Airlines Industry Yield Management. Ken Homa

Airlines Industry Yield Management Ken Homa

Airlines Industry Challenging Environment Complex, interconnected network Thousands of dynamic prices 90% discount prices 20% pay less than half of average 2/3 s big companies get 35-45% off 50% cancellations 15% no shows

Airlines Industry Passenger Info Business / leisure split 50/50 Business: 50% passengers, 60% profits 25% of passengers pay more than 2.5 times average fare Heavy users: top 5% = 40% of trips No brand preference for 50% of leisure and 25% of business travelers

Airlines Industry Fundamental Economics Very high investment and fixed costs Equipment & maintenance Computer systems ( reservations) Flight Fixed: fuel, crew, airport fees Low variable cost Agent commissions (8-10% on 85% of volume) In flight food & beverage, incremental handling Empty seats: nil incremental cost Fixed, highly perishable inventory

Airlines Industry Low Frills Economics Variablize the fixed costs Source services & personnel Streamline offerings Precisely match segment s value function Accept lower margins Lower relative investment

Anybody Remember PeopleExpress? Simple strategy: low frills, low price (Too) rapid expansion No infrastructure (I/T, res system) Very low average cost, but AA killed PeopleExpress AA marginal cost < PE average cost AA attacked with laser fars

Available Passenger Miles (APM) Gross measure of capacity Revenue Passenger Miles (RPM) Number of passengers weighted by distance flown Load Factor RPM divided by APM Yield Factor Airlines Industry Performance Metrics Revenue per RPM Fly full with high paying passengers

Airlines Marketing Network routing Capacity planning Flight Scheduling Yield Management

Network Routings Point to point OD pairs (origin - destination) Originating & continuation flights Hub-and-spoke connections Roughly 2/3 s passengers arriving at a hub connect to other flights

Capacity Planning Aggregate Seats and configurations Route-specific Through flight considerations Load factors The performance metric

Flight Scheduling Customer preferences Peaks & valleys Connections Planes & crews Disruptions Weather, equipment

Yield Management Overbooking Fares Allocation Traffic management Sell as many seats as possible at full fare, then fill otherwise empty seats with discounted fares that exceed variable costs.

Jargon Displacement High price customer rejected in favor of low price customer Usually undesirable, but not always Dilution Price insensitive customers pay lower prices Diversion Customer is shifted to an alternative available flight Spillage Customer turned away because of capacity limits Spoilage An empty seat on departure

Jargon Cancellation Roughly half of all confirmed reservations are ultimately cancelled No show Roughly 15% of confirmed passengers neither cancel nor show up for the flight Overbooking Accepting more reservations than seat / fare capacity on a flight Oversold Confirmed passengers are denied boarding on a sold out flight

Overbooking The No Show Issue On average 15% of confirmed passengers don t show up for a flight Changed plans (without cancellation) Double-booking Spoilage: very high opportunity cost But only on flights with denied reservations Objective: sell-out the flight Take more reservations than capacity in anticipation of no shows

Overbooking Overbooking only applies to a portion of all flights Overbooked not the same as oversold Overselling results from stochastic nature of no show pattern

Overbooking Costs Volunteer Inducements Rerouting costs Hospitality concessions Loss of goodwill (involuntary denials)

Volunteer Inducement Magnitude of inducement Increases with number of seats oversold Ultimate cost depends on the method of fulfilling the incentive Space available negligible cost, except possible fare dilution (to free) Space constrained displacement / opportunity cost unless controlled Credit certificates... Dilutive or stimulative?

Rerouting Cost dependent on fulfillment method Space available negligible cost Sold out displacement / opportunity cost 2nd round oversale Competitor flight cash cost (at premium fare)

Overbooking The Number Ceiling to limit goodwill impact Estimate (and re-estimate) no show probability function Calculate expected cost of overselling Probability of occurrence Cost of remedial action Calculate expected opportunity cost of possible spoilage Marginal cost = marginal benefit

Fares Allocation Pricing Considerations Dilution Price insensitive customers pay lower prices Displacement High price customer rejected in favor of low price customer Usually undesirable, but not always Share Shift Movement of volume among competitive carriers Stimulation New demand in response to lower prices

Fares Allocation Fundamentals Fence to minimize dilution Advance purchase, minimum stay, etc. Equalize expected marginal revenue Restrict inventory, nest reservations access Dynamically re-estimate probabilities Link to overbooking policies and to traffic management

Traffic Management Maximize system revenue (global optimum) not specific segment (local optimum) Tied to inventory availability (vs. sold out) Can create favorable displacement...

Desirable Displacement A to B: full = $100, discount = $50 B to C: full = $250, discount = $125 A to C: full = $350, discount = $175 A to B is full, and B to C is available Accept discount reservation A to C since $175 > $100

Yield Management Overbooking Fares Allocation Traffic management Sell as many seats as possible at full fare, then fill otherwise empty seats with discounted fares that exceed variable costs.

Airlines Industry Yield Management