defining revenue management as a game gert hartmans agifors - berlin 2002

Defining Revenue Management

as a Game

Gert Hartmans

Agifors - Berlin

2002

Objectives

• Better understanding revenue management for system development

• Breakdown processes in small sub-processes

• Represent each sub-process as a game

• Link all games to reflect total process and enable review of strategies

• Derive system implications

Conceptual view of RevMgt 2000

Forecast

Display Availability

Reservations & Departure Control

GroupDesk

Fares & Rules

CapacityOptimise

Fares CapacityCompetitor

But daily issues ... 2002

• Corporate account access/effects

• Loyalty Program redemption access

• Alliance partner access

• Interline/SPA (non-) access

• Product differentiation (Economy +)

• CRS costs

• Ticket Class / Booked Class mismatch

• Waivers by sales

Systems - ‘ modular design ’

Salescontracts

Pricing

InventoryControl

Account-ing

Loyalty

SPA’sReserva-

tions

DepartureControl

Systems - links

Pricing

InventoryControl

Account-ing

Loyalty

SPA’sReserva-

tions

Salescontracts

DepartureControl

Systems in Alliance

Pricing

InventoryControl

Account-ing

Loyalty

SPA’sReserva-

tions

Salescontracts

DepartureControl

Pricing

InventoryControl

Account-ing

Loyalty

SPA’sReserva-

tions

Salescontracts

DepartureControl

Game Concept

• Players/Rules

• Rewards/Loss

• Choices/Strategy

• Enables modeling– Expectations/Guessing– Deception/Cheating– Cooperation/Retaliation

Inventory Control - Game

• Players Objectives– Maximize Revenue

• Rules – Players set availability access per round

without prior knowledge of others steps

– Two classes: H earns 1 points, L earns 0.5 points– L books first

• Actions– Open class or Close class

Inventory Control - Game 1.1:2

• Capacity 2 per player, Demand H1 L1 per round

• Pay off matrix for Blue– Per round one H-pax books valued at 1 and one

L-pax books valued at .5

• Dominant strategy = All open

Action red

H O L O H O L C H C L C H C L O AvgH O L O 0.75 1 1.5 1.25 1.125H O L C 0.5 0.5 1 1 0.75H C L C 0 0 0 0 0H C L O 0.25 0.5 0.5 0.25 0.375

Rewards Demand CapacityH = 1 1L = 0.5 1

Act

ion

Blu

e

2

BluePay-offMatrix


• Capacity still 2, demand H2 L1, L books first• Pay off matrix for Blue

– Per round two H-pax books valued at 1 and one L-pax books valued at .5

• Dominant strategy = H Open/ L Closed

Action red

H O L O H O L C H C L C H C L O AvgH O L O 0.75 1 1.5 1.25 1.125H O L C 1.5 1 2 2 1.625H C L C 0 0 0 0 0H C L O 0.25 0.5 0.5 0.25 0.375


Act

ion

Blu

e

2

BluePay-offMatrix


• Capacity still 2, demand H1 L4, L books first• Pay off matrix for Blue

– Per round one H-pax books valued at 1 and four L-pax books valued at .5

• Dominant strategy = Keep L open * Reward for H needs to be > 1.14 to close L

Action red

H O L O H O L C H C L C H C L O AvgH O L O 1 1 1 1 1H O L C 1 0.5 1 1 0.875H C L C 0 0 0 0 0H C L O 1 1 1 1 1


Act

ion

Blu

e

2

BluePay-offMatrix

spill

Usage of concepts

– Dominant strategy best for both, can be used for guessing expected competitor action

(leads to Nash Equilibrium)

– If competitor deviates from dominant strategy alternatives do not seem more profitable,avoid copy-cat marketing

– When reality/rules differs for both players, different strategies may be advantageous(larger capacity, different fares, lower frequency etc.)

Sub-processes

• Inventory control game

• Pricing game

• Fare Rule game

• Sales game

• Sales - Agents game

• Agents - Customer game

… products … loyalty ….

Pricing - Game 2.2:2

• Capacity 2 per player, demand H2L2, L books first

• Pay off matrix for Blue– Per round two H-pax books valued at 1 and two

L-pax books valued at .5

• Dominant strategy = Offer H fares only

BluePay-offMatrix

Action red

H A L A H A L X H X L X H X L A AvgH A L A 1.5 1 1 1.5 1.25H A L X 2 1 2 2 1.75H X L X 0 0 0 0 0H X L A 0.5 1 1 0.5 0.75


Act

ion

Blu

e

2

Fare Rule - Game 2.2:2

• Capacity 2 per player, demand H2L2 • L books first, H books L if no rule exists• Pay off matrix for Blue

– Per round two H-pax books valued at 1 and twoL-pax books valued at .5

• Dominant strategy = Add fare rules

BluePay-offMatrix

Action red

No Rule Rule AvgNo Rule 1 1 1Rule 1.5 1.5 1.5


Act

ion

Blu

e

2

Sales Game 4.4:4

• Capacity 4 is shared per 2 players (sales office) based on bids H:L 3:1 or evenly 2:2 (gray area)

• Demand H2 L2 per round per player, 4 per market• Dominant strategy = bid high and sell high,

but potential for cheating

B H S H B H S L B L S L B L S H AvgB H S H 2 2 3 3 2.5B H S L 1 1 1.5 1.5 1.25B L S L 0.5 0.5 1 1 0.75B L S H 1 1 2 2 1.5

Rewards Demand CapacityH = 1 2:2L = 0.5 2:2

Act

ion

Blu

e

4

BluePay-offMatrix

Sales - Agents Game

• Commission % differs, Demand 1 per round• Pay off matrix for Blue (Sales office)• Dominant strategy = Surpass competitor

commission levels if possible

Action red

20% 10% 5% Avg20% 0.4 0.8 0.8 0.6710% 0 0.45 0.9 0.455% 0 0 0.475 0.16

Rewards Demand1 1

BluePay-offMatrix

Agents - Customer Game

• Discount differs, Demand 1 per round• Pay off matrix for Blue (agent)• Dominant strategy = Match or surpass

competitor agent

Action red

20% 10% 5% Avg20% 0.4 0.8 0.8 0.6710% 0 0.45 0.9 0.455% 0 0 0.475 0.16

Rewards Demand1 1

BluePay-offMatrix

Value Chain

Action red

H O L O H O L C H C L C H C L OH O L O 1 1 1 1H O L C 1 0.5 1 1H C L C 0 0 0 0H C L O 1 1 1 1A

ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Airlines - Inventory game

Airlines - Pricing game

Airlines - Fare Rules game

Sales game

Agents -Customers game

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Action red


ctio

n B

lue

Sales - Agents game

Conclusions

• Market position is chain of games

• Organization, systems do not reflect inter-relations which are reflected in processes

• Open to cheating and deception

• System alignment and interfaces should help in achieving more optimal results

Enforcing rules

• Currently: Booking =/= Sale =/= Fare

• Commission variation, rule waivers, or over stating fares, leads to incorrect information

• Objective: 1 product = 1 contract =1 booking = 1 sale = 1 fare

Place CommercialHere

defining revenue management as a game gert hartmans agifors - berlin 2002

Documents