Executive appointment decisions
Assess a leader against the calibrated bar for the role rather than against the last person interviewed.
— Talent & Leadership
Grades an individual leader's evidence against a reusable calibrated Blueprint, producing comparable verdicts across assessors and time.
30–45 minutes → ~3 minutes
For one document, brief or record at a time
No coding required
— USE CASES
Assess a leader against the calibrated bar for the role rather than against the last person interviewed.
Ensure two assessors reach comparable conclusions because they use the same Blueprint.
Compare leaders assessed across a hiring cycle on identical dimensions.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Each leader is assessed against explicit criteria you control, so the same standard is applied across the leadership population on every run.
The run produces a calibrated standard you can reapply to future leaders.
The run works from assessment, review and performance evidence you supply, so conclusions about the leadership population are anchored to your evidence rather than general model knowledge.
One leader, one calibrated Blueprint, one consistent verdict. In practice it shows up as executive appointment decisions: assess a leader against the calibrated bar for the role rather than against the last person interviewed. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 30–45 minutes of capacity for it.
Here the same job runs as a Skill. Your material goes in; a dimension-by-dimension match against the Blueprint comes out, alongside named strengths and gaps with evidence. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. The practical effect: 30–45 minutes of manual work becomes a ~3 minutes run, held to an identical standard on the tenth engagement as on the first.
Leader vs Blueprint exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
Builds evidence-backed employee skills profiles within HR systems, mapping documented experience to the organisation’s skills catalogue and assigning proficiency levels using consistent rules.
Assesses how clearly people explain their technical work against a consistent four-level rubric, producing a human-approved report with quoted evidence behind every score.
Reveals how organisational culture is lived through anonymous employee accounts, producing an evidence-backed diagnostic of shared themes, differences between functions and gaps between values and practice.
Turns a high-potential's assessment evidence into an acceleration plan weighted to real experience and exposure, naming the stretch assignments, mentors and programmes that will compound fastest.
Builds a calibrated, reusable benchmark from source material so every later screen, shortlist or review is graded against the same bar.
Screens candidate evidence against a saved Blueprint, applying the same calibrated bar and traceable reasoning to every applicant.