Many field service providers (FSPs) are feeling the result of the demanding and ever-changing customer requirements on field service, insufficient manual service dispatch, and unpredictable traffic situations. They are willing to leverage AI technologies to better meet customer expectations with higher service dispatch efficiency and lower costs.
According to Gartner’s 2020 Magic Quadrant for Field Service Management, “Algorithms and bots will schedule over two-thirds of field service work for FSPs dependent on automated schedule optimization by 2025.” Alibaba Cloud’s AI Service Dispatch solution can help FSPs fulfill customer’s service scheduling and re-scheduling requirements in real-time through the latest Reinforcement Learning AI technology to improve field service dispatch capabilities and efficiency.
Industry-Leading Real-Time AI Dispatch
This solution leverages advanced Reinforcement Learning AI technology to implement real-time AI-informed decision support on service dispatch, enhancing field service efficiency compared to traditional AI solutions in batch mode.
Our service dispatch algorithms are trained from the logistics industry best practices from Cainiao, founded by an Alibaba-led consortium. The algorithms have proved to bring at least a 15% efficiency improvement on deliveries with 99.99% accuracy of arrival.
Robust Cloud Platform
Alibaba Cloud’s robust cloud-native platform provides reliability, scalability, security, high performance, operational excellence, and cost optimization on your service dispatch system. Alibaba Cloud’s powerful machine learning platform powered by Machine Learning Platform for AI can continuously improve algorithm quality.
This solution enables you to develop machine learning models with zero coding, allowing you to turn your domain experts into data scientists with little effort. With the highly scalable modular architectures, you can quickly replicate the same service dispatch system to other regions on a weekly basis.
How Reinforcement Learning AI Works
Many field service providers (FSPs) are facing challenges when leveraging traditional AI solutions. It is difficult to model business rules as they are complicated and everchanging. Planning routes on a map for thousands of tasks is a complex task, especially for the real-time traffic situation and precision of location. Customers would like to stay in touch. Balancing customer requirements and the overall field service efficiency is another challenge. This solution uses AI technology based on Reinforcement Learning (RL) to tackle these problems. The AI algorithms are trained during tasks to achieve the best result within the predefined business restrictions; the more it runs, the smarter it becomes. This solution provides a business rule plugin system to model business operations, so different business environments can be customized in the solution. When the existing business rules change or new rules are added, the algorithm will adapt quickly to remain smart and responsive. In addition, our AI service dispatch algorithms leverage the existing FSM tools from FSPs. Only technician lists, tasks, and locations are required for AI to analyze priorities, plan routes, and assign tasks. New business rules can be implemented by adding attributes to the AI to ensure the agility of your business. Alibaba Cloud can help you integrate popular map engines to the platform to help AI make better routing choices based on real-time traffic situations. Your end customers will have a clear view of how much closer the technicians are to the field after ordering the field service, improving user experience significantly.
Six Steps to Implement AI Service Dispatch
- Data Modeling
- Organize your data to build a data model according to your business.
- Architecture Design
- Design a modular architecture for agile deployment.
- Scalability Implementation
- Implement scalability to quickly adapt to load changes and reuse business rules on new scenarios. Replicate the same service dispatch system to other regions on a weekly basis.
- DevOps Support
- Use CI/CD tools for DevOps with end-to-end collaboration services and easy-to-configure scripts.
- Project Delivery
- Deliver projects with agility to meet frequent requirement changes.
- Continuous Support
- Quantify the effect of the AI service dispatch algorithm in real-time to check its efficiency.
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