Big data analytics should be at the top of every utility’s priority list since they manage networks of devices that are constantly emitting growing streams of data. However, a new report from market watcher, International Data Corporation (IDC), reveals that utilities are uncertain about what they're doing or why they're doing it.
Data analytics – market hype?
Utilities manage widely distributed networks of smart devices, many of which are equipped with telemetry sensors, radio frequency identification (RFID) tags, and remote management and administration facilities. These devices are constantly generating big data. It would therefore make sense that utilities should be investing in some serious data analytics solutions.
IDC’s study, The Maturity of Analytics Strategies in the Utility Industry, shows that utilities are undertaking big-data-oriented initiatives or pilot projects but that more than a few admit they are unsure about what they're doing or why they're doing it.
"Conversations with utilities continue to indicate a significant amount of uncertainty about the drivers for big data analytics, key success factors, and how to leverage internal expertise, [as well as] how to direct an initiative," IDC says. "While a rapidly growing volume of incoming data is certainly a strong motivator for some utilities, other utilities are simply reacting to market hype, and jumping on what they perceive as a bandwagon."
Fence-sitting utilities are delaying big data analytics progress
In the utility vertical, early adopters of big data analytic technologies tend to be proactive. IDC notes that some are already partnering with consultants or integrators, both to help them develop big data analytic programs and to identify potential applications and cultivate expertise. Fence-sitters are content to wait until the hype is over.
IDC notes that fence-sitters "are intentionally delaying the [big data analytic] technology component pending progress in other dimensions of their analytics maturity."
Many utilities don't yet have their decision-support houses in order. From this perspective, big data analytics -- with its new (and largely unfamiliar) skill requirements, its tolerance of (and preference for, in some cases) semi-structured or multi-structured data-types, and its far-from-commoditized technology stack -- could be seen as a distraction.
A common best practice in any emerging technology area is to identify a limited number of applications, for instance, low-hanging fruit, such as a Hadoop-based data landing zone, or clearly defined projects (perhaps with more complex requirements) that could deliver high-value returns quickly -- and to focus on developing these. IDC says this is just what most big data adopters in the utility industry are actually doing.
The report also indicates that utilities should look at the telecommunications industry which, in addition to presenting structural and business similarities to the utility industry, has some worthy examples of analytics leadership.