What It Does

This project tests the “Stagnation Hypothesis”—the idea that people leave because they aren’t moving up. Using the IBM HR dataset, I analyzed the attrition rates of high potential employees based on their time since last promotion.

The Problem It Solves

Companies often view promotions as a “Retention Lock,” assuming a promoted employee is safe for at least 2 years. This false sense of security leads to a lack of support during the critical transition period.

How It Works

I performed a cohort analysis using Python (Pandas), segmenting high performers into “Stagnant” (>2 years without promotion) and “Propelled” (<2 years since promotion) groups and calculating their respective flight risk.

Key Findings

  • The Promotion Paradox: “Propelled” high performers had a 17.0% attrition rate, compared to 13.7% for their “Stagnant” peers.
  • Title Shopping: New titles make employees significantly more marketable to external recruiters.
  • The Valley of Despair: The stress of a new role combined with “Mission Accomplished” syndrome increases vulnerability to poaching.

Results / Impact

Reframed the internal mobility strategy to include “Post-Promotion Onboarding” programs, treating internal movers with the same care and support structure as new external hires.

Tech Stack

LayerTechnology
AnalysisPython (Pandas)
VisualizationMatplotlib
DataIBM HR Analytics Dataset

Stagnation Heatmap