Airline Business Process Optimization

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Copyright (c) 2009 JeppesenJeppesen.com

Airline Business Process Optimization

[email protected]
http://www.jeppesen.com/lookagainhttp://www.jeppesen.com/lookagain


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Copyright (c) 2009 Jeppesen 2

Presentation Plan

Introduction

Research

Application

Case Study 1

Case Study 2

Summary


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Introduction


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How All These Happened

Visited/met several airlines worldwide

Performed an extensive research of airline businessprocesses

Developed template business process model

Developed methodology to analyze and streamlinebusiness processes by providing business, system anddata views

Applied acquired knowledge at several airlines


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Research


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Methodology

Developed methodology to captures airlines business

processes allowing to understand: How an airline works,

Who is involved,

How activities flow from beginning to end.


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Metrics

Developed structured set of metrics allows:

Comparison of alternatives and identification of best practices Focusing on global value rather than on value by silo is crucial in

showing the added value

0

50

100

150

200

250

300

10 20 30 40 50 60 70 80 90

Initial Delay Time

ScheduleDeviationMetrics

Recovery

TimeDelayed

Flights

Delay

Time

OverlapTime

Delay &

Overlap

Delay propagation

0.20.4

0.60.8

1

1

0.8

0.6

0.4

0.2

0

0.1

0.2

0.3

0.4

0.50.6

0.7

0.8

0.9

1

(0.50, 0.40, 0.70)

(0.60, 0.60, 0.60)

(1.00, 0.80, 0.88)

(1.00, 1.00, 1.00)1

*5

R


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Combined

Combination enables:

Better transparency Bottleneck identification

Processes streamline

Identification and validation of optimization opportunities


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Application


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Current Work

Focus on implementation of developed methodology by

customizing templates to the actual airline processes

Providing system, data and decision flow views withinexisting business process model

Identifying process optimization opportunities andproviding best practices

Two case studies showing results obtained at two mid-size airlines with large international networks, one withscheduled and other with ad-hoc operations

Deliverable includes: As-Is process models

To-Be process models


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Case Study 1


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Airline Business Processes

Flight

Scheduling

Fleet

Scheduling

Maintenance

Scheduling

Crew

Scheduling

Transition &

Coordination Operations

Revenue

Management

Planning &

Maintenance


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AS-IS Planning Process Model

Initial

plan

Flight

Scheduling

Initial

plan

Fleet

Scheduling

Plan

maintenance

Maintenance

Scheduling

Plan

maintenance

Crew

Scheduling

Initial

plan

Plan

reoptimization

Pairing

Plan

maintenance

Final

plan

Plan

maintenance

Rostering

Plan

maintenance

Manual

adjustments

Plan

maintenance

Roster

maintenance

Revenue

ManagementReservations


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TO-BE Planning Process Model

Initial

plan

Flight

Scheduling

Initial

plan

Fleet

Scheduling

Plan

maintenance

Maintenance

Scheduling

Plan

maintenance

Crew

Scheduling

Initial

plan

Plan maintenance &

reoptimization

Pairing

Plan

maintenance

Final

plan

Rostering Roster

maintenance

Revenue

ManagementReservations


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AS-IS Transition Process

System View

Aircraft/

crew

connect

ions

dataexch

ange

Planning Data transfer Operations

Tail assignmentsTail

Assignment

Crew

Pairing

Validation

Transition

Crew

Rostering

Crew

pairings

Tail assignments

Movement

Control

Aircraft

Recovery

Passenger

Recovery

EDS

Flight Dispatch

Tail assignments

Reservations

Reservation

System

Bookings

Crew

Tracking

Reroutes


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Operational DataPlanning Data

TO-BE Transition Process

System View

Planning Data transfer Operations

Tail

Assignment

Crew

Pairing

Crew

Rostering

Crew Rosters

Movement

Control

Aircraft

Recovery

Passenger

Recovery

EDS

Flight Dispatch

Tail Assignments

Reservations

Reservation

System

Bookings

Crew

Tracking

Reroutes


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AS-IS Operations Process Model

Flight

Scheduling

Aircraft

Tracking

Pax

Rerouting

Flight updates

Crew

Tracking

Aircraft

recovery

Maintenance

recovery

Flight

history

Flight

Dispatch

Maintenance

Management Maintenance updates

Maintenance

history

Reservation updatesBooking

history

Tail updatesFleet

history

Crew updatesCrew

historyCrew

recovery

Flight

planning &monitoring

Pax

recovery


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TO-BE Operations Process Model

Flight

Scheduling

Aircraft

Tracking

Pax

Rerouting

Future operation updates

Crew

Tracking

Maintenance

recovery

Operations

history

Flight

Dispatch

Maintenance

Management Maintenance updates

Maintenance

history

Aircraft &passenger

recovery

Crew

recovery

Flight



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Case Study 2


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Airline Business Processes

Flight

Scheduling

Fleet

Scheduling

Crew

Scheduling

Planning &

Maintenance Operations

Sales

Customer

Services


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AS-IS Planning Process Model

Flight

request

Sales

Feasibility

Check

Flight

Scheduling

Flight

acceptance

Fleet

SchedulingFleet

assignment

Account

management

Plan

maintenance

Crewassignment

Rostermaintenance

CrewScheduling


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TO-BE Planning Process Model

Flight

request

Sales

Fleet &

Crew

assignment

Flight

Scheduling

Flight

acceptance

Fleet

Scheduling

Account

management

Plan maintenance

& reoptimization

CrewScheduling


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AS-IS Operations Process Model

Flight

Scheduling

Aircraft

Tracking

Flight updatesFlight

history

Flight

Dispatch

Tail updatesFleet

history

Flight


Fleet

assignment

Feasibility

Check

Aircraft

tracking

Schedule

tracking

Crew

Tracking Crew updates

Crew

historyCrew

assignment

Crew

tracking

SalesPassenger updates

Booking

history

Flight

request

Flight

acceptance

Pax

tracking


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TO-BE Operations Process Model

Flight

Scheduling

Aircraft

Tracking

Flight

history

Flight

Dispatch

Future operations updatesFleet

history

Flight


Aircraft

recovery

Crew

Tracking

Crew

history

Crew

recovery

SalesPassenger updates

Booking

history

Flight

request

Passenger

tracking & recovery


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Summary (cont.)

Allows profit centric operations - at each moment it is

possible to see cost/revenue effects of using certaintail/crew, rerouting passengers and diverting flights

Set of KPIs available to evaluate consequences for eachaffected area as well as to find pareto efficient solution

Initial findings show response time and solution qualityimprovement

Airline Business Process Optimization

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