Hyperautomation: from data to fully connected processes
Utility companies have always led the way in managing, learning from and protecting data. From handling millions of customer accounts to managing the transmission and distribution of power across complex, utility companies understand good data practice. Now it’s time to take the next step. It’s time to move beyond data and data mining and explore how we can mine the processes behind data generation.
To do so, we must ask how continually monitoring and measuring performance across multiple processes can help us take operational efficiency and customer experience to another level. In short, it’s time to ask how hyperautomation (extreme automation involving robotics and artificial intelligence) can help utilities achieve greater efficiency and responsiveness, along with ever-higher levels of sustainability and customer satisfaction.
Before looking to the future of utilities, it is useful to reflect on some of the major changes we have seen in recent years in data management, operational execution and cultural shift – because these changes form the context for the ever-more ambitious plans to place intelligence and automation at the core of energy and utility businesses.
The context for change
Over the last fifteen years or so, all areas of business have been talking about the importance of breaking out of silos. This is certainly true of utilities, where the interdependencies between the once-discrete operational units of generation, distribution, domestic and commercial sales, billing and compliance are now being recognized. Breaking down barriers between silos is also strongly driven by technology, legislative and cultural change. The grid has been changed forever by the emergence of renewables and pursuit of a net-zero agenda. The renewable revolution extends to local generation and the growth of “prosumerism.” The management of low-voltage networks and the distribution of network intelligence to the sub-station, home and business is now the reality — with smart meters playing a key role.
All this change is made even more turbulent by market liberalization that empowers customers to switch at will, and also by people’s expectations. When every customer is accustomed to
a world of apps and smartphones, personalized contracts and micro-control become the norm. Put all this together and the conditions are perfect for the next step in digitally-enabled operations – the shift to hyperautomation.
It’s time to move beyond data and data mining and explore how we can mine the processes behind data generation.
I always try to think of hyperautomation in terms of outcomes rather than technologies. The technology challenges are enormous, and the skills needed to derive reliable and accurate information from multiple, non-integrated technology platforms are highly specialized.
Back to outcomes. When we begin to create a fully interconnected mesh of processes through hyperautomation, AI and robotics, we can expect two basic benefits to emerge:
- Continual and incremental automated improvementWith interconnected and highly-automated processes, we can expect systems and processes to self-adapt. The degree of success will depend, in part, on the skill with which robotic process automation (RPA) is developed and applied.For example, if a smart meter shows anomalies in domestic consumption and the account holder is registered as a vulnerable person, the investigation and resolution process (whether remote or on-site) should be automatically prioritized and triggered.
- Provision of actionable intelligence for expert considerationIf hyperautomation can deliver solutions and improvements without any human intervention or decision-making, so much the better. However, the intelligence revealed through hyperautomation is also hugely valuable in supporting executive and strategic decision making. With every intervention, AI and machine learning will feed back into a cycle of continuous improvement.
Our readers will know that discerning meaningful patterns in energy fraud can be notoriously difficult. When hyperautomation begins to integrate usage and account data with new data from low-voltage grids, fraud patterns can be revealed and made available for consideration and action.
Where do we go from here?
Although hyperautomation is in its infancy, we are already beginning to see the impact, not only in terms of operational improvement, but also in client expectations for actionable business intelligence.
For the last few years, the operational efficiency of many utility companies has lagged behind innovation in customer engagement. In short, the front office has been smarter than the back office.
This can be risky in terms of business reputation. The apps you offer your customers may be shiny and attractive, but unless you can deliver on the expectations you create, disillusion could soon set in.
My team of hyperautomation experts is currently focused on resolving this mismatch, and we are not doing it alone. The ability to co-author solutions with the right specialist partners has always been our hallmark. We are working with both Appian and Celonis, and we’re especially pleased to see how their relationship is paying dividends in hyperautomation and process mining.
With RPA taking a central role in these initiatives, we are also building strong relationships and know-how with RPA market leaders, UiPath and Blue Prism.
Energy and utility companies are becoming increasingly articulated, which means that the breadth and range of processes that underpin their businesses are continually expanding.
For Atos, the ability to continually examine the relationships between processes and explore opportunities for learning and improvement is of paramount importance.
We are keen to share our growing pool of experience and are already building a hyperautomation reference repository. While we will always respect the confidentiality of our projects with individual clients, it is in everyone’s interest to share best practices and —whenever possible — accelerate adoption by drawing on our collective experience and achievement.