Track what changed and what improved

Improvement needs a before and after

Operational change often fails at the reporting stage. Teams launch something new, feel a short-term lift, and then struggle to prove whether the new approach reduced workload or improved output.

That is why measurement should be part of the workflow redesign from the start.

Keep the measures practical

Useful measures often include:

• Time spent in queue
• Number of touches per item
• Percentage of work that needs escalation
• Time spent on repeat admin versus decision-making
• Error or rework rates after the workflow change

These are easier for teams to understand than abstract maturity scores.

Separate activity from progress

More activity does not equal improvement. A team can process more internal updates while still taking too long to resolve the underlying work. The measures should show whether effort is moving toward a better outcome, not just whether the team is busy.

Review the controls as well

When AI is part of the workflow, review more than speed. Also track:

• Whether approvals are happening in the intended places
• Whether exceptions are being routed correctly
• Whether new manual checks have appeared around the AI output

That keeps the operating model honest and helps leaders improve it over time.