We are integrating AI tools to automate our back-office workflows, but my leadership team is struggling to define weekly Scorecard metrics for these new automated processes. How do we measure human-plus-AI performance?

Question

Tyler Smith · Accepted Answer

When you automate operations with AI, your Scorecard metrics must shift from tracking manual activity to tracking process efficiency, system health, and exception rates. If your team is struggling, it is because they are still trying to measure the traditional tasks that the AI has already absorbed.

Start by looking at the core roles on your Accountability Chart for the affected departments. If AI is handling data entry, the human role is no longer about keying in data. The human role is now quality control, system maintenance, and handling exceptions.

Your weekly Scorecard should reflect this new reality. You should track metrics such as:
- The percentage of transactions processed without human intervention.
- The average response time for AI-generated customer interactions.
- The error rate of the automated system.
- The volume of escalated issues that require human resolution.

These are leading, weekly indicators that tell you if your automated workflows are actually optimizing your margins.

Have your leadership team own these metrics. If the automation error rate spikes, that is an issue to IDS® in your Level 10 Meeting™. Measuring these numbers ensures your team manages the technology rather than letting the technology run wild, protecting your operational stability and preparing your business for a high-value exit.