By Randy Cozzens, Contributor
The traditional utilities business model is under pressure worldwide. Decarbonization, deregulation, and decentralization are having a significant impact on the energy and utilities industry. And the change isn’t only within the industry itself: renewables capacity is growing exponentially, and a formerly passive consumer is becoming more aware and demanding more from their utilities, including a response to climate change.
Digitalization will be critical in responding to, and capitalizing on, the changes in the industry. Intelligent automation will play a pivotal role in managing the balance between demand and supply, boosting efficiencies across the entire value chain, innovating customer experience and transforming business models.
Intelligent automation is boosting operational efficiency, topline growth and customer engagement
Intelligent automation is the combination of automation and artificial intelligence to create systems that make real-time changes and adaptations to operations based on input from sensors. The Capgemini Research Institute (CRI) recently spoke with 530 business leaders about intelligent automation in energy and utilities, including oil and gas, electricity utilities, water utilities and energy services. The research reflects the voices of industry leaders who are experimenting with or implementing automation solutions.
The report also analyzed more than 80 use cases to assess maturity, complexity and benefits. This resulted in important insights into the power of intelligent automation and how the forerunners of this technology are leading to a new energy and utilities dynamic. Based on the report, the U.S. industry is leading the charge, with 23% of companies implementing multiple use cases at scale.
Intelligent automation should not be underestimated. The CRI estimates that the industry can save between $237 billion and $813 billion globally over the next three years. The potential is significant, but nearly half of the leaders surveyed under-estimated the benefits derived from their intelligent automation initiatives.
Xcel Energy, a U.S.-based electric and gas utility, uses data from sensors on wind turbines to develop high-resolution wind forecasts through AI techniques. The company reduced costs to end customers by $60 million by increasing the efficiency of generation. Savings like that, driven by digital technologies, mean it is time to realize the potential of automation.
Organizations are missing opportunities by ignoring high-impact use cases
Analyzing 80 use cases led to the conclusion that most companies are missing a big opportunity. They should be targeting projects that are easy to implement and which will deliver big benefits. Instead, more than one third of energy and utilities companies (38%) are focusing on projects that are easy to implement but which deliver small benefit. Fewer than one in five (18%) are focusing on the sweet spot of quick wins with big value. It is time to think beyond support projects, as these companies have done:
- GE Renewable Energy is using machine learning to support yield optimization. It builds virtual wind farms in a cloud-based platform that mimics a real-world, physical design. The model runs wind patterns and calculates electrical output to optimize production on an individual turbine level. GE expects to generate a 20% boost in energy production, resulting in $100 million in savings over the lifetime of a 100MW farm.
- Vermont Electric Power Company (VELCO) uses advanced data science and machine-learning techniques to develop a hyperlocal weather forecasting system. It applies this weather model to all its solar and wind farms in Vermont, and has reduced average energy forecasting errors by 6% for solar and 9% for wind. Every 1% of load reduction means better resource allocation and saves ratepayers $1 million.
- Better complaints management has made a significant difference for Exelon, a U.S.-based electricity and gas utility. Its AI-powered chatbot, developed to resolve customer complaints on issues such as outages and bills, has reduced customer churn and generated deeper insights into their consumers’ needs.
The roadmap to intelligent automation at scale
It is time to move beyond a conservative mindset. The research shows only a few companies we call forerunners have been able to depart from past methods to create truly breakthrough initiatives. Industry leaders consistently display five elements in common:
- A pragmatic approach to evaluate and choose intelligent automation use cases to move forward, so they know the impact before scale up. They need to have the minimum technical talent to collaborate with a functional team. They also need to address fundamentals such as legal, ethics and risk.
- An investment of effort to integrate and optimize the right processes for intelligent automation deployments. More than 50% of forerunners have a plan to set-up dedicated teams over the next two to three years to investigate the impact and adoption of automation, compared to 11% of their peers.
- A greater emphasis on technology, backed by larger budgets. Forerunners are spending more now and are planning to spend more in the future.
- A dedicated and centralized leadership supported by governance for intelligent automation. The centralized approach builds the experience and expertise needed.
- A drive to involve the workforce and invest in their capabilities. Resistance can be a significant barrier, but forerunners have higher employee satisfaction levels, and that has created new job profiles rather than eliminating them.
The demand for traditional, centralized provision of power from coal, gas and nuclear sources is diminishing. Automation and AI will be instrumental in meeting the new demands of the market, including addressing climate change. The new industry, one that is more efficient and driven by customers, will be built on reimagined operating and business models created by intelligent automation.
Randy Cozzens is executive vice president, North America sector head of energy utilities and chemicals with Capgemini.