3 Ways IoT is Transforming Field Service
Together, the Internet of Things (IoT) and big data are reshaping the way we shop, interact with devices, and work. Can’t find your keys? Not a problem anymore. Out of paper towels? Just holler at Alexa, and they show up at your doorstep.
For those in field service willing to embrace new technology, IoT likewise stands to transform the role of field techs, improve the efficiency of service, and bolster tech safety.
But what exactly does “Internet of Things” mean? We’ll start with a definition, and then dive deeper into how IoT is impacting field service both today, and tomorrow.
Internet of Things Definition:
Wikipedia defines IoT as the internetworking of physical devices, vehicles, buildings, and other objects containing electronics, sensors, software, or actuators that allow them to exchange data over wireless networks. The most notable and popular smart devices include the Apple Watch, Nest Smart Thermostat, and Amazon’s Echo.
Here are three ways IoT and smart devices are transforming field service:
#1: Increasing Resolution Efficiency
Resolving jobs efficiently and quickly is key to achieving field service profitability. But often times dispatch, or even field techs, are unable to obtain necessary details for achieving swift resolution prior to arrival. The result? They return to job sites more than once.
The Internet of Things is completely eliminating the need for return visits, and thereby improving resolution efficiency drastically. How?
By embedding smart devices in the field, logging performance at scale, and crunching this data to uncover analytics insights, savvy field service management organizations are embarking on a new era of smarter field service. Field-based equipment can now send service signals immediately, and log performance data in real-time. This means the need for service calls will soon disappear completely. In its place, machines will inform techs of issues directly, while the customer might not even know there’s a problem.
General Electric (GE) is currently using IoT at scale to significantly improve efficiency across manufacturing, transportation, healthcare and more. Their innovations include:
- Embedding data-collecting sensors on industrial equipment (like airplane engines)
- Leveraging insights across sensors to make efficient decisions
- Using data and data-collecting sensors to improve operational and industrial efficiency
GE has also teamed up with Microsoft in an effort to improve cloud data capabilities, thereby unlocking greater industrial and equipment efficiencies. A recent GE study forecasts this “Industrial Internet” will add $10 to $15 trillion to global gross domestic product (GDP) in the next 20 years.
Is your field service management team ready for the Industrial Internet?
#2: Increasing Opportunities for Predictive Maintenance
Obviously, diagnosing and addressing issues before they happen is key to saving time and money on service calls. And as more customer equipment gets embedded with sensors, the opportunities for predictive maintenance will likewise increase.
But there’s an important distinction to be made between preventative, and predictive maintenance. Preventative maintenance means performing service tasks at regular intervals to ensure no major breakdowns occur.
On the other hand, predictive maintenance means using data-driven insights to better understand equipment, and predict exactly when specific parts might fail, or the equipment should be replaced. When using IoT sensors and data-driven insights, predictive maintenance can completely revolutionize a field force by delivering more accurate parts performance reports, equipment lifecycles, and more.
As an agency of the state of Arizona, the Salt River Project utilizes predictive maintenance as a part of their monitoring and diagnostics process. This ensures the residents of Phoenix receive power and water in the most efficient manner possible, and industrial efficiency remains high. Here’s how it works:
- SRP predictive analytics software analyzes historical and real-time data
- Machine learning algorithms create performance models based on this historical data
- The software then takes readings every 10 minutes to ensure performance matches models
Since piloting the program in 2012, SRP has resolved more than 800 issues, all of which they define as predictive “catches” (problems the plant was not previously aware of). These resolutions minimize downtime, power outages, and improve customer satisfaction.
#3: Getting Techs Focused on Customer Satisfaction
The final and most important aspect IoT can provide is helping technicians focus on improving customer satisfaction through newfound data. While many currently use net promoter scores (NPS) and customer satisfaction scores (CSAT) as benchmarks, these old-world key performance indicators (KPIs) contain one major flaw: They are fueled by surveys. Unfortunately, fewer customers answer surveys every year.
With customer opt-in, new data streams can deliver deep insights with zero customer surveys. By opening up a data stream between customer devices and an IoT Complex Event Processor, field service organizations can analyze connected products, mobile devices, website clicks, social media posts and mobile text messages. Using artificial intelligence algorithms, software can crunch data from different sources to determine customer satisfaction based on multiple digital behaviors. By delivering this knowledge to techs prior to service, they can come prepared to satisfy customers based on specific data.
Sound like science fiction? It’s truly not far off.