The massive rivers of data streaming off of the smart grid can be used for multiple purposes. They can lead to more effective business, customer, and operational decision-making. But information graphics are often misused by visual enthusiasts who combine complex data with ornamentation. If those tendencies penetrate the utility industry, we may be in for infrastructure challenges of epic proportions.
In his seminal work, The Visual Display of Quantitative Information, Edward Tufte described what he called “chartjunk”:
The interior decoration of graphics generates a lot of ink that does not tell the viewer anything new. The purpose of decoration varies — to make the graphic appear more scientific and precise, to enliven the display, to give the designer an opportunity to exercise artistic skills. Regardless of its cause, it is all non-data-ink or redundant data-ink, and it is often “chartjunk.”
The biggest danger with chartjunk is not only that it is often downright silly, but that what is trying to be informative may instead be misleading or totally devoid of meaning.
In an earlier blog on SmartGridNews.com, titled “Smart grid data analytics in the real world,” I talked about the dangers for operational decision-making and fatigue if mental models don’t align with the information that is being conveyed. But smart grid data analytics holds hazards for business stakeholders as well. In a related example, the Harvard Business Review recently described marketing-oriented “data hounds” as dangerously distractible.
Helping consumers save energy, with targeted programs based on consumption information combined with detailed marketing information, could be among the biggest wins for utilities in driving ROI from their smart meter investments. With consumer behavior changing so quickly, though, manipulating dials and chasing bright shiny lights could divert utilities from their key strategic goals. The analyst who buries her head in a data dashboard is likely to miss the big picture, erratically changing direction and wreaking havoc in the organization by zigzagging from decision point to decision point.
Utilities have new opportunities to use advanced analytics to help secure our energy supply by personalizing the delivery of energy. But it’s critical to remember that the people who use the systems matter as much, if not more, than the systems themselves. New opportunities in data analysis will drive better decision making, but the business goals must be paramount. In fact, most program managers will likely underuse data in creating new programs in the initial stages of data availability. Utilities looking to improve their data analytics capabilities are advised to consider that top performers are those who not only own a statistics book, but are able to filter out the noise that might prevent them from accomplishing their strategic goals.