Turn ticket data into clear daily throughput. See per-agent pace, net flow, and capacity instantly. Export reports, justify hires, and reduce customer wait time.
Enter a period and your support ticket numbers. Then compute throughput, net flow, backlog, and a practical staffing view for ecommerce operations.
A realistic example from a mid-sized online store support team. Use it to sanity-check your inputs.
| Period (days) | Agents | Created | Resolved | Starting Backlog | Hours/Day | AHT (min) | Utilization |
|---|---|---|---|---|---|---|---|
| 14 | 6 | 840 | 910 | 320 | 7.5 | 9.5 | 75% |
| 30 | 10 | 1,950 | 2,020 | 410 | 7.0 | 11.0 | 78% |
Seasonal spikes from promotions, delivery delays, and returns can lift daily ticket creation by 20–60%. Throughput turns raw counts into comparable rates, letting teams compare weeks with different staffing. When resolved/day trails created/day, queues grow, response times stretch, chargebacks increase, and loyalty drops.
This calculator blends operational inputs: period length, agents, starting backlog, working hours, utilization, and average handle time. Utilization captures meetings, training, and tooling friction; 70–85% is typical for stable teams. Example: 6 agents × 7.5 hours × 60 × 75% yields 2,025 capacity minutes per day. If effective handle time is 10.3 minutes, sustainable throughput is about 196 tickets per day, before quality buffers and wrap-up tasks.
Net flow equals created minus resolved. A positive net flow of 70 tickets over 14 days adds 70 to backlog, even if daily service feels steady. Ending backlog highlights the work carried forward into the next period and influences first-response time. Combine backlog with tickets/agent/day to estimate whether queues will clear organically. The forecast backlog repeats the same net flow once more to show momentum, not destiny, helping leaders plan before peak weekends.
Workload minutes per day equals resolved/day × effective handle time, where escalation overhead increases effort for approvals, refunds, or warehouse checks. Comparing workload to capacity produces a minutes gap that explains overtime, missed targets, or idle time. A negative gap suggests under-capacity; a positive gap suggests headroom for quality, coaching, or proactive outreach. The staffing estimate converts a daily target into required agents using your hours and utilization assumptions, creating a defensible hiring narrative.
Automation deflection reduces created volume handled by agents, while escalation overhead increases per-ticket effort. Testing both helps teams justify self-service, better order status messaging, and smarter routing. A 12% deflection on 840 created tickets removes about 101 agent-handled contacts in the same period. Use the backlog-clearance horizon to model recovery plans, such as clearing 420 open tickets in 21 days by adding 20 extra resolves per day, then validating whether capacity minutes support that goal reliably.
It is the average tickets resolved per day for your selected period. Use it to compare weeks, teams, or tools using a consistent rate instead of raw totals.
Match your reporting cadence. Use 7–14 days for fast operational tuning, and 28–30 days for planning. Keep the same definition when comparing trends.
Start with 70–85% for steady operations. Higher utilization can reduce quality and increase rework. Lower utilization may fit training, onboarding, or heavy cross-team coordination.
The forecast applies the same net flow (created minus resolved) to the next period, starting from the current ending backlog. It is a directional indicator, not a guaranteed outcome.
Escalation increases effective handle time, reducing capacity. Deflection reduces created volume handled by agents, lowering net flow and backlog pressure. Test scenarios to quantify process and automation benefits.
Yes, if your “created” and “resolved” counts reflect the same combined scope. If channels differ in complexity, consider separate runs with different handle times to avoid blended averages.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.