As new technologies like artificial intelligence (AI) transform organisations across industries, the potential business benefits are a powerful argument to help a business go through the transition. An example of this would be within the ever-evolving nature of the field service industry; companies can now schedule a technician to come and check a network fault or conduct a service call for their customers almost immediately, thanks to AI.
This is worlds away from ten years ago when the only option would have been to call and talk to a dispatcher as they flicked through employee logs and schedules manually to find an available, and properly skilled, technician. And often, the right technician required to resolve the issue was generally not available for a week, or longer.
For any business, seven days without a resolution is a definite failure. But, the field service industry has come a long way over the past ten years. Thanks to the rapid expansion and advancement of field service management (FSM) technology, this industry is seeing business issues being resolved faster and with minimal disruption to services. Today, service companies are using AI for various tasks, including… to scan every single employee log they have, to identify the right technician for the job who is closest to the customer to offer an almost immediate appointment. Though not an easy task, this level of detail is critical to meet arduous customer expectations.
While it takes various layers of technology to complete a full suite of FSM tools, AI plays a significant role; in many ways FSM could be considered as the poster child for AI. It is an important element that’s being used to assist companies in meeting their experience standards and business continuity objectives.
On an average day, a field service company may have 5,000 problems to resolve – whether those are routine maintenance checks or emergency call outs – but with only 500 technicians in the field to handle them, all of whom are likely to be spread across a vast geographic area. Finding the best technician for the job, and the one closest to the right location, requires service management companies to optimise their resources quickly and efficiently, to address the highest volume of problems while minimising costs and keeping customers happy. This is just one of the multi-dimensional problem-solving elements that AI is helping with.
As we can see, AI technology is already making an impact on the field service industry, but there is still so much more potential to explore. Let’s take a look at how AI is transforming field service today, and what we can expect in the not-so-distant future.
Automatic schedule optimisation for customer retention
We’re still at the very beginning of AI-driven schedule optimisation, with room to improve and reduce the often frustrating and sometimes too lengthy scheduling process. The need for automation is essential for reducing wait times and offering customers a quicker and better experience – FSM is a key component to this, alongside AI automation. For example, one of ClickSoftware’s customers, Belron UK Ltd, saw a 65per cent increase in scheduling of same-day repairs after implementing FSM, after reducing technician travel time by 20per cent. This increased the number of field technician jobs completed per week by 10per cent.
Service leaders have access to lots of quantitative data such as the average amount of time it takes to complete a certain task and how different factors impact that time, such as the weather that day which could make travel slower or situational factors like whether a technician needs to get permission to access a property. As in the case of Cablex AG, the FSM solution provides field technicians with all work-order information relating to customer contracts, project plans, diagrams and sketches – through one application. This increases the daily service assignments completed by field technicians by 15per cent and generates real-time statuses to let customers know when to expect field technician visits. The integration with back-office business-process workflows also offers Cablex a 25per cent reduction in running costs and provides the ability to scale its capabilities easily as the company continues to grow.
Before the onset of the internet of things (IoT), your washing machine or dishwasher would break down without warning, and you would have no insight into what happened or how to fix it. Alternatively, a company’s HVAC might malfunction, disrupting business and impacting revenue. Today, connected equipment are constantly monitoring their own health and relaying information to a hub. This information helps identify problems quickly and arm technicians with the right tools and parts for the job.
Forward-thinking organisations are already outfitting machines with IoT sensors to identify issues and fix broken equipment – but the real money is in the emerging predictive maintenance model, that allows companies to get ahead of problems and tend to them before the inconvenient disruption.
While some service organisations are beginning to make use of sensors and intelligent machines, we have only scratched the surface. As more connected machines are deployed, organisations will be able to aggregate historical performance data on hundreds of thousands of units, enabling machines to learn and identify patterns in their own performance to predict and prevent problems. Ultimately, we can expect artificial intelligence to eventually bring equipment downtime to zero.
The next step after optimising scheduling and moving to preventative maintenance models is improving the effectiveness of the visiting technician and, again, AI plays its role here too. The ratio of work orders completed in one visit – a first-time fix rate – against the total work orders increases a service providers’ opportunities for additional revenue due to increased capacity. Customer satisfaction is also improved by increased productivity and a reduced average time taken for a given repair due to a shorter outage duration, which in turn increases revenue.
In a report it released in February of last year, “How to build a business case for field service management software investment”, Gartner indicates that the implementation of FSM provided savvy service providers with an average 25.1per cent improvement in technician productivity. Gartner cites potential contributing factors to this as going from manual to electronic forms, from technicians self-scheduling to a centralised process, and automating data collection where it had been done manually. Other average improvements cited by Gartner are a 12.7per cent drop in customer complaints and a 52.6per cent reduction in dispatch overhead – the latter was directly related to the majority of work being scheduled automatically and intuitively, and a faster close rate.
Personalisation from start to finish
Arguably the most important aspect that AI technology is bringing to the field service industry is its ability to deliver personalisation. In an era where every service is commoditised, customer experience is the critical differentiator. In addition to learning more about machine performance and technician abilities, AI technology can take in information about individual consumer preferences and behaviour. For instance, do you prefer to schedule appointments in the morning or afternoon? Is your home gated? How likely are you to cancel your appointment and with how much warning? How much advance notice do you prefer before a technician arrives? Is there a specific technician you’d like to request? Again, it’s all about data – as service companies learn more about their customers, they can better leverage AI software to provide a personalised service experience.
At the end of the day, those field service companies that prioritise AI technology in their business strategy will have an advantage over their competitors when it comes to the customer experience. Service is a commodity, and it’s no longer just about how nice or polite the technician is with the customer. Consumers today expect speed and accuracy from their service providers, and we need the help of technology to meet their higher than high expectations.
Paul Whitelam, senior VP of marketing, ClickSoftware
Image Credit: Razum / Shutterstock