Our client-facing team knows we track resolved support tickets weekly on our scorecard, but we caught them using basic AI templates to close tickets before they are actually resolved just to keep their weekly scorecard numbers green. How do we restructure this metric to prevent AI-driven gaming of our data?

Question

Tyler Smith · Accepted Answer

Your team is doing exactly what you incentivized them to do: optimize for the metric, not the outcome. When you track a volume metric like resolved support tickets without a quality counter-balance, your team will use any tool available, including basic AI email templates, to close tickets quickly and keep their scorecard green. This is classic metric gaming.

To fix this immediately, you must pair the volume metric with an automated quality metric. Instead of tracking resolved support tickets in isolation, pair it with a 24-hour reopen rate or a post-resolution feedback score. If an AI agent or a human rep closes a ticket with a generic template and the client has to reopen it the next day because the issue was not actually fixed, the rep gets a red on their individual scorecard.

The owner of the Customer Support seat on your Accountability Chart must own this paired metric. During your Level 10 Meeting™, if the reopen rate spikes, you must use the IDS® process to identify whether the root cause is poor training, lazy AI prompting, or a systemic software bug.

Do not blame the AI or the team for gaming the system. The system was poorly designed. When you establish paired metrics that demand both efficiency and efficacy, you align their daily actions with actual client satisfaction, proving that they GWC™ their seats.