Travel Delay Domino Impact Calculator

📖 Overview

This calculator models domino failure risk in tight itineraries.

It tracks residual delay across dependent events to estimate likely misses and financial impact before disruption escalates.

Use these default and higher-pressure example inputs to explore how sensitive this calculator is before using your real numbers.

Input	Base Case	Higher Pressure Case
Initial Delay (minutes)	55	66
Number Of Dependent Events	4	4.6
Average Buffer Per Event (minutes)	25	30
Recovery Time Per Event (minutes)	10	12
Cost Per Missed Event ($)	180	216

Models cascading disruption across linked travel events by tracking residual delay after each buffer/recovery cycle and estimating misses.

The Formula

Per event: Residual Delay = max(0, Delay − (Buffer + Recovery)); if exceeded, count miss and carry delay forward.

Initial Delay	Delay entering the sequence
Dependent Events	Timed commitments exposed to propagation risk
Buffer/Event	Slack per event before failure
Recovery/Event	Delay reduction achievable between events
Cost/Miss	Economic loss per missed event

💡This calculator is scenario-based. Better input quality leads to better decision quality.

⚠️Real disruption chains can be nonlinear. Use conservative assumptions for tight itineraries with low rebooking flexibility.

Initial Delay	Events	Buffer+Recovery	Typical Risk
20 min	3	30 min/event	Low domino risk
45 min	3	25 min/event	Moderate miss risk
90 min	4	20 min/event	High multi-event risk

Use this tool when you need a fast decision during active planning or execution.
Use this before committing money, time, or tradeoffs that are hard to reverse.
Use this to compare options using the same assumptions across scenarios.

Results can be misleading if key inputs are missing, stale, or unrealistic.
Very small or very large values may amplify rounding effects and interpretation risk.
If assumptions change mid-decision, recalculate before acting.

💡 Increase slack at the earliest link to reduce full-chain risk.

💡 Track rebooking cost and time loss separately for realism.

💡 Use this before committing tight same-day multi-leg plans.

❓ Why include recovery time?

Not all delay propagates unchanged; some can be clawed back between events.

❓ Can this be used for non-flight trips?

Yes, for any sequence with hard timing dependencies.