Your question is Use CUPED to Boost Ops Test Sensitivity. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You work on an operations workflow where a new dispatch rule is being tested to reduce late deliveries. The team believes the change will help, but the expected effect is small and the historical outcome is noisy, so a plain A/B test may be underpowered.
How would you use CUPED or another variance-reduction approach to make this operations experiment more sensitive? Explain how you would define the pre-period covariate, estimate the variance reduction, and decide whether the test is powered enough to run.