00:11:17: They realized they didn't actually have an it cost

00:11:19: problem right there.

00:11:20: Had a complexity problems

00:11:21: Which connects perfectly to Tiger Tia Garjeon's warning about the upcoming agentic AI

00:11:26: era.

00:11:27: As large enterprises scramble to adopt AI, there is this tremendous pull toward decentralization.

00:11:43: Exactly.

00:11:44: The strategy of letting a thousand flowers bloom, give the marketing team their own AI budget let logistics pick their own vendor and just assume that innovation will naturally trickle up to balance sheet.

00:11:54: Tiger Rajin argues approach is catastrophic architectural error?

00:11:58: Yes absolutely because if you inject highly capable AI agents into complex siloed legacy processes exactly like the ones Swiss company was suffering from you do not achieve enterprise transformation.

00:12:12: Right,

00:12:13: what was this phrase?

00:12:13: You simply weaponize inefficiencies at scale.

00:12:17: Weaponizing inefficiency—that is such a stark way to put it!

00:12:20: It implies that if a bad process used to cost you ten thousand dollars per month in wasted labor an AI agent running the same bad process millions of times a second could cost you exponentially more

00:12:31: Precisely In corrupted data and fragmented customer experiences, TigerAgen points out that you absolutely need a centralized forcing mechanism.

00:12:40: He argues the GBS unit must be retained as the Enterprise AI control tower.

00:12:44: So their mandate is to enforce horizontal building blocks across the company?

00:12:48: Yes!

00:12:49: And establish what he calls minimum viable semantics which basically means creating unified data ontology

00:12:56: A single map of how all companies' data connects so information actually machine readable by whatever AI you deploy.

00:13:02: Exactly!

00:13:03: If you dismantle that central backbone in the name of moving faster, You are left with a chaotic landscape where marketing AI can't read supply chain's data.

00:13:13: Okay so we have built operational thesis here... You need an AI-native operating model focused on decision flows.

00:13:20: You need private equity funds structured to scale capability.

00:13:24: You must respect psychological laws inherent culture change and centralized control tower.

00:13:30: But the final piece of the puzzle is recognizing that this finely tuned internal machine, it's operating in an incredibly volatile external environment.

00:13:39: Which brings us to our third and final theme Geopolitics Macro Risk And Deal Certainty.

00:13:44: Right

00:13:45: because you can possess cleanest data ontology on market but if geopolitical conflict suddenly severs your primary supply chain Your EBITDA will collapse regardless of software.

00:13:55: This really is defining friction.

00:14:06: The

00:14:07: headline figures are pretty sobering.

00:14:09: Global GDP growth decelerating to two point nine percent

00:14:12: Yeah, and we are no longer dealing with standard cyclical business fluctuations where you just tighten the belt and wait for the rebound.

00:14:19: We're navigating deep structural supply-side

00:14:22: shocks... We are talking about aggressive tariff regimes fundamental energy insecurity an active geopolitical conflict.

00:14:30: The baseline environment has fundamentally altered.

00:14:33: So the key takeaway from business leaders is that volatility is now structural.

00:14:36: Stop waiting normal to return.

00:14:38: Strategy must pivot from optimization to resilience.

00:14:42: But despite how obvious that sounds, there's a massive execution gap.

00:14:45: There really is!

00:14:46: Christian H. Rodriguez-Chefell recently highlighted BCG survey data... ...that quantifies this disconnect perfectly.

00:14:52: According to the data, eighty percent of companies report significant exposure to geopolitical forces.

00:14:57: So they are acutely aware of their risk?

00:14:59: It's exactly.

00:15:01: However only fifteen percent of those companies systematically integrate that geopolitical analysis into their actual capital allocation or major investment decisions.

00:15:11: That

00:15:11: sixty-five percent gap between feeling the heat and actually moving out of the fire is where enterprise value was destroyed.

00:15:17: So let's make this highly actionable for the listeners, specifically those structuring deals in M&A and private equity.

00:15:24: For our listeners how does ignoring this macro and geopolitical risk Actually hit the bottom line when it is time to exit an asset?

00:15:32: To map that out we can look at Adrienne mom insights on The Private Equity Investment Lifecycle.

00:15:38: His core thesis is that macro risk has no longer a peripheral legal compliance issue.

00:15:42: It is ideal critical variable.

00:15:45: So where does the financial erosion actually begin?

00:15:47: Well,

00:15:47: The bleed begins on day one of the holding period Sanctions and unmapped supply chain exposures just act as a continuous drag slowly eroding the EBITDA margin.

00:15:56: But the truly catastrophic financial impact materializes at the exit phase

00:16:01: right because That Is when the prospective buyer brings their own diligence teams into the data room

00:16:06: Exactly, when you go to sell the asset.

00:16:08: The buyers are running aggressive stress tests on the company's geopolitical exposure.

00:16:13: if massive compliance gaps emerge late in game it instantly destroys your negotiating leverage as a seller

00:16:20: leading two buyers demanding massive escrow holdbacks to cover potential fines.

00:16:24: yes

00:16:24: and ultimately causes severe multiple compression.

00:16:28: The market looks at the geopolitical mess tied to your revenue, decides that risk is too high and agrees pay you a five-times multiple instead of eight times projected.

00:16:43: And as Florian Meyer detailed, sanctions and export controls are no longer exceptional measures deployed only during crises.

00:16:50: They're the everyday foundational tools of modern

00:16:53: geopolitics.".

00:16:54: So companies have to adapt their capabilities accordingly?

00:16:57: You can't just treat this a siloed issue for a junior compliance officer anymore...

00:17:01: No!

00:17:01: It is core revenue protection capability now…

00:17:05: perfectly ties together everything we've explored today.

00:17:08: There is this constant friction between the expectation of precision and reality in extreme

00:17:13: complexity."

00:17:27: If a new, heavily funded AI native competitor launched tomorrow possessing zero technical debt to unwind.

00:17:34: Zero legacy culture to manage and absolutely no geopolitical legacy exposure.

00:17:39: what parts of your current business or portfolio would be completely indefensible?

00:17:44: That is a lot to mull over.

00:17:45: if you enjoy this episode new episodes drop every two weeks.

00:17:48: also check out our other editions on private equity venture capital in M&A.