In part 1 of this series, we covered 2 of the 5 ways artificial intelligence (AI) is making field service management (FSM) better, particularly through optimized route planning and customer support delivered by chatbots. Now we’ll round out the next 3 ways:
3: Connected equipment and predictive maintenance
AI is already playing a leading role in the Internet of Things (IoT). This is a big deal for FSM companies because AI will be used for predictive maintenance on connected equipment. And we already know that IoT with AI can work well in the real world. In fact, it won’t be long before service companies will use IoT sensors to monitor customer premises equipment using AI tools, including chatbots, routing optimization solutions, and mobile apps for field technicians.
The end of time-consuming maintenance plans
You know how it goes. Companies set up maintenance plans based on the estimated equipment life cycle. The sequence often goes like this: technicians visit the customer site at regular intervals to check on the status of the equipment. When a problem is identified, a second visit is scheduled to make the repair. Then the technician goes to the depot to get the spare parts needed for the maintenance/repair work order.
All in all this is a time-consuming process for the maintenance company. It’s also frustrating for the customer who may end up waiting days for a resolution, depending on the availability of spare parts. Making matters worse, customers in a manufacturing context can suffer significant losses from an equipment-related work stoppage. Not surprisingly, customers of all types are often dissatisfied with the maintenance company.
IoT and data sensors
With connected equipment and IoT, times are changing. Equipment can be fitted with multiple sensors that transmit data, such as status indicators, in real time. And, when these sensors are connected to work order management software, a predictive maintenance process can be established.
The maintenance service provider can monitor the equipment in real time, and, using algorithms anticipate breakdowns. This triggers a work order just before a failure occurs. The benefits of “just in time” maintenance are that the equipment service life is optimized and the maintenance provider productivity is increased.
Prediction and automation
Fault control and prediction can be fully automated using AI. When connected to sensors, algorithms analyze data flows so humans don’t have to. This approach is more accurate and allows for much faster decision-making.
As a result, maintenance technicians are only called in when the analysis predicts that a problem is imminent. If so, the technician is provided with a work order, including a description of the problem, the skills required, and the parts needed to perform the repair. By using AI, technician and equipment up time is optimized so everyone wins.
4: Smart mobile apps for field technicians
AI is also a valuable tool for field technicians working at a customer site. An AI-enabled mobile app can be a virtual assistant. For example, when the technician arrives at the job site, the mobile app can send detailed and context-sensitive information, including the number and types of equipment on site, models and serial numbers, operating status, maintenance history, as well as step-by-step repair instructions.
Furthermore, an intelligent mobile app allows technicians to connect directly to the equipment sensors so they can more quickly and efficiently resolve problems.
5: Improved customer experience
Service expectations are rising, particularly in more competitive service sectors. By design, AI technologies allow service companies to better respond to customer expectations.
Productivity and efficiency
Gone are the days when work orders were managed using Excel. The focus has shifted to automation. AI technology increases responsiveness, productivity, and diagnostic accuracy for each and every customer.
Connected devices and IoT, chatbots, intelligent planning, and powerful mobile apps all come together to create a positive customer experience. Here’s how it works:
A sensor registers a failure is about to occur and the data is transmitted to the maintenance provider, using the work order management software.
The software assembles the work order instructions/information then assigns the job to a qualified technician.
The technician receives the work order using the mobile app and proceeds to do the work.
The mobile app transmits the repair instructions and spare parts needed, as well as availability status at the depot.
At the same time, the mobile app notifies the depot of the work order and allocates the spare parts to the job.
Route and travel time to the site is also managed by the mobile app so the technician can arrive on schedule.
As a result, the technician arrives just before a failure occurs with the right parts and all the information needed for the job. And, the mobile app virtual assistant helps guide the repair ― step by step.
Optimized customer relationship
At each stage of the process, from initiation through to resolution, the software keeps the customer informed of progress on the work order. And an informed customer is a more satisfied customer.
As we have seen, digital transformation, IoT, and advances in AI technologies are changing the way FSM companies do business by reducing planning uncertainty and streamlining maintenance processes. That’s important because AI-enabled features, such as real-time information sharing, predictive maintenance, more rapid response, work order traceability, and increased productivity can have a significant impact on profitability.
So what are you waiting for? Find out more about field-proven, AI-enabled turnkey software solutions.