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Analytics and the Modern Energy Supplier

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Mark Konya's picture
Principal Industry Consultant SAS Global Utilities

Mark Konya, Principal Industry Consultant in the Energy Practice department of SAS Global Products, Marketing and Enablement, earned graduate degrees in physics at Washington University (St....

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  • Jan 27, 2019

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An Industry Disrupted

Disruptions in the energy supply chain continue to challenge the viability of traditional utility business models. For example, some utilities confronting disruptors like market liberalization, declining load growth, and extreme events such as major storms or wildfires – are struggling financially. Such disruptors erode revenue and ultimately could sound the death knell for some companies who traditionally make money based on their capital investments and the amount of energy they sell.

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In response to disruptions in the electric energy sector, modern energy suppliers have emerged. Thanks to data from the Internet of Things (IoT), deep learning, artificial intelligence (AI), and other advances in analytics, new and existing energy suppliers are adapting to – and even thriving in – the quickly changing energy supply landscape.

Who Is the Modern Energy Supplier?

It depends on who you ask. And it’s not singular.

Modern energy suppliers are a collection of business entities whose ultimate purpose is to deliver energy to customers. They fulfill a variety of roles and interact with each other and 3rd parties to:

  • Generate electric power.
  • Transmit it over the bulk delivery system.
  • Distribute power to end-use customers.
  • Collect a fee that reflects all supply chain costs, including a return to participating business entities.

Modern suppliers are involved in one or more of the supply chain functions described above. And they inherently respond to external factors not directly under their control, such as the rise of electric vehicles and installation of distributed energy resources. Modern energy suppliers might be described as innovative, socially aware and agile.  Their business models vary depending upon core business objectives and regulatory environments, but they generally revolve around performance-based principles and competitive marketplaces.

Compare this to traditional suppliers who manage most or all pieces of the energy supply chain and are owned by shareholders, which reduces risk appetite. They earn allowed returns on capital investments, but otherwise pass operating and maintenance costs straight to consumers. In this traditional cost-of-service model, end-use customers were historically known as “load” and growth or decline of individual “loads” hugely affects revenues. If gauging the personality of a traditional energy supplier, they could be described as risk averse and focused on maintaining the status quo.

But regardless of the supplier’s business model and “personality” type, external forces are driving radical changes across the energy supply chain – from generation and transmission of power to distribution and services. Enterprising modern energy suppliers will take advantage of change, and fill gaps that arise, to create new opportunities for success.

The Forces of Change

The gaps between the current energy supply chain landscape and its future vision are driving change and fall into at least five categories:

Figure 1: The forces of change in the energy supply chain landscape.

Sharing Economy

The success of companies like Uber, Lyft and VRBO was predicated on two fundamentals:

  • Underutilized capacity existed in asset fleets that could be profitably tapped to provide value to customers.
  • New technology platforms made it possible to match capacity with available demand in these markets.

With regard to the energy supply chain, parallels to Uber, Lyft and VRBO exist. Within the energy supply chain, it is only a matter of time before business value from a shared economy is harnessed. For example, consider the underutilized capacity to generate power and transmit it to customers at certain times of the day. With technologies such as blockchain, customers can directly enter into contracts with energy suppliers to tap into these underutilized assets, thus yielding substantial energy cost savings.

The sharing economy is moving quickly to tap idle capacity in the energy sector, creating new opportunities for innovative organizations.

Digital Technology

Whether applied to advanced control schemes for wind-turbine generators or better detecting security intrusions in substations, modern digital technology has revolutionized the entire energy supply chain. Among the more dominant technologies exerting forces of change are cloud services, intelligent controls, advanced data management, artificial intelligence, machine learning, streaming analytics and sophisticated visualization.

The data for these applications is largely generated by sensors connected to the Internet of Things (IoT). This new extended IT infrastructure enables new sense and control capabilities, powered by advanced analytics. Utilities are rapidly scaling up their skills in areas of machine learning and artificial intelligence to enhance grid modernization and automation efforts.

Transmission and Distribution Transformation

Digitalization is not the only revolution in the energy supply chain. Advances in science and engineering have made it possible to tap renewable energy sources on a scale not previously contemplated. Consider the capability to store electric energy in central station battery installations and electric vehicles. Concurrent advances in these technologies provide endless opportunities to reconfigure the energy supply chain in a way that makes the distribution grid more efficient and resilient.

Advances in transmission technology are also profound, as illustrated by widespread deployment of phasor measurement units (PMUs) through the North American SynchroPhasor Initiative.

Perhaps one of the more transformative technologies in the energy supply chain is deployment of automated metering infrastructure (AMI). The new generation of AMI meters is packed with capabilities that enhance distribution operations. For example, two-way AMI meters allow utilities and customers to interact to support smart consumption applications using real-time or near-real-time electricity data. Smart meters can support demand response and distributed generation, improve reliability and provide information that consumers can use to save money by managing their electricity.

AMI data also provides detailed outage information in the event of a storm or other system disruption, helping utilities restore service to customers more quickly and reducing the overall length of electric system outages. Smart meters provide:

  • Insight into loading distribution circuit components that can be used for planning purposes.
  • Monitoring power quality to help avoid damage to equipment.
  • Remote disconnect capability to avoid dispatching crews when an account is deactivated.

Modern energy suppliers engaged in transmission, distribution and services are now equipping their systems to meet the challenges of the future.

Customer Expectations

Over the past 20 years, energy customer expectations have become more demanding. Whether it’s reliability, affordability, communications or community involvement, customers around the globe expect modern energy suppliers to perform at a high level to earn and retain their loyalty.

The American Customer Satisfaction Index (ACSI), a national economic indicator of household consumer evaluations of product and service quality in the United States, reports evidence that supports this view. The ACSI 2018 report[1] states that customer satisfaction with electric service increased slightly from the previous year, although progress has been “glacial.” ACSI survey results indicate large variations between utilities, suggesting that some energy suppliers are meeting the challenges of increased expectations while others are falling behind.  Modern energy suppliers who have high customer satisfaction and loyalty typically perform better financially than those who don’t, thus providing a powerful incentive to adapt to more demanding expectations.

Regulation and Liberalization

Regulation modernization has been a prime driver for change in the energy supply chain. From “greening” energy generation to restructuring transmission operations, government regulators at all levels – federal, state and local – have imposed numerous new policies and rules on supply chain participants.

Energy supply chain regulations have multiple objectives that include ensuring affordable and reliable sources of power for modern society – all by balancing the interests of affected stakeholders. But outside of the energy domain, regulators also imposed new requirements on workplace safety, corporate accounting and operations affecting the environment, to name just a few.

Nowhere is the impact of modernized regulations felt more strongly than at the state level in the US. It is here that public utility commissions define the landscape in which the modern energy supplier operates. The 50 states, each with its own set of regulatory bodies, offer a smorgasbord of strategies for achieving their energy visions and goals. Naturally, this has resulted in a great variety of rules, rates and incentives that vigorously affect the energy supply chain business environment. Still, modern energy suppliers have rapidly adapted to the changing regulatory environment, if for no other reason than to survive without filing for bankruptcy or becoming an acquisition target.

Robust retail markets have also emerged in the electric energy sector. Spurred by changes in laws and regulations, competition in the energy marketplace has helped customers realize significant savings while advancing suppliers’ future visions of supply across the globe.

Utilities in competitive markets have turned to data and analytics to supercharge marketing efforts and woo customers back by earning their trust and creating new value. Adopting retail marketing techniques from best-in-class companies is one way that utilities are transforming into customer-centric organizations.

Advanced Analytics Enable the Modern Energy Supplier

To succeed, modern energy suppliers must adapt to the fast-paced change occurring in the energy supply chain landscape. Many are implementing IoT-enabled systems and innovative new business processes to provide the capabilities required to support a more agile energy company. Enabling the business with an enterprise-wide analytics platform to support digital transformation is at the top of many CIO agendas.

The digital transformation taking place in the grid will realize the most value when paired with advanced analytics capabilities. Below are some of the initiatives and value propositions which support transformation to a modern energy supplier.


Figure 2: Analytics solutions support transformation to a modern energy supplier.

Figure 3:  Value-added initiatives supporting transformation to a modern energy supplier

How the Analytics Life Cycle Supports the Digital Utility

At the heart of this transformation is the ability to collect, understand and act on the information flowing from a wide variety of sources. The analytics life cycle enables these capabilities and ultimately helps ensure the success of modern energy suppliers.

What Is the Analytics Life Cycle?

Successful modern energy suppliers recognize analytical models are essential corporate assets which produce and deliver answers to production systems for improved customer relationships, improved operations, increased revenues and reduced risks. Therefore, they seek to create the best models possible.

However, few fully manage all the complexities of the complete analytics life cycle. It’s a multifaceted process which guides modern energy suppliers through data preparation to discovery to deployment in business processes. When effectively managed these elements combine to create repeatable, reliable results.


Technologies like Hadoop and faster, cheaper computers have made it possible to store and use more data, and more types of data, than ever before. But this has only amplified the need to join data in different formats from different sources and transform raw data so that it can be used as input for predictive modeling. With new data types from connected devices, such as machine sensor data or web logs from online interactions, the data preparation stage has become even more challenging.


The discovery process starts by asking business questions that produce tangible value. Then, the business question is translated into a mathematical representation of the problem, which can be solved with predictive analytics.

Analytical tools search for a combination of data and modeling techniques that reliably predict an outcome. There is no single algorithm which always performs best in a given situation. The “best” algorithm for solving a business problem depends  on the data. Experimentation is key to finding the most reliable answer, and automated model building can help minimize the time to results and boost the productivity of analytical teams.


When predictive analytical models are embedded into production systems and  a business process uses the results to produce instantaneous answers, you have effectively deployed analytical models. Continuous improvement (CI) is fundamental to achieving business value through application of analytics results. CI programs establish the framework that guides you to ask the right questions and then applies analytics insights to improve process performance.

In most organizations the deployment environment is very different from the discovery environment, especially when the predictive models are supporting operational decision making. Often, it is necessary to apply rigorous governance policies in this environment to ensure service level agreements are satisfied. Additionally,  a transparent, governed continuous improvement process is important for everyone – especially executives, managers and auditors.


The modern energy supplier operates in a complex, dynamic business climate. Factors driving change include the shared economy, digitalization, T&D advances, increasing customer expectations, and modernized regulatory environments.  Adapting to these forces-of-change is necessary to thrive in a new energy economy. Adaptation – and ultimately success - is enabled by embedding continuous improvement in an organization’s DNA, which can only happen when an enterprise analytics initiative with a well-governed analytics life cycle is included in the DNA chain. This approach embeds agility and flexibility into the supporting IT fabric so that innovative business leaders reduce the time from problem recognition to discovery to action – and realize the value for which they’re striving!

[1]   “ASCI Utilities, Shipping, and Health Care Report, 2018.” American Customer Satisfaction Index.

Mark Konya's picture
Thank Mark for the Post!
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Richard Brooks's picture
Richard Brooks on Jan 31, 2019

Thank you, Mark. It's obvious that you did your research in producing this insightful piece. I also see the opportunity in today's disruptions, especially your points on sharing:

  • Underutilized capacity existed in asset fleets that could be profitably tapped to provide value to customers.
  • New technology platforms made it possible to match capacity with available demand in these markets.

A proposal has been submitted, and is under consideration, as an industry standard to create an "Always on Capacity Exchange" that would enable interested parties to secure green energy capacity or "power purchase agreements", and prioritize State energy tarkets for renewables, and properly value excess capacity resources, just like you cited in your article, using a standards based trading platform for North America.

Great article. Well done.

Ben Ettlinger's picture
Ben Ettlinger on Feb 6, 2019

Figures are not appearing in the article. Not sure if it's our fire wall or or an issuewith the Energy Central posting.

Ben Ettlinger's picture
Ben Ettlinger on Feb 6, 2019

Thanks for the post. I especially liked the last three paragraphs.

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