Utilities need to take a few things into account before they can extract value out of their data.
We’ve all heard it; data is the new oil. It’s valuable. It’s a differentiator. Like crude oil, it needs to be extracted, cleaned-up, and processed. And for the utility industry, there is certainly no shortage of companies that construct rigging and analytic tools to help pump data from the smart grid.
As the old saying goes, when a new technology trend emerges, you can mine for gold or you can sell pick-axes.
But, as Bernard Marr wrote recently in Forbes, “while oil is a finite resource, data is effectively infinitely durable and reusable. This means that treating it like oil – hoarding it and storing it in siloes, has little benefit and reduces its usefulness.”
Honestly, if you’re loading voltage sensor data into a metaphorical tanker truck, driving it back to the utility data center, and dumping it in a data lake, you are not doing this thing right.
Is there a better way to calculate the Value of Data?
There is no shortage of confusion about how to demonstrate a return on investment from a data project. But that’s not the extent of the problem. In the utility industry, there is no consensus for how to give data a valuation—opportunity is surely being left on the table as leadership grapples with direct data monetization, driving new investments, or even in merger and acquisition activity.
Data may be the new enabler of value, but when we treat it as a scarce resource like oil, we may be miscalculating utility assets and liabilities, as well as discounting new business.
Ironically, the utility may have a head start in valuing new commodities by learning how to accommodate distributed energy resources. Now that data-producing sensors and devices are plentiful in the field and as costs for data analytics hardware, data processing, and integration decrease, the economic proposition for data will also have to adapt.
Utility data is abundant like wind and sunshine, not scarce like oil
If we drive the metaphor of oil into utility data valuation models, we run right over the vision of the smart grid. This is a vision which has never been one of scarcity, but generativity. Data is not a single-use resource—it can be analyzed, envisioned, and communicated in many ways, over and over. The same data that measures grid behaviors in one condition, could inspire an entirely new proposition.
Utilities that wish to increase their future potential will explore, integrate, and implement new services based on data that can co-create value for electricity customers and the utility alike.
The concept of the smart grid grows ever more expansive with new technologies, and the side effects created by the impact of data analytics complicates traditional valuation models—new issues and opportunities emerge from making interconnections among old approaches. The more innovation we bring to analyzing the smart grid, the less order and predictability there are in calculating its value.
Data as a Resource
This dynamism and rapid change underscores why it’s important to begin thinking in earnest about how the utility can better articulate the contribution that data contributes to the overall value of the enterprise and operations. And where unique forms of data—such as that from the smart grid—can transform the utility in partnerships and other positive investment outcomes.
The lack of ability to prognosticate the costs and calculate value to build a smarter grid has brought utility executives plenty of confusion. Data management and analytics are already one of the most challenging tasks for the utility, especially in scaling to the massive levels required to handle the sheer preponderance of existing and anticipated forms of data.
Further, utilities (especially those that generate) that are concerned with the prospect of diminishing profits as a direct effect of smart grid–enabled demand-response initiatives and operational efficiencies, must deploy new thinking into how the benefits of smart grids (and their data emissions) can be converted into revenue.
While valuing improved revenue protection and reducing asset maintenance and replacement costs are straightforward, other functions such as assessments and improved planning are just not as clear-cut. With average utility investments in the smart grid rising to very significant levels over the next decade, many stakeholders expect a rapid return on investment (ROI). But the shape of that return may be unexpected, missed or overlooked.
Taking current approaches, utilities that deploy a scarcity model of value to their data are likely to be as limited in their thinking about new business prospects; especially if they think only in very traditional ways about the value of data in terms of risk reduction or capital expenditure.
Recognizing the desired level of return from a fully-fledged smart grid data analytics program requires a shift in how utilities calculate value. In much the same way that the utility adapted its financial models which evaluate the costs and benefits of grid-connected PV to the electricity system, data also be an enterprise resource. Like sunshine, an abundance of data can bring new forms of flexibility to the modernized utility. It just has to be treated as such.