How do we track automated AI workflows on our weekly EOS Scorecard so the leadership team catches process breakdowns before they impact customer deliverables?

Question

Tyler Smith · Accepted Answer

When you automate a core operational workflow, you cannot assume it runs flawlessly in the background. Automated systems fail silently. An API updates, an input format shifts, or a model update subtly alters how instructions are interpreted. You must monitor automation health on your weekly EOS Scorecard.

Add two specific measurable numbers to the Scorecard for every critical automated process. The first is Volume Processed vs Manual Fallbacks. This tracks how many transactions the automation handled completely versus how many hit a system exception and were kicked back to a human queue. If your exception rate spikes from three percent to twenty percent in a single week, your leadership team will catch the process break in your Level 10 Meeting before clients notice.

The second metric is Quality Audit Error Rate. Assign a specific human seat on your Accountability Chart to spot-check a random five percent sample of all machine-completed actions each week. They log any errors in pricing, data entry, or customer communication. This number gets reported on the Scorecard weekly.

If the Quality Audit Error Rate breaches your acceptable tolerance, drop it down to the Issues List and IDS it immediately. Do not turn the automation off in a panic. Identify whether the root cause is corrupted source data, updated vendor software, or a flawed prompt. Tracking these operational tripwires ensures technology serves the business without introducing unmonitored risk.