People Analytics: Proactively Addressing Agent Attrition

Harnessing machine learning to spotlight agents at risk of voluntary departure. 

Goal

Significantly curtail voluntary agent departures, specifically among those with over 90 days of tenure.

Goal

Significantly curtail voluntary agent departures, specifically among those with over 90 days of tenure.

Strategy

  • Devised a predictive model that not only allocates a risk score to each agent but also elucidates the significance of influencing factors.
  • By spotlighting agents with pronounced attrition risks, targeted preventative strategies are promptly initiated.

Strategy

  • Devised a predictive model that not only allocates a risk score to each agent but also elucidates the significance of influencing factors.
  • By spotlighting agents with pronounced attrition risks, targeted preventative strategies are promptly initiated.

Highlights

  • Our innovative model confers a unique probability score on every agent, facilitating individualized management.
  • By classifying agents into distinct programs and hierarchical tiers, we streamline the process of prioritizing intervention measures.

Highlights

  • Our innovative model confers a unique probability score on every agent, facilitating individualized management.
  • By classifying agents into distinct programs and hierarchical tiers, we streamline the process of prioritizing intervention measures.

Results

We’ve registered a substantial dip in monthly attrition rates by 0.8 percentage points, which concurrently produced a favorable ripple effect on absenteeism rates.

Results

We’ve registered a substantial dip in monthly attrition rates by 0.8 percentage points, which concurrently produced a favorable ripple effect on absenteeism rates.

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