Manufacturers and services teams are constantly pressed with reducing costs while driving higher levels of efficiencies. Organizations are turning to technology to resolve these colliding occurrences and enable digital transformation across the service lifecycle.
Three ways technology is underpinning massive reductions in labor, assets, parts, and customer costs for industrial enterprises are:
1. Resolution of service issues remotely
2. Equipping technicians with the right tools, parts, information, and skills
3. Enablement of customer self-service
Below we will provide more detail on how forward-thinking organizations are driving transformative change in the service lifecycle today.
Truck rolls are known as the service processes related to dispatching a service technician to resolve service issues. They are typically the highest service cost ranging between $150-$500 per dispatch, and even $1,000 in some instances. These costs compound for organizations with thousands of technicians completing multiple dispatches a day. However, in 17-20% of truck rolls there is ‘No Fault Found’ (NFF), meaning the technician didn’t need to make the costly trek to service the asset. As a result, the business has a massive sunk cost.
Increasingly for industrial companies with standardized asset installed bases, these physical service interventions can be mitigated with digital capabilities. Solving these issues remotely can drastically decrease truck roll associated labor costs, as well as asset (warranty, compliance penalties) and customer downtime costs.
Connecting products to the Industrial Internet of Things is rejuvenating the service cost structure and propelling innovative use cases. Specifically, remote monitoring is connecting, collecting, and managing real-time asset performance data from out in the field. Remote service provides a method to trigger remote actions such as over-the-air software troubleshooting or package updates.
Implementing these IIoT-enabled remote use cases across fleets of thousands of assets can greatly reduce sunken costs for trivial service tasks or situations where there is NFF. Service leaders expect a 57% increase in remote service activities over the next year to further minimize service response times.
Even with remote monitoring and service driving massive cost savings across fleets of products, some service tasks will require physical interventions. In these situations, enabling the technician to resolve the service issue as efficiently as possible is critical.
But many industrial companies have heterogenous and dated asset install bases, which require more complex and resource-intensive maintenance actions. These industrial companies report higher service unpredictability (48.9% incidents on site) and longer first visit repair times (4.4 hours) than others. These complex service issues magnify with a growing amount of experienced technicians approaching retirement, which 70% of service teams claim they’ll be burdened by in the next five to ten years.
The effects on first-time fix rates are noticeable with the industry standard averaging around 75%, meaning one-fourth of service dispatches require at least one subsequent visit with the dispatch of an unqualified technician and the absence of the right part or tools being primary reasons why.
There are a few different technology levers service teams can pull to better prepare their technicians for the service task at-hand. Predetermining the issue through root cause analysis can give the service team and technician a better idea of the resources they’ll need. Technicians must know the skillset, tools, replacement parts, consumables, and service information (product manuals, instructions) prior to dispatch to complete the task efficiently.
IIoT provides more granular asset health information at both a system level and more specific component failures, which inform any critical repairs. Service parts management systems importantly pinpoint any part information the technician would need to know tomake this critical repair.
Augmented reality is the emerging service tool to empower the technician to make timely repairs. AR is being used to improve training for junior-level technicians to alleviate skills gap concerns and heighten the workforce knowledgebase to tackle more complex issues.
On-the-job AR service instructions virtually overlay critical step-by-step sequences and procedural guidance to reduce cognitive distance and improve document scalability versus traditional paper-based methods.
Remote assistance and knowledge capture and transfer AR applications are also rapidly scaling workforce expertise in the wake of this skills gap as well as during the COVID-19 crisis, where travel restrictions are limiting frontline worker productivity.
Manufacturers of complex products operating in mission-critical environments have performance intensive considerations for downtime. End users and customers of these products simply cannot afford downtime in these high stakes situations, such as power equipment in Arctic Circle mines.
Enabling a degree of customer self-service benefits the OEM and end user. The manufacturer can offload several service responsibilities and costs like truck rolls associated with guaranteeing uptime of their products, while the customer is given more operational control and can maintain uptime of their own assets with minimal assistance. Providing the customer with IIoT-generated operational and service data empowers them to predict any failures, minimizing any disruption to operations and gain insights for unprecedented levels of uptime.
Organizations are moving away from the traditional mindset that service organizations are inefficient cost-centers and instead viewing it as a function poised for significant optimization. Pulling one or multiple of these service cost-cutting levers will be unique to the business drivers and value desired. However, with increasingly powerful technology underpinning cutting-edge use cases, the opportunity to create service transformation in your company has never been more attainable then today.