Many field service providers (FSPs) experience demanding and ever-changing customer requirements, inefficiencies arising from inadequate manual service dispatch processes and unpredictable traffic situations. With AI-enabled technologies improving service dispatch efficiency, they can better meet customer expectations.
Alibaba Cloud’s EasyDispatch solution – named in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms – uses the latest reinforcement learning AI technology to improve field service dispatch capabilities and efficiency, helping FSPs fulfil customers’ service scheduling and rescheduling requirements in real time.
Industry-Leading Real-Time AI Dispatch
This solution uses advanced Reinforcement Learning AI technology to implement real-time, AI-informed decision support for service dispatch, enhancing field service efficiency when compared to traditional AI solutions.
Our service dispatch algorithms are trained on logistics industry best-practices developed by Cainiao, a pioneering logistics business launched by an Alibaba Group-led consortium.
Robust Cloud Platform
Alibaba Cloud’s robust cloud-native platform provides the reliability, scalability, security, high performance, operational excellence, and cost optimization your service dispatch system needs. Alibaba Cloud’s machine learning platform, powered by Machine Learning Platform for AI, continuously improves algorithm quality.
By allowing your teams to develop machine learning models with zero coding, this solution allows you to turn your domain experts into data scientists with little effort. With highly scalable, modular architectures, you can quickly replicate a service dispatch system to other regions on a weekly basis.
How It Works
Traditional AI solutions have only limited capability to model complicated and everchanging business rules. . Planning routes on a map for thousands of tasks is also a complex activity, particularly when real-time traffic situations and precise location requirements are involved. Balancing customer requirements and overall field service efficiency can also prove challenging.
This solution uses AI technology incorporating reinforcement learning to tackle these problems, with algorithms trained and improved during tasks to achieve optimal results within predefined business restrictions, and to evolve with changing business circumstances.
· Real Time Dispatching is based on three types of dispatching algorithms: heuristic, optimization, reinforcement learning.
· Flexible Business Rule Pluginsmaximize compatibility with your business requirements.
· Commonly-used FSM tools from FSPs are included in EasyDispatch algorithms.
· Explainable AI enables ‘what-if’ analysis through drag-and-drop. You can implement new business rules to ensure agility by adding attributes to the AI.
· A full set of REST API and API documents, and popular map engine.
Scheduling tasks manually is inefficient and does not enable rapid response to changing business circumstances, compromising the end-customer experience. Resource waste causes additional costs.
Hundreds of dedicated planners schedule and allocate tasks based on requests, expertise and schedules of technicians, existing assignments, and business rules incorporated into system parameters. Rules-based management and monitoring is executed throughout business processes to reduce risks and boost efficiency.
· Improves task dispatch efficiency by up to 90% and reduces on-site travel time
· Enhances on-site service quality
· Reduces manpower and material costs
Security and Compliance
SOC2 Type II Report