Overcoming stumbling blocks to successful predictive maintenance yields 25% – 30% reductions in maintenance costs: U.S Department of Energy

As field service organizations increase their investments in mobility, cloud technology, and big data to optimize maintenance, predictive analytics are redefining service with a focus on preemptive support: “Advanced data analytics and artificial intelligence solutions enable a model of predictive asset maintenance; where the probability of fault can be detected before it happens,” according to Deloitte.

New, predictive asset maintenance systems can solve routine problems, allowing organizations to realign technicians to solve more complex issues associated with managing end-to-end asset lifecycles and extending the life of assets. This allows manufacturers and distributors to minimize downtime and improve the customer experience.

But implementing predictive maintenance technologies has its stumbling blocks, and their costs can be prohibitive for some organizations. Automating processes gives organizations less control over the cost of those processes, for example; and complications with the transmission and analysis of data can lead to costly bottlenecks and mistakes.

Predictive maintenance is a worthwhile long-term investment, despite short-term difficulties

Despite complications, predictive maintenance tools have become a required investment among field service organizations. “The advantages of predictive maintenance are many,” says the U.S. Department of Energy. Independent surveys show companies realized a 10× return on their predictive maintenance investments and up to 25% increase in productivity, according to the department, and predictive maintenance has become a competitive differentiator among organizations as well.

Predictive maintenance is no longer a question of “Why,” in this case, but a question of “How.” Organizations may all arrive at an investment of this nature in time, or fail trying—the question on their decision makers’ minds must be, “How can I get there first?”

Q2 2020 Study: ‘Defining Expenses and Key Implementation Challenges with Predictive Tools’

In our upcoming report, WBR Insights helps business leaders make sense of modern predictive analytics tools, capabilities, and use cases, with key insights into how these tools can transition field service organizations from ‘maintenance’ to ‘customer solutions’ operations.

Through an interview-based survey of 100 industry professionals, we identify key opportunities and implementation pain points among leading field service organizations. We identify the “if I only knew” insights field service decision makers have after their implementations. Finally, we uncover the real costs and ROI potential of these investments as you prioritize them for your own organization.

Access the Full Report: Available May 2020

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