Pattern Computer,® Inc. (PCI) is excited to announce the discovery of new insights that can lead to significant reductions in the flights delays experienced across the United States.
According to the Federal Aviation Association (FAA)/Nextor, the estimated annual costs of delays, which includes direct costs to airlines and passengers, lost demand and indirect costs, in 2018 was $28 billion. Based on the Bureau of Transportation statistical data, 34% of all flights in 2018 experienced some type of departure delay and 18% of all flights experienced delays of 15 minutes or more, with an average delay of 66 minutes. The direct costs of those delays to airlines and passengers was $4.5 billion.
PCI’s team assembled a novel, integrated dataset which encompassed the FAA flight, aircraft and operational network data, and relevant US national weather data for the 7.2 million US commercial passenger flights in 2018.
Utilizing the Pattern Discovery Engine®, the PCI team was able to uncover a number of patterns underlying US commercial passenger flight delays. While many previous approaches focused on arrival delays, the PCI team chose to focus on flight departure delays as it more accurately reflects the operational efficiency of the individual airlines, as well as the airlines’ operational partnership with the FAA air traffic control facilities.
The most significant pattern, which was reflected as the top driver of delays in 11 of the 12 months, were flight departure delays due to weather factors along the route of travel, combined with the scheduled departure time (congestion). Together these two factors were the most consistent throughout the entirety of 2018. The flight leg for that day also played into this pattern in 10 of the 12 months as well – indicating that the cascading effect of flight delays continued to impact flights later in the day.
“When we used the Pattern Discovery Engine to understand the factors behind flight departure delays, we saw delays initiated by the FAA’s Traffic Management Initiatives due to en route weather as having created the most significant delays over the course of the year. The second most significant pattern was due to icing conditions at the departure airport, which also has cascading effects through the day for the impacted aircraft. A differentiating factor for Pattern Computer is that we do not see just one pattern; we see all the interrelated patterns in the dataset regarding a specific outcome in ranked order,” said Mark R. Anderson, CEO of Pattern Computer.
The newly discovered patterns indicate that most flight delays through the year were the results of significant weather events having regional limiting effects on the available flight routes. These large regional storms are typically predicted by the NOAA/FAA at least 48-72 hours in advance, airlines cancel flights ahead of the worst storms to avoid the high costs of long-delayed flights, including staffing costs, dissatisfied passengers, and crews cancelled due to duty-time expiration and required rest periods. While canceling flights is one option in reducing the costs of flight delays, the negative impact to customer satisfaction is high, and there is significant disruption to the airlines’ careful scheduling of crews, equipment and supporting staff. Too often the case is to carry on with the planned schedule and let the FAA determine how many planes are impacted as the weather event occurs. In many aspects, this is the same operating strategy as has been in effect for the past 4 decades.
“Due to the pandemic, the travel industry is facing a challenging period of uncertainty, but with that is the opportunity to improve operations, pricing, and offerings in a way that is future-ready. There is an opportunity to develop services tailored for the life styles, needs, and interests of business and leisure passengers alike. Post-pandemic, people are expecting a ‘new normal’ to emerge with many of the known patterns of life being different. Now is the time to introduce new capabilities, preparing for a post-pandemic swell in leisure travelers wishing to get out and travel,” said Bob Edwards, former CIO for United Airlines.
Without changes, the airlines will continue to bear substantial direct and indirect costs due to flight departure delays. But informed by these new Pattern discoveries, leading airlines could use technology, data and analytics combined with agility to create new solutions in the form of flexible scheduling, routing, pricing, and packaging to avoid these costs, which will only increase as the passenger loads begin to recover to their new normal, which may exceed the historical norms.
This work by Pattern Computer could allow informed, flexible scheduling. Dynamic load levels could be shifted and adjusted to the changing conditions, optimizing for costs, better utilizing available resources and resulting in more reliable schedules. Pattern is continually innovating and looking for ways to improve and optimize complex challenges in multiple industries, including the global airline industry, where new partnerships are now being sought.
The foregoing contains statements about the Pattern Computer’s future that are not statements of historical fact. These statements are “forward looking statements” for purposes of applicable securities laws, and are based on current information and/or management’s good faith belief as to future events. The words “believe,” “expect,” “anticipate,” “project,” “should,” “could,” “will,” and similar expressions signify forward-looking statements. Forward-looking statements should not be read as a guarantee of future performance. By their nature, forward-looking statements involve inherent risk and uncertainties, which change over time, and actual performance could differ materially from that anticipated by any forward-looking statements. Pattern Computer undertakes no obligation to update or revise any forward-looking statement.
About Pattern Computer
Pattern Computer, Inc., a Seattle-area startup, uses its proprietary Pattern Discovery Engine to solve the most important and most intractable problems in business and medicine. Its proprietary mathematical techniques can find complex patterns in very-high-order data that have eluded detection by much larger systems.
While the company is currently applying its computational platform to air traffic operations, it is also making pattern discoveries for partners in several other sectors, including drug discovery and biomedical research, materials science, aerospace manufacturing, veterinary medicine, and finance.
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