Pyramid Principle
An executive-communication structure, associated with Barbara Minto's work at McKinsey in the 1970s, that leads with the conclusion or the single most important fact before providing supporting detail, in contrast to a build-up structure that arrives at a conclusion only after extensive background.
Defined in 3 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in Certified AI Data Governance Professional (CADGP).
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
An executive-communication structure, associated with Barbara Minto's work at McKinsey in the 1970s, that leads with the conclusion or the single most important fact before providing supporting detail, in contrast to a build-up structure that arrives at a conclusion only after extensive background.
Barbara Minto's answer-first communication method developed at McKinsey in the 1960s: lead with the answer, group supporting points, then provide evidence beneath each; the standard structure for executive communication.
A top-down writing structure described by Barbara Minto, stating the governing idea first, then grouping supporting arguments beneath it, each summarized before its own detail follows.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Prompt Template Library for Communication Scenarios · Practical AI Workflow Design and Prompt Engineering, Certified AI Practitioner: Workplace Foundations
- Data literacy for the C-suite: the briefing that changes what leadership asks for · The Humans of Data, Certified AI Data Governance Professional (CADGP)
- Engineering writing: reports a non-engineer can act on · Design Reviews and Engineering Communication, Engineering Judgment and Professional Formation
Where it shows up at work
A definition is where Pyramid Principle starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Turns technical uncertainty into a one-page decision: material risks, trends, exceptions, remediation, and what the board is being asked to accept.
2 lessons on this page teach it as a primary outcome.
Briefs a model like a good manager: context, constraints, examples, verification, and knows when to stop delegating.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- Chief AI Officerneeds it at depth
- Chief Audit Executive, AI audit editionneeds it at depth
- Chief Risk Officer, AI risk editionneeds it at depth
- VP of AI Governance and Ethicsneeds it at depth
- Chief Compliance Officer, AI compliance editionneeds it at depth
- Chief Data Officer, data leadership editionneeds it at depth
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
One interview question about it
Brief a board on an AI risk in two minutes. What do you say, and what do you leave out?
Asked of candidates for executive and board communication on ai risk. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Internal audit and IT audit carries it as a claim to back up: Audit committee reporting is part of senior audit roles.
- Nonprofit program and grants oversight carries it as a claim to back up: Board and funder reporting is the cadence a governance committee needs.
- A business, MBA or technology management degree carries it as work you can show: Executive briefs and presentations are your assignments.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.