I Watched Three Firms Pitch for the Same Mandate Last Month

The frameworks are different. The labels are different. The slides are identical. A Field Report from a former partner who has been on both sides of the table.

A friend on the buy side invited me to sit in on an advisory selection last month. Three firms. One mandate. Mid-market industrial company looking at a portfolio review and potential divestiture. The kind of engagement that used to be genuinely interesting work.

Each firm got ninety minutes. I sat through all three.

Every deck opened with a “proprietary framework.” Firm A called theirs the Strategic Value Matrix. Firm B called theirs the Portfolio Optimisation Lens. Firm C used something like the Growth-Complexity Navigator. All three were 2x2 matrices. High-low on one axis, high-low on the other. The quadrant labels differed; the logic was identical. Plot your business units, see which ones fall in the “divest” box, recommend further analysis on the ones near the boundary.

I have seen this matrix hundreds of times. I have presented versions of it myself, under at least four different firm logos over the course of my career. The template has not changed in twenty years. What has changed is the confidence with which partners now present it as proprietary thinking. It is not proprietary. It is a recombination of ideas from BCG’s growth-share matrix (1968), McKinsey’s GE-McKinsey nine-box (1970s), and the portfolio logic taught in every MBA strategy course since the 1990s. Everyone in the industry knows this. Nobody says it in the room.

Two of the three firms proposed a “phased approach.” Phase 1: diagnostic and data gathering, six to eight weeks. Phase 2: strategic assessment and scenario modelling, six to eight weeks. Phase 3: recommendations and implementation roadmap, four to six weeks. The timelines were so similar that if you shuffled the decks and removed the logos, you could not tell which firm proposed which. The third firm proposed the same phases under different names and added a fourth (”stakeholder alignment”), presumably to justify charging for a few extra weeks.

Then came the detail that stayed with me. The partner leading Firm C’s pitch had been at Firm A two years earlier. I know because I worked with him at Firm A. He was pitching the same client, using the same framework, with the same phased methodology he had used at his previous firm. The only differences: his business card, the colour palette on his slides, and the proprietary name stamped across the top of the 2x2.

I do not begrudge him the career move. Partners move between firms constantly, and they take their playbooks with them because the playbooks are the only consistently portable asset a partner has. But his presence at that pitch table made visible something the industry prefers to keep invisible: the firms are selling interchangeable products under competing brand names.

This convergence did not happen overnight, and we did not need this particular pitch to notice it. We started seeing it decades ago. The decks were already getting similar by mid-2000s. Talent rotation was homogenising the analytical traditions. When partners and senior managers cycle between firms every few years (sometimes every 18 months at the VP and principal level), they carry their methods with them. The receiving firm absorbs those methods. McKinsey partners who move to Deloitte bring McKinsey’s frameworks. BCG managers who move to EY bring BCG’s hypothesis structure. Over a decade of constant cross-pollination, the approaches merged. Consolidation accelerated it: when PwC acquired Booz & Company in 2014 to create Strategy&, and Deloitte absorbed Monitor Group to build Monitor Deloitte, the acquired boutiques lost their distinctive analytical cultures within a few years. The industrialisation of methodology continued it, with every firm building internal “knowledge libraries” and “accelerators” that packaged engagement types into repeatable templates.

But there was still, ten years ago, a residual difference in quality. A team that had done its homework, spent time with the client’s operations, interrogated the data with genuine curiosity, could produce something the client had not already thought of. The framework might be familiar, but the thinking applied within it could surprise you. Occasionally, a pitch would contain a genuine insight, a connection the client had missed, an angle that reframed the problem in a way that justified the fees. Those moments were already rare by 2016. They have now almost vanished. AI finished the job.

Every firm now runs its pitch preparation through large language models. The analysts use them to draft market analyses, synthesise industry reports, generate scenario frameworks, and write the narrative sections of the deck. This is rational behaviour and we are not objecting to it on principle. What we are observing is what it produces in aggregate: when six competing teams feed the same public data into the same family of foundation models and ask for a strategic assessment, the outputs converge on the same median analysis, expressed in the same register, structured with the same logical scaffolding. The idiosyncratic brilliance of a team that had genuinely wrestled with a problem, argued about it internally, and produced something unexpected gets replaced by fluent, competent, and utterly interchangeable prose.

We have, among the contributors to this publication, become embarrassingly good at identifying which model produced which section of a pitch deck. Claude has a particular cadence: measured, structured, slightly formal, with a tendency toward precise qualifications. ChatGPT produces a breezier, more expansive register, often with a characteristic pattern of listing implications in groups of three. Copilot-assisted sections carry a recognisable Microsoft house style, and Gemini has its own tells (a certain flatness when synthesising, an inclination toward neutral balancing of perspectives). Read enough AI-assisted pitch decks across enough firms and you start pattern-matching the model before you have finished the second paragraph.

We mention this not to embarrass anyone. Every firm is doing it. We would have done it too, had these tools existed during our tenure. The point is that “proprietary framework” has become an even more absurd label than it was before. The frameworks were already interchangeable when they came from the same business-school case studies and the same partner playbooks rotating between firms. Now they come from the same four or five language models available to everyone. The label “proprietary” applied to AI-generated analysis is not just a marketing claim. It is a fiction.

What used to differentiate a great team from a competent one was the willingness to go beyond the template: to spend a weekend reading the client’s SEC filings from five years back, to call twelve industry contacts and synthesise what they heard, to argue with each other until the analysis said something the client could not have produced alone. AI has made the template-level work almost free, which should in theory liberate teams to spend more time on the genuinely original thinking. In practice, the economics run the other direction. If AI can produce an 80% draft in two hours, the engagement manager ships the 80% draft. The remaining 20%, the part that required judgment, experience, and actual intellectual commitment, gets trimmed because the utilisation model does not reward the extra time it takes to produce it.

That brings us to what made the whole exercise feel slightly absurd. Before the three pitches, I had coffee with two members of the client’s internal strategy team. They are a group of four: two former consultants (one ex-McKinsey, one ex-Deloitte), an industry veteran with fifteen years in the sector, and a data analyst who had built a set of automated models on their company’s operational and financial data. They had already produced a 40-page draft analysis of the portfolio. It included granular unit-level economics that none of the three pitching firms could access without six weeks of data requests. It incorporated scenario modelling that covered more permutations than any of the firms’ proposed Phase 2 workstreams. And it had something none of the external firms could offer: the internal team knew which plant managers would resist a divestiture, which union contracts contained change-of-control provisions, and which business units had undocumented customer relationships that would not survive a transfer.

The client was running the advisory selection because the board wanted external validation. The CEO told my friend as much: “We know what the answer is. We need a name on the cover.” That is the insurance policy theory of hiring consultants (a subject for another post in this publication), and it is rational behaviour on the CEO’s part. But it means the three firms were competing to provide a branded stamp of approval on analysis that had already been done, more thoroughly, by four people who actually understood the business.

The fees proposed ranged from £800,000 to £1.4 million. The internal team’s cost for producing the superior analysis was their existing salaries and roughly £15,000 in software subscriptions.

I left the final pitch early. On the way out, I passed the engagement manager from Firm B in the hallway, rehearsing talking points on her phone. She looked tense. I recognised the expression from fifteen years of watching my own teams prepare for competitive pitches: the mixture of performance anxiety and the quiet awareness that what you are about to present is, in every way that matters to the client, indistinguishable from what the competitors presented an hour ago.

She will probably make partner in a few years. She is good at her job. The job has just stopped requiring anything that the other firms’ people cannot do equally well.

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When was the last time you saw a genuinely differentiated pitch from a Big 4 or MBB firm? Not a better deck or a smoother partner. A fundamentally different way of thinking about the client’s problem. If you can name one, we would like to hear about it. If you cannot, that is the point.