Written by 10:58 pm Digital Transformation, Editor's pick, Feature

How AI Is Being Used To Speed Up The Delivery Of Off-Site Services To Clients?

In this article for Field Service News, Ryan Condon, Head of Content at Comparesoft, discusses how Artificial Intelligence is changing field service management.

Artificial Intelligence (AI) was something we imagined would transform our lives in the future. But, since it’s now a part of our everyday lives, field service managers and technicians should get up to speed on how AI is changing Field Service Management (FSM) for the better.

When most customers say that speed of service is the main motivator for customer service—as many as 80% of Americans according to PWC—it’s good to know that AI has the ability to speed up the delivery of off-site services.

So, what is AI?

In essence, AI is when machines simulate or mimic human intelligence. It’s a broad, catch-all term that includes subsets such as machine learning and deep learning. All of which aim to enhance and add to human interaction with positive effect.

What Does AI Look Like for FSM?

The traditional model for the field service industry was to once assess, diagnose, and then resolve failed equipment or machinery. But since the advent of AI devices, and the distancing measures taken to address the impact of the pandemic, AI has given way to a transformation of these standard practices.

Today, by predicting when problems may arise before they occur, or estimating when machinery will need repair, AI technology is speeding up field service delivery and, with it, customer satisfaction.

AI devices include a broad range of software and hardware. Much of AI falls into the category of Internet of Things (IoT) or, in other words, devices that are disrupting field service management in very positive ways.

For instance, utilities company Thames Water is using sensors and real-time analytics to forecast asset failures. This is helping them move faster in situations that demand it, such as unexpected storms or water leakages.

Plus, there’s US firm Aquant’s AI-driven Remote Triage. Thanks to decision-making AI, this system is supporting an increase in first-time fix rates. By offering its users a range of possible solutions to problems, it asks questions about the symptoms of each piece of faulty equipment and helps technicians get a head-start before they’ve reached the site.

By reducing the length of response time to urgent matters, AI is improving all aspects of delivery – from communication to scheduling and customer service. And, according to 80% of industry experts, these efficiencies are boosting employees’ morale and their skill sets.

How AI is Used by Field Service Companies

The use of AI in field service management has grown in recent years. Here are some of the ways it’s supporting improvements in the field and making delivery faster:

Job Scheduling and Dispatching

By using intelligent technology to analyze various data sets, AI programs use specific algorithms to determine whether future jobs are likely to be successful or not. This is helping service technicians to achieve higher first-time fix rates than before.

Where it used to be incumbent on dispatchers to ask customers the right questions before technicians arrived on-site, this predictive technology is freeing up dispatchers’ time for more visits while reducing repeat visits.

Automated scheduling, via AI programs, is also changing the way schedulers handle their workload. By giving them the time back to focus on more difficult cases, real-time AI scheduling is managing those easy, quick win scheduling jobs while letting staff focus their time on what matters. Equally, AI technology is overcoming problems with repeat or inappropriate bookings by prioritising jobs according to data held on technicians’ skillsets, locations, and availability.

Predictive Maintenance and Management

AI Management Software is helping field service companies take a proactive approach to addressing field service needs. By using a wide range of data, AI enables more accurate forecasting. This is preventing potential failures, errors, and interruptions to field service. It’s also driving productivity through a reduction in errors.

AI technology is able to optimize route management in real-time, which is particularly helpful during emergencies. So, if there is heavy traffic, for example, a technician can decide whether they’d be able to get to a site or otherwise find an alternative or nearby technician who could help address the issue in time.

By addressing unplanned or unforeseen circumstances before they happen, field service companies are better able to address problems and reduce negative cost implications from any disruptions or interruptions to service.

Computer Vision AI

Computer Vision is where AI algorithms process, analyze, and make sense of visual data such as images or videos. They do this in the same way as humans, basing their complex assessments on pattern recognition.

So, when it comes to technician’s seeking additional expertise on specific areas of a job—where they may not know themselves—Computer Vision AI can interpret the technician’s problems and provide solutions based on the images it sees. So, how does this work in practice?

  • Stage 1: Technicians use their smartphones to take pictures, having followed instructions on the app
  • Stage 2: Neural AI networks process the image by detecting specific aspects and acknowledging the issue
  • Stage 3: The system sends back information to technicians relating to the issue
  • Stage 4: Technicians resolve the issue and send back the new images
  • Stage 5: Once the photo is clear of all issues, AI confirms the job is complete
Guidance Through a Knowledge Base

Having an up-to-date knowledge base is a great way to provide field technicians with the additional tools and information they need to ‘self-help’ when problem-solving issues.

But there will be times when they either can’t find the information they need or don’t know where to look for it. This is where AI comes in – to aid field service technicians with finding the solutions they’re looking for.

Using technology such as Natural Language Processing, AI enables a computer to understand the full meaning and intention of any written or spoken language. By summarising bigger amounts of text, AI is helping technicians get the information much faster than they would have.

Areas Of Field Service Management That AI Can Improve

While AI has been embraced by the industry in recent years, there are many ways it can help management teams to make significant and lasting improvements to service delivery.

Customer Experience

Keeping customers and clients happy is the essence of field service management. So, it’s good news that AI can help. With fewer opportunities for in-person interactions due to the Covid-19 pandemic, companies can keep customer communication more consistent with AI-driven communication channels.

24/7 helpdesks are possible with the help of AI-supported chatbots. Because, when customers need support, chatbots can be there at any time of the day. They can assist with general queries, or even with helping the customer navigate the knowledge base.

Self-service portals are also an excellent way to keep the customer in control. Self-service allows customers to register problems, upload photos of the issue or schedule maintenance jobs themselves. This will not only speed up maintenance but will keep customers satisfied.

Job Prioritisation and Optimisation

The beauty of AI and machine learning technologies is that they can handle the jobs that we don’t want to do. For example, by prioritising based on a range of factors such as location, type of machinery, skill levels, customer needs, and any KPI’s, customers are more likely to get the service they expect. This also makes sure technicians and dispatchers’ optimise their time.

Intelligent AI systems can also scan service requests and generate priority lists for customer tickets. By analysing data and gleaning insights on historical activity, intelligent AI is efficient in handling the management of scheduling and dispatch of technicians.

Accuracy and Efficiency

Most field service teams are doing everything they can to reduce the potential for human error and improve accuracy. But, in reality, staff teams have much to handle and need all the help they can get.

Using a predictive and proactive approach to maintenance, AI has the ability to make radical changes to levels of service efficiency. Through the infrastructure of IoT devices that track and monitor progress with precision, AI makes the work of field service technicians much easier by notifying them of necessary repairs and well in advance of when problems are likely to occur.

Also, with intelligent scheduling, AI enables technicians to arrive at a job based on the priorities of the business. Or, whichever factors are most important. With any changes to scheduling managed in real-time, AI-powered intelligent dispatching and inventory management ensures technicians have the right information and tools to have a better chance of meeting their first-time fix rates.


Further Reading:

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