What Would Elon Do?

Sit in almost any conversation about business strategy these days — a board meeting, a leadership offsite, the LinkedIn post you scrolled past this morning. Sooner or later, someone reaches for the same small handful of names. Either Nadella on transformation or Huang on the courage to make big bets, Zuckerberg on holding a position under attack or Cook on operational rigour. The names have become a kind of shorthand for what good strategy is supposed to be.

They are impressive businesses. But it's worth asking a question that the conversation almost never does: whether the logic that carried them to the top has anything useful to say to the rest of us.

I've come to think it mostly doesn't — and that there are four reasons why, which together point somewhere far more interesting.

The room is smaller than it looks

In 2024, the agency Golin worked through 2.3 million data points across 250 of the largest companies in the Fortune 500. When they looked at who was shaping the conversation about leadership and AI, they found that the top ten chief executives — almost all of them from technology — accounted for around 40 per cent of all the coverage across those 250 companies. Four per cent of the group generating something close to half of the attention.

Step back and the picture gets starker. The seventeen or so individuals who really anchor the leadership conversation — Nadella, Huang, Zuckerberg, Cook, Amodei, Jassy, C.C. Wei at TSMC, Hock Tan at Broadcom, Christophe Fouquet at ASML, and a few more — between them run companies worth around $25 trillion. Set that against total global listed market value of roughly $110 trillion, and you find that seventeen people are running close to a quarter of everything publicly traded on earth.

There is nothing wrong with finding them interesting. The mistake is treating them as the instruction manual.

The manual was written for a different building

The trouble is that the strategies we admire in these companies tend to compound from a starting position — and it's the position that makes the strategy work, rather than the other way round.

Meta's logic, where more users create more connections and more connections create more value, only holds once you already have the users. Nvidia's CUDA platform built from 2006, years before anyone could see why it mattered — only became decisive when deep learning arrived in 2012 and turned out to need precisely the kind of computing Jensen Huang had quietly spent the previous six years constructing.

TSMC's grip on advanced manufacturing rests on forty years of Taiwanese industrial policy that no competitor can simply decide to replicate. Tim Cook inherited the iPhone and its supply chain at the exact moment they became the most valuable machine in business history.

None of these is an insight you can lift and carry home. They are strategies welded to a position, and the position itself was built out of timing, geography and structural advantage that no longer exist in the same shape.

This is the part that gets missed. What works when you're the giant rarely works when you're the challenger — they aren't the same problem dressed up at different sizes. Almost all the leadership content in circulation is written for the giants, yet most of the people reading it are challengers. We rarely say this out loud, and it costs us.

Then there's luck

There's a third element that rarely makes it into the coverage, and I think for two reasons. One is that luck is uncomfortable to talk about, because admitting it means admitting the rewards weren't entirely earned. The other is that these stories are told backwards, from the outcome — and by the time you're writing the ending, the luck has quietly been edited out of it.

Luck plays a far bigger part in leadership success than we tend to allow. Not luck in the sense of a coin landing the right way, but something more interesting and more demanding than that: a set of conditions that certain leaders manage to create around themselves, often without quite realising they're doing it. Why that happens, and what it actually asks of a person to hold a position before the outcome is clear, is a thread that runs through every case in this series — and one I'll give an article of its own. The research is stranger than you'd expect, and the human challenge harder.

The short version: Nvidia had CUDA ready when the moment came, not because Huang foresaw deep learning, but because he'd committed to that position six years before it arrived and was still standing on it when fortune did. SpaceX survived on its fourth launch attempt, with the company nearly out of cash; Musk has said openly there might not have been a fifth. Zuckerberg happened to be building a social network at the highest-status university in the world at the precise moment broadband made photo-sharing take off.

In each case the luck was real — and so was the decision to be in position when it landed. What it takes to make that decision, to stay with a bet while the outcome is unknown and every pressure pushes you to move, turns out to be less a question of strategy than of character.

The cases worth looking at instead

There are companies that have answered that question rather well, mostly without ever appearing in anyone's keynote.

Fever-Tree was started in 2003 by two people who noticed something simple: premium spirits had been multiplying for a decade, while the mixer sitting next to them in the glass was still commodity Schweppes. They built a category by believing it ought to exist. By 2024 the brand was turning over £364 million, holding twenty-seven per cent of the US tonic water market and standing four times larger than its nearest premium rival on American shelves.

Mistral AI was founded in June 2023 — more than a year after ChatGPT, by which point any sensible reading said the window had closed. Rather than try to out-compute OpenAI, they went after the dimension where sheer scale becomes a liability rather than an asset: European businesses and governments for whom routing sensitive data through American infrastructure is a compliance problem, not a preference. By early 2026 they were at around $400 million of annual recurring revenue and a valuation approaching €20 billion. Three years old.

Vinted began in Lithuania in 2008, when one of its founders was moving house and simply wanted to sell the clothes she no longer wore. It is now the largest clothing retailer by volume in France — ahead of Amazon — on revenue of €1.1 billion.

Different sectors with different starting points in different decades. The same underlying move every time: each found the dimension where the dominant player couldn't or wouldn't follow, and then had the discipline to stay there.

What this series is for

"The Other $85 Trillion" is meant literally, take out the value held by those seventeen companies and you're left with the overwhelming majority of the world's listed businesses — and that's before you reach the 400 million or so private firms and SMEs who never show on a market index at all. That is where almost everyone reading this actually works, and it deserves a strategy conversation of its own.

Three ideas run through everything that follows. The first is to know whose playbook you're reading: the examples worth learning from are the ones structurally close to your own situation, not the ones that happen to be famous. The useful question was never 'what would Nadella do?' — it was 'who succeeded from roughly where I'm standing?' The second is to know which side of that line you're on. What works when you're the giant rarely works when you're the challenger, and the coverage quietly assumes you're the giant when most of us are not. The third is to position for luck rather than copy it: the particular moments those seventeen caught will not come round again, but the ingredients of luck — specificity, patience, a willingness to sit at the right intersection long enough — are open to everyone.

Over the coming pieces I'm going to take the challenger cases apart properly: what made each one work as strategy, what it cost the people involved to hold their position before the outcome was clear, and what all of it suggests for organisations that will never enjoy years of spare cash flow to fund the wait.

The question underneath the whole series is this. Once you strip away the position, the timing and the capital — what exactly is left that you'd call the strategic insight? That's what I want to find out.

Key references and inspiration

Golin, CEO Impact Index (2024) — the data behind the concentration of leadership and AI coverage among Fortune 250 CEOs.

FTSE Global All Cap Index / Siblis Research — global listed market capitalisation, end-2025, used as the basis for the $110tn / $85tn estimate.

Company filings and annual reports: Tate & Lyle, Siemens, Hasbro, Fever-Tree, Birkenstock, Vinted, Mistral AI, Nvidia — individual market caps and financial figures as reported in company communications and primary financial press, end-2025/early-2026.

Phil Rosenzweig, The Halo Effect (2007) — on how success narratives are constructed backwards from the outcome.

Robert H. Frank, Success and Luck: Good Fortune and the Myth of Meritocracy (2016) — on the underacknowledged role of luck and timing in competitive outcomes.

Richard Wiseman, The Luck Factor (2003) — on the behavioural patterns associated with people and organisations that are consistently fortunate.

Clayton M. Christensen, The Innovator's Dilemma (1997) — the structural diagnosis this series builds on and departs from.

Opening article — The Other $85 Trillion series | redebuter.com #Leadership #Strategy #Innovation #Redebuter