Proof
/ Supply Chain & LogisticsAI Model for Employee Churn Prediction for a $400M Logistics Company
Business situation
A $400 million logistics company with high employee turnover driving up training costs, disrupting operations, and destabilising service delivery.
The challenge
No predictive capability to identify at-risk employees before they resigned, and no visibility into the pay, management, and benchmarking factors driving turnover.
Why it matters
Quantum Rise built predictive churn models using four years of historical data, deployed an HR analytics dashboard pinpointing top turnover drivers, and enabled proactive leadership interventions.
What Quantum Rise delivered
The QR/OS™ approach in practice
- • Predictive employee churn model using 4 years of historical data • HR Analytics Dashboard with risk classification and turnover driver visibility • Pay gap, manager impact, and salary benchmark analysis • 400+ employees analysed monthly across 12+ metrics • Cost savings business case modelling
Measurable outcome
17% reduction in employee churn in less than 3 months. 92% precision in identifying potential churn risks. 400+ employees analysed monthly across 12+ metrics.
Proactive leadership interventions enabled, workforce stability improved.
What became repeatable
A reusable HR churn prediction platform: 4-year data model + risk classification dashboard + intervention playbook applicable to any logistics or service-intensive business.