A working paper for founders who can't write a $2,000,000 check — and shouldn't have to, to think at that level.

The Method Was Never the Secret

McKinsey generates roughly $16 billion a year. Not because it hires people smarter than you — its median hire is a 26-year-old with a good GPA and zero industry experience. What McKinsey actually does is take that 26-year-old and spend two years installing a set of analytical frameworks into how they think, until running them is instinct.

By the time that person sits across from a CEO, they aren't winging it. They're executing a methodology refined across fifty years and tens of thousands of engagements — and none of it is secret. Minto published the Pyramid Principle. Porter published Five Forces. Kaplan and Norton published the Balanced Scorecard. Martin and Lafley published Playing to Win. The intellectual infrastructure of elite consulting has been sitting in business school libraries for decades.

The barrier was never access to the ideas. It was the time and organizational muscle required to operationalize them on a live problem, under deadline pressure, for your specific situation — with nobody but you to do it.

That's the barrier this removes. What follows is 13 Claude skills — 12 built directly on the frameworks strategy consultancies train into their people, plus one they don't have to teach because their org chart already does it for them. Not paraphrased, not dumbed down: the intellectual foundation, the method, and a prompt built to actually run it on your business, not a generic one.

This is written for one kind of reader: the founder who is building something meant to last, doing it mostly alone, and who has better use for $2,000,000 than a slide deck. If that's you, keep going.

What $2,000,000 Actually Buys

Strip away the brand, and a McKinsey-style engagement is three things: a team of analysts running a known methodology, on your timeline, with a partner's judgment layered on top. Two of those three things are now available to anyone with a laptop. The third — judgment, and someone's professional reputation staked on the call — is still not for sale at any price. Keep that distinction in mind for the whole rest of this piece; it's the difference between what this stack replaces and what it doesn't.

Bars are square-root scaled within each panel so both ends of a 100,000× range stay legible on the same page. Read the labels, not the visual ratio.

The Operating System

Twelve skills, four phases, one check that runs after every single one of them. This is the shape of every hard founder decision — a fundraise, a pivot, a hire, a shutdown call — whether you draw it out or not. The stack just makes each step explicit enough to actually run.

DIAGNOSE

Find out what's actually true before you decide anything.

DECIDE

Commit to a choice, and to what that choice rules out.

EXECUTE

Turn the choice into dates, owners, and metrics.

COMMUNICATE

Get other people to fund it, join it, or approve it.

The 13 Skills

Condensed here for reading; the copy-and-paste-ready version of every prompt below ships in the attached Prompt Pack, and the installable Claude Skills ship in the attached .zip. Feed each one your real numbers, real transcripts, real documents — the frameworks are only as sharp as what you hand them.

DIAGNOSE

01 — Problem Framing

McKinsey Issue Tree + Minto's Situation-Complication-Question

USE WHEN Your problem statement is really a solution wearing a disguise ("we need more growth", "we need to raise", "we need a better website").

WHY THIS WORKS

Most founders skip straight to solving. Consultants are trained to distrust the first version of a problem, because it usually smuggles in an answer. A presenting problem gets decomposed into a MECE tree of 3–5 genuinely distinct hypotheses about the root cause — mutually exclusive, collectively exhaustive — and only then does the real problem statement get written, using Barbara Minto's three-part structure: the Situation (what's true now), the Complication (what changed or is threatening), and the Question (the decision this actually forces).

METHOD

  • Break the presenting problem into 3–5 branches, each a distinct root-cause hypothesis — not shades of the same idea.

  • For each branch, name the one assumption that has to be true for that branch to be the real problem.

  • Apply the "so what" test: if this branch is true, does the solution actually change? If not, the branch is decoration.

  • Flag which branch is falsifiable with data you can get in the next 48 hours.

  • Rewrite the problem using Situation → Complication → Question — and check the tree for overlap or gaps (MECE audit) before trusting it.

FAILURE MODE TO WATCH FOR

A tree that only looks MECE. Branches quietly overlap, or one whole category of explanation (often: "the team", or "my own decisions") never appears because it's uncomfortable. Make the audit step mandatory, not optional.

02 — Financial Modeling & Value Drivers

McKinsey Value Driver Tree (Koller, Goedhart & Wessels) + tornado sensitivity analysis

USE WHEN You're about to build a spreadsheet before you know which 2–3 numbers actually move the outcome.

WHY THIS WORKS

The standard McKinsey valuation logic holds that a business's worth reduces to free cash flow, its growth rate, and the cost of capital discounting it — everything else (revenue, EBITDA, logos) is either a driver of those three or noise. The value driver tree maps the causal chain from an operational lever (pricing, churn, CAC, capital intensity) down to enterprise value, so that sensitivity analysis can be run on drivers instead of line items — and the model gets built around the 2–3 levers that actually matter, instead of forecasting every row with false precision.

METHOD

  • Build the value driver tree from the outcome (enterprise value, runway, or whatever the decision hinges on) down to operational levers — 3–4 levels deep.

  • Assign each leaf-level driver a base case and a realistic range, not just an optimistic and a pessimistic guess.

  • Run a conceptual tornado: move each driver one standard deviation, holding everything else at base case, and rank by the swing it produces.

  • Take the top 2–3 drivers — these are your value levers. Everything else in the model can stay simple.

  • Cross-check: are those levers actually within your control? Or did the model just discover a fantasy (high margin AND high reinvestment, simultaneously)?

FAILURE MODE TO WATCH FOR

Building the full model before the tree. A beautifully precise spreadsheet that answers the wrong question is still the wrong answer — just harder to challenge because it looks rigorous.

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