Artificial Intelligence Will Change The Field Service Industry

The growing focus on artificial intelligence (AI) in various fields is difficult to miss.From the now oft-quoted buzz term big data to chat bots, new methods of applying AI are frequently being uncovered. A recent Forrester report indicates that 6 percent of American jobs could be replaced by AI in 2021. On the other hand, technological advances in field services have been happening at a snail’s pace. One might, therefore, wonder how AI can potentially impact such a change resistant sector.

Changes Artificial Intelligence Will Herald in the Field Service Industry

There are a variety of ways that AI will affect field services. Here is a look at some of them:

Using Service Management Software to Assist Technicians

Technicians help businesses solve various problems that occur on a daily level. To deliver quality services a firm needs to have a standardized method of approach that technicians use when responding to calls. Every step in the process needs to be constant scrutiny, and its rate of efficiency graded using service management software.
To improve the quality and speed of services, there needs to be a continuous focus on uncovering better methods of solving the same problem in less time. All this calls for a dedicated function that pays attention to new trends, to adopt them and improve operations.

AI, therefore, becomes a useful tool for analyzing large amounts of data efficiently generated by the software to generate insights. New patterns that emerge are quickly picked out and several scenarios played out on how adopting these new patterns can impact current services offered by technicians. The time it would take to learn these lessons through trial and error is saved and contributes to an overall improvement of services and operations.

Using AI to Improve Maintenance Services

Equipment employed in every day operational processes break down. Technicians regular schedule maintenance checks to ensure that everything is working as expected. The problem is that this takes up a lot of their time since they have to perform site visits to facilitate the maintenance.

As more devices become connected to the internet of things (IoT), data can be used to remotely check on their operational conditionAI can analyze the daily data generated by this machinery as part of field service management to predict future maintenance issues that might occur.

A technician would be able to remotely keep an eye on the equipment without having to make as many site visits as before. The time saved can be put to better use and the added side effect of data on machinery use can help optimize operations. Site visits can also become more efficient and take less time through the use of mobile devices connected to the cloud.

A technician on site will be able to immediately gain all the historical data AI has analyzed on a piece of equipment and attend to its maintenance faster. Such an approach will only revolutionize field service management.

Using AI to Improve Job Scheduling

One aspect of field service management today that becomes problematic at times is the matching of skill versus the task. Once in a while, a technician who isn’t as skilled to solve a specific problem is dispatched causing further frustration to the client. At times, unexpected weather changes or traffic issues cause a scheduling problem that leads to pairing up technicians with problems they may not be best suited to solve.

AI can monitor weather patterns and generate insights based on historical data. This can then be used to predict weather conditions which help in efficiently scheduling field visits for technicians. AI can monitor traffic patterns and learn to predict the flows so that technicians can most effectively plan their field trips to save on time.

Using AI to Improve Customer Service

The field service industry faces many client complaints concerning the varied quality of customer care. AI can help solve this problem by monitoring customer satisfaction trends more effectively. The large volumes of data generated by clients as feedback on services rendered can be analyzed to identify patterns that point to weaknesses in service delivery. Technicians can then act on these recommendations to better serve the customers.

Conclusion

The breakneck development of AI is inevitable and so is its impact on various industries. Field services will not be immune to the onslaught, and it will experience several ways in which dynamic application of AI will alter how operations are carried out.

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