Sauna Skills

Flight Risk Signals

Flight risk combines multiple signals into a composite retention risk score. Each signal has different predictive weight depending on availability and context.

Signal Categories

Tenure signals are the strongest predictors: employees at 18-24 months tenure are at highest risk (past ramp-up, marketable skills, haven't hit vesting cliffs). Time-in-role matters separately—same role for 2+ years without growth signals stagnation. Time since last promotion over 18 months in a growth-track role indicates career friction.

Workload signals overlap with burnout: sustained 45+ hours, weekend work patterns, and meeting overload all correlate with departure. If hours data is available, apply burnout thresholds from Manager Diagnostics Guide as one input to flight risk.

Engagement signals require survey or pulse data: declining scores over 2+ quarters, scores below team average, or sharp drops after specific events (reorg, manager change, project cancellation) all indicate risk. Missing engagement data means this signal is unavailable—note it in output.

Growth trajectory tracks career movement: lateral moves without clear rationale, passed over for promotion (especially if peers advanced), or no skill development opportunities in 12+ months suggest disengagement.

Risk Scoring Framework

Calculate a weighted risk score based on available signals. Not all signals will be present—score what's available and note confidence level.

Scoring Weights (CSV Data)

Signal	Weight	Threshold for Points
Tenure 18-24 months	+3	Hire date in range
Tenure 12-18 months	+1	Hire date in range
Time in role > 24 months	+2	Role start date
No promotion > 18 months	+2	Last promotion date
Burnout risk (high)	+3	50+ hrs sustained
Burnout risk (moderate)	+1	45+ hrs sustained
Engagement declining	+2	2+ quarters down
Engagement below avg	+1	Below team median

Slack Signal Scoring (Optional)

If Slack signals are available from People Directory, incorporate them into the risk score. These signals come from Setup Slack Signals and provide engagement data from workspace activity.

Slack Signal	Weight	Threshold
Message frequency decline	+2	> 20% drop week-over-week
Message frequency decline	+1	> 10% drop week-over-week
After-hours activity increase	+1	> 10% above team average
Regular weekend messaging	+1	3+ weekend messages
Channel participation narrowing	+1	< 50% of team avg channels

Interpreting Slack signals: A person's message frequency declining 20%+ while their after-hours percentage increases is a strong combined signal—they're doing less visible work but working longer hours, suggesting disengagement or burnout. Channel narrowing (retreating to fewer channels) often precedes departure.

Matching names: The Slack data uses display names. Match to CSV data by name when possible. Note any employees who appear in CSV but not Slack (or vice versa) as partial matches.

Risk Levels

Total Points	Risk Level	Action Urgency
6+	🔴 High Risk	Immediate retention conversation
3-5	🟡 Moderate Risk	Proactive check-in within 2 weeks
1-2	🟢 Low Risk	Standard 1:1 cadence
0	✅ Healthy	No action needed

Signal Availability

Report which signals were available for scoring:

CSV signals: tenure ✓, time-in-role ✓, promotion history ✗, hours data ✓, engagement ✗
Slack signals: message frequency ✓, after-hours ✓, weekend activity ✓, channel breadth ✓
Confidence: High (4 CSV + 4 Slack signals available)

If fewer than 2 signals are available, note that the assessment has limited confidence and recommend collecting more data. Slack signals are optional enhancement—analysis works with CSV alone.

Data Validation

Required Fields

• Employee identifier (name or ID)
• Hire date OR tenure value (months/years)

Optional Fields (enhance accuracy)

• Role start date (for time-in-role signal)
• Last promotion date (for growth trajectory)
• Weekly hours or timesheet data (for burnout signal)
• Engagement score (for engagement signal)

Validation Checks

• Hire dates must be in the past and parseable
• Tenure values must be positive numbers
• Engagement scores should be on consistent scale (1-5, 1-10, or percentage)
• Flag any employees missing the required identifier field

Output Format

# Flight Risk Assessment: [Team/Period]

## Summary
- **Employees analyzed:** [N]
- **Signals available:** [list which were present]
- **High risk:** [N] people
- **Moderate risk:** [N] people

## Risk Assessment

### 🔴 High Risk (Immediate Attention)
| Employee | Tenure | Risk Signals | Score | Key Concerns |
|----------|--------|--------------|-------|--------------|
| [Name] | [X mo] | tenure, hours | [N] | [Specific flags] |

**Recommended actions:**
- Schedule retention conversation this week
- Discuss career growth and pain points
- Identify if concerns are addressable

### 🟡 Moderate Risk (Proactive Check-in)
| Employee | Tenure | Risk Signals | Score | Key Concerns |
|----------|--------|--------------|-------|--------------|
| [Name] | [X mo] | [signals] | [N] | [Specific flags] |

**Recommended actions:**
- Check in within next 1:1
- Ask about satisfaction and growth
- Surface any emerging concerns

### 🟢 Low Risk / Healthy
[List or note count]

## Data Gaps
[Note which signals were unavailable and how that affects confidence]

## Retention Conversation Starters

For high-risk individuals, consider asking:
- "How are you feeling about your growth here?"
- "What would make this role more fulfilling?"
- "Is there anything frustrating you that we could address?"
- "Where do you see yourself in a year?"

Avoid: directly asking "are you thinking of leaving?" - this often triggers defensiveness.

Context Considerations

Adjust interpretation based on role and level:

• Early career: Tenure risk is lower (expected job-hopping), growth signals matter more
• Senior IC: May stay in role longer by choice; check if it's contentment vs stagnation
• Management: Tenure patterns differ; departures often follow team changes or reorgs
• Recently promoted: Reset the "time since promotion" clock; they're in a new evaluation window

Market conditions matter: in hot job markets, moderate risk signals become more urgent. In downturns, employees may stay despite dissatisfaction (creating future attrition risk when market recovers).