# 7. Sensitivity Analysis

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Overview

Sensitivity tables help you understand the impact that changing various input values can have on the final output - in our case additional profit per plane.

Summary

Sensitivity analysis

- Sensitivity table re-runs the model multiple times for various input values
- The tables help you understand the relationship between inputs and outcomes

Keyboard shortcuts

ALT + H , H: Color cells white (remove gridlines)
ALT + H , B , T: Add a thick border around selected cells
ALT + A , W , T: Insert Data Table
ALT + H , L: Open conditional formatting menu

Case study details

Zippy Airways has been operating for 3 months out of Gatwick Airport in London and has 16 flights per day between London and four European cities.

No-overbooking policy... yet

Unlike most other airlines Zippy does not operate an overbooking policy – which allows the airline to sell more tickets than the number of seats (180) available on a flight - thereby increasing revenue. The policy relies on a certain number of customers that book a ticket but do not show up for the flight (no-shows).

No-shows

If the number of no-shows is greater than the additional tickets sold, no extra cost. If too many passengers show up, however, the airline must pay a ‘bumping cost’ to move passengers to a later flight.

Bumping costs

If a customer gets bumped to another Zippy Airways flight later that day, then Zippy will pay them on average £150 in vouchers for the inconvenience.

If a passenger is bumped from a flight that has no Zippy Airways planes later that day, she will fly home with SloMo Airways, which has an agreement with Zippy to look after all bumped passengers at a cost of £175 per passenger. The passenger still receives the voucher from Zippy.

Transcript

Contents

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04:59

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05:56

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05:29

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06:07

03:33

#### 18. Limitations of the Model

02:03

My Notes

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