Support Staffing Workload Forecast
Calculate support staffing needs based on ticket volume and utilization. Enter values for instant results with step-by-step formulas.
Frequently Asked Questions
How do I calculate support staffing requirements?
Formula: Required agents = Total handle time / (Work hours × Utilization target). Example: 200 tickets/day, 15 min handle time = 3,000 minutes = 50 hours. Agents work 8 hours at 75% utilization = 6 productive hours. Required: 50 / 6 = 8.3 → 9 agents. Utilization target (70-80%) accounts for: breaks, meetings, training, buffer for spikes. Don't target 100%—no capacity for volume increases or complex tickets. Erlang C formula provides more precise queueing model for real-time support (chat, phone).
What is a good utilization target for support teams?
Optimal: 70-80% utilization. Below 70%: Overstaffed (high labor cost relative to volume). Above 80%: Risk of burnout, long queues, quality drops. At 90%+: Critical—any spike causes queue explosion. Why not 100%: (1) Agents need breaks, training, meetings. (2) Ticket volume varies—need buffer for peaks. (3) Complex tickets take longer—averages don't account for variance. (4) Quality degrades under constant pressure. Different channels: Chat (higher utilization OK, ~80%), phone (70-75%), email (can flex to 85% since async).
How do I forecast ticket volume growth?
Methods: (1) Historical trend: Plot last 12 months, calculate growth rate. If 10% MoM growth, forecast next month = current × 1.1. (2) Customer correlation: Tickets per customer is stable (~0.5-2/month for SaaS). Forecast = Projected customers × Tickets per customer. (3) Product launches: Major releases spike volume 2-3x for 2-4 weeks. Plan temporary staffing. (4) Seasonality: Retail spikes Q4, tax software spikes April. Use year-over-year comparison. Combine methods: Base forecast (historical) + adjustments (launches, seasonality). Add 10-20% buffer for unknowns.
Should I use Erlang C for staffing calculations?
Erlang C is queuing theory formula for real-time support (phone, chat) where customers wait in queue. Calculates: Probability of waiting, expected wait time, service level. Use Erlang C when: (1) Real-time channel (phone, live chat). (2) Need specific service level (e.g., 80% answered in 60 seconds). (3) Volume is high enough for statistical modeling (>100 interactions/day). Simpler approach OK when: (1) Async channel (email, tickets). (2) Lower volume. (3) Planning at daily/weekly level, not hourly. Most support tools (Zendesk, Intercom) have built-in Erlang calculators. For email/ticket support, simple handle time / available hours calculation is sufficient.