Atos: The Data-driven Utility, focus on customers and operations
Most days we see AI and data analytics featuring in mainstream media stories: these themes are no longer buried in technical and academic domains. Over the last twenty-five years, I have rarely seen a technology theme adopted in the utility sector with such enthusiasm – or indeed with such speed.
As always, when a technology topic hits the headlines, we need to look beyond the hyperbole and explore the actual implications. We need to ask what constitutes a data-driven utility and what is the most direct route to making the benefits a reality.Intelligence: macro and micro
Right across the utility sector, we are witnessing extraordinary change: the accelerated rise of renewables and the corresponding decline in fossil fuels; the emergence of grid intelligence; the rise of storage and electric vehicles; the disruption of deregulation; and the social changes amongst customers whose expectations have been radically altered by digital behavior.
There is a real interdependence between these changes and digital innovation: solar in itself, for example, can happen without digital. But solar as a contributory part of a balanced grid can only happen if we can capture and manage the associated data.
We can look at the intelligence which underpins the data-driven utility from both macro and micro perspectives.
In the world of data-driven utilities, we are able to build complex, accurate and agile pictures of mass demand, usage and trend. These big pictures don’t just guide development and investment strategies for utilities. They also underpin our wider social and industrial responsibilities to sustainability and the environment.
The data-driven utility can also drill-down into the micro with more precision and granularity than ever before. Relationships with individual domestic and commercial customers can now be crafted according to individual patterns of usage and payment preferences. This micro view is, of course, influenced by the emergence of smart devices, the IoT, and always-on communication.A dual focus on customers and operations
Over the last eighteen months or so, in discussions with clients, I have seen two distinct focus areas emerge in relation to the data-driven utility. We ask how a data-driven approach can help:
- Build more responsive, more enduring and more mutually beneficial relationships with customers – both domestic and commercial
- Optimize operational efficiency and performance, with ever-greater emphasis on agility and cost-effectiveness
Regarding customer-relationships, utilities need to understand individual customer behavior and, even more importantly, know how to add value in terms of service and responsiveness. If, for example, a customer covers thousands of kilometers a week in an electric vehicle, how can the utility offer benefit in terms of cost and convenience of re-charging?
In terms of operational agility and cost-efficiency, we may, for example, look at how to combine complex streams of IoT data with job-planning systems and mobile applications. A data-driven utility helps field service engineers step away from book-schedules and refocus on priority-driven and pre-emptive service intervention. This data-driven transformation is also particularly evident in asset lifecycle management based on predictive maintenance using industrial data analytics.Data transformation: volume, timeliness and automation
In both customer relationships and operations, the new digital landscape is fuelled by actionable intelligence. Intelligence in a data-driven utility is fundamentally different from the data we relied on just a few years ago:
- Volume – the volume of data available to today’s utilities far exceeds anything known in the past. Utilities are also continually looking beyond the data they own: it’s not just meter-readings any more – it’s open data exchange with smart buildings, smart cities, etc.
- Timeliness – data is increasingly real-time. Because data-driven utilities know what’s happening in the moment, they can and must operate with ever-increasing agility. The need, for example, to balance nuclear and renewables means managing the switch in minutes not months.
- Automation – the range, volume and immediacy of data cannot be managed without automation. A smart washing machine, for example, needs to communicate with the grid to decide on the optimal turn-on time – the householder does not want a text reminder to press “start” at three in the morning.
So what are the technology enablers behind this transformation to the data-driven utility?
The new digital horizons in the utility sector are formed by the ability to generate, store and process data in all its forms. The IoT, with all its associated technologies is central not only to managing assets owned by the utility company; it also impacts interaction across an ecosystem of smart buildings, smart devices, smart cities and smart transport systems.
New computing models especially edge and swarm computing, also gain importance. Distributed grids and mixed generation models dominated by renewables can only be fully efficient when they are supported through distributed computing capabilities.
And of course analytics and AI, because without the ability to analyze and act on data, there is no point having it. Let’s not forget robotics, because the scale of data-driven activity demands both machine learning and massive automation.
In this landscape, co-innovation becomes an essential characteristic – not just between utilities and their technology partners, but across an increasingly interconnected ecosystem. Civic and industrial partnerships, and indeed active relationships with customers, become the foundation for success in data-driven utilities.
This blog is part of the Atos Look Out 2020+ Utilities “From commodities to high-value service providers” where we explore the business opportunities and key technologies which will shape the future of Utilities.
Join us at the European Utility Week #EUW 2018 where we are showcasing solutions central to the new digital landscape for forward-thinking utilities.