AI Service Dispatch for Field Service Management

Apply the latest Reinforcement Learning AI technology to your Field Service Management (FSM) to obtain real-time AI-informed decision support, improve dispatcher efficiency, and enhance the customer experience.

Overview

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.

Service Highlights

  • 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.

  • Logistics Expertise

    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.

  • Quick Implementation

    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.

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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.

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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.

Step 1: Data Modeling

The solution combs through the customers’ business data according to their business processes and helps the customers build a data model based on basic worker information, basic customer information, order information, event information, and other auxiliary information. The solution also supports cross-cloud deployment and data flow on different cloud systems. For example, customers can send production data from their Field Service Management (FSM) system to Alibaba Cloud for service scheduling and service dispatch and then send the results back to the FSM system.

Step 2: Architecture Design

For the core of an AI service dispatch system, we created a modular design that decouples the data algorithms from the engineering processing modules. The overall architecture leverages the architecture design of serverless and microservice and includes the access layer, functional layer, data layer, algorithm layer, and operation and maintenance layer of the service. In this architecture, modules can communicate and are discovered through services, and are upgraded and scaled independently. This architecture allows constant iteration of the algorithm with as few engineering changes as possible, which is great support for an agile project management approach.

Step 3: Scalability Implementation

For companies with branches across many regions, every branch has a different business model. The service dispatch algorithms are required to solve an NP (non-deterministic polynomial) problem, where more rules lead to a more complex situation, causing an exponential growth of the arrangement. Businesses need to get service dispatch results in a very short period, so the requirement for linear scaling of the algorithm is extremely high. Alibaba Cloud’s scalable cloud-managed products, such as OSS, Function Compute, ACK for Kubernetes, and EMR, are used to receive and distribute service dispatch tasks and implement big data computing. The scalability of these products enables the AI service dispatch system to automatically adapt to the load changes coming from the customers’ existing systems. Alibaba Cloud can help you standardize different business rules and put them into different algorithm packages, which can be distributed and executed instantly through task configuration, thus achieving the scalability of different business scheduling rules. In addition, the modular architecture design allows you to quickly replicate the same service dispatch system to other regions on a weekly basis.

Step 4: DevOps Support

This solution offers a CI/CD tool called Yunxiao to implement DevOps. Empowered by Alibaba Cloud’s DevOps capabilities, Yunxiao provides end-to-end collaboration services and R&D tools that cover all stages of the product life cycle, from requirements and development to testing, release, and operation and maintenance. You can directly edit scripts to configure environment variables and pipelines. Once the pipeline is edited, you can release and rollback on the pipeline. Algorithm images compiled on Yunxiao are stored on the ACR. Yunxiao will notify you to go to the ACR to get the latest image to complete a series of subsequent deployment updates.

Step 5: Project Delivery

Alibaba Cloud products have a comprehensive testing system. Alibaba Cloud can complete comprehensive functional regression testing on data, algorithms, and engineering. Alibaba Cloud can design test scenarios, complete systematic testing, and provide test reports according to different business rules and forms, especially for algorithm regression testing. In addition, the Alibaba Cloud Delivery Team’s expertise in project management can efficiently support international customers' agile delivery methods to respond to frequent requirement changes.

Step 6: Continuous Support

This solution provides an inspector with scripts to quantify the effect of the AI service dispatch algorithm in real-time, allowing you to quickly check whether the algorithm improves the overall efficiency and AI service dispatch results meet business expectations. This inspector can also facilitate regression testing during algorithm iterations for future algorithm optimization.

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