Big Data for the Airport How can it Contribute to an Enhanced Travel Experience?

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1 Big Data for the Airport How can it Contribute to an Enhanced Travel Experience? Nikolaos Papagiannopoulos Project Leader, Business Information Systems & Technology Athens International Airport

2 Athens International Airport Big Data for the Airport How can it Contribute to an Enhanced Travel Experience? Photo (if necessary) Airport IT 2014 Frankfurt 17/11

3 Agenda Athens International Airport Why Big Data? Challenges Opportunities Airport Business Cases Data sources 3

4 AIA is a pioneer PPP greenfield project Hellenic Republic Asset Development Fund 30.00% Greek State 25.00% Ministry of Finance Ministry of Development, Competitiveness, Infrastructure, Transportation & Networks AviAlliance 26.67% AviAlliance Capital 13.33% Hastings Fund Mngt (Australia) Caisse de dépôt & placement du Québec (Canada) KfW-IPEX Bank (Germany) Copelouzos Group 4.99% BOT contract (ADA) Opened in March 2001 A 2.2 billion Euro Project 2.14% contribution to Greece s GDP 60% funded by commercial debt User recovery principle 4

5 creating a modern airport Original T1 Phase Masterplan 2 independent runways 24-hr operation 168 T m 2 MTB, 34 T m 2 STB 24 Contact Bridges 75 active remote positions 3 Maintenance Hangars 4 Cargo Facilities, 30+ T m 2 3 Catering Facilities 300 enterprises, employees airport community 53km External Fuel Pipeline 5

6 Lean client-focused organisation designed on business units BoD Internal Audit C E O Communications & Marketing Legal Corporate Planning Corporate Control COO CDO CFO Business Unit IT & T Business Unit Aviation Security Services Environmental Business Unit Consumers Business Unit Property Technical Services Corporate Unit Finance & Admin. Human Resources Corporate Quality 6

7 An Airport City has been developed.with potential for more Train Station 2003/04 Leroy Merlin 2006 IKEA & Electronics Store Exhibition Centre Factory Outlet Cargo & Catering 2001 Offices MW PV Park 2011 Airport Hotel 2001 Terminal Retail Area 2001

8 Why Big Data? Strategic Business areas of Deployment Optimize resources and enhance operational efficiency Improve Customer Experience Improve existing & Create new revenue streams Manage Airport capacity related investments and maximize use and availability of infrastructure -8-

9 Objectives Increase Productivity Provide new decision support capabilities (e.g. real time). Produce new services Identify activity patterns and optimize utilization of existing infrastructure Project future demand and make smarter capacity investments. Increase maintenance efficiency from facilities and equipment -9-

10 Why Big Data? Optimize resources and enhance operational efficiency Improve Customer Experience Improve existing & Create new revenue streams Manage Airport capacity related investments and maximize use and availability of infrastructure Commoditize decision support capabilities to more users. Embrace more data sources (e.g. external sources, Social) Allow for real time decisions Correlate more information for enhanced results (e.g. sales vs flights vs passenger nationalities vs shop locations vs products vs time of day vs ) Eliminate data silos and create a single version of truth. -10-

11 Why Big Data? Optimize resources and enhance operational efficiency Improve Customer Experience Improve existing & Create new revenue streams Manage Airport capacity related investments and maximize use and availability of infrastructure Personalize Products and Services Know your customers Focus Marketing Initiatives Enhance existing services and identify new ones Improve customer support Identify & Mitigate negative experiences -11-

12 Why Big Data? Optimize resources and enhance operational efficiency Improve Customer Experience Improve existing & Create new revenue streams Manage Airport capacity related investments and maximize use and availability of infrastructure Develop new services and enhance existing by: Profiling and segmenting customer base Identifying & Recording Trends and buying patterns Fine tuning and personalizing loyalty programs Introduce revenue/yield management in strategic areas. Promote ancillary services. Produce Passenger Traffic heat maps of the Airport terminal to optimize concessionaire placement. -12-

13 Why Big Data? Optimize resources and enhance operational efficiency Improve Customer Experience Improve existing & Create new revenue streams Manage Airport capacity related investments and maximize use and availability of infrastructure Identifying activity patterns and optimize utilization of existing infrastructure Projecting future demand based on current utilizations but also local, regional & global trends and events (e.g Conferences, sporting events, Market growth, GDP, Travel forecasts and trends, Pandemic & epidemic of infectious diseases, geopolitical developments etc.) Making smarter capacity related investments. Increase maintenance efficiency from facilities and equipment. -13-

14 Challenges Opportunities Volume of data ever growing: IATA Forecasts that by 2017 total passenger numbers are expected to rise to 3.91 billion - an increase of 930 million passengers over the 2.98 billion carried in All these Passengers generate a large number of data such as reservation, consumer, financial, geolocation, social information etc. By capturing and processing these data customer trends, preferences, identification, profiling, segmentation is possible. Aircrafts generate 2 terabytes of data per flight from their sensors. -14-

15 Challenges Opportunities Velocity ever increasing: Real or near real time decision support processing require capturing data sources generating data in high speeds. Sources such as Video Analytics and CCTV data streams require the capturing and processing of fast data streams to identify passenger patterns in real time such as security screening queue management, passenger emergencies, security incidents. Social data have a remarkable generation rate e.g. 277K Tweets, 2.5 million Facebook shares, 72 hours of YouTube video every single minute Machine Data generated by electromechanical equipment (e.g. PBBs, sensors), Building management systems, ( e.g. energy consumptions readings etc.)

16 -16-

17 Challenges Opportunities Variety of data increasing: Value of using big data derives from the correlation of different data sources to create a holistic and multidimensional perspective for a given business case. Data need to be consumed at the source as it may become resource expensive because of the ETL processes and input / normalization needed in case of processing within Datamarts or Data warehouses. Data sources may vary from Airline Reservation data, Flight schedules, Duty Free POS, to Video analytics, Social and External Sources data. -17-

18 Challenges Opportunities Veracity of data is vital: Trusted data are paramount for effective decision making. Big data allow for evaluating the different data streams by crosschecking information provided by diverse sources. -18-

19 Big Athens International Airport Identify Business Cases Promote Big data Initiative within the organization and consult every Dept. for existing or desired Business cases or decision support activities based on existing or non yet exploited data. Data Sources Identify available data sources either in-house or from a third party (e.g. sub-contractor, commercial data sources etc.). Perform a gap analysis and identify information that are missing or that could be used for future business needs. Under Implementation Car Park Case Retail Case -19-

20 Airport Business Cases Data sources Airport Operations Real time terminal utilization. Capacity optimization. Delay mitigation. Terminal Heat maps. Marketing Focused marketing activities. Efficiency of marketing Campaigns New engagement methods and services Retail Concessionaire real time input. Analytics on buying patterns. Personalized Services. Optimized position of outlets - flights

21 Business Cases cont. Technical & Maintenance Services Usage of infrastructure Energy Consumption Optimization of equipment service cycles Corporate planning Security Identification of irregular passenger activity patterns. Security screening optimization and queue management Terminal Capacity Optimization Passenger forecasting Future Capacity Related Investments

22 Data Sources Available Data Sources AODB CUTE CCTV BHS/BRS Video Analytics Passenger Surveys Concessionaire s Sales Data Technical & Maintenance Services Website clickstreams Newsletter and E-Campaign analytics -22-

23 Data Sources cont.. Available Data Sources Building Management Systems Energy consumption Systems Data logs form electromechanical equipment Available External sources Social Media Meteorological data Traffic management updates Public Transport itineraries -23-

24 Airport Car Park Business Case -24-

25 Car Park Business Case Objectives Increase Car park utilization Promote car park usage for passenger arriving at the airport. Profile customers (e.g. returning customers, corporate, leisure) Identify Market Segments Identify usage trends (nationalities, destinations etc.) Identify sweet points for Yield Management. Identify customer buying capacity and personalize offers Upsell and cross sell Promote ancillary services Share and receive input from other Airport functions (Retail, Airport Operations, Security) Dynamically project usage and adjust prices accordingly. -25-

26 Car Park Business Case Available Data Sources Car Plate Identification system Paying points (cash, credit, invoice) Parking Management System Road Sensors in car park Area E-Parking website Video Analytics CCTV Passenger surveys AODB Retail data Social Media Meteo data Airport Mobile Applications -26-

27 Airport Retail BU Business Case -27-

28 Retail BU Business Case Objectives Increase Concessionaire utilization Profile customers based on spending, nationality, destination (e.g vias), type of flight etc. Identify Market Segments Identify sweet points for Yield Management. Identify customer buying capacity and personalize offers Promote ancillary services Smart positioning of concessions, products, flights to maximize sales Increase revenue per visit Reduce the non buying visit Cross sell Up sell Perform basket analysis -28- Available Data Sources Point of Sales Video Analytics CCTV Passenger surveys AODB Retail data and analysis Social Media Meteo data Airport Mobile Applications Location Based Services

29 Facilitators Sharing of all airport stakeholders information sources to create common situational experience Airline Reservation data Hotel reservation Data E-booking sites Data Travel agencies Data Airline Operations Data Ground Handlers Operations Systems Data Car rental systems Data Mobile Operator s Data etc. -29-

30 Future - Innovation trends Internet of Things - IoT Internet of Everything IoT + Data + People + Proceses Wearable Technology (Google glass, smartwatches, biometric sensors, smart clothing etc.) Indoor navigation systems Indoor & On shelf Beacons Smart Spaces Enhanced video analytics Enhanced Locations Based Systems Augmented reality Limitless opportunities!!! -30-

31 T H A N K Y O U

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