We helped one of the world's largest operators of fast-moving catamaran ferries, digitalise its core, enabling them to utilise advanced analytics and artificial intelligence, increasing business customers per departure by 14%.
We helped one of the world's largest operators of fast-moving catamaran ferries, digitalise its core, enabling them to utilise advanced analytics and artificial intelligence, increasing business customers per departure by 14%.
Problem
Forecasts were static, manually processed and made from historical statistics and experience. Molslinjen wanted to become more data-driven and forward-looking.
Solution
Together with Molslinjen, Halfspace developed a Forecast Engine to predict the number of arriving vehicles for each departure, enabling Molslinjen to optimise ferry load and bookings.
How AI adds value
Molslinjen was able to transform its demand forecast from a manual, historical and time consuming approach to an automated, data-driven, AI based forecast, delivering more accurate forecasts on arriving vehicles for each departure. The AI solution was one of the most recognized and award winning AI cases in the world last year.
“We see from the results that there is huge business potential to extend the Forecast Engine made by Halfspace to the rest of our organisation.”
Jesper Skovgaard, CCO, Molslinjen
Forecasting as a success factor
One of the most crucial factors in optimising ferry operations is the ability to accurately forecast the number of vehicles and passengers arriving for departure. Not all individuals who make reservations will show up.
Still, if operators like Molslinjen can accurately predict the number of vehicles and passengers that do arrive, they can utilise their capacity more effectively and optimise pricing and ticket sales.
Business impact
However, until recently, forecasts were relatively static, manually processed and made from historical statistics and experience. Molslinjen wanted to become more data-driven and forward-looking. The objectives were clear:
- Improve load times
- Minimise delays
- Meet staffing and catering requirements with greater accuracy
- Guarantee reservations for business customers
- Sell unused reservations
- Prepare marketing to be more targeted
From manual forecast to an AI-Based forecast
Molslinjen hired Halfspace to assist the company in moving from manual estimation to a fully automated AI-based solution. The result was a Forecast Engine that sources data into a data lake, then processed by three different engines, advanced forecasts are generated. The first engine makes predictions based on historical patterns, the second engine adjusts these predictions based on up-to-date bookings, and the third engine combines the first two to make real-time predictions based on actual check-in times and traffic conditions.
Organisations that effectively use data and predictive modelling can improve customer satisfaction, optimise sales, and align better with their ESG strategy. This can be achieved by capturing and visualising data and outcomes from advanced modelling, which can simplify vast amounts of data and complex modelling, and improve operational decision-making.
