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Related Expertise: Power and Utilities, Energy Networks: Transmission & Distribution

Why Technology Alone Is Not Enough

By Philip HirschhornOxana Dankova, and Pavla Mandatova

BCG’s new compendium of articles sheds light on how leading energy network utilities are addressing the industry’s critically important challenges. These bionic companies achieve superior business performance through a combination of sophisticated technological capabilities and human expertise. The articles include:
  • Electrifying Your Digital Transformation, a discussion of how bionic energy networksunlock the value that digital initiatives have to offer
  • The Energy Transition Needs Next-Gen Network Planning, which explains how collaborative scenario modeling across the ecosystem can smooth the journey to net zero
  • Let’s Get Digital in Asset Management, which outlines how technology, data, and advanced analytics,can be used to predict potential failures, optimize asset performance, and reduce the time to deploy
Across these discussions, one theme remains constant. Energy networks that focus on advancing their digital and human capabilities today will be better poised to tackle tomorrow’s challenges.

Human expertise has proved critical to realizing the full potential of a digital transformation at scale.

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:

  • Implementing new technology without a clear understanding of how it will translate into benefits
  • Failing to help a team change itself and its processes to get the most out of the technology
  • Seeking to implement digital change on a technology platform that isn’t flexible enough for today’s rate of change

Energy networks can overcome these challenges by becoming bionic.

What Is a Bionic Network?

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.)

  • Purpose and strategy set the direction. They inspire and align rapidly moving autonomous teams because they establish “an unbroken chain of why” that links the work that teams do to the business outcomes required.
  • Business outcomes are specific goals that fall into three categories: bionic operations, personalized customer experiences, and new offers and services. For energy networks, creating bionic operations is the most relevant of the three, although personalized customer experiences are becoming more important.
  • Human enablers include the right mix of talent, an organization structure, cross-functional teams, and new ways of working that will transform the business. For example, the bionic energy network requires talent with a variety of skills—user experience designers to improve the employee or customer experience, as well as data scientists to organize data and develop and train algorithms. The bionic network achieves the right mix by retraining the existing team and hiring new employees.
  • Technology enablers encompass the modern stack of modular, flexible—often cloud-based—systems that underpin the new digital processes running the network. The enablers also include the suite of technologies—such as satellite and LiDAR imagery, drones, artificial intelligence, and network sensors—that provide the data that is the lifeblood of a bionic energy network.

How to Become a Bionic Network

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.

Transforming Vegetation Management

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:

  • How do we quantify the risks—to human life and property—of vegetation-induced outages and crises, such as wildfires?
  • How do we determine when to treat vegetation so that we can manage the risks yet minimize the number of visits? How can we predict vegetation growth and when vegetation will affect the network?
  • Which data—including LiDAR, satellite, and ground imagery; weather information; and vegetation species data—should we analyze in aggregate to predict growth?
  • What information architecture is needed for reaching informed conclusions from a variety of data using artificial intelligence algorithms?
  • How do we change the processes and contracting models with our vendors so they can treat vegetation in the right way at the right time?
  • Which experts—data scientists, designers, and developers—do we need on a cross-functional team to deliver the new vegetation management process and help arborists?

The answers to these questions reveal the combination of the technology and human enablers required to achieve the desired business outcome.

The Benefits of Becoming a Bionic Energy Network

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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