Veovo machine learning platform to power short, medium, and long-term forecasts and planning across Norwegian airports.
OSLO, Norway & LONDON, UK – Norwegian airport operator Avinor has partnered with Veovo to provide an integrated platform that will forecast, plan, and optimise operations across all areas of their airports. In one of the most comprehensive machine learning programs in the industry, the strategic collaboration aims to result in better passenger experiences across its 40+ airports and allow for more cost-effective and reliable operations.
Now more than ever, airports are operating in a very dynamic environment, increasing the need for planning to be more agile and backed by evidence-based data. As part of this program, Avinor and Veovo will effectively build data that reflects the processes of passenger and flight movements across each airport. This will enable service providers to continually improve performance by making automated and accurate predictions and putting actionable insights directly into the hands of staff, where and when they need it.
“To reach our strategic goals of delivering better services more sustainably and more efficiently, we must become a data-driven organisation,” said Abraham Foss, CEO of Avinor. “I look forward to seeing the operational, financial and service improvements of our partnership with Veovo.”
The Veovo machine learning platform will mesh data from multiple third-party systems and IoT devices to accurately automate predictions for multiple operational services and use cases across all time horizons. The program scope includes providing accurate forecasts and capacity planning for passenger and baggage flow, check-in, security, and border control resource planning. It can also be used to provide predictions for baggage handling, concession footfall, shuttle services and terminal services such as cleaning, passengers with reduced mobility (PRM) assignments and transfers. This will enable the airports to match the availability of services to demand at any time and proactively address any potential issues, improving both the passenger and staff experience while lowering the overall cost to serve.
The technology may also be used by Avinor to improve airside decision-making such as turnarounds, de-icing, gate allocations and maintenance planning. The prediction capability will extend between airports; if Avinor understands the impact of events in one airport on others in the Norwegian network, the operator can take early action to minimise disruption.
Lars Vagsdal, CTO at Avinor, said, “The Veovo machine learning platform was chosen after a comprehensive selection procedure involving technology pilots. Veovo’s ability to accurately aggregate multiple data sources and automate the delivery of accurate forecasts with no human intervention required stood out as a clear point of difference. We look forward to rapidly expanding its use across our airside and terminal processes.”
James Williamson, Veovo CEO, said, "We are delighted to enter this partnership with such an innovative and forward-thinking partner as Avinor. Our aligned vision will supercharge operational decision-making, long-term planning, and airport performance. Jointly, we will deliver more precise and detailed predictions and powerful ML-driven capacity optimisations, creating the smoothest possible journey for Avinor passengers.”
Vicky is the co-founder of TravelDailyNews Media Network where she is the Editor-in Chief. She is also responsible for the daily operation and the financial policy. She holds a Bachelor's degree in Tourism Business Administration from the Technical University of Athens and a Master in Business Administration (MBA) from the University of Wales.
She has many years of both academic and industrial experience within the travel industry. She has written/edited numerous articles in various tourism magazines.
