making air travel smarter 2016 Resilient Ops, Inc.

Transcription

1 making air travel smarter

2 Don t just react to flight delays manage them ~30,000 passengers will fly into Orlando from within the US each day On average, 2,500 of those passengers will have their plans disrupted by a significantly delayed or cancelled flight What could your business do differently if you knew who was delayed or not arriving today? Enter flightsayer Predicting delays hours to days out, so you can proactively manage disruption caused by flight delays

3 Sample case study: LaGuardia to Ford Lauderdale on Oct 28 th We rank flights on a 1-10 scale of delay risk, and provide alternatives when delays are likely Departure Flight From To prediction 12 hours before departure 9:41 pm Suggested alternatives: 1371 LGA FLL High risk Flight may be delayed because of a late incoming flight and departure constraints at LGA. 50% likelihood of a 2hr+ delay 7:53 pm 1201 JFK FLL Low risk 8:03 pm 553 JFK PBI Low risk Low likelihood of 30+ minute delay. 8:45 pm 711 EWR FLL Low risk 3

4 Sample case study: LaGuardia to Ford Lauderdale on Oct 28 th We rank flights on a 1-10 scale of delay risk, and provide alternatives when delays are likely Departure Flight From To prediction 12 hours before departure Actual delay 9:41 pm 1371 LGA FLL High risk 2 hr 29 min Suggested alternatives: 7:53 pm 1201 JFK FLL Low risk 49 min 8:03 pm 553 JFK PBI Low risk 1 min 8:45 pm 711 EWR FLL Low risk On time 4

5 Our algorithms sort through vast and complex data to identify patterns that can predict future delays Historical flight performance Network connectivity Real-time status FAA advisories Weather Powerful algorithms Proprietary machine learning algorithms State-of-the-art technology Diverse data sources Domain expertise Deep expertise in modeling the airspace Working with NASA on developing airspace optimization tools 5

6 flightsayer helps the travel ecosystem deliver a better customer experience and drive down disruption costs Cruise lines Ground transportation Travel agents Hotels Airport businesses 6

7 flightsayer helps the travel ecosystem deliver a better customer experience and drive down disruption costs Proactively rebook customers; avoid cost of last-minute scrambling; deliver a smoother customer experience Cruise lines Ground transportation Travel agents Hotels Airport businesses 7

8 flightsayer helps the travel ecosystem deliver a better customer experience and drive down disruption costs Drive higher efficiency through better planning and resource utilization Cruise lines Ground transportation Travel agents Hotels Airport businesses 8

9 flightsayer helps the travel ecosystem deliver a better customer experience and drive down disruption costs Deliver a new service offering to stand out in a crowded marketplace, drive higher customer satisfaction Cruise lines Cars Travel agents Hotels Airport businesses 9

10 flightsayer helps the travel ecosystem deliver a better customer experience and drive down disruption costs Better yield management through delay forecasting, especially at airport hotels Cruise lines Cars Travel agents Hotels Airport businesses 10

11 flightsayer helps the travel ecosystem deliver a better customer experience and drive down disruption costs Align resourcing of airport businesses (e.g., restaurants and ground crew) to predicted delays Cruise lines Cars Travel agents Hotels Airport businesses 11

12 The team combines domain expertise with deep data mining capabilities Company has received two NASA SBIR grants to develop algorithms for air traffic optimization Bala Chandran (Ph.D., Berkeley) Optimization geek, graduate research in optimizing air traffic flows and predicting airspace congestion, former operations consultant Hamsa Balakrishnan (Ph.D., Stanford) MIT professor working on ways to improve airspace efficiency, working closely with the FAA and airlines Diana Pfeil, (Ph.D., MIT) Machine learning and airspace weather buff, PhD thesis on impact of weather on airspace capacity, worked on big data at Amazon before it was cool Loren Werner (M.S., MIT) Stats and modeling guru, former operations consultant, developed probabilistic risk models for healthcare, marketing, and financial services 12

13 How to work with us today Business Travelers Go to flightsayer.com and start tracking your flights as Beta testers Travel Businesses Conduct a low-overhead pilot to validate the value of our predictions Predictions can be accessed via web / License our API for integration into your travel application Access our predictions via an API / info@flightsayer.com 13