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AI agent for call center supervisors

Call Volume Forecast and Staffing Agent

Staff levels that meet service level with the fewest idle hours

Call Volume Forecast and Staffing Agent: what goes in, what the agent does and what you get

What it does

Call centers that guess staffing end up with long queues on busy mornings and idle agents in the afternoon. Each week this agent forecasts call volume by 30-minute interval for the next two weeks, using past volume, seasonality and known events like bill runs, marketing sends and holidays. It converts the forecast into the staff needed to hit the service level. It compares that with the current schedule and drafts changes, such as shift swaps, overtime offers or moving training sessions. After each week, it checks forecast accuracy. If the error is above the limit, it looks for the missed driver and adds it to the model before the next forecast. The supervisor approves every schedule change. Edge case: a planned system outage lowers handling capacity, not volume, and is modeled that way.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
ApprovedYes, continueNo 1 STARTS WHEN Weekly forecast run 2 USES A TOOL Pull call history and upcoming events 3 DOES Forecast volume by 30-minute interval 4 USES A TOOL Calculate staff needed per interval 5 DOES Draft schedule changes for gaps 6 YOU APPROVE Supervisor approves changes 7 CHECKS THE RESULT Was last week's forecast within the error limit? If not: find the missed driver and add it to theforecast. Back to step 3. 8 RESULT Schedule updated and accuracy logged
Read the steps as a list
  1. Weekly forecast run
  2. Pull call history and upcoming events
  3. Forecast volume by 30-minute interval
  4. Calculate staff needed per interval
  5. Draft schedule changes for gaps
  6. Supervisor approves changesThe agent waits here for your OK.
  7. Was last week's forecast within the error limit?If not: find the missed driver and add it to the forecast. Back to step 3.
  8. Schedule updated and accuracy logged

How it decides

It staffs each interval to the service level target and proposes the cheapest change first: swaps, then moved training, then overtime.

  • Prefer shift swaps over overtime
  • Move training out of peak intervals
  • Model outages as lower capacity

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Service level target (default 80% in 20 seconds)
  • Forecast error limit (default 10%)
  • Overtime rules
  • Planning horizon

What keeps you in control

It always asks you first

  • Schedule changes
  • Overtime offers

Hard limits

  • Never changes schedules without approval
  • Never contacts staff directly

It stops when

  • Done: schedule approved
  • Stop: call data missing for over a day

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensThe forecast showed Monday, March 3, 9 to 11 a.m. needing 34 agents against 27 scheduled, because of a bill run. The agent moved a training block and proposed four swaps, which the supervisor approved. The next accuracy check showed 14% error on Tuesday, above the 10% limit. It found a marketing email it had missed and added email sends to the event calendar.

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