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Flight Risk Score

Predictive score for employee departure probability

How it’s computed

MODEL(features)

What the evidence shows

Evidence (effect sizes, priors, validity) is syncing from Principia.

What this metric can show you

Flight Risk Score can tell roughly 27 pre-built stories — each a designed scene the data either confirms or it doesn’t. Bring your numbers and the Story Finder runs every one of these shapes against them.

specific to engagement & retention

Engagement is eroding

engagement · T1

ABCDE

It's two companies, split by manager

leadership-quality · T1

Most are fine — a tail is struggling

engagement · T1

On this trajectory, you breach the benchmark

regretted-loss · T1

ABCDE

One condition is the binding constraint

cams · T1

ABCDE

One exit reason towers over the rest

exit-knowledge · T1

Retention is working

retention · T1

P1P2P3

The workforce is splitting in two

engagement · T1

Top talent is quietly leaving

regretted-loss · T1

universal shapes — any single metric can take these

A few large values are doing the talking

any focus · T1

A one-time event, not a trend

any focus · T1

It doesn't track — the premise is false

any focus · T1

ABCDE

It's concentrated — one group stands apart

any focus · T1

Scenes are pre-built; your data is the toggle. Browse the full deck or watch one play end-to-end in The Quiet Exodus.

Run it on your data

This metric is computed in the People Analytics Toolbox on your own numbers. See pricing — posted, no quotes.

sources: toolbox:metrics-catalog

What the literature says

The measurement literature behind this signal — sourced, so you can defend it.

  • In the table below, PETA computes risk scores for each employee and sums them into high risk groups, such as age groups, potential groups, salary groups, gender groups, tenure groups, performance groups. (1) Flight Risk Scoring [image "Flight risk scoring table"…

    Predictive HR Analyticsmatch 68%

  • One of the hottest areas in business is the ability to predict critical organizational risks such as key employee turnover, work accidents or absenteeism. (1) Instead of the usual reporting groups such as section, department or business unit, predictive employee turnover…

    People Analytics Text Mining with Rmatch 65%

  • Line managers wants to know what problems or opportunities will happen in the future, so that they can work to prevent them from occurring – this is where predictive employee turnover analytics (PETA) can add value. One of the hottest areas in business is the ability to predict…

    Predictive HR Analyticsmatch 63%

Resources: Predictive HR Analytics · People Analytics Text Mining with R