Your IoT, Automation & Predictive Analytics Questions Answered
The Internet of Things, service automation and predictive analytics all promise to reshape the field service management landscape. But each of these terms and technologies likewise cause confusion, and even frustration among many management-minded service professionals. At conferences, on software demos, and during customer calls, we’re constantly getting asked about emerging technology.
“What the heck is automation software?”
“What are these ‘things’ in the Internet of Things”
“Can you really predict service behavior? Seems bogus.”
You’re not alone, and we totally get it. New technology can be frustrating, and at times even seem unnecessary.
We believe when new technology becomes more readily available, it’s essential to map it back to specific business outcomes. Technology for its own sake won’t help anyone in field service.
In the hopes of demystifying some frustrating technology topics, below are dirt-simple definitions of IoT, automation, and predictive analytics. In addition, we lay out why each matter in field service, and ideas for how each can be applied.
1. The Internet of Things
What is it?
Simply put, the Internet of Things (IoT) includes any device, product, vehicle, or electronic product capable of connecting to the internet and sending signals to each other. This could include everything from washing machines, headphones, coffee makers, and smartphones to clothing, space stations, jewelry, and jet engines.
If it can transmit data over a wireless network, it can be part of the IoT.
Why does it matter in field service?
The Internet of Things opens up hundreds of cross-device possibilities and efficiencies in service. By bringing machines, devices, vehicles, and equipment online, service providers can effectively close huge communication gaps that currently exist, and resolve customer issues faster.
Imagine a heating, ventilation, and air conditioning (HVAC) unit that alerts the field service team the instant an outage happens. Or imagine capital equipment parts that can communicate their efficiency in real-time. The possibilities for streamlining service are simply endless.
Ideas for implementing IoT in field service:
Embed sensors on equipment
The first and most obvious application is to bring equipment that needs regular maintenance online. Consider embedding temperature, pressure, or other sensors on key pieces of equipment that can communicate this information back to a database, field tech, or to dispatch.
Instead of customers discovering major issues and equipment issues, these sensors can deliver real-time updates that keep you ahead of failures.
Bring vehicles online
Efficiency in service requires techs to remain efficient both on the road, and at the job site. By equipping your service vehicles with sensors, you can quickly learn whether tech drive time remains efficient. Over time, you can optimize specific routes, as well as coach the broader organization on how to improve travel efficiency.
Empower your techs with wearables such as smartwatches that allow them to transmit service data via voice recognition back to headquarters. In essence, bringing your techs online while at job sites empowers real-time data transfer, and greater service efficiency.
2. Field Service Automation
What is it?
Field service management, and field service automation are often used interchangeably. They are in fact, quite different.
Service automation technology takes human, or manual service tasks and automates them through software applications. It’s highly common for service organizations to start by automating the most cumbersome, or undesirable tasks. The purpose of field service automation is streamlining service processes to increase productivity and efficiency.
Why does automation matter in service?
Customer expectations are higher than ever. For decades, service organizations have struggled to keep up with both changing technology, and ever-increasing customer expectations. Service automation is essential in today’s landscape in freeing up techs to focus on the human side of service. Customer relationships have also suffered due to technology. Applying automation to tasks that are better suited to robots frees up field techs and dispatch to focus on satisfying customers, answering tough questions, and servicing equipment.
Ideas for implementing automation in field service:
Various aspects of service scheduling and staffing can be completely automated. When service and dispatch professionals put in requests for desired work hours, software can bump these recommendations up against customer needs, finding opportunities for greater efficiency.
In addition, alerts and real-time updates can keep leadership abreast of scheduling improvements.
Streamline work order management
Human error is unavoidable when it comes to pricing, invoicing, and closing out costly jobs. Consider streamlining work order management through automation software. Various tools can provide work estimates to customers, forecast based on previous numbers, and send automated payment or invoicing reminders to all parties involved.
Field service personnel managers know how challenging dispatch can be. Keeping track of techs, and job completions are key to a dispatch manager’s daily grind. Dispatch automation and route optimization software can simplify dispatch by delivering real-time route information, tech activity while on-site, and notices when jobs are completed.
3. Predictive Analytics
What is it?
Inventory, service scheduling, and even customer satisfaction can all be predicted. That is of course, if you have access to the right data.
Predictive analytics leverages statistical algorithms, or machine learning techniques to identify the likelihood of future outcomes. In short, it’s all about predicting customer behavior, equipment failures, and field tech performance.
It requires the tracking of historical data, in order to model and project what will happen in the future.
Why does being predictive matter in field service?
Customer’s desires are changing faster than ever. New consumer services like Uber, Airbnb, and Amazon have completely redefined customer expectations. Instant answers, mobile-first frameworks, and complete transparency are now the norm.
Unfortunately, field service has been slow to catch up. Predictive analytics offer field service management professionals an opportunity to get ahead of customer, and service needs through smarter use of data. This promises a path to satisfying more customers, and faster.
Ideas for implementing predictive analytics in field service:
Embrace big data
Every mobile device, customer touchpoint, and piece of equipment can now deliver data. Embrace all of these newfound touch points, and find a means of tracking them in a single software. Understanding patterns of behavior across multiple touch points is how you’ll unlock deep customer insights
Track select metrics
Having newfound data at your fingertips can be overwhelming. Hone in on the metrics that matter most, and seek to uncover patterns within the data.
Project future performance with machine learning models
Machine learning leverages pattern recognition and artificial intelligence algorithms to predict future trends based on historical data. Preconfigured machine learning models can help you get from data to insights faster.
As an alternative, consider mapping your own data over a set period of time, creating a basic statistical analysis. Then, forecast across customer satisfaction, tech performance, and more.
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