As companies contemplate business after the pandemic, executives of energy network utilities are recognizing that there is an opportunity to accelerate the adoption of digital technology in order to build smarter, more resilient, and more customer-responsive networks.
Energy networks are under growing pressure from many directions: regulation, which squeezes returns; climate change, which increases the frequency of wildfires and other extreme weather events; and distributed energy resources, which impose new technical requirements.
A wide variety of digital technologies have the potential to relieve these pressures: drones, satellites, and light detection and ranging (LiDAR) imagery can map an energy network and identify defects; artificial intelligence can help process the imagery and predict asset failures; advanced distribution management systems can orchestrate network flows; and robotic process automation can make the back office more efficient and productive.
Many energy networks are pursuing digital initiatives using these and other technologies. Yet, despite their efforts—and considerable investments—few companies feel that they are realizing the full potential of digital transformation at scale. Most struggle to move beyond pilot programs to having real business impact.
Energy networks’ less-than-satisfying outcomes have common sources:
Energy networks can overcome these challenges by becoming bionic.
A bionic energy network melds technology with human expertise to create business outcomes worth more than the sum of these parts. In a bionic organization, four elements work together. (See Exhibit 1.)
The bionic journey begins with the energy network identifying the business outcomes that it wants to achieve, rather than focusing on use cases or applications of specific technologies. The challenge is to reframe the starting point. Rather than asking which new tool should be added, the network asks what business need or problem must be solved and how can the company’s capabilities, human and technological, combine to deliver the solution. By starting with clear outcomes in mind, the approach becomes targeted and relevant, leveraging the full mix of technological capabilities and human expertise. Energy networks should pursue six main business outcomes to realize the benefits of new technologies. (See Exhibit 2.)
The next step in the journey involves identifying the human and technology enablers needed to achieve a few prioritized business outcomes, rather than trying to build a suite of technology or implementing new ways of working across the business. The company can then progressively expand its initiatives to achieve other business outcomes, building momentum that eventually leads to having bionic capabilities across the organization.
Vegetation management provides a good example of how the bionic approach can work. All too often, companies implement LiDAR technology in their vegetation management process, only to find that it adds cost without improving compliance very much.
Instead, companies should first identify the business outcome that they want to achieve: for instance, a 30% reduction in vegetation management costs without increasing network risk. That step raises a series of questions that companies should ask themselves. For example:
The answers to these questions reveal the combination of the technology and human enablers required to achieve the desired business outcome.
The cost-reduction benefits of adopting a bionic approach are substantial. Bionic energy networks have reduced replacement expenditures by 10% to 15%, cut vegetation management costs by 20% to 30%, increased workforce utilization by more than 50%, and reduced contact-center call volumes by 40%.
In addition, bionic networks experience substantial improvements in customer outcomes: the time to make connection offers falls from weeks to seconds, and reliability measures rise significantly for targeted parts of the network.
Perhaps most important, working in a bionic energy network leads to more engaged and productive employees with a real sense of purpose.
The authors thank their former colleague Javier Argüeso for his contributions to this article.
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