A common problem faced by expanding companies is the shortage of skilled and experienced domain experts, especially planners and controllers. This can seriously slow down or impede growth.
Our client is one of the largest travel agencies in Hong Kong. They operate a fleet of luxury limousines and shuttles servicing mainly business travelers. To alleviate this problem, we created a Web-based mission critical Fleet Management System (FMS) that supports the scheduling and management of their fleet of luxury limousines. The system used AI to support decision-making and problem-solving so that their planners/controllers can be more productive in sustaining business growth while providing quality service.
The Fleet Management System (FMS) was created for the Airport Limousine Services Ltd. (ALS), a subsidiary of Swire Travel. Established in 1948, Swire Travel one of the largest travel management companies in Hong Kong and widely recognized as the leader in service quality in the local travel industry. It was the first agent to be appointed to the Hong Kong Travel Industry Council (TIC) and has been registered as an IATA-approved travel agent for over 50 years (TIC 2010). Swire Travel is part of the worldwide Swire group, which has over 145 years of history.
ALS is a young and fast-growing company with aggressive expansion plans. However, one of the major bottlenecks in expansion capability is the availability of skilled planners and controllers. Besides long and extensive training, the job can be hectic and stressful at times. Planners/ controllers need to take in information from many different channels, constantly communicate with limousine chauffeurs to record statuses and dispatch orders, and continuously perform scheduling/re-scheduling decisions while trying to balance various business/operational criteria to maximize profit and productivity while maintaining service quality. A fair amount of problem solving is needed as traffic can be congested and leading to delays, clients might be late, flights might be delayed, etc. ALS found it hard to train fast enough an adequate number of high quality planners/ controllers who are up to these challenges, to meet ALS's aggressive growth plans. Hence they approach the University to create a system that took advantage of AI.
The AI scheduling algorithm considers constraints and rules, such as travel time, flight time, vehicle location, etc. to suggest the best vehicle to service each order. The system automatically extracts flight times and terminal building information to support scheduling. Estimated and actual times are logged and problems highlighted. This allows human planners/operators to focus on critical decision-making.
Deployed since 1 Jan 2009, this system enabled ALS to dramatically increase business volume with their existing planners/operator and also improving vehicle utilization at the same time.