Is 2012 Year of Analytics for the Utility Industry?

As we all get back into the flow of things after the Thanksgiving holiday break, it's not only a good time to give thanks for our work, family and friends. It's also a time to reflect on the developments in the energy industry to date and consider what the current trend lines look like for the next year. There has been a lot of press coverage over the torrent of data that is going to be spewing out from the smart meters and the Smart Grid investments - several issues have been listed by various analysts that the utility management have to wrestle with as a result of this projected data flood: cyber security, customer data privacy, data storage, customer backlash, lack of analytics to derive useful insights from the data and general lack of preparedness to deal with the data issues.

Since many of these projects are still not fully executed, I think it's somewhat premature to sound the doomsday scenario. Still, it's never too early to consider what a utility company would like to get from the new data streams and plan out actions each utility can take to ensure it's collecting the right amount of data and putting in place a suitable system to track and generate actionable analytics from such data. Collect too much data and you end up drowning in data without being able to gain any useful insights. Collect too little and you end up not getting full value for the investment.

Along with the decisions on the right amount of data to collect and hold - these would be necessarily driven by the insights desired: if one is looking to generate more granular load curves, then that would dictate the frequency at which the data need to be collected and analyzed. On the other hand, if one is looking to verify the impacts of DSM programs [DR, EE, or renewables], then a different frequency would be indicated.

So, as each utility begins to wrap up this year's activities and start their plans for the upcoming year, we think they should devote a good chunk of time to address the data issues along with the analytics they are interested in deriving from the data.