By Uri Pintov and Gary Brandeleer, Salesforce
As businesses look for better ways to keep customers happy, they’re exploring a new approach to maintenance that’s driven by insights, instead of errors and missteps. The Internet of Things (IoT) is changing the way businesses maintain equipment, rewriting service agreements and resetting customer expectations in the process. Savvy customer service leaders are realizing they can use data to predict the future and they’re turning to a pioneering dream team combining field service and IoT to prevent unwanted things from happening.
Most companies today offer scheduled maintenance as part of an equipment service contract but that’s starting to evolve, thanks to IoT. Companies are using real-time data from connected devices to gain visibility into the current condition of equipment and using that information to deliver a different type of field service. Instead of performing regularly scheduled maintenance every three months, people are prioritizing work according to data from sensors that indicate an asset’s health and only taking action based on the probability of an outage or the necessity of an upgrade.
Being proactive and predictive decreases the overall cost to serve customers and allows businesses to provide a seamless service experience. Imagine a bus line that would notify maintenance before a fuel pump goes out and strands customers on the side of the road. In this example, using IoT to avoid customer dissatisfaction — not to mention accidents — could potentially deliver a huge ROI.
From Reactive and Preventative to Proactive and Predictive
Service contracts are becoming less about the frequency of maintenance and more about equipment uptime. Basically, the industry is moving to a system where businesses are fixing problems before the customer even notices something might be wrong. Maintenance contracts based on uptime can secure revenue streams for service providers while decreasing the overall cost to serve.
IoT enables businesses to shift from reactive break-fix services and recurring preventative maintenance plans to proactive monitoring of devices and predictive maintenance. Sensor data flowing into an IoT platform is analyzed and the resulting high-value signals are sent to a CRM platform where they can be contextualized and processed. It’s the lack of context in IoT data that’s the missing element for most service providers today. Context can connect IoT data to business rules in a CRM which then prompt predictive maintenance, driving value for both the service provider and the customer. Used in this way, IoT data will change the way field service is dispatched, and even the way customers think about service.
How Predictive Service Works
Predictive service relies on artificial intelligence (AI) in an IoT platform to monitor trends and predict which components are likely to fail and when. Sensors monitor things like the asset’s age, voltage fluctuations, usage data, temperature, humidity, and much, much more. AI is developing the ability to process massive amounts of information, and given the right data sets, machine learning algorithms can predict equipment failures with a very high level of accuracy. This kind of knowledge will mean maximum equipment uptime and far fewer maintenance visits, reducing costs and improving customer satisfaction at the same time.
Consider the following example: An alert is created when IoT data informs a manufacturer that something is wrong with a machine belonging to one of its customers. After automated diagnostics and log parsing, error codes point to a malfunction that might cause an outage soon. A technician is dispatched with the required parts to fix the issue and prevent the disruption. Error codes and required parts are shared with the technician, ensuring a first time fix rate. Cost savings are achieved because replacing parts before a major outage happens is often cheaper than the cost of repairs that would be necessary if the equipment had been allowed to fail.
IoT, Field Service, and New Revenue Models
Using IoT for preventative maintenance allows companies to start selling services on a subscription basis — much like SaaS — instead of selling products on an occasional basis with a service contract thrown in as an afterthought. In this new way of doing things, the customer pays for uptime of the equipment, without ever worrying about upgrades. The manufacturer’s job then becomes servicing and replacing the equipment with minimal to zero disruption.
The shift from preventive to predictive maintenance is part of a trend called servitization. In the past, manufacturers made things and maintenance companies serviced them. The last few decades have witnessed a big change in this approach. It’s now much more common for a manufacturer to offer a package deal of product and service rolled into one. Servitization is now reaching an advanced stage where IoT is enabling a much more refined type of service aided by artificial intelligence (AI) and big data — but many companies still have a ways to go before they catch up with this trend.
Making the Shift
When companies collect IoT data, it’s usually fed into an enterprise asset management (EAM) system or enterprise resource planning (ERP) software where the data stays until it’s analyzed. This process can often take weeks, if not longer. Doing it this way means that important information is not in the hands of the people who can use it to improve service. So how can a business start to embrace servitization and become more proactive and predictive?
Companies should flag anomalies picked up by sensors that may need action and send them to a CRM right away. When funneled into a CRM, this actionable data can be used to automate business processes that improve service. Surfacing actionable IoT data in a CRM enables a more proactive approach that empowers customer service supervisors, agents, and field technicians. With access to this data, field service can track the current state of equipment and be proactive in emergencies or predictive in responding to trends. By using actionable IoT data, manufacturers can start to develop steady revenue streams from maintenance contracts based on uptime, instead of charging for occasional repairs.
Alternatively, companies can use IoT data to see when something is about to wear out and can sell their own replacement parts before the unit breaks, and the customer starts looking for inferior alternatives offered by competitors. Imagine a hot tub manufacturer that struggles to find the right time to sell replacement filters to existing customers. Simply monitoring IoT data from filters means the business can offer the right solution with the right replacement component at the moment the customer needs it — a great way to increase sales while building trust and loyalty with customers.
The Internet of Things has the potential to take field service to a much higher level. Most companies won’t become proactive and predictive overnight but feeding signals from IoT data into a CRM platform allows customer service to begin evolving. The journey to a highly refined level of service based on actionable IoT insights also depends on empowering field service with better information that allows workers to see into the future — and change it.