Case studies/Causal AI Case-Study
Optimised crew and fleet planning.
Aviation · 2024
Challenge
Large volumes of flight, maintenance, and operations data were hard to access, and earlier analytics projects did not reach high forecast accuracy. In addition, workforce planning for around 450 crew members and 500 weekly flights was barely solvable efficiently by hand.
Solution
Askantis built an automated data pipeline that unifies all data sources in real time, plus a modular causal analytics platform. A probabilistic forecast model for crew availability was combined with a multi-KPI optimiser that minimises working days, maximises satisfaction, and reduces costs.
Impact
Crew utilisation rose by 6%, while the rate of approved time-off requests also increased. Interventions were also identified that prevent failures due to part defects, reduce fuel consumption, and improve operational safety.