Employee Retention Analytics

Dashboard

Executive overview of workforce health with key retention metrics, risk distribution, and trend charts. Covers overall retention rate trend, risk distribution (low/medium/high/critical), attrition cost summary and department-level comparisons.

Employee Data

Master employee database with demographic, role, compensation, and tenure information. Covers employee demographics and role info, compensation and benefits data, tenure and performance history and manager and department mapping.

Engagement Metrics

Tracks engagement survey results and behavioral indicators that correlate with retention. Covers survey scores by dimension, enps (employee net promoter score), participation rates and period-over-period trends.

Turnover Risk Scoring

Predictive scoring model that identifies employees most at risk of voluntary departure based on multiple factors. Covers multi-factor risk score calculation, tenure, compensation, engagement weighting, risk category assignment and watch list generation.

Attrition Cost Analysis

Quantifies the full cost of employee turnover including direct and indirect costs. Covers recruitment cost per hire, training and onboarding costs, lost productivity estimates and total cost per departure by level.

Historical Trends

Analyzes turnover patterns over time by department, level, tenure band, and other dimensions. Covers monthly/quarterly attrition rates, voluntary vs. involuntary split, cohort analysis and seasonal patterns.

Retention Strategies

Framework for evaluating and tracking retention initiatives with expected impact and ROI. Covers initiative catalog with descriptions, target population and cost, expected retention improvement and roi calculation per initiative.

Assumptions & Config

Configurable parameters for risk scoring weights, cost assumptions, and model settings. Covers risk factor weighting, cost multipliers by level, benchmark attrition rates and model calibration settings.

Attrition Rate

Attrition Rate = Departures / Average Headcount × 100

The percentage of employees who left during a period. The most fundamental retention metric.

Cost Per Departure

Cost = Recruiting + Onboarding + Training + Lost Productivity

Total cost when an employee leaves. Typically ranges from 50% to 200% of annual salary depending on role level.

Turnover Risk Score

Risk = Σ(wᵢ × factorᵢ)

Weighted composite score combining tenure, compensation ratio, engagement score, manager rating, and other predictive factors.

Retention Initiative ROI

ROI = (Avoided Turnover Cost − Initiative Cost) / Initiative Cost

Measures the return on investment for each retention program by comparing avoided costs to program spend.

1.Define and Collect the Right Employee Data

Retention analytics requires both employment data and engagement data. Start with structured HR records: tenure, department, role level, salary, performance ratings, promotion history, manager changes, and training participation. Supplement with engagement signals — survey scores, absenteeism patterns, internal mobility applications, and participation in discretionary activities. The most predictive retention models combine objective employment data with behavioral signals that indicate disengagement. Establish a clear definition of "attrition" (voluntary vs. involuntary, regrettable vs. non-regrettable) because what you're trying to predict determines which data matters.

2.Calculate the True Cost of Turnover

Before building predictive models, quantify what turnover actually costs the organization. Direct costs include recruitment fees, advertising, interview time, and onboarding training. Indirect costs — often larger — include lost productivity during the vacancy, reduced team performance, knowledge loss, and the productivity ramp-up time for the replacement (typically 6-12 months to reach full effectiveness). Cost varies dramatically by role level: replacing an entry-level employee might cost 50% of annual salary, while replacing a senior leader can cost 200-400%. These cost estimates make the business case for investing in retention.

3.Build Risk Scores Using Predictive Factors

Analyze historical turnover data to identify which factors are most predictive of voluntary departure. Common high-impact factors include: time since last promotion (flight risk increases after 2-3 years without advancement), pay relative to market (employees below 90% of market rate leave at significantly higher rates), manager quality (people leave managers, not companies), and recent life events (relocation, manager change). Weight these factors based on their statistical relationship with actual turnover, then combine them into a composite flight risk score for each employee. Validate the model against a holdout sample of historical data.

4.Segment the Workforce and Prioritize Interventions

Not all attrition is equally costly. Segment employees by both flight risk and business impact (performance, criticality of role, difficulty to replace). The intersection of high flight risk and high business impact identifies your priority population — these are the employees where retention interventions will generate the highest return on investment. For this critical segment, design targeted retention strategies: career path discussions, compensation adjustments, development opportunities, or role redesigns. One-size-fits-all retention programs are expensive and ineffective; targeted interventions based on individual risk drivers produce better outcomes at lower cost.

5.Monitor Trends and Measure Retention ROI

Retention analytics is not a one-time project — it's an ongoing capability. Track attrition rates by segment over time, monitor the accuracy of your risk predictions (are the employees you flagged as high-risk actually leaving?), and measure the effectiveness of retention interventions. Calculate retention ROI by comparing the cost of interventions against the turnover costs avoided. Report to leadership with clear metrics: overall attrition rate versus target, regrettable attrition trend, retention program participation and impact, and predicted hotspots for the coming quarter. Continuous monitoring turns reactive firefighting into proactive talent management.