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Support team simulator

Describe a support team (agents, channels, volume, handle time and targets) and see the staffing it needs, its daily capacity, whether a backlog builds up and which SLA it can hold. Every formula is written out under the results.

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Team

AgentsPeople who handle tickets, full-time equivalent. Example: 16Team leadsLeads who coach and review, not on the queue. Example: 2Working hours per dayhOpening hours; each agent is assumed to cover them. Example: 8 hWorking days per weekExample: 5

Shrinkage%Paid time not spent on tickets: breaks, meetings, training, leave. Example: 30%

Demand and channelsTickets and contacts per dayAll channels together, on an average working day. Example: 520

Email share%Chat share%Phone share%

Email handle timeminChat handle timeminPhone handle timemin

Busiest hour share of daily chats and calls%From your hourly reports. An even 8-hour day is 12.5%. Example: 13%

Targets

Email first responsehExample: 4 hOccupancy target%Share of available time agents should spend on tickets. Example: 85%Chat and phone SLA%Example: 80%Answered withinsecExample: 60 sec

CSAT target%Kept as context: staffing cannot predict CSAT, so the risks below flag what tends to pull it down. Example: 90%

Agents needed

2 spare: 14 would still meet every target.

Capacity per day

613

93 tickets of headroom a day.

Utilization

72%

64.6 h of work for 89.6 productive hours.

Backlog after a week

The team keeps up with what arrives.

Workload by channel

Email286 · 33.4 h

Chat156 · 23.4 h

Phone78 · 7.8 h

Chat20 per peak hour, 5 agents on it → 80% within 60 s (target needs 5 on the queue)

Phone10 per peak hour, 3 agents on it → 93% within 60 s (target needs 3 on the queue)

3 of the 11 agents available at the peak hour are left for email.

This team holds its targets

Capacity covers the volume, occupancy stays under your target and the live channels meet the SLA at the busiest hour. Keep an eye on CSAT itself: staffing is only one of its drivers.

Head-count scenarios

The same demand with fewer or more agents. Your current team is highlighted.

Agents	Utilization	Capacity / day	Backlog / day	Chat SLA at peak	Phone SLA at peak	Every target met
12	96%	460	+60	80%	93%	No
13	89%	498	+22	80%	93%	No
14	82%	537	-17	80%	93%	Yessmallest
15	77%	575	-55	80%	93%	Yes
16current	72%	613	-93	80%	93%	Yes
17	68%	652	-132	80%	93%	Yes
18	64%	690	-170	80%	93%	Yes

Go further with the ebook

Head of Support

The blueprint to build, staff and lead a 50-agent support department, with the dashboards I used.

$39.99 · 233 pages · View the book

How the simulator calculates

Workload hours: tickets per day × channel share × handle time ÷ 60, added up over the three channels.
Productive hours: agents × working hours per day × (1 − shrinkage).
Capacity per day: productive hours × occupancy target × 60 ÷ average handle time (weighted by the channel mix).
Utilization: workload hours ÷ productive hours.
Backlog: tickets per day − capacity. A positive number is what is left open each day; a week is that × working days.
Chat and phone SLA: Erlang C at the busiest hour. The agents available then (agents × (1 − shrinkage), rounded down) go to chat, then phone, each up to what its SLA needs; the rest answer email. Service level = 1 − P(wait) × e^(−(agents − traffic) × target seconds ÷ handle time).
Agents needed: the smallest team where capacity covers the volume, utilization stays at or under the occupancy target and chat and phone meet the SLA at the busiest hour.
Email wait at week end: open emails in the weekly backlog ÷ emails the team answers per hour.