HR & Talent500+ (Mid-market)Cross-industry

Turnover prediction

Identify employees at risk of leaving using multiple HR signals.

ROI ★★★★☆Complexity ●●○○○3-6 months500+ (Mid-market)

The problem

No reliable steering on turnover prediction.

The current process is manual or inconsistent.

Decisions come too late due to weak signals.

People risk rises (turnover, absence, costs).

Prerequisites: required data & tools

Required data

  • HRIS
  • évaluations
  • mobilité interne
  • absentéisme

Compatible tools

  • Visier
  • Peakon
  • custom ML (Python)

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What we implement in 3-6 months

In 3-6 months: Identify employees at risk of leaving using multiple HR signals. with measured impact on turnover reduction.

Weeks 1-2

Diagnosis

Weeks 3-6

Build

Week 7+

Delivery

Concrete deliverables

Business framing and decision rules for turnover prediction

Operational engine for turnover prediction

Steering dashboard with alerts

Action playbook and governance

Expert insight

Cost of a departure = 6–9 months of salary. Sensitive topic: GDPR and ethics must be addressed.

— Datasive, expertise terrain

Tech maturity

High

Mature solutions, fast deployment

Medium

Maturing tech, requires customization

Emerging

Cutting-edge innovation, R&D approach

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Ready to solve this problem?

First step: a 30-minute call to understand your context.