Dec. 9, 2016

Ensuring that flight schedules are optimized to customer needs, internal resources and operational and legal requirements, is one of the most challenging aspects of running any aviation operation – and that’s before factoring in dynamic, real-time disruptions or the desire for sustained profitability.

“The complexities and real-time dynamic nature of on-demand aviation operations are significant, and much more than many other industries we have seen,” said Roei Ganzarski, president and CEO of BoldIQ, which makes real-time schedule-optimization and disruption-recovery software. He will be presenting on this topic during a free, Jeppesen-sponsored webinar on Dec. 14.

“Creating a schedule that meets demand, satisfies all legal and physical constraints, and at the same time utilizes resources in the most efficient way while meeting internal needs, is a difficult problem, even if all of the key variables remain static, which of course they don’t,” he added.

As any flight department team member knows, many variables hardly ever remain static, and this usually presents the biggest challenges when adjusting plans on a day-to-day basis. While schedulers and dispatchers are incredibly capable, they’re also human. Simplifying the problems, such as factoring out a variable or two, to make them easier to solve, means sacrificing effectiveness and efficiency.

This is where software can help, said Ganzarski. Advancements in technology and complex algorithms can provide schedulers and other decision-makers with solutions on how to practically optimize operations – both initially and during disruptions. By understanding more about how best to combine human expertise and science to create a practical, optimized operation, aircraft operators can maximize their resources and gain a competitive advantage.

For an in-depth look at the science behind complex problem-solving and how software can help flight departments maximize their decision-making process, join NBAA and Ganzarski for the webinar titled “Decision Making in Complex Dynamic Environments: Experienced Human vs. Sophisticated Software.”