Breaking Down the Buzz about Big Data

Electricity
General Energy
Breaking Down the Buzz about Big Data

Breaking Down the Buzz about Big Data

November 13, 2012

By Ben Holland

“I feel so trendy. Now I can say I spoke on a ‘big data’ panel!”
—Matt Eggers, VP of operations, SunRun, speaking at SXSW ECO

“Big data” is the buzzword du jour in the energy efficiency world. That’s right, “smart grid” is losing its title as the little understood, least agreed upon term that everyone loves to use. But that is not to say that such concepts are without merit. In fact, one would be foolish to discount their importance.

In the tech community, the concept of big data is nearly passé. Once the domain of niche IT and tech blogs, big data has exploded into an emerging industry in itself. According to the SXSW Interactive PanelPicker, over 180 proposals addressing the subject were submitted for March 2013 session. In that world, big data as a concept or business opportunity is quickly rounding the “Peak of Inflated Expectations,” coined in Gartner’s Hype Cycle.

"Big However, for utilities, smart grid startups, and environmentalists alike, this offers a new and very real opportunity for improving efficiency and integrating renewables. So what do we mean when we talk about big data?

Big data is often described as the challenge of managing massive sets of fast-moving data from disparate sources—volume, velocity, and variety are the key attributes most cited. In its early use, the term was often referenced in conversations about online buying behavior—consumer purchases on Amazon, for instance.

A few years ago, entrepreneurs began to recognize opportunities arising from our online behavior. And in response, they built applications to help database managers to organize and distill this influx of data into clear insights about behavior. (Check out the Harvard Business Review’s recent article for a full history.) With the rise of social networks, mobile phones, and location-based applications, big data as a business term has risen to near ubiquity. After all, every click, search, or comment users post leaves behind a trail of data.

As more businesses and entrepreneurs harness the potential to better manage these massive data sets, not only can they understand behavior and preferences but can predict or influence those behaviors. Whether selling products or seeking votes for a presidential candidate, this is extremely valuable information. In the highly connected world in which we live, businesses are competing to collect high quality insights about consumer preferences, sentiment, and purchasing habits.

The energy space is just as rich in data and opportunities to predict behavior. With the advancement of technology, nearly every thing we do that uses energy will generate a stream of data, whether it’s running an air conditioner, charging an electric car, or generating power with a solar panel. For electric utilities, that data can be hugely valuable for predicting future generation needs, balancing renewable energy loads, or suggesting measures to consumers for reducing energy use. Access to this data is already enabling entrepreneurs, software engineers, and app developers to create new services. Consumers interested in tracking and managing their energy use can remotely turn off lights, set their thermostats, or time the charging of their electric car.

Individual behavior has been one of the biggest black holes of information. Take buildings, for example. Efficiency measures like those implemented in the Empire State Building retrofit have had considerable success. However, the behaviors and habits of individuals and tenants—and, most importantly their impact on total energy use—remain difficult to collect, analyze and manage.

“Up to 60 percent of energy use in buildings is for plug loads—all the appliances, chargers, and other things you plug in the wall,” said Michael Bendewald, an RMI consultant. “Managing this form of energy use is not so simple as the others, because it often requires occupants to act differently.”

"Big Energy efficiency and smart grid companies have attempted to tackle these challenges. OPower and Simple Energy are two companies that have garnered attention for their customer engagement platforms, which compare users to their peers and make efficiency recommendations based on their energy consumption.

Another newer company, Bidgley, which recently raised $3 million in venture capital funding from Khosla Ventures, claims to offer a product capable of accurately measuring energy consumption associated with specific appliances that would otherwise be impossible to track without sub meters or other expensive hardware. Companies like Bidgley promise to replace the need to integrate appliance or “plug” level sensors with data analytics and thus create information about energy use from data at much lower price and with much greater flexibility.

The transportation space is seeing a similar shift. In-vehicle communications services like OnStar and Ford Sync are beginning to connect cars to the Internet and to each other, while mobile app developers are providing users with real-time information on mobility options. Aside from the convenience these advancements may provide, they more importantly open up opportunities to improve the sustainability of our transportation choices.

The same kind of data crunching that Amazon uses to recommend books or that Facebook employs to connect long lost friends, could be used by cities or entrepreneurs to serve up potential carpooling partners with similar routes to work or nearby EV charging stations. Or imagine a car that’s linked to the cloud and automatically customizes itself, including the layout of the dashboard’s controls and instrument panels, based on information it receives as you and your phone enter the car. Many, believe once that’s possible, it’s far more likely that consumers will accept car sharing as a viable option.

It’s too early to gauge the impact that big-data business models will have on energy use and efficiency improvements. While improved analytics are always a good thing—and unquestionably valuable to utilities—many of the more lofty predictions set forth by the big-data devout rest on significant assumptions.

Will consumers embrace the more connected, social perception of energy use on which many startups are banking? The success of mobile apps and social networks has led many observers to predict that nearly every other industry will follow suit (“Your car is the next iPhone”).

But it’s hard not to recall Amory Lovins’s statement about what people most want out of their energy—hot showers and cold beer. That being said, if today’s entrepreneurs and startups can harness the power of big-data analytics to provide those services in a cleaner, more efficient manner, than this is one buzzword that might stick.