English
The pressure on utilities to deliver on customer experience, invest in new infrastructure and technology and deliver shareholder value has only been intensified by the Covid-19 pandemic, which exposed the shortcomings of semi-manual business processes that were over-reliant on people.
As a result, current operating models have proved unsustainable in the face of dramatic change in the industry, driven by competition from new entrants, customer demands for a truly digital experience, brand erosion, rising operational costs and a fall in return on equity.
A widespread dependency on large numbers of people to perform low value, repetitive tasks cannot continue in the face of these trends. Dependence on people working in expensive offices to rigid schedules and prescriptive practices limits responsiveness and the rapid evolution of business models.
Digitization has an outsize impact
The ongoing digitization of operations has the most significant impact on the way utilities function. However, research shows the majority of organizations are some distance away from reaping the full benefits of digitization and automation.
For example, the Capgemini Research Institute’s report Intelligent Automation in Energy and Utilities finds that while technologies such as automation and artificial intelligence offer the potential to save between $237 billion and $813 billion over the next three years, most organizations are not yet ready to make a success of them.
In core functions, only 18% of organizations are deploying quick-win use cases such as forecasting, energy trading, yield optimization, grid behavior interfaces and complaints management. Just 11% of organizations are focusing on quick wins in support functions such as order management, contract management, employee data management, and defect detection.
Yet somehow, utilities need to cross this productivity and acceleration gap to build more agile and responsive operating models. The complex models commonly used today tend to equate to steep operating costs because of maintaining a high head count and lack of efficiency in back office and customer services, which means cost-to-service claims and contracts are also punitively high.
However, the notion of replacing IT systems to deliver a more cohesive set of processes is untenable for utilities, which are already wrestling with managing the costs of legacy infrastructure and addressing inefficiencies exposed by the pandemic.
Enter intelligent automation
There is an alternative, which is to use intelligent automation to embark on a short-to-medium path to value, starting with the digitization of customer and worker experiences. These relatively simple, processes may not be strategically game-changing, but still have huge impacts on the efficiency of an organization, and the time that can be freed up for other, more complex tasks.
Having identified quick wins, utilities can move on to bring further improvements to customer service centers, back office processes and risk management. Some real-life examples of where utilities have acted at pace to automate processes using Blue Prism intelligent automation are below:
- Utilita cleared £6.4 million of debt by implementing a change of account types to pre-pay, while saving 12-14 hours per week on average by using digital workers to validate, collect and transfer data from pre-payment smart meters
- DTE automated 35 processes over the course of nine months and gave 250,000 annualized hours back to the business
- Npower renegotiated 95% of expired contract transactions through intelligent automation. Two million hours are handled by digital workers annually, with 400 digital workers being managed by just two people
- Uniper manages 60% of new contracts through intelligent automation following quality checks
Beyond using intelligent automation to improve customer facing processes, some utilities are beginning to think about how to apply it to wider efficiencies such as predictive and preventative maintenance. Technologies such as IoT sensor data monitoring and prepayment meter automation can be incorporated into utilities’ intelligent automation strategies, for example.
One of our utility customers recently tested an AI platform to analyze large data sets on factors such as weather, demand for water, pump performance and electricity prices, then used the information to make decisions on the most cost-effective and efficient way to run pumps, detect burst pipes and minimize the risk of discolored water. During the trial, the utility achieved energy savings of 22%.
Pressure on the world’s valuable resources and the global battle with climate change will put utilities under huge scrutiny in the years ahead, not just from regulators and customers but from shareholders too. Failing to take action on inefficient generation and distribution processes will no be acceptable.
Using intelligent automation to predict demand and safeguard efficient usage in an agile and highly responsive way will therefore become a necessary element of tomorrow’s operating models, together with a higher quality customer experience.