We want to use our Level 10 Meeting™ to systematically track the efficiency gains of our new AI-powered operations, but we are unsure where this tracking belongs without cluttering our standard Scorecard or Rocks. How do we monitor operational automation performance within the EOS framework?

Question

Tyler Smith · Accepted Answer

Integrating AI tools and automation into your operations is critical for scaling, but you must track their performance without breaking your existing meeting structure.

The best way to monitor these automated processes is through your weekly Scorecard. Your Scorecard should already track key operational activities, such as response times, error rates, or processing volumes.

When you automate a process, you do not need to create new metrics specifically for the AI tool. Instead, you should watch your existing metrics to ensure they improve.

For example, if you automate customer support routing with an AI tool, your weekly metric for average response time should drop. If it does not, or if your customer satisfaction score drops, that metric will turn red on your Scorecard.

This red metric will automatically trigger an issue for your Level 10 Meeting. During the IDS portion, your team can discuss whether the AI system is failing, if it requires better training, or if human oversight is needed.

By tracking automation through your standard operational metrics, you keep your Scorecard clean. You ensure your technology is held accountable to the same high standards of performance as your human team members, driving your business toward maximum efficiency.