BEONTRA Scenario Planning
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1 BEONTRA Scenario Planning Operational Terminal Prediction: The BEONTRA CDM solution for Passenger Terminal Flows Manuel Heidler Director Product Management BEONTRA AG META-CDM, Toulouse
2 What is wrong with this picture? Picture taken on a summer Saturday morning around 6am in 2011 Page 2
3 What is wrong with this picture? Picture taken on April 23 rd 2014 around 830am Page 3
4 What is wrong with these pictures? Pictures taken in 2013 Page 4
5 Be on track? Shop opening hours not reflecting passenger show-up Immigration desks not staffed according to changed operational situation Lack of input data & differentiation of passenger flows Inadequate planning input resulting in bad passenger experience Page 5
6 Be on track! Operational Terminal Prediction: The BEONTRA CDM solution for Passenger Terminal Flows 24/7 Update Cycle Page 6
7 BEONTRA Integrated Corporate Planning Suite for Airports Be on track. Beyond traffic. Page 7
8 BEONTRA Scenario Planning Integrated Corporate Planning Suite for Airports Page 8
9 BEONTRA Scenario Planning Operational Terminal Prediction Use Case: Amsterdam Airport Schiphol Manuel Heidler Director Product Management BEONTRA AG Page 9
10 BEONTRA CDM Solutions Use Case Amsterdam Airport Schiphol Extended Scope (Optional) Page 10
11 Operational Terminal Prediction - The Schiphol Experience The challenge at Amsterdam Schiphol 323 Direct destinations Jobs on airport 52,6 million Travellers 1 Terminal 1,5 million Tonnes of cargo 8 Passport checks Air transport movements 6 Centralized security checks Page 11
12 Operational Terminal Prediction - The Schiphol Experience A joined approach Initial Situation Data input & output not sufficient (long) waiting times and queues for the passengers Inefficient resource planning Project Goals Up-to-date information for all processes Act instead of react Increase passenger satisfaction Efficient use of resources and reduction of operational costs Joined Approach Actual prognosis best known by airlines Share information with all stakeholders Develop a better passenger prognosis together with all stakeholders Page 12
13 Operational Terminal Prediction - The Schiphol Experience A joined approach Initial Situation Data input & output not sufficient (long) waiting times and queues for the passengers Inefficient resource planning Project Goals Up-to-date information for all processes Act instead of react Increase passenger satisfaction Efficient use of resources and reduction of operational costs Joined Approach Actual prognosis best known by airlines Share information with all stakeholders Develop a better passenger prognosis together with all stakeholders Page 13
14 Operational Terminal Prediction - The Schiphol Experience A joined approach Initial Situation Data input & output not sufficient (long) waiting times and queues for the passengers Inefficient resource planning Project Goals Up-to-date information for all processes Act instead of react Increase passenger satisfaction Efficient use of resources and reduction of operational costs Joined Approach Actual forecast best known by airlines Share information with all stakeholders Develop a better passenger forecast together with all stakeholders Page 14
15 Operational Terminal Prediction - The Schiphol Experience Steering of passenger process at Security & Boarder Control Expected passengers at filters Expected waiting times at filters Expected passengers at filters during the remaining of the day Page 15
16 Passagiersaanbod per kwartier Passagiersaanbod per kwartier lengte wachtrijen lengte wachtrijen Advies aantal benodigde balies/rijen Advies aantal benodigde balies/rijen :00 0:00 0:00 0:00 0:00 0:00 1:00 1:00 1:00 1:00 1:00 1:00 2:00 2:00 2:00 2:00 2:00 2:00 3:00 3:00 3:00 3:00 3:00 3:00 4:00 4:00 4:00 4:00 4:00 4:00 5:00 5:00 5:00 5:00 5:00 5:00 6:00 6:00 6:00 6:00 6:00 6:00 7:00 7:00 7:00 7:00 7:00 7:00 Heet Warm Koud 8:00 9:00 10:00 Heet Warm Koud 8:00 8:00 8:00 8:00 8:00 9:00 9:00 9:00 9:00 9:00 10:00 10:00 10:00 10:00 10:00 11:00 11:00 11:00 11:00 11:00 11:00 12:00 12:00 12:00 12:00 12:00 12:00 13:00 13:00 13:00 13:00 13:00 13:00 14:00 14:00 14:00 14:00 14:00 14:00 15:00 15:00 15:00 15:00 15:00 15:00 16:00 16:00 16:00 16:00 16:00 16:00 17:00 17:00 17:00 17:00 17:00 17:00 18:00 18:00 18:00 18:00 18:00 18:00 19:00 19:00 19:00 19:00 19:00 19:00 20:00 20:00 20:00 20:00 20:00 20:00 21:00 21:00 21:00 21:00 21:00 21:00 22:00 22:00 22:00 22:00 22:00 22:00 23:00 23:00 23:00 23:00 23:00 23:00 Passagiersaanbod per kwartier Passagiersaanbod per kwartier Advies aantal benodigde balies/rijen Advies aantal benodigde balies/rijen lengte wachtrijen :00 0: :00 0: lengte wachtrijen 0:00 1:00 1:00 1:00 1: :00 0:00 2:00 2:00 2:00 2:00 2:00 1:00 3:00 3:00 3:00 3:00 3:00 2:00 4:00 4:00 4:00 4:00 4:00 3:00 5:00 5:00 5:00 5:00 5:00 4:00 6:00 6:00 6:00 6:00 6:00 5:00 7:00 7:00 7:00 7:00 Heet Warm Koud 7:00 6:00 8:00 8:00 8:00 8:00 7:00 9:00 9:00 9:00 9:00 8:00 10:00 Heet Warm Koud 8:00 9:00 10:00 10:00 10:00 10:00 9:00 11:00 11:00 11:00 11:00 11:00 10:00 12:00 12:00 12:00 12:00 12:00 11:00 13:00 13:00 13:00 13:00 13:00 12:00 14:00 14:00 14:00 14:00 14:00 13:00 15:00 15:00 15:00 15:00 15:00 14:00 16:00 16:00 16:00 16:00 16:00 15:00 17:00 17:00 17:00 17:00 17:00 16:00 18:00 18:00 18:00 18:00 18:00 17:00 19:00 19:00 19:00 19:00 19:00 18:00 20:00 20:00 20:00 20:00 20:00 19:00 21:00 21:00 21:00 21:00 21:00 20:00 22:00 22:00 22:00 22:00 22:00 21:00 23:00 23:00 23:00 23:00 23:00 22:00 23:00 Operational Terminal Prediction - The Schiphol Experience Steering System Input & Output Day of Operation 1day 1wk 2wk 3wk 1mon 2mon 3mon 4mon Passagiersaanbod Vertrekfilter Passagiersaanbod Vertrekfilter Pax-prognose + differentiation options (e.g. premium, ShoCon/temp, carrier) Data Input Airlines Passagiersaanbod Vertrekfilter Passagiersaanbod Vertrekfilter Expected number of passengers per flight from the Airline Optimal resources Security & Border control Advies aantal benodigde balies/lanes Advies aantal benodigde balies/lanes Calculated waiting times Verwachte wachtrijlengte Verwachte wachtrijlengte Planned resources Security Advies aantal benodigde balies/lanes Advies aantal benodigde balies/lanes Calculated waiting times Security Verwachte wachtrijlengte Verwachte wachtrijlengte b.o. planned resources 0 Indication of available resources Border control Page 16
17 Operational Terminal Prediction - The Schiphol Experience Solution based on off the shelf BEONTRA Modules Launch Stakeholders: Page 17
18 BEONTRA CDM Solutions Operational Terminal Prediction Added Value for Airport Airlines Security Border Police Added Value for Airport Airlines Centralized Reporting Platform Access to all Calculated Information Day of Operation System Scope: - Calculation of DoO Data - New Results every 15min users - Mobile Reporting Access - High Availability System What-If System Scope: - Creation of scenarios - Usage of any Time Period - Calculation on Demand - 5+ users Automated Data Exchange ETL Process, Data Warehouse Data Sources Airlines AODB Border Police Security Other Stakeholders Other Sources Page 18
19 BEONTRA Scenario Planning Operational Terminal Prediction Setup of Prediction Model Manuel Heidler Director Product Management BEONTRA AG Page 19
20 OTP Planning Mode 1. Specify Airport Model Page 20
21 OTP Planning Mode 2. Specify Service Levels Page 21
22 OTP Planning Mode 3. Connect to Traffic Forecast Page 22
23 OTP Planning Mode 4. Get planning results Page 23
24 BEONTRA Scenario Planning Operational Terminal Prediction Showcase Manuel Heidler Director Product Management BEONTRA AG Page 24
25 OTP Showcase Day of Operations System At 9:00: Prediction for 12:00 Normal Ops Flight Arrivals Time Flight Destination Gate Remarks 12:05 KL 1010 London H2 12:15 KL 1673 Barcelona H12 12:30 KL 1603 Rome H5 12:50 KL 1087 Manchester H26 13:15 KL 1843 Vienna H11 13:20 KL 1175 Trondheim H84 13:40 KL 1189 Bogota H23 13:55 KL 1267 Nice H18 14:05 KL 1977 Budapest H23 14:25 KL 1317 Bordeaux H9 14:35 KL 1325 Alesund H41 14:50 KL 1365 Warsaw H8 15:05 KL 0411 Amman H6 15:20 KL 0415 Kuwait H22 15:30 KL 0427 Dubai H11 15:40 KL 0685 Mexico H55 15:55 KL 1115 Aarlanda H9 Page 25
26 OTP Showcase Day of Operations System At 10:30: INCIDENT BAD WEATHER Prediction for 12:00 Flight Arrivals Departures Time Flight Destination Gate Remarks 12:05 KL 1010 London H2 Delay 12:25 12:15 KL 1673 Barcelona H12 12:30 KL 1603 Rome H5 Delay 12:55 12:50 KL 1087 Manchester H26 13:15 KL 1843 Vienna H11 Delay 13:35 13:20 KL 1175 Trondheim H84 Delay 13:50 13:40 KL 1189 Bogota H23 13:55 KL 1267 Nice H18 Delay 14:30 14:05 KL 1977 Budapest H23 14:25 KL 1317 Bordeaux H9 Delay 14:40 14:35 KL 1325 Alesund H41 Delay 15:00 14:50 KL 1365 Warsaw H8 15:05 KL 0411 Amman H6 15:20 KL 0415 Kuwait H22 15:30 KL 0427 Dubai H11 15:40 KL 0685 Mexico H55 15:55 KL 1115 Aarlanda H9 30m waiting times at transfer security Page 26
27 OTP Showcase Day of Operations System Plan Do Check ACT!! CDM predictive decision support change gate announcement times change stand and gate allocation Mobilize/ demobilize crews to cope with situation Decide based on real time forecasts at your fingertips (mobile reporting) Page 27
28 BEONTRA Scenario Planning Operational Terminal Prediction Conclusion & Outlook Manuel Heidler Director Product Management BEONTRA AG Page 28
29 Operational Terminal Prediction - The Schiphol Experience Conclusion Real Time View of pax numbers at all filters with differentiation: e.g. Economy/Premium, Hot/Cold Reduce total lead time for passengers at the filters Reduced lead time for passenger at Border Control and Security filters at Schiphol. Increased passenger, personnel and airline satisfaction Increased satisfaction of passenger on passenger flows at Schiphol. Increased Commercial Dwell time of happy passengers Reduction of total costs for the business Better input data for the planning of security staff A better performance on passenger flows at Schiphol with lower costs for the business (due to e.g. better staff planning, decreased missed connections ). Page 29
30 Step 1: Prediction Step 2: Realtime measurement Page 30
31 Operational Terminal Prediction Outlook ipad App Flight Arrivals Departures Time Flight Destination Gate Remarks 12:05 KL 1010 London H2 Delay 12:25 12:15 KL 1673 Barcelona H12 12:30 KL 1603 Rome H5 Delay 12:55 12:50 KL 1087 Manchester H26 13:15 KL 1843 Vienna H11 Delay 13:35 13:20 KL 1175 Trondheim H84 Delay 13:50 13:40 KL 1189 Bogota H23 13:55 KL 1267 Nice H18 Delay 14:30 14:05 KL 1977 Budapest H23 14:25 KL 1317 Bordeaux H9 Delay 14:40 14:35 KL 1325 Alesund H41 Delay 15:00 14:50 KL 1365 Warsaw H8 15:05 KL 0411 Amman H6 15:20 KL 0415 Kuwait H22 15:30 KL 0427 Dubai H11 15:40 KL 0685 Mexico H55 15:55 KL 1115 Aarlanda H9 Page 31
32 BEONTRA Scenario Planning Operational Terminal Prediction: The BEONTRA CDM solution for Passenger Terminal Flows Manuel Heidler Director Product Management BEONTRA AG Page 32
33 Page 33
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