— Talent & Leadership
Learns what separates your strongest people from the rest, ranks the factors that genuinely predict performance, and turns the result into a hiring profile and a development profile you can act on.
1–2 weeks → ~15 minutes
For a full population, not a sample
No coding required
— USE CASES
Identifies characteristics associated with strong performance in the existing workforce and produces an evidence-based profile to inform hiring criteria. Keeps observed associations distinct from proven predictors of future success.
Produces a development profile grounded in the differences between higher-performing employees and their peers. Gives talent teams a clearer basis for discussing development priorities and areas that warrant further investigation.
Examines whether factors such as tenure, engagement, prior industry and internal hiring are associated with the chosen performance outcome. Gives leadership teams evidence to challenge or qualify familiar explanations of success.
Assesses how closely employees match patterns associated with the defined outcome. Provides a comparative view to support talent reviews alongside managerial judgement and wider context.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Each row of your export is processed on the same basis, so no person is skipped however long the table is.
Findings on the talent population are written up as a document that reads like professional output, with each claim tied back to a person.
Detail rows are summarised into the grouped view of the talent population without losing the underlying people.
High performance is often explained through anecdotes or assumptions about what successful people have in common. Defining a hiring profile is the typical trigger — identifies characteristics associated with strong performance in the existing workforce and produces an evidence-based profile to inform hiring criteria. Keeps observed associations distinct from proven predictors of future success. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 1–2 weeks of manual work.
As a Skill, the work is already sequenced. You bring the evidence, and the run produces summary of characteristics associated with high performance plus analysis of relationships between workforce factors and the defined outcome. 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. Net effect: 1–2 weeks down to ~15 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
High-performer profile finder 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.
