How 6 Technology Trends are Changing the Business of Utilities
We rarely think about how water, electricity, or other utilities come into our homes when they’re working—when they stop, that’s a real problem. What we almost never consider is the laws and rules that govern utilities, and the challenges of doing business in a highly regulated industry and keeping customers like us happy. While the inner workings of utility providers are a mystery to most consumers, careful observers can see they’re wrestling with powerful market and regulatory forces that demand major transformation.
While in most places across the globe utilities don’t face competitive pressures similar to other businesses, they are increasingly tasked with balancing disruptive forces with a deep commitment to customer satisfaction. Leveraging new technologies and keeping a customer-centric mindset will help utility companies adapt and thrive.
Let’s explore the technologies that are contributing to this shift, and their impact on the business of utilities.
Cloud-based software has been a boon for just about every industry, enabling businesses of all sizes to take advantage of security, speed, and scalability ensured by massive services providers like Amazon Web Services (AWS). It has also helped software companies rapidly deploy, refine, and update their offerings with features and enhancements in ways that were impossible for software installed on a local machine in someone’s office. Most enterprise software providers are now cloud first, and their best features are only available in their cloud offerings. So why is that a challenge for utilities?
Utilities have historically (and understandably) been risk averse, and thus slow to integrate new technologies into how they operate. In the United States, when a utility company makes a large software investment—let’s say in a field service management solution—a one-time purchase is treated as a necessary capital expense, and some of this expense can be passed on to the customer. With a perpetual investment in cloud software, the same solution is now treated as an operational expense. Regulators expect utilities to keep operational costs down in order to keep margins and profitability higher, and as such don’t allow these expenses to be paid for by customers.
Not upgrading to the latest software means losing out on efficiency, profitability, and service quality gains enabled by modern, best-in-class solutions. But taking on a large investment as an operational cost has an immediate and sweeping impact on profitability. Until fiscal regulations catch up to how the business world buys software, many utilities will struggle with moving their tech infrastructure to the cloud.
The Internet of Things
Aside from interacting with and repairing things for customers, utilities are also responsible for managing powerlines, pipelines, dams, and everything else that makes up the infrastructure that enables them to generate and deliver power and water. Consumers are increasingly comfortable with connected lights, thermostats, and other smart devices in their homes. What’s more, with the helps of apps and devices like Amazon Echo, there’s a growing expectation of connectivity among all things. In parts of Europe and the UK, there is a mandate to install smart meters in every home to more accurately capture energy usage data in real time—helping the suppliers better forecast demand, and helping consumers save money.
Utilities can rely on a more connected, smarter infrastructure to help anticipate repairs before something breaks, and to better diagnose the nature of a problem to supply the correct fix—or technician—rather than dispatching an all-purpose engineer and hoping for the best.
Constant connectivity and increasingly smarter equipment add up to a lot more data being collected and in need of being processed. Today, virtually every business is in the data business. As utilities incorporate sophisticated equipment and assets into their portfolios and accumulate more user data (via smart meters, for example), that data can translate into real business insight with measurable impact.
The potential for all of this data is only realized when a service organization has the tools to analyze and understand it. The sheer volume and variety of data make it impossible—and inadvisable—for humans to make sense of it all without smart artificial intelligence based solutions. Machine learning can enable organizations to take historical and real-time data that can lead to better decisions around everything from demand forecasting to workforce capacity management, emergency planning, predictive maintenance, optimized scheduling, more accurate travel times, seasonal service patterns, and more.
Renewable Energy Sources
It’s not surprising that renewable energy sources and mandates are affecting utilities. Some are now required to include greener sources as part of their overall energy portfolios. Some are enabling customers to send—and sell—power back to the grid. And government subsidies for green energy sources are making traditional sources less attractive for investment.
Renewable sources still account for a small amount of the global energy market, but their adoption makes pricing power increasingly complex.
In the coming years, utilities will continue to wrestle with developing more flexible pricing models, take on management of surplus energy storage, and balancing the need to maintain and repair aging infrastructure while investing in and building greener options.
When utilities serve a large region or initiate special projects while working with a fixed size or less experienced workforce, being able to teleport seasoned technicians at will sounds like the best solution. Augmented reality (AR) is the next best tool, and maybe even better.
With AR enabled mobile devices, headsets, goggles, or other wearables, a technician at a job site can view additional information about a piece of equipment, or receive instructions from another tech who is assisting remotely. While keeping both hands free for the actual repairs, a field service tech can view the service history of a machine, see the location of a part that needs to be swapped out, or follow visual cues provided by someone more senior. This enables a utility to dispatch the closest technician to a job and to make the experience of older technicians more mobile without requiring them to travel.
As utilities face both great demand and an aging workforce and the inevitable knowledge loss, AR can keep costs down and alleviate the impact of changing employee demographics.
Disruptive Service Models
Interestingly, not all disruption to utility business operations is coming from technologies they can use. Some is coming from tech companies and apps most utilities wouldn’t consider direct competitors. While regulators set customer satisfaction targets for utilities, companies like Airbnb, Uber, and Amazon set expectations in terms of transparency, visibility, and seamless experiences.
Customers can now take for granted that it’s possible to track a driver—or technician—in real time, to easily schedule appointments and communicate preferences, and to change everything on the fly. When speedy, seamless service experiences become the norm for the average consumer, every service organization must catch up or face some unpleasant feedback.
In addition, various apps have made it possible to make almost anyone part of an ad-hoc workforce (whether it’s your Lyft driver or someone picking up your dry cleaning by way of TaskRabbit), enabling a level of responsiveness and elasticity most workforce managers wouldn’t dare dream of. A third-party workforce needs to quickly align with the core workforce when work type or volume changes, and do so without the customer experiencing any disruption in the quality of service or their experience.
Categories:Artificial Intelligence, Field Service Management, Wearable Technology, Workforce Management Trends