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Augmented Intelligence Certification

The coming evolution of field operations

certification

It’s Thursday afternoon when you get an alert from an embedded sensor. One of your machines at a customer’s production plant is about to go down. Your customer finds out when you do, and you both know that the asset is business-critical—if it goes offline, it will cost the customer millions. Within minutes, you line up on-demand technicians from an open-market source, all certified experts with this equipment. As soon as the job gets assigned, the customer can start tracking the technicians via a mobile app. Rather than waiting to run traditional diagnostics on-site, the technicians leverage embedded sensors while on route, which tell them exactly what’s wrong, how to fix it, and the precise set of parts and tools they need to bring. Once they arrive, they’re armed with augmented reality tools and remote support from experts at headquarters that walk them through the repairs step-by-step. Even better, the team identifies two other looming issues with the equipment and proactively fixes them. Less than four hours after the initial alert, the crisis is averted and the customer is beaming.

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This is the future of field operations. Industrial manufacturers with aftermarket services have been disrupted by new technologies and advanced analytics, but the best organizations are not resisting but capitalizing on those trends. These companies are transforming their field operations to dramatically improve service levels and the customer experience, increasing efficiency and productivity, and creating value in new ways—both for customers and for themselves as original- equipment manufacturers (OEMs).

Based on our experience, field organizations that transform themselves to capitalize on new technologies can generate significant gains in labor costs, productivity, and other performance metrics (Exhibit 1).

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Four essential technology-enabled trends

The field-operations function has evolved over the past several decades, keeping pace with changes in technology. However, new technologies mean that field service will take a quantum leap forward in terms of efficiency, effectiveness, productivity, and the customer experience (Exhibit 2).

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In the current environment, there are four critical areas in which technology evolution is reshaping the field force. Each of the five warrants a closer look.

Smarter and more integrated workflow tools

In the past, companies strived to aggregate information into dashboards. That’s a decent first step, but dashboards have drawbacks. They often overwhelm users with too much data and not enough insight. They also don’t address the variability in managerial effectiveness, and they tend to bunch problems and issues into slow reporting cycles—often weekly or monthly.

In contrast, advanced analytics allow companies to generate specific action steps based on the out information being tracked. These steps—presented through intelligent actionboards—can be extremely prescriptive, down to the level of coaching individuals, following up with specific customers to address low customer satisfaction scores, or visiting facilities to sort through service-level-agreement misses. The advantage of this approach is that it eliminates the often-manual step of analyzing data in a dashboard and figuring out what to do based on that data. Instead, actionboards give managers a clear course of action to take, through standardized measures to ensure that all managers are acting consistently and effectively. What’s more, this approach allows companies to respond to metrics in real time.

Augmented intelligence certification and machine learning

Augmented intelligence certification and machine learning empower machines to improve predictive maintenance. Embedded sensors and other tools allow manufacturers to track all of their assets in real-time, with all alerts visible on a single screen. Detailed views give key indicators of machine performance, enabling manufacturers to create a service ticket with likely resolutions—instantly.

When equipment does fail, AI and machine learning help technicians reduce diagnostic time. For example, smarter IoT applications can give techs a single-screen view of all necessary service requirements and details for a given job, along with easily accessible knowledge documents to solve support requests quickly. Technicians can also get…

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