Calculate optimal staffing levels to balance customer service quality with operational costs.
How to Use#
Step 1: Enter Volume Data#
- Historical call volumes by hour
- Day-of-week patterns
- Seasonal variations
- Special event impacts
Step 2: Set Service Targets#
- Target answer time (e.g., 20 seconds)
- Service level goal (e.g., 80%)
- Maximum abandonment rate
- Occupancy targets
- Agent shift patterns
- Break schedules
- Training time
- Overtime limits
Erlang C Calculator#
The Erlang C formula predicts wait times and service levels:
Service Level = 1 - (P(wait) × e^(-(Agents-Traffic)×(Target Time/AHT)))
Where:
- Agents = Number of agents
- Traffic = Call arrival rate × AHT
- AHT = Average Handle Time
- Target Time = Service level target (e.g., 20 seconds)
Required Agents = Traffic Intensity × (1 + Service Level Buffer)
Traffic Intensity = Calls per Hour × (AHT / 60)
Example Calculation#
Calls per hour: 100
Average Handle Time: 5 minutes
Target: 80% in 20 seconds
Traffic Intensity = 100 × (5/60) = 8.33 Erlangs
Required Agents = ~12 agents (for 80/20 service level)
Optimization Strategies#
Time-Based Staffing#
| Time Period |
Volume Pattern |
Staffing Approach |
| Morning rush |
High |
Full staff + OT if needed |
| Mid-day |
Moderate |
Standard staffing |
| Afternoon |
Moderate-High |
Full staff |
| Evening |
Low |
Reduced staff |
| Night |
Very low |
Skeleton crew or voicemail |
Day-of-Week Adjustments#
| Day |
Typical Pattern |
Adjustment |
| Monday |
+15-25% |
Add staff |
| Tuesday |
+5-10% |
Slight increase |
| Wednesday |
Baseline |
Standard |
| Thursday |
-5% |
Slight decrease |
| Friday |
-10-15% |
Reduce staff |
| Weekend |
-40-60% |
Minimal staff |
Seasonal Patterns#
- Q4 retail: +30-50% staffing
- Tax season (finance): +20-40%
- Summer (healthcare): -10-20%
- Holiday periods: Varies by industry
Service Level Targets#
Industry Standards#
| Industry |
Service Level |
Target |
| E-commerce |
80/20 |
80% in 20 sec |
| Banking |
80/30 |
80% in 30 sec |
| Healthcare |
80/60 |
80% in 60 sec |
| B2B Tech |
90/30 |
90% in 30 sec |
| Emergency |
95/10 |
95% in 10 sec |
Cost vs. Service Trade-offs#
| Service Level |
Agent Cost |
Customer Impact |
| 95/20 |
Very High |
Excellent |
| 90/20 |
High |
Great |
| 80/20 |
Moderate |
Good |
| 70/30 |
Low |
Acceptable |
| 60/60 |
Very Low |
Poor |
Practical Recommendations#
Occupancy Guidelines#
- Target: 75-85% occupancy
- Below 70%: Overstaffed
- Above 90%: Risk of burnout
Shrinkage Allowance#
Always account for shrinkage:
| Factor |
Typical % |
| Breaks |
10-12% |
| Training |
2-5% |
| Meetings |
2-3% |
| Absenteeism |
5-10% |
| After-call work |
10-15% |
| Total shrinkage |
30-40% |
Scheduled Agents = Required Agents / (1 - Shrinkage%)
Example:
12 required × (1 / 0.65) = 18.5 → 19 scheduled
Advanced Optimization#
Multi-Skill Routing#
- Cross-train agents
- Use skills-based routing
- Balance specialization vs. flexibility
Flex Staffing Options#
- Part-time agents: Cover peak periods
- Remote agents: Geographic flexibility
- Overtime: Handle unexpected spikes
- BPO overflow: External capacity
AI Integration#
- AI handles simple queries 24/7
- Reduces base staffing needs by 30-50%
- Humans focus on complex issues
- Better peak handling
Implementation Checklist#