Airline & Travel Revenue Management

What you'll build

What you will be able to do

Each lab ends with a concrete result that you build yourself and the checker confirms, cell by cell.

• Turn one month of route data into ASK, RPK, load factor, yield, RASK, CASK and the break-even load factor, and spot the routes that fly below break-even.
• Decide how many seats on flight 214 to protect for late Flex passengers and how many Saver seats to sell, with Littlewood's rule and NORM.INV.
• Extend Littlewood's rule to four fare classes with EMSR-b and set nested booking limits for flight 380.
• Measure cancellation and no-show rates on 12 past departures and forecast how many passengers will actually board on Fri 30 Oct.
• Set the overbooking level for flight 214 from the costs of empty seats and denied boardings, then check the risk and the expected cost with the binomial distribution.
• Build the average booking curve of flight 214, forecast the current flight with additive and multiplicative pickup and chart it against history.
• Compare three views of route profitability and find the route that looks like a loss-maker but should stay in the network.
• Calculate ancillary revenue per passenger and choose the fare for the last 40 seats of flight 517 that earns the most in total.