Is Big Data the Next Next Thing?
The â€˜Next Big Thing.â€™ Itâ€™s the latest trend, the newest technology or product. Itâ€™s what everyoneâ€™s talking about.
But here at Smart Grid News we couldnâ€™t help wondering during this prediction-packed beginning of a new year: Whatâ€™s coming after the Next Big Thing? That new or evolving smart grid wrinkle, development, technology, concept thatâ€™s waiting just over the horizon where we canâ€™t see it yet. The Next Next Thing.
The Next Big Thing is already here. The Next Next Thing is still a mystery.
So we asked professionals working in the smart grid industry to help solve the mystery and weigh in on what could be the Next Next Thing. We gave them some suggested clues to work with but nothing more. We also gave them free rein to take their own approach. The result? Interesting and insightful observations on a number of possibilities for the Next Next Thing series of articles weâ€™re launching now.
By Doug Peeples
Of the several areas we suggested, Big Data attracted the most attention. As one of our series respondents observed, the smart grid industry has done a great job of creating the technology to gather massive amounts of data, but managing it well and wringing the most out of it remain challenging. In the first article of our Next Next Thing series, you will get a broad range of perspectives on what industry professionals believe are the rough spots, the best ways for utilities to take advantage of Big Data and where it will provide the most value.
Tom Osterhus, Integral Analytics CEO, laid out the current Big Data dilemma clearly. â€œOne of the reasons utilities are so slow to adopt innovations in this space is that they continue to think in terms of the overall system. IT staff feel that any innovation needs to conform to the overall corporate IT infrastructure, and so small, quick proof of concept innovations about how using this data to yield significant operational results is lost in the bureaucracy.â€ The problem, he says, is that utilities tend to concentrate on IT/OT security, data integrity and integration far too soon â€“ and that makes it harder to test winning applications , and harder to decide what to integrate after that. â€œAs such, we see many Big Data discussions merely discussions of IT infrastructure, and no discussion of business value or need.â€
Comverge CEO R. Blake Young further explains the challenges. â€œItâ€™s no secret that utilities today are faced with the dilemma of how to turn big data into actionable insights. Theyâ€™re focused on collecting vast amounts of data from all aspects of energy use â€“ including sizes of homes and customer usage patterns â€“ in hopes that they can learn from the past. Today, our customers area also now using data specific to demand response programs â€“ such as the correlation between weather and opt-outs â€“ and to better forecast load drop and improve the performance of control events.â€
Kim Getgen, marketing VP for Tollgrade Communications, believes the major difference between the â€œold dataâ€ and todayâ€™s â€œBig Dataâ€ is now weâ€™re beginning to see â€˜near real-timeâ€™ information that presents utilities with several ways to deal with problems and communicate with customers. â€œThis is not about software, but more about business process transformation and improvement. How will utilities capitalize on this data to gain competitive advantages, take costs out of their business, operate more profitably and improve customer service? We are beginning to see the value of â€˜Near Real-Time Big Dataâ€™ can provide.
â€œWatch out. It could be addictive.â€
Steve Jones, VP for product management at Pulse Energy, gives utilities more credit for moving quickly on Big Data. â€œThe amount of data that utilities are collecting is still small in comparison to what is being done in other industries such as geological surveys, Internet search and scientific research. Whatâ€™s notable with utilities is how quickly they are transforming to embrace Big Data. We recommend that utilities start leveraging this data by focusing on a handful of specific applications that can deliver immediate value. The application we are most excited about is helping utilities to better understand and engage with their commercial customers. Through benchmarking, load disaggregation and other analytics, we are enabling utilities to use their Big Data to improve the depth of their relationship with their commercial customers.â€
***image10***For David Meyers, VP of sales for DC Systems, the key to successful mastery of Big Data lies in utilities asserting more control over the acquisition, communication and management of real-time data from the field. â€œAs long as the data are byproducts of whatever the melting pot of field devices happens to provide rather than of a thoughtful, integrated data management effort, even the most advanced utilities will struggle to reap the benefits of Big Data analytics techniques.â€
Doug McCall, marketing director for Sensus, seconded Big Dataâ€™s important role in outage management and response. â€œWith Mother Nature continuing to disrupt our infrastructures, itâ€™s vital that utilities adopt resilient communications networks. Think about tornadoes, hurricanes or floods. Make sure you have back-up generation so that in a natural disaster, you have power and the technology to soften the blow.
â€œElectric, water and gas utilities can collect and access real-time data from various smart sensors that provide a critical view of a utilityâ€™s infrastructure. Itâ€™s this access to system status before, during and after a storm that helps utilities restore services faster and avoid additional damage.â€
Tim Wolf, Itron marketing director, sums up much of the thinking from the other contributors. â€œAs an industry, weâ€™ve done a great job of innovating and developing the technology to gather data and apply it to transform billing and revenue cycle services. Our challenge now is to manage it effectively and put it to work to drive better operating and business decisions.â€ He also observes that some Big Data analysis is relatively straightforward, and as an example cites interval data that gives utilities more insight into demand forecasting and load shedding. In other instances, much more in-depth analysis is necessary. He explains that a meter tamper alert may not be all that useful by itself, but is much more valuable when integrated with load data, transformer metering, account billing history and utility field service dispatch information. The result? The ability to pinpoint possible energy theft with a lot more precision.
In his opinion, utilities can avoid much of their struggling if they follow this strategy: â€œIn terms of time-to-value, more focused analytics solutions, pre-integrated with meter data management systems and addressing specific utility-business problems is likely the more efficient route to value and results.â€
There you have it. Itâ€™s fairly easy to see why so many in the smart grid industry are so concerned about Big Data and the best, most cost-effective approach to managing it and extracting the most value possible. And itâ€™s just as easy to see why Big Data could be the Next Next Thing.