CASE STUDY
Improved forecasting accuracy and efficiency: How London Luton Airport managed to reduce time spent on forecasting from 3 hours to 20 minutes a week.
London Luton Airport
18.2 mill. passengers (2019)
124 Destinations
London Luton Airport is an international airport located in Luton, Bedfordshire, England, situated 56 km north of Central London. The airport is owned by London Luton Airport Ltd (LLAL), a company wholly owned by Luton Borough Council, and operated by London Luton Airport Operations Ltd (LLAOL).
The airport handled more than 18 million passengers in 2019 to more than 120 destinations.Â
Introduction to the collaboration with London Luton Airport.
London Luton Airport (LLA) engaged with Copenhagen Optimization (CopOpt) to improve the accuracy and efficiency of their passenger forecast. Once a time-consuming and complex task depending on one specialized employee, passenger forecast at LLA is now more accurate and more accessible than ever.
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The Solution: Better Forecast
Copenhagen Optimization worked in close collaboration with key stakeholders from LLA to gather a detailed understanding of the site-specific challenges and secure a smooth and fast implementation process lasting only three months.
Better Forecast, Copenhagen Optimization’s cloud-based forecasting solution, provides detailed forecasts of passenger numbers, load factors, and presentation profiles on a flight-by-flight basis. Accuracy is of high priority since the forecast serves as the foundation for planning and correct staffing to demand.
Already within the first two months, the forecasted number of passengers per day came within a 2% margin. Since the solution is self-correcting, accuracy is constantly improving. The impact is clear: LLA has expressed great satisfaction at all steps in the process.
Outcome achieved:
- The time spent on forecasting has been reduced from 3 hours to 20 minutes a week – a 89% reduction.
- Several stakeholders are now able to update the forecast.Â
- 75.4% of the days are forecasted within ± 2%.
- 96.7% of the days are forecasted within ± 5%.
Final thoughts
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