Latest / Best of LinkedIn: Strategy, M&A & Investments / Best of LinkedIn: Strategy & Consulting CW 24/ 25

Transcript

Best of LinkedIn: Strategy & Consulting CW 24/ 25 · Best of LinkedIn: Strategy, M&A & Investments

• 0:00
  Speaker 0: Provided by Thomas Allgaier and Frennus, based on the most relevant LinkedIn post about strategy in consulting from CW-TwentyFour and TwentyFive.
• 0:08
  Speaker 0: Frenness is a B to B market research company supporting consultancies with the marketing competition perspective for example in commercial due diligence's CDD.
• 0:17
  Speaker 0: CDD engagements.
• 0:18
  Speaker 0: don't forgive slow starts!
• 0:20
  Speaker 0: Frennes embeds directly into your consulting team as white label Market & Competitive Intelligence Partner.
• 0:25
  Speaker 0: slide ready fully adapted to your client's design and operational within twenty four
• 0:30
  Speaker 1: hours.
• 0:31
  Speaker 0: You can find more info in the description,
• 0:33
  Speaker 1: so welcome everyone to The Deep Dive.
• 0:35
  Speaker 1: today we are looking at the top strategy and consulting trends that have popped up across LinkedIn over last two weeks.
• 0:40
  Speaker 0: yes specifically calendar Weeks.
• 0:42
  Speaker 0: 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.
• 0:53
  Speaker 1: Exactly, no fluff just pulling insights straight from The French's to understand how value Is actually being created and destroyed right now.
• 1:01
  Speaker 1: so To kick things off I want you to imagine a scenario
• 1:04
  Speaker 0: okay?
• 1:05
  Speaker 0: i'm listening.
• 1:05
  Speaker 1: 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.
• 1:14
  Speaker 0: sounds like A pretty standard Tuesday.
• 1:16
  Speaker 0: honestly
• 1:16
  Speaker 1: great but you have audited their code, checked customer retention and everything looks incredibly solid.
• 1:23
  Speaker 1: 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?
• 1:33
  Speaker 0: Oh wow!
• 1:34
  Speaker 1: Yeah like... If the fundamental product can just be cloned in few days is that companies' code actually competitive moat
• 1:41
  Speaker 1: anymore?!
• 1:42
  Speaker 0: I mean, that is the exact question we are tackling first.
• 1:45
  Speaker 0: This whole theme of AI strategy and how it's totally flipping traditional operating model for investors.
• 1:51
  Speaker 1: Yeah because scenario just laid out It isn't a science fiction anymore but rapidly becoming baseline reality.
• 1:58
  Speaker 0: No really not.
• 1:59
  Speaker 0: Hugo Reimaker has shared this explosive insight on LinkedIn about how Bain adapting their approach to private equity due diligence right now
• 2:07
  Speaker 1: Right!
• 2:07
  Speaker 1: And massive shift in how they evaluate target.
• 2:11
  Speaker 0: It really is.
• 2:11
  Speaker 0: They aren't just validating a target's financials or architecture anymore.
• 2:15
  Speaker 0: During the diligence phase itself, they are literally using AI to try and recreate the Target company software products
• 2:23
  Speaker 1: Which if you think about it completely changes how we calculate risk.
• 2:27
  Speaker 1: 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.
• 2:35
  Speaker 0: Right because that formed a barrier of entry
• 2:37
  Speaker 1: Exactly.
• 2:38
  Speaker 1: 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.
• 2:50
  Speaker 0: It is wild.
• 2:51
  Speaker 0: It forces investors to ruthlessly separate what is genuinely hard-to-build from what has basically become commoditized.
• 3:00
  Speaker 0: Imagine tweeting a software company like a physical manufacturing plant?
• 3:03
  Speaker 1: Okay, a factory!
• 3:04
  Speaker 1: Yeah
• 3:04
  Speaker 0: 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
• 3:13
  Speaker 1: yeah but value as to live somewhere else
• 3:15
  Speaker 0: Exactly.
• 3:16
  Speaker 0: If the code itself is replaceable, we are basically forced back to old school business fundamentals.
• 3:22
  Speaker 0: The actual moat becomes proprietary data deeply entrenched distribution networks and you know institutional brand trust.
• 3:29
  Speaker 1: Which perfectly tees up this analysis from Antrix Gupta.
• 3:33
  Speaker 1: 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.
• 3:43
  Speaker 0: Okay so wait breaking that down a use case would be like dropping an AI co-pilot into a legacy workflow.
• 3:50
  Speaker 1: Yeah, exactly!
• 3:50
  Speaker 1: Like giving your marketing team a text generator so they can write the exact same email campaigns They always wrote just ten percent faster.
• 3:57
  Speaker 1: It is an automation play but it doesn't change The actual structure of the business right?
• 4:01
  Speaker 0: So he doesn't really move the needle on transformation.
• 4:03
  Speaker 1: 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.
• 4:15
  Speaker 0: So you can't just plug AI into random departments and hope for
• 4:36
  Speaker 1: Well, Neha Khabar shared a really good framework for this recently.
• 4:39
  Speaker 1: She argues that the redesign has to happen at fun level now because let's face it… The macro reality is firmly behind
• 4:49
  Speaker 0: us.
• 4:49
  Speaker 0: 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?
• 4:57
  Speaker 1: Exactly!
• 4:57
  Speaker 1: The margin-for-operational error has completely evaporated.
• 5:01
  Speaker 1: 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.
• 5:11
  Speaker 0: You don't want to reinvent a bespoke operating plan And she laid out four specific moves to standardize this across a portfolio.
• 5:19
  Speaker 0: The first one is standardizing the core technology calls,
• 5:22
  Speaker 1: which is huge for avoiding technical debt.
• 5:25
  Speaker 0: it Is like every time affirm buys an asset that asset faces the same fundamental IT choice.
• 5:32
  Speaker 0: Do we patch our legacy systems try?
• 5:34
  Speaker 0: To simplify them or do we just rip them out and modernize.
• 5:37
  Speaker 1: And if a firm reinvents its methodology for making that choice with every single deal, they just accumulate massive technical fragmentation across their portfolio.
• 5:46
  Speaker 0: Exactly!
• 5:47
  Speaker 0: Standardizing those plays means the diligence and integration teams move with significantly higher velocity.
• 5:53
  Speaker 0: Her second point focuses on building a shared interpretation layer across the portfolio.
• 5:58
  Speaker 1: Yeah, and she points to EQT Group's mother brain as the gold standard for this fund-level capability.
• 6:04
  Speaker 0: Oh right they're a proprietary AI engine.
• 6:07
  Speaker 1: 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.
• 6:16
  Speaker 1: That
• 6:16
  Speaker 0: makes a lot of sense.
• 6:17
  Speaker 0: if a fund owns five different financial services companies They shouldn't be paying to build five completely separate data intelligence platforms from scratch
• 6:26
  Speaker 1: Exactly.
• 6:27
  Speaker 1: The underlying intelligence layer should travel across the entire portfolio.
• 6:30
  Speaker 1: So Cabra's
• 6:31
  Speaker 0: third and fourth points really focus on the human element, right?
• 6:35
  Speaker 0: Like backing operating partners who actually build the systems.
• 6:38
  Speaker 0: Yes
• 6:39
  Speaker 1: not just high-level advisors who parachute in for a steering committee meeting once a quarter.
• 6:44
  Speaker 1: You need technologists who get deep into the operational friction and make the painful trade-offs.
• 6:49
  Speaker 0: 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.
• 6:58
  Speaker 1: But you know we really needed transition from boardroom whiteboard to factory floor here.
• 7:02
  Speaker 0: Oh absolutely!
• 7:03
  Speaker 0: The messy reality of execution.
• 7:05
  Speaker 1: 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
• 7:18
  Speaker 0: attacks it.
• 7:19
  Speaker 0: Yeah...the friction is immense!
• 7:21
  Speaker 0: And this brings us to our second theme A reality check on functional and enterprise transformation.
• 7:26
  Speaker 0: Christian Rouch recently published a very blunt assessment Of large-scale SAP software transformations
• 7:32
  Speaker 1: Right like as forehand on migration.
• 7:34
  Speaker 0: Just exactly Replacing the digital central nervous system That runs accompanies finances in supply chain.
• 7:40
  Speaker 0: Raj highlights that an astonishing seventy-five percent of these ERP projects failed to meet their objectives.
• 7:47
  Speaker 1: Seventy five percent?
• 7:48
  Speaker 1: That is a staggering failure
• 7:50
  Speaker 0: rate!
• 7:50
  Speaker 0: 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.
• 8:02
  Speaker 1: Okay I have challenge this narrative slightly though.
• 8:05
  Speaker 1: in consulting circles culture often used as really convenient scapegoat
• 8:09
  Speaker 0: You mean when a project goes over budget?
• 8:11
  Speaker 0: Leadership just blames culture.
• 8:13
  Speaker 1: Right, isn't this usually just the symptom of poor software training?
• 8:16
  Speaker 1: The enterprise buys one hundred million dollar tool does two-hour webinar on which buttons to click and then wonders why productivity plummets!
• 8:23
  Speaker 0: I think that is very common perspective.
• 8:26
  Speaker 0: But Rauch makes structural distinction here.
• 8:28
  Speaker 0: that separates training from psychology.
• 8:30
  Speaker 0: A training program addresses skill gap but organizational resistance doesn't usually stem form lack of skills.
• 8:37
  Speaker 1: So what it actually stems from?
• 8:39
  Speaker 0: It stems from a profound sense of loss.
• 8:42
  Speaker 1: Loss, like the fear of impending layoffs?
• 8:45
  Speaker 0: Sometimes it is headcount reduction sure but more insidiously...it's the loss status influence and professional identity.
• 8:53
  Speaker 1: Oh interesting
• 8:54
  Speaker 0: Yeah imagine mid-level supply chain manager who has spent fifteen years mastering this highly convoluted manual excel macro that keeps the warehouse running.
• 9:04
  Speaker 0: That macro makes them indispensable.
• 9:06
  Speaker 1: Uh, I see.
• 9:08
  Speaker 1: And if a new ERP system automates that process they lose their edge?
• 9:12
  Speaker 0: Exactly!
• 9:13
  Speaker 0: 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.
• 9:24
  Speaker 0: Wow
• 9:25
  Speaker 1: Yeah i can see how that derails a project.
• 9:27
  Speaker 0: Organizations typically deploy ninety-five percent of Their transformation budget on software licenses Leaving maybe five percent for change management.
• 9:34
  Speaker 0: They treat technology as hard infrastructure and the human element,as a soft metric.
• 9:39
  Speaker 1: When really Ratch's point is that The psychology of the workforce Is the hardest infrastructure Of all.
• 9:44
  Speaker 0: exactly.
• 9:46
  Speaker 0: And to see what happens when you systematically clear out?
• 9:48
  Speaker 0: The operational debris blocking That infrastructure.
• 9:51
  Speaker 0: Nadine charlon detailed A highly revealing case study of a swiss industrial company.
• 9:56
  Speaker 0: Oh
• 9:56
  Speaker 1: I read this one.
• 9:57
  Speaker 1: the financials tell the whole story.
• 9:58
  Speaker 1: they
• 9:58
  Speaker 0: Really do.
• 9:59
  Speaker 0: 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.
• 10:09
  Speaker 1: And the board basically mandated immediate cost reductions?
• 10:12
  Speaker 1: Yep,
• 10:13
  Speaker 0: and the operations team naturally panicked.
• 10:15
  Speaker 0: assuming a mandate like that meant severe disruption to their daily workflows.
• 10:19
  Speaker 1: It is classic standoff between CFO looking at spreadsheet and COO trying keep lights on
• 10:26
  Speaker 0: Exactly.
• 10:27
  Speaker 0: But when they actually audited the systems, They didn't need a massive restructuring.
• 10:30
  Speaker 0: It just needed to untangle unchecked complexity!
• 10:34
  Speaker 0: They recovered over half a million Swiss francs annually simply by cleaning house.
• 10:38
  Speaker 1: Just by removing legacy servers and shadow IT?
• 10:41
  Speaker 1: Right...they
• 10:42
  Speaker 0: found eleven on-premise legacy servers operating at incredibly low utilization.
• 10:47
  Speaker 0: Migrating those saved a hundred and forty-eight thousand francs.
• 10:51
  Speaker 0: They found rampant shadow IT with individual departments just swiping credit cards for redundant sauce tools,
• 10:57
  Speaker 1: which is so common in large companies
• 10:59
  Speaker 0: it Is centralizing.
• 11:01
  Speaker 0: those contracts received another seventy four thousand.
• 11:04
  Speaker 0: They even found that forty-two percent of their expensive IT help desk tickets were just employees asking for manual password resets,
• 11:11
  Speaker 1: which they obviously automated.
• 11:13
  Speaker 1: It is funny the COO had an epiphany That really encapsulates this entire theme?
• 11:17
  Speaker 1: They realized they didn't actually have an it cost
• 11:19
  Speaker 0: problem right there.
• 11:20
  Speaker 0: Had a complexity problems
• 11:21
  Speaker 1: Which connects perfectly to Tiger Tia Garjeon's warning about the upcoming agentic AI
• 11:26
  Speaker 0: era.
• 11:27
  Speaker 1: As large enterprises scramble to adopt AI, there is this tremendous pull toward decentralization.
• 11:43
  Speaker 1: Exactly.
• 11:44
  Speaker 1: 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.
• 11:54
  Speaker 0: Tiger Rajin argues approach is catastrophic architectural error?
• 11:58
  Speaker 1: 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.
• 12:12
  Speaker 1: Right,
• 12:13
  Speaker 0: what was this phrase?
• 12:13
  Speaker 1: You simply weaponize inefficiencies at scale.
• 12:17
  Speaker 0: Weaponizing inefficiency—that is such a stark way to put it!
• 12:20
  Speaker 0: 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
• 12:31
  Speaker 1: Precisely In corrupted data and fragmented customer experiences, TigerAgen points out that you absolutely need a centralized forcing mechanism.
• 12:40
  Speaker 1: He argues the GBS unit must be retained as the Enterprise AI control tower.
• 12:44
  Speaker 0: So their mandate is to enforce horizontal building blocks across the company?
• 12:48
  Speaker 1: Yes!
• 12:49
  Speaker 1: And establish what he calls minimum viable semantics which basically means creating unified data ontology
• 12:56
  Speaker 0: A single map of how all companies' data connects so information actually machine readable by whatever AI you deploy.
• 13:02
  Speaker 1: Exactly!
• 13:03
  Speaker 1: 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.
• 13:13
  Speaker 0: Okay so we have built operational thesis here... You need an AI-native operating model focused on decision flows.
• 13:20
  Speaker 0: You need private equity funds structured to scale capability.
• 13:24
  Speaker 0: You must respect psychological laws inherent culture change and centralized control tower.
• 13:30
  Speaker 1: But the final piece of the puzzle is recognizing that this finely tuned internal machine, it's operating in an incredibly volatile external environment.
• 13:39
  Speaker 0: Which brings us to our third and final theme Geopolitics Macro Risk And Deal Certainty.
• 13:44
  Speaker 0: Right
• 13:45
  Speaker 1: 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.
• 13:55
  Speaker 0: This really is defining friction.
• 14:06
  Speaker 0: The
• 14:07
  Speaker 1: headline figures are pretty sobering.
• 14:09
  Speaker 1: Global GDP growth decelerating to two point nine percent
• 14:12
  Speaker 0: Yeah, and we are no longer dealing with standard cyclical business fluctuations where you just tighten the belt and wait for the rebound.
• 14:19
  Speaker 0: We're navigating deep structural supply-side
• 14:22
  Speaker 1: shocks... We are talking about aggressive tariff regimes fundamental energy insecurity an active geopolitical conflict.
• 14:30
  Speaker 1: The baseline environment has fundamentally altered.
• 14:33
  Speaker 0: So the key takeaway from business leaders is that volatility is now structural.
• 14:36
  Speaker 0: Stop waiting normal to return.
• 14:38
  Speaker 1: Strategy must pivot from optimization to resilience.
• 14:42
  Speaker 1: But despite how obvious that sounds, there's a massive execution gap.
• 14:45
  Speaker 0: There really is!
• 14:46
  Speaker 0: Christian H. Rodriguez-Chefell recently highlighted BCG survey data... ...that quantifies this disconnect perfectly.
• 14:52
  Speaker 0: According to the data, eighty percent of companies report significant exposure to geopolitical forces.
• 14:57
  Speaker 1: So they are acutely aware of their risk?
• 14:59
  Speaker 0: It's exactly.
• 15:01
  Speaker 0: However only fifteen percent of those companies systematically integrate that geopolitical analysis into their actual capital allocation or major investment decisions.
• 15:11
  Speaker 0: That
• 15:11
  Speaker 1: sixty-five percent gap between feeling the heat and actually moving out of the fire is where enterprise value was destroyed.
• 15:17
  Speaker 0: So let's make this highly actionable for the listeners, specifically those structuring deals in M&A and private equity.
• 15:24
  Speaker 0: For our listeners how does ignoring this macro and geopolitical risk Actually hit the bottom line when it is time to exit an asset?
• 15:32
  Speaker 1: To map that out we can look at Adrienne mom insights on The Private Equity Investment Lifecycle.
• 15:38
  Speaker 1: His core thesis is that macro risk has no longer a peripheral legal compliance issue.
• 15:42
  Speaker 1: It is ideal critical variable.
• 15:45
  Speaker 0: So where does the financial erosion actually begin?
• 15:47
  Speaker 0: Well,
• 15:47
  Speaker 1: 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.
• 15:56
  Speaker 1: But the truly catastrophic financial impact materializes at the exit phase
• 16:01
  Speaker 0: right because That Is when the prospective buyer brings their own diligence teams into the data room
• 16:06
  Speaker 1: Exactly, when you go to sell the asset.
• 16:08
  Speaker 1: The buyers are running aggressive stress tests on the company's geopolitical exposure.
• 16:13
  Speaker 1: if massive compliance gaps emerge late in game it instantly destroys your negotiating leverage as a seller
• 16:20
  Speaker 0: leading two buyers demanding massive escrow holdbacks to cover potential fines.
• 16:24
  Speaker 0: yes
• 16:24
  Speaker 1: and ultimately causes severe multiple compression.
• 16:28
  Speaker 1: 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.
• 16:43
  Speaker 1: And as Florian Meyer detailed, sanctions and export controls are no longer exceptional measures deployed only during crises.
• 16:50
  Speaker 1: They're the everyday foundational tools of modern
• 16:53
  Speaker 1: geopolitics.".
• 16:54
  Speaker 0: So companies have to adapt their capabilities accordingly?
• 16:57
  Speaker 0: You can't just treat this a siloed issue for a junior compliance officer anymore...
• 17:01
  Speaker 1: No!
• 17:01
  Speaker 1: It is core revenue protection capability now…
• 17:05
  Speaker 0: perfectly ties together everything we've explored today.
• 17:08
  Speaker 0: There is this constant friction between the expectation of precision and reality in extreme
• 17:13
  Speaker 0: complexity."
• 17:27
  Speaker 1: If a new, heavily funded AI native competitor launched tomorrow possessing zero technical debt to unwind.
• 17:34
  Speaker 1: Zero legacy culture to manage and absolutely no geopolitical legacy exposure.
• 17:39
  Speaker 1: what parts of your current business or portfolio would be completely indefensible?
• 17:44
  Speaker 0: That is a lot to mull over.
• 17:45
  Speaker 0: if you enjoy this episode new episodes drop every two weeks.
• 17:48
  Speaker 0: also check out our other editions on private equity venture capital in M&A.