Use this to size staffing for tickets across email, chat, and marketplace messages. Concurrency helps model parallel work, like handling two chats at once.
| Scenario | Tickets/day | AHT+ACW (min) | Shrinkage % | Occupancy % | Agents needed |
|---|---|---|---|---|---|
| Peak sale week | 420 | 12 | 30 | 85 | 18 |
| Normal month | 250 | 10 | 28 | 85 | 10 |
| Light season | 120 | 9 | 25 | 80 | 5 |
Tickets_in = Tickets_per_day × Period_daysTickets_worked = Tickets_in × (1 − Deflection) × (1 + Reopen)Minutes_per_ticket = (AHT + ACW) + (Escalation_rate × Escalation_extra)Effective_minutes = Minutes_per_ticket ÷ ConcurrencyTotal_work_hours = Tickets_worked × Effective_minutes ÷ 60Available_hours = Shift_hours × Period_days × (1 − Shrinkage)Productive_hours = Available_hours × OccupancyAgents_required = Total_work_hours ÷ Productive_hoursUtilization = Total_work_hours ÷ (Agents_current × Productive_hours)Backlog_hours = max(0, Total_work_hours − Current_capacity_hours)- Enter your period and average tickets per day.
- Set handle time and after-call work from reporting.
- Add escalation, deflection, and reopen percentages.
- Choose shift hours, shrinkage, and occupancy target.
- Press Calculate to see agents, utilization, and backlog.
- Include marketplace messages, returns, and payment disputes in tickets/day.
- Increase shrinkage during onboarding or process-change periods.
- Use higher concurrency for chat, lower for email-heavy queues.
- Track reopen rates; they often rise after peak promotions.
Demand drivers
Ticket volume rises with order growth, promotion spikes, and delivery issues. A store averaging 250 tickets daily creates 7,500 contacts in 30 days before deflection. If 8% are resolved by self‑service, worked volume drops to 6,900. Reopens matter: a 5% reopen rate adds 345 extra touches, often concentrated in refunds, replacements, and payment disputes.
Time per ticket
Effort per contact combines handle time and after‑contact work. An 8‑minute handle time plus 2 minutes of wrap produces 10 minutes baseline. Escalations increase effort: with 12% escalations adding 6 minutes, average effort becomes 10.72 minutes. Concurrency adjusts effective effort; a concurrency factor of 1.5 reduces effective minutes to about 7.15, which is common when chat agents multitask.
Capacity planning
Paid time is not productive time. With an 8‑hour shift over 30 days, each agent has 240 paid hours. Shrinkage of 28% leaves 172.8 available hours after breaks, coaching, and meetings. Applying an 85% occupancy target yields 146.88 productive hours per agent for the period. This creates a clear ceiling for sustainable throughput.
Staffing decisions
Total work hours come from worked tickets multiplied by effective minutes, divided by 60. Using the sample values above produces roughly 822 work hours per month. Dividing by 146.88 productive hours indicates 5.6 agents, rounded up to 6. If you staff 10 agents, utilization falls near 56%, allowing faster response, training, and proactive outreach during quieter weeks.
Operational signals
Utilization above 90% typically correlates with longer queues, higher reopens, and lower quality. Backlog hours quantify the gap between work demand and current capacity. Track deflection, reopens, escalation rate, and average minutes weekly; small changes compound quickly. Use the calculator to test scenarios like peak sale weeks, policy changes, or staffing shifts before SLAs slip.
For channel mix, weight chat higher for concurrency, email lower, and phone highest for after-work. If 40% of tickets are chat with concurrency 1.8 and the rest email at 1.0, use a blended factor near 1.32. Recalculate monthly, and compare required agents to scheduled coverage and absentee trends. Also review seasonality, carrier delays, and launches.
Q1. What does shrinkage mean here?
Shrinkage is paid time not available for tickets, including breaks, coaching, meetings, and admin. Higher shrinkage reduces available hours, raising required headcount. Use recent schedules and adherence data to estimate it realistically.
Q2. How do deflection and reopens affect the load?
Deflection reduces worked tickets through self-service. Reopens add repeat work. Even small shifts matter at scale: a 5% reopen on 6,900 tickets adds 345 more touches. Track both weekly and tune content, macros, and policies.
Q3. What occupancy target should I plan for?
Occupancy is the share of available time spent working tickets. Many teams plan 80–90% to protect quality and allow recovery time. If your channels are volatile or complex, choose the lower end and monitor queue times.
Q4. How should I set the concurrency factor?
Use 1.0 for email-focused work. For chat, agents often handle 1.3–2.0 conversations depending on tooling and complexity. If your platform measures concurrent chats per agent, use that average; otherwise start at 1.5 and validate against actual effort.
Q5. Does this calculator guarantee SLA compliance?
It estimates period effort and sustainable capacity, not minute-by-minute queueing. For strict SLAs, add hourly arrival patterns, response targets, and staffing by interval. Use this tool first to size baseline headcount, then refine with intraday scheduling.
Q6. How can I use the results for hiring decisions?
Compare rounded agents required to your current staffed agents. If utilization exceeds 90% or backlog grows, add coverage, reduce handle time, or improve deflection. If utilization is low, reassign time to training, QA, and proactive retention tasks.