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Jan 23, 2019

What's Disrupting Utility Analytics - Part II

Part II: People

By Paul McRoberts

In part one of our series, we explored how disruptions to technology and data are reshaping the utilities space. Now we’re taking a closer look at how this evolution disrupts our people—and like part one, part two starts in a car.

What the Tesla Tells Us About Utilities

If you want to be blown away by the capabilities of machine learning, ride in a Tesla on auto-pilot. My friend took me for a spin the other day, and he didn’t touch the steering wheel once. The car was 100% aware of its environment—where the other cars were, how far away the next stoplight was and when it was time to make a right-hand turn. It was a real eye-opener in terms of where we’re at with equipping machines to provide second-to-second feedback based on the information they’re consuming from the outside.

My question is this: How long before cars go beyond taking us from point A to point B and start making decisions for us, like taking the fastest or most fuel-efficient route to a destination?

Like with cars, this is where utility operations are going.

Can You Imagine a Self-Managed Utilities Network?

For decades now, when a compressor has failed or a transformer has gone down, we’ve had operators go and fix them. And as alarms have gotten more predictive, operators have been able to cut response times, improve performance and reduce downtime. This is equivalent to minding the “change oil” light in a car—the quicker we respond to that light, the healthier our vehicle will be and the more likely we’ll avoid future costs and headaches. However, in the case of both underperforming utilities systems and oil-craving vehicles, resolving the situation requires manual work and know-how, which will forever be an obstacle to real-time performance optimization…unless a system no longer has to wait on the operator.

Operators Become Advisors

Let me be clear—nothing will ever replace the experience and skill of a plant operator or system engineer, but today’s machine learning and artificial intelligence (AI) capabilities urge companies to leverage their experts’ skillsets in more innovative ways. The more we can understand how experts assess and respond to the billions of bytes of data streaming through our systems, the better we can utilize machine-learning technology to replicate their behavior and embed advanced understanding and decision making in our networks. From here, our engineers’ experience and domain knowledge won’t be needed for diagnostics at all, only in advisory capacities where they’re assuring machine learning decisions are correct. Not only does this free up our most vital assets—our people—to focus on more innovative, revenue-oriented work, it also creates new jobs.

New Opportunities for Experts

We’re already starting to see these new job opportunities take shape. Think about the rise in demand for data scientists in every corner of the market. In the utilities space, I think we’ll soon have business analysts or business unit managers, experts whose sole responsibility is to interpret data and, using tools like machine learning and AI, dictate decision making based on what the data means across a network. In utilities, this could translate to decisions around what fuel type to purchase or how much energy to generate for a system to run more efficiently.

Your Transition Needs to Start Now

The “people disruption” being caused by next-generation technology and data utilization is real, it’s far-reaching and it’s quickening. That means that, for us in utilities analytics, transitioning from old skillsets to new ones has to start immediately. For many companies, adopting technology like machine learning and AI might be the first step. For others, it might be upping their staff’s comfort and know-how with new technology so they can educate future generations of workers. No matter what, we have to acknowledge that the way we approach utilities is changing, and the sooner we adapt our tools, processes and people, the better we’ll be able to take advantage of new opportunities when the industry is undoubtedly disrupted again.

If staying ahead of the utilities analytics curve is on your priority list, you’re welcome to participate in a demo of our ASSET360 platform and learn more about its uses for system monitoring, diagnostics, risk assessment and more. Just contact us.

Read part one of our “What’s Disrupting Utility Analytics” series? Just click here.


Paul McRoberts is the President at Atonix Digital. Paul oversees the development and deployment of the company’s suite of software solutions powered by the ASSET360 analytics platform. Paul brings to Atonix Digital both rich software development experience and an in-depth understanding of how deep data exploration is helping transform businesses through greater insight and intelligence.

Read more blogs by Paul McRoberts