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AI agent for service managers

Shared Services Service Level Review Agent

Show whether each shared service meets its agreed level and what to fix

Shared Services Service Level Review Agent: what goes in, what the agent does and what you get

What it does

IT, HR, finance and facilities all promise service levels to the business, such as password resets in 4 hours or invoices paid in 30 days, and nobody checks whether the promises are kept. Complaints arrive instead of data. This agent runs a monthly review. It pulls ticket and request data per service, compares each with the agreed level, finds the misses and gathers the likely causes from ticket tags, volumes and staffing. It drafts a review for each service team with the numbers, the trend and a suggested action. It checks again next month to see if the fix worked. The manager approves each review before it is shared. Edge case: a service has no agreed level. The agent proposes one from the last 6 months.

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
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Monthly ticket data closes 2 USES A TOOL Pull ticket data and the agreed service levels 3 CHECKS THE RESULT Does every service have a defined level? If not: Propose a level from six months of data and markit as draft. Back to step 2. 4 DOES Calculate performance per service against its level 5 DOES Identify misses and group them by cause 6 DOES Compare with last month and note the trend 7 DOES Draft a review per service team with numbers and asuggested action 8 YOU APPROVE General manager approves each review before it isshared 9 USES A TOOL Send the reviews to service owners 10 CHECKS THE RESULT Did last month's actions improve the result? If not: Revise the suggested action and flag repeatedmisses. Back to step 5. 11 RESULT Service level review pack
Read the steps as a list
  1. Monthly ticket data closes
  2. Pull ticket data and the agreed service levels
  3. Does every service have a defined level?If not: Propose a level from six months of data and mark it as draft. Back to step 2.
  4. Calculate performance per service against its level
  5. Identify misses and group them by cause
  6. Compare with last month and note the trend
  7. Draft a review per service team with numbers and a suggested action
  8. General manager approves each review before it is sharedThe agent waits here for your OK.
  9. Send the reviews to service owners
  10. Did last month's actions improve the result?If not: Revise the suggested action and flag repeated misses. Back to step 5.
  11. Service level review pack

How it decides

A service passes when at least the agreed share of requests meets the target time. Causes are ranked by how many missed tickets they explain.

  • A service passes if the agreed share of tickets meets the target time
  • Two months of misses trigger a deep dive on causes
  • Services with fewer than 20 tickets are reported as small sample
  • A proposed level needs the service owner's agreement

Make it yours

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

  • Service levels and targets
  • Minimum ticket sample (default 20)
  • Review day of the month
  • Services included
  • Who receives the reviews

What keeps you in control

It always asks you first

  • General manager approves reviews before they go to the teams

Hard limits

  • Never changes an agreed service level without the owner
  • Reports teams, not individual staff

It stops when

  • Done: all services reviewed and shared
  • Stop: data is missing for a service, request access from its owner

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 happensIT promises password resets in 4 hours for 95 percent of tickets. In May the agent finds 81 percent, with 70 percent of misses on Mondays after weekend queues. It drafts a review suggesting Monday coverage. The manager approves it. In June the rate is 93 percent, so the agent proposes one more shift tweak.

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