ProHance AI-Powered Insights: Preventing Employee Disengagement and Retention Risks

  • Employee disengagement and attrition remain critical challenges for businesses worldwide.
  • High performers are nearly 47% more likely to leave, and replacing an employee can cost up to 33% of their annual salary.
  • ProHance leverages Machine Learning (ML) and AI-powered analytics to proactively identify disengagement and retention risks before they escalate.
  • This helps businesses retain top talent and boost workforce productivity.

ProHance Workflow Demo

Identifying Disengagement Before It’s Too Late

Traditional methods of identifying disengagement rely heavily on manager intuition, surveys, and post-facto evaluations. These approaches are subjective and often fail to provide timely, actionable insights.
ProHance changes the game by using real-time system usage data to track employee engagement levels based on:

Idle time trends

Idle time
trends

Absenteeism patterns

Absenteeism
patterns

Time spent away from the system

Time spent away
from the system

Non-productive vs. productive work hours

Non-productive vs.
productive work hours

Historical work behavior

Historical work
behavior

By analyzing workforce patterns over three-month intervals, our AI models predict attrition risks and flag disengaged employees, allowing HR and leadership teams to take proactive action rather than react to costly turnover.
Disengaged employee also contribute to an organization's latent capacity, even if their risk to resign is low. Engaging employees with meaningful work and consistent interventions will add to organization's overall productivity goals.

AI-Powered Retention Risk Analysis

How ProHance's AI-Powered Retention Risk Works?

  • Categorizes employees by engagement level to enable timely intervention.
  • Uses machine learning to detect early signs of disengagement.
  • Predicts retention risk by correlating trends with past attrition data.
  • Delivers actionable insights for proactive re-engagement.
  • Helps shift medium-risk employees to low-risk, reducing costs and improving productivity.

Get multiple cuts and slices of the data by tenure, location, and user roles for a deeper analysis

Data analysis by tenure and location

Proven Impact: Reducing Attrition and Increasing Productivity

A real-world analysis using ProHance's AI models found that:

  1. 12% of employees were categorized as high-risk for attrition.
  2. 29% of employees flagged as high-risk actually resigned, marking the accuracy of this model at 90 - a gold standard.
  3. Organizations using ProHance's proactive approach saved substantial costs on rehiring, retraining, and lost productivity.

With millions of workforce data points processed across multiple industries and geographies, ProHance provides one of the most precise and accurate workforce engagement insights available today.

Current Disengagement Pie Chart

Why ProHance?

AI-Driven Precision

AI-Driven Precision

Advanced ML models trained on clean, labelled workforce data. Any AI/ML model is as good as the quality of the data. ProHance's accurate, irrefutable, and empirical data is the real gold mine.

High attrition isn't just a workforce challenge—it's a business risk. With ProHance's AI-powered disengagement and retention risk insights, organizations can take a proactive approach to talent management, ensuring a more engaged, productive, and stable workforce.

Discover how ProHance can help
your business retain top talent

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