It is absurd to think that there is a single modernized utility that doesn’t derive some significant value from analyzing data.
Without data and its analysis, it’s impossible to improve customer segmentation for improved demand-response targeting, revenue protection, and the most basic demand forecasting. No system operators could ever hope to maintain their operational intelligence and management of their grid without data analysis. And in the back office, you are sure to find asset and finance managers wrestling with data to help them size the impact of distributed generation effects on revenue.
So, what does it really mean to be data-centric? And how did it become the modern-day mantra for the utility enterprise?
Achievement Unlocked!
Data-centricity (which by the way has its own manifesto) is a term that establishes the position that data should be at the center of the enterprise, and the consumption of it secondary. Very simply, it means that data should be liberated from its applications, and provided as a common resource for the needs that come and go. In that way, the utility’s data becomes the common denominator for all work that is done now and in the future. When that mindset finally takes hold in the utility, you have become data-centric.
Always an asterisk
But paradoxically, a data-centric enterprise ought to rarely be focused on the data, but on solving business and operational problems with the benefit of insights gained from that data.
Data centricity is an odd primary goal for the utilities that have been working over the last decade to generate momentum for data-driven projects. Especially projects that help the organization learn how to put data and data analysis to work in a way that can be applied to future projects. Frankly, it’s even an odd stretch goal: Utilities might consider clamoring a bit less for a paradigmatic mind shift to data centricity and a bit more about improving their ability to generate value for customers.
Data-centricity is an absolute requirement for any utility that wants to recognize investments made in its digital grid. It keeps the utility “heart-healthy.” But a healthy heart is what enables us to enjoy our lives, pumps oxygen to our brains, and allows us to accomplish what we hope to in our lives. It’s crucial, we take care of it if we have any sense, but it’s a means to the ends we desire; not the other way around.
Value lies in…
The truth is, that utilities that are making progress in their goals towards data-centrism are succeeding not because they are focusing on the data, but because they are not. Utilities that claim success with their data programs may be serious about their data collection and scrupulous in maintaining data fidelity, but as a core capability within the enterprise. The most exciting utility big data analytics programs are demonstrating how they are using insights revealed through their data that help explain, predict, and expose hidden opportunities to deliver real-world situational awareness and business results.
There are many case studies for how a utility was able to generate immediate ROI by picking the low-hanging fruit of utility data made available by smart meter or grid sensor data. Don’t get me wrong, these efforts have been a great place to start with understanding the value of data—they have helped build confidence in the role of data analytics with quick results, and created buy-in for big data, establishing its importance to long-range strategic planning.
But, I’m going to go out on a limb here and say that behind the majority of successful smart grid data programs, there was someone who was thinking about the utility’s business goals, not the data lake. This is the person who observes, “If I could solve this problem, we could improve our performance. Where can I get the data the will help me achieve this?” Data-centrism on the other hand creates a different sort of thinking, which is far more difficult to capitalize upon, “Oh wow, check out all this data! I wonder if there is anything cool I can do with it?”
Despite the inner fantasy landscape of every one of us who have promoted grid digitalization over the last two decades (raises hand), we must acknowledge that the push for a data-driven grid was never going to be as simple as picking up the bits and poof! a more reliable grid. Creating value from data by definition requires access to data, but it also has to be analyzed, communicated appropriately, and well-understood in its application.
Data-centricity may be the technical key to establishing ROI from the colossal investments made in the smart grid, but it is the insight from the strategic use of that data that will lead to the realization of the hoped-for long-term benefits and societal gains.
