Many of us are still relatively sheltered from the world of Big Data, regardless of how much we may gripe about how many emails clog our inboxes.

Compare that fairly common perspective with that of an energy grid operator who measures and meters power consumption for millions of homes, or perhaps a local Department of Transportation and their efforts to maximize toll revenue, while minimizing traffic and congestion.

Between the people, processes, and systems involved in the world of critical infrastructure, and the volume of data generated, it quickly becomes apparent just how massive the challenge can be, and how enticing the opportunity is.

According to Aberdeen Group’s recent 2015 Business Analytics survey, organizations in the public sector are driven toward a more formal data management and analytical strategy for three main reasons:

  • Data is too spread out and inaccessible. The complexity of data inherent to this industry would be daunting to even the most data-savvy and technically advanced. Energy and infrastructure organizations manage a bevy of information, from traditional structure application-generated data to potentially thousands of individual devices spewing out real-time sensor data. It can be hard enough to simply access the necessary data, let alone do anything useful with it.
  • Competitively, analytics is no longer a “nice to have.” The world of business intelligence and analytics has evolved quickly, if somewhat predictably. Where the occasional canned report or dashboard was once sufficient, companies are now looking to get more active in the analytical process. Moreover, that level of increased activity and engagement would have once been a competitive advantage for companies, but now is considered table stakes (at least in the public sector).  These organizations are driven to analytics to simply remain competitive, rather than surpassing the competition.
  • People are clamoring for better decision support. As the complexion of analytical technology has evolved, so has the usage of the technology. Once reserved for IT staff and those close to the data, analytical activity has seeped into more job roles and departments within the typical organization. Public sector organizations cite a growing demand for analytics in their workforce as a top driver of its implementation.

In the face of these pressures, it’s easy to see why organizations in the energy and infrastructure sectors are drawn to analytics.  These tools and processes empower companies to sift through mountains of data and find the proverbial “needle in the haystack” of insight that can become game-changing. Prior Aberdeen research demonstrates why an effective analytical strategy is so enticing for these organizations:

Data -> Insight -> Execution

Companies may experience explosive growth in data, but the value of that data is gated by their ability to explore and discover the insights hidden within. Those using analytics in the critical infrastructure sector saw a marked improvement in searchable business data, helping to uncover new opportunities for growth and efficiency, and ultimately leading to improved revenue and operating profit.

Conclusion and Recommendations

When looking at the core organizations that make up energy and infrastructure, one would be hard-pressed to find companies more beholden to data, either as the proverbial albatross around their neck or the pot of gold at the end of the rainbow. The road to analytical nirvana is paved with clean, usable data. While the specific direction of that path varies from company to company, those exploring business analytics should consider the following recommendations.

Turn the challenge into an opportunity

A major distinguishing characteristic of analytically driven organizations is their formalization of a data strategy. Sixty-three percent (63%) of analytics users have adopted a long-term strategy or roadmap for capturing and managing the influx of operational data as their top strategic action. Companies that prioritize their data, the ways they manage and cleanse it, and how they facilitate its delivery, will be well-positioned to succeed with business analytics.

Beware of analytical “shelfware”

Aside from the dangers of inaccessible or poor-quality data, the biggest barrier to effective business analytics is underutilization. Many organizations in the energy and infrastructure sectors have significant analytical or data management skill sets residing in-house. But that doesn’t mean that any solution can be simply thrown at them without consideration of their specific needs. The research shows that analytics users are more than twice as likely as their peers to establish a process to gather and incorporate end-user needs and requirements into their analytical implementation.

Capture fast, analyze faster

According to the research, 75% of critical infrastructure organizations require information within the day or faster, in order to make critical decisions, and 28% need information in real time or near-real time. While the promised land of real-time analysis and decision-making may be a pipe dream for some, the point stands that the faster one captures information, the quicker a critical decision can be made. Analytics users start the data transformation as quickly as possible in order to get to a point of decision more rapidly.

For more information, explore the full report here, available 100% free of charge for registered Aberdeen community members: Allocation and Optimization: ERP and BI Team up in the Public Sector.

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