The introduction of IoT into the service and repair process for commercial assets has not yet fundamentally changed the operations of companies responsible for running industrial assets. That needs to change if organizations are to realize the full potential of their IoT deployments.
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For change to happen, people up and down the service chain — managers, technicians, call center operators, and all the individuals that play a role in service management and repairs — need to buy into a new system built on the use of IoT data. Instead of traditional information sharing methods, they must use information derived from connected sensors to prioritize and organize workflow.
Unfortunately, most of the time teams are provided with only the most basic information without context, leaving them to piece together the root of the problem on their own. An alert that something is amiss with a piece of equipment is practically useless unless it is accompanied by insight into the cause of the failure or recommendations on how to address the problem.
The ensuing process tends to foster more chaos than efficiency. A fleet manager who receives a basic sensor alert from a vehicle’s temperature or pressure gauge, for example, will pick up the phone as the first step in attempting to identify the issue. That leads into other calls and emails between drivers, technicians, schedulers and others, all of whom try to work out a course of action. In the midst of the activity, various members of the service team will attempt to track down warranty and service history information, create work orders and more. It’s a time-consuming, frustrating process that mitigates many of the efficiency benefits that IoT offers.
Driving actionable data from IoT
Service relationship management (SRM) provides a much more effective means of managing the repair process. SRM is a closed-loop service management system that allows organizations to derive actionable data from their IoT deployments and makes it easier to prescribe a fix for faulty operations.
With SRM, teams are provided context behind IoT alerts, including insight into faults and recommended actions to take to repair the problem. They also receive access to a dashboard highlighting all relevant information, including vehicle information, records, notes, directions to dealer service staffs, parts availability and inventory, repair estimates, alerts and more. Everyone, from drivers to repair specialists to managers and others, can view this information at any time, ensuring that all service team members remain on the same page.
Having this data at the ready — and accompanied by appropriate contextual information — greatly enhances asset management, repairs and IoT investments. There is no more need for an arduous communications process. The detailed insight into IoT alerts helps take the guesswork out of repairs. Asset downtime is reduced, repair costs are minimized and IoT investments begin to pay off because the information teams are receiving becomes far more valuable. SRM effectively becomes the catalyst for change that can have a direct and positive impact on companies’ bottom lines.
Real-world results of SRM
Let’s take a closer look at how SRM works by examining how it has helped one major truck manufacturer. This particular company invested seven years into building a repeatable, trackable, consistent process to improve uptime for customers across its network of dealers in North America. For the first six years, work focused on three elements:
- Creating consistent customer experiences, including customer greetings, estimate creation, communication, tech support, warranty processing and remote diagnostics
- Seamless call center integration into the service and repair process
- Generating and using actionable intelligence
The company ultimately took these three elements, which historically are managed separately, and integrated all of them into an SRM platform. With this approach, the IoT-enabled sensors that provide 24/7 monitoring of the engine and transmission generate the data used throughout the SRM process — not just alerts when there are problems, but in the mean time between failure data, environmental data such as weather temperatures that affect tire wear, and anything else a sensor can detect and transmit. All of this data taken together enables proactive (preventative) diagnostics, detailed analysis of critical fault codes to facilitate repair planning in advance and streamlined service procedures.
The results of this approach were striking: Dealers in the program generated more than $8,400 more labor sales per 100 repair orders than other dealers, with an average cycle time (from open to close of a repair ticket) of 6.89 days per repair order versus the 10.25 days for other dealers, an almost 33% faster result. Overall, the manufacturer’s dealer network has seen a 70% reduction in diagnostic times and a 22% improvement in repair times.
Faster service order processing times result in more throughput for the service centers, better capacity utilization of existing facilities and much more satisfied clients. SRM is helping organizations achieve these goals. The aforementioned truck manufacturer invested in the technology, but also invested in training its dealerships, service managers and technicians in how to use it, track its effectiveness and measure its effect on the bottom line. This is one example of a manufacturer that was able to improve service efficiencies, maximize throughput and profitability and deliver better customer experiences — all while truly capitalizing on its IoT investment.
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