Structural decisions with evidence
Show the role-level basis for a design or headcount decision instead of defending a judgement call.
— Organisation & Workforce
Sentiment Analysis reads every comment against eight fixed themes — Leadership, Manager, Workload, Recognition, Career growth, Pay and benefits, Culture, Wellbeing — scoring each theme only where it is actually mentioned, so a comment that praises the team but slates the workload is recorded as both.
2–3 weeks → ~40 minutes
For a full population, not a sample
No coding required
— USE CASES
Show the role-level basis for a design or headcount decision instead of defending a judgement call.
Apply the same criteria to every part of the organisation in scope, so functions are genuinely comparable.
Re-run against updated org data each cycle and see what actually moved.
— 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 role is skipped however long the table is.
Movement across the organisation in scope is visualised from the computed data, so the trend is legible at a glance.
Findings on the organisation in scope are written up as a document that reads like professional output, with each claim tied back to a role.
Detail rows are summarised into the grouped view of the organisation in scope without losing the underlying roles.
Work on the organisation in scope normally means pulling org data, role documentation and headcount exports together by hand, then applying a standard that only exists in the head of whoever is doing it. In practice it shows up as structural decisions with evidence: show the role-level basis for a design or headcount decision instead of defending a judgement call. It is the kind of work that decides whether a recommendation survives scrutiny — and the kind that quietly eats 2–3 weeks of senior time whenever it comes round.
Here the same job runs as a Skill. Your material goes in; a role-level view of the organisation in scope with the reasoning attached comes out, alongside a roll-up for leadership at the level you report at. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. Net effect: 2–3 weeks down to ~40 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Employee engagement & culture diagnostic 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.
Workforce capacity planner
The scenario model recalculates required FTE, the gap against headcount and utilisation for every row under nine named scenarios — base, P50 / P90 / P95 absence, demand +10% / +20%, a productivity dip, an attrition-adjusted view and a combined downside — and flags every team-period where the gap turns positive.
Workforce Plan
Builds the core workforce plan by comparing what a strategy requires against current workforce and skills evidence, expressed as roles and capability gaps.
Workforce scenario comparison
Runs gap analysis for base, upside and downside workforce scenarios against org and skills evidence, bucketing and comparing what changes between them.