Spindox MENU ABOUT EN Case StudiesSpindox NewsUbliqueuncategorized Europcar boosts revenues with Opticar, an integrated demand intelligence and revenue management solution. By Alessandra Bossi - 25 June 2021 476 The revenue management solution of the European car rental giant is called Opticar, which has helped to bring in increased revenues and savings of $14 million per year. Like all car rental companies, the Europcar Mobility Group must make decisions every day based on two objectives: maximizing the use of the fleet and optimizing revenues. In both cases, decisions depend on the ability to correctly predict demand. Opticar is the fleet capacity management and revenue optimization system that the French multinational has created with Ublique’s Demand Intelligence and Revenue Management solutions. This project has allowed Europcar to save $14 million a year. Opticar is based on algorithms that can provide sales forecasts and fleet composition optimization output. After the success of the Italian pilot in 2014, the system has been extended to nine other countries in which the other branches of the company are located. Implemented solution Ublique is Spindox’s suite of decision intelligence solutions that implements statistical tools and applied artificial intelligence for simulation, forecasting, and process optimization. Europcar Mobility Group (EMG) is one of the main players in the mobility industry. With its four brands (Europcar, InterRent, Ubeeqo, and Goldcar) and span over a network across 140 countries, it offers alternative solutions to vehicle ownership through a wide range of services related to mobility: vehicle rental, chauffeur services, car sharing, and scooter sharing. The increase in available data has prompted the group to exploit computing powers and an operational research approach with the aim of improving systems related to the decision-making processes. The resulting project is called Opticar and can be summarized through four main objectives. Implemented solution: Ublique | Demand Intelligence Forecast of new rentals – This module contains forecast algorithms that cross-match fleet utilization data from previous years and provide day-to-day 24-week forecasts of new rental estimates. The forecasts are not related to vehicle availability, although they are tied to various user-defined criteria, such as holidays, special events, and weather conditions. Demand Simulation – The abovementioned forecast module estimates the number of new rentals each day, but not their duration or where the car will be returned. This is where the simulation system comes in. In addition to the estimate of the rental contracts expected in the next 24 weeks, the simulations provide an overview of the current situation of Europcar’s activity in that specific period and the relative daily use of the fleets. To perform these simulations, some variables are considered such as the delay in vehicle returns, changes in requests, and cancellations. Optimization of the use of the fleet and intelligent assignment of the vehicles to specific areas – through a metaheuristic algorithm, the composition and use of the fleet are simultaneously optimized. Specifically, the output provides information on the following aspects: how to optimize the use of the fleet, taking into account constraints such as the acquisition and assignment of vehicles to specific areas on the basis of revenue, costs, and demand; how to optimize the transfer of vehicles, i.e., the transfer of available vehicles in the fleet from one area to another. The system considers the times and costs of the transfers and the forecast of the demand for each zone; how to optimize decommissioning, i.e., the removal of operational vehicles from the fleet when needed. Implemented solution: Ublique | Revenue Management 4. Dynamic Price Optimization – This module optimizes vehicle rental prices with mathematical models, matching Europcar’s list rates and competitors’ market prices and determines the balance between the two parameters to satisfy the simulated demand of the identified fleet and increase global revenues. Advantages obtained Optimization and better use of the fleet capacity. The first pilot project implemented in 2014 resulted in an increase in the level of use of the fleet by 4.8%. Increase in revenues, equivalent to a savings of $14 million dollars per year. The most prominent examples include the 3% daily increase in revenues in Spain and a savings of £1.3 million pounds in the UK. Over the past 5 years, Europcar’s global vehicle rental revenue has increased by nearly $584 million. These results must be taken into consideration bearing in mind the context of the mobility industry. This is a very competitive market where the growth of competitive low cost companies has exploded, and this has forced all companies in the sector to a global lowering of market prices with a consequent decrease in daily revenues. 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