In virtually every case, the company’s demise was due to their inability to rapidly adjust to market conditions and to account for new, disruptive technologies or more innovative competitors. Although most utilities don’t run the same risk of being driven to the brink of bankruptcy or extinction by competition, there is still an express obligation for us to be good stewards of resources for the sake of our customers and stakeholders.
To that end, how can smart utilities avoid some of the more obvious pitfalls and be more creative while leveraging the endless research that exists? Is there a way for us to incorporate groundbreaking technologies such as artificial intelligence (AI) without fear of failure?
In many cases, operations in utilities are notoriously slow to adapt and are based on decades-old legacy systems that exist in siloes. These same systems are oftentimes mainframe based and managed by redundant, paper-based processes that worked better in an analog world.
However, the growing expectation from our customers is that we provide real-time access to account data such as bills which requires us to take a closer look at those same systems in order to identify opportunities for modernization. Increasingly, there is also an expectation for digital platforms that keep data secure, are available 24/7, and easy to use.
Both requirements are complementary and provide avenues for introduction of disruptive technologies that drastically improve our ability to become smart utilities.
In order to bring solutions like this center stage, we, as digital leaders, must lead the effort to automate back-end processes and centralize data in order to increase our capacity and expand our insights by leveraging analytics that allows us to make more informed decisions about where best to use our limited resources.
Digital leaders must lead the effort to automate back-end processes and centralize data to make more informed decisions about where to use the limited resources
Ideas for these improvements could come as the result of joint brainstorming sessions with business units and customers or by collaborating with external focus groups comprised of industry leaders, university students, and research partners.
The outcome of one of these focus groups could result in a possible use case for a water utility that proposes the use of analytics against existing datasets to predict which pipes are most likely to burst. It can be done by applying algorithms that take into account the age of pipes, the number of customers served, and the most recent preventative maintenance performed. By focusing efforts on replacing these pipes, money would be saved in the long run by avoiding costly repairs and lost revenue.
Another example of a possible use case that could emerge would be anticipating utility bills for customers based on historical usage and making recommendations for cost-savings in advance of peak utilization periods such as the middle of summer when pools are filled or on weekends while everyone is home.
In order to move forward with either use case, there would have to be recommendations made that would include a robust architecture that allows for the demands of non-stop processing. There would also have to be a reliable predictive analytics platform that takes an operational look at trends in order to understand what might occur, allowing key knowledge workers to make higher level contributions and gain increased job satisfaction. Lastly, there would also have to be an internal ecosystem that allows the entity to maintain a competitive edge by encouraging, proving, and introducing cutting edge technologies and use cases.
This ecosystem is created and will be managed through a collaborative trust that must be cultivated across the business and further expanded by leveraging the expertise of external partners. IT plays an important role in implementing and understanding capabilities of the technologies. The business plays a critical role in serving as subject matter experts who are familiar with their data and potential pain points of customers. External partners play a vital role by ensuring that the business is aware of new advances in technology that expand capability.
Together, they create a collaborative endeavor that is constantly researching and seeking new ways to use data in pursuit of higher level contributions that can be exponentially optimized by applying AI.
Industry research has shown that providing effective analytics is the most urgent capability requested by businesses and one of the most visible ways to show immediate value. These same analytics platforms also demonstrate opportunities for automation of operational or business processes which exponentially decreases the amount of human intervention required.
The possible uses for artificial intelligence in smart utilities are only limited by our imagination and willingness to experiment, but still, require human interaction in order to develop viable use cases. However, artificial intelligence presents us with tremendous opportunities to increase our capacity and improve customer satisfaction.
In addition, AI has the potential to drastically reduce costs and errors in compliance. Therefore, it is our duty to create and manage a digital innovation ecosystem that cultivates and incorporates those technologies.
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