Predictive model to reduce attrition

Goal

To substantially reduce voluntary agent departures, particularly among those who have worked with us for more than 90 days.

Goal

To substantially reduce voluntary agent departures, particularly among those who have worked with us for more than 90 days.

Strategy

  • Developing a highly effective predictive model that calculates a risk score for each agent and identifies the factors that contribute to their risk of leaving.
  • Quickly identifying agents who are at high risk of leaving and taking targeted preventative action

Strategy

  • Developing a highly effective predictive model that calculates a risk score for each agent and identifies the factors that contribute to their risk of leaving.
  • Quickly identifying agents who are at high risk of leaving and taking targeted preventative action

Highlights

  • Assigning a unique probability score to each agent, enabling us to manage each agent more effectively.
  • Categorizing agents into different programs and hierarchical tiers, making it easier to prioritize intervention measures.

Highlights

  • Assigning a unique probability score to each agent, enabling us to manage each agent more effectively.
  • Categorizing agents into different programs and hierarchical tiers, making it easier to prioritize intervention measures.

Results

We are proud to report a significant decrease in monthly attrition rates by 0.8 percentage points, which has positively impacted our absenteeism rates. Our proactive approach has proven to be highly effective in retaining valuable agents and improving our overall performance.

Results

We are proud to report a significant decrease in monthly attrition rates by 0.8 percentage points, which has positively impacted our absenteeism rates. Our proactive approach has proven to be highly effective in retaining valuable agents and improving our overall performance.

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Cases

Anomaly detection to optimize operations

Salesforce implementation for Enhanced Courier Services

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