Estimation question

If the Philadelphia airport was to shutdown for 24 hours, how long would it take to get back to running like normal? Come up with number estimates and assumptions.

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Tests estimation of a complex operational recovery timeline: decomposing a systemic shutdown into recovery phases with defensible assumptions.

Define the scope: a 24-hour full shutdown of a major hub airport, and clarify 'back to normal' means flight schedules and passenger flow returning to baseline, not just reopening.
Segment the recovery into phases: reopening operations (hours), clearing the immediate backlog of delayed and cancelled flights (a day or more), and absorbing ripple effects across connected routes and crews (additional days).
Estimate the backlog: a 24-hour shutdown at a major hub could cancel or delay roughly a full day's worth of flights, which then need to be re-accommodated using existing capacity plus some spare capacity.
Estimate re-accommodation rate: airlines typically can absorb some backlog per day using available seats and extra sections, so full backlog clearance might take 2 to 4 additional days, stated as an assumption.
Account for crew and aircraft positioning, since aircraft and crews are often out of position after a major disruption, adding further delay before full normal operations resume.
Combine phases into a total estimate, such as roughly 3 to 5 days to fully normalize, clearly marked as an assumption-driven range, not a precise figure.

Breaks the recovery into distinct phases (reopening, backlog clearance, ripple effects) instead of giving one flat number for 'getting back to normal.'
Names the real operational bottleneck, aircraft and crew repositioning, which is a common and often underestimated driver of extended airline disruption recovery.
States a range (roughly 3 to 5 days) rather than false precision, while showing the reasoning chain behind it.
Distinguishes the airport reopening (fast) from full network normalization (slower), which is the crux of the question.

Assuming the airport returns to normal the moment it physically reopens, ignoring backlog and crew positioning effects.
Giving a single number with no visible breakdown of phases or assumptions.

How would this estimate change for a smaller regional airport versus a major hub like this one?
What data would you want from the airport or airlines to refine this estimate?