— Organisation & Workforce

Talent Flight Risk Radar

Keeps a standing read on the risk universe in scope, working through risk registers, controls and policy documents on a regular cycle to show where each risk stands, what has moved since the last run and which items now need an owner's attention.

  • Organisation & Workforce
  • Traceable reasoning
  • Runs anywhere
Preview methodology

2–3 weeks → ~25 minutes

For a full population, not a sample

No coding required

Input
Employee names and departments
Output
Individual departure-risk bands with the clearest recorded contributing factor
Runs in
Skillsize · ChatGPT · Claude · Copilot
Export
SKILL.md · MCP
Time saved
~2–3 weeks per run

— USE CASES

What people use Talent Flight Risk Radar for

Focusing manager retention conversations

Identifies employees with elevated departure risk and the clearest recorded contributing factor. Gives managers a specific basis for a supportive retention conversation.

Understanding departmental risk patterns

Shows how assessed departure risk is distributed across departments. Helps leadership distinguish concentrated concerns from broader workforce trends.

Tracking changes over time

Maintains a period-by-period history of assessments, making increases, reductions and persistent concerns visible.

Briefing leadership on retention

Provides a one-page leadership summary of current risk and departmental patterns. Limits personal identifiers in reporting to employee name and department.

What it works from

  • Employee names and departments
  • Tenure and time since last role move
  • Engagement scores and missed one-to-one counts
  • Pay position measures and nearby recent departures

What you get back

  • Individual departure-risk bands with the clearest recorded contributing factor
  • Period-by-period assessment history
  • Department-level risk charts
  • Manager retention-conversation prompts for elevated-risk employees named in the assessment under applicable access controls and review policies, without assuming intent to leave or recommending punitive action. These prompts should be used to offer voluntary support and understand workplace concerns, not to make disciplinary, dismissal, compensation, promotion, or other consequential employment decisions based on predicted flight risk alone. Human review should check data quality, context, fairness, and privacy before any employee-facing action. The assessment should not infer protected or sensitive traits, use covert monitoring, or treat engagement scores and missed meetings as reliable proof of an intention to resign. Outputs should communicate uncertainty and allow correction of inaccurate records.

— HOW IT BEHAVES

How Talent Flight Risk Radar produces its result

The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.

Every row of the risk universe in scope

Each row of your export is processed on the same basis, so no risk is skipped however long the table is.

The pattern charted

Movement across the risk universe in scope is visualised from the computed data, so the trend is legible at a glance.

Composed as work product

Findings on the risk universe in scope are written up as a document that reads like professional output, with each claim tied back to a risk.

Each risk enriched in place

Derived columns are added row by row, keeping your source data and the judgement about each risk side by side.

Roll-up alongside risk-level detail

Detail rows are summarised into the grouped view of the risk universe in scope without losing the underlying risks.

Why this is expensive by hand

Retention concerns often sit across disconnected workforce measures, making it difficult to distinguish isolated signals from a wider pattern. In practice it shows up as focusing manager retention conversations: identifies employees with elevated departure risk and the clearest recorded contributing factor. Gives managers a specific basis for a supportive retention conversation. 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.

How this Skill produces it

Skillsize turns that work into a Skill: you supply the material, and what comes back is individual departure-risk bands with the clearest recorded contributing factor, with period-by-period assessment history. What sits between input and output is the codified method: thresholds, sequencing and the points where a human confirms a call — all of it visible and editable in the Skill. The practical effect: 2–3 weeks of manual work becomes a ~25 minutes run, held to an identical standard on the tenth engagement as on the first.

Who it's for

  • Org design and workforce planning leads
  • COOs and functional leaders reshaping teams
  • Transformation consultants sizing people impact
  • HR business partners supporting redesign

Run it in Skillsize — or export it anywhere

Talent Flight Risk Radar 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.

ChatGPTClaudeCopilotAI Products (MCP)