Data Analytics And Utility Industry's Seismic Shift

Guerry Waters, VP, Industry Strategy, Oracle Utilities
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Guerry Waters, VP, Industry Strategy, Oracle Utilities

Guerry Waters, VP, Industry Strategy, Oracle Utilities

There is a seismic shift occurring in the utilities industry. Far beyond the technology evolution, a fundamental industry transformation is beginning to occur, a cultural shift in which utilities are altering their thinking about data and analytics, and the ways in which both might be more useful to the enterprise as a whole. The goal: a new utility structure capable of meeting the twenty-first century needs and demands of its enlightened customers.

Terabytes of new data streaming in from many different sources has forced utilities to re-examine how they look at information strategy, operational structure and customer engagement, as well as their abilities as an enterprise to cope with change and take a more holistic, enterprise-wide approach to optimizing the new data flow. As operational processes and tools within the grid have increased and matured, so too has the amount of data being collected and the expectations of analytics capabilities evolved. Where once utilities could only analyze data on an ad hoc, hands-on basis through white boards, complex spreadsheets and business intelligence (BI) reports, the industry is now moving to a clearer reactive analysis (both descriptive and diagnostic) incorporating a much higher volume of historical data, with more complexity, and analyzing it much more quickly.

A proactive cultural shift
Knowing what to look for, utilities can also yield insights from real-time information streams. Finally, with historical and realtime data at hand, utilities are also beginning to look forward with predictive and prescriptive analytics, creating real value to proactively mitigate potential operational problems before they arise.

By using analytics, utilities are better able to improve customer satisfaction through segmentation and communication personalization; improve operational reliability through monitoring and predictive maintenance; and expand operational efficiencies through improved planning and execution.

And there are other benefits to using analytics, too. Across industries, studies by MIT and Nucleus Research have found the following to be true:

• Top performers are three times more likely to use analytics than low performers.
• 53 percent use analytics to drive strategy.
• 50 percent use analytics to transform daily operations.
• Organizations that use analytics get $10.66 for every $1 they spend on analytics.

Throughout the business, the new data offers distinct opportunities to drive increased operational efficiency and reliability, improved customer service, and greatly enhanced customer relationships. It also offers utilities distinct opportunities to drive better and more efficient operations and maintenance spending, including predictive maintenance rather than runto- failure operations, load forecasting and balancing, asset optimization and failure analysis, better economies of scale, and more.

By operationalizing analytics— bringing analytics back into business processes and into transactional and operational systems and processes— utilities can better optimize expenditures and cut unnecessary costs to create a more responsive, proactive enterprise.

Challenges driving need for change

Today's utility faces complex challenges to its mandate of delivering an affordable product (electricity, gas or water) to its customers reliably, cleanly and safely.

You can imagine these challenges as five cogs that engage to run the business: Infrastructure Transformation, Customer Relationships, Demand Management, Revenue and Profitability, and Environmental and Regulatory Requirements. Additionally, each of these "cogs" interacts in a complex fashion with the rest, continually changing the operating equation.

For example, as many utilities complete their advanced metering infrastructure (AMI) deployments and begin to bring more frequent interval data back to the enterprise to better feed transactional applications such as the customer information system, customer care and billing, and operational applications such as the network management system (NMS), they are also adopting more informed, proactive and interactive operations and customer service roles. This reflects customers' expectations that their utilities will benchmark their own service against that offered by other service providers such as financial institutions, telecommunications companies, airlines, and retailers.

However, the collection of interval data and events through AMI is not a necessary prerequisite for utilities to begin using analytics to direct datadriven business decisions. Utilities can also make substantial changes today with data from monthly meter reads (automatic or manual); supervisory control and data acquisition (SCADA), geographic information systems (GIS), and other grid sensor data, as well as third-party weather and forecasting data, or data and feedback generated by customers from various communication channels (including web, mobile and social traffic).

Utility companies are continuously focused on replacing an ageing infrastructure while often under severe economic constraints that not only can negatively affect the utilities themselves, but also their customers, who are similarly trying to do more with less and keep their own costs down. In addition, changing environmental and regulatory requirements—lower carbon emissions, more renewable energy, ever-increasing reliability even in the face of severe storms, and better reporting standards, to name but a few—have utilities turning to new tools with increased flexibility in order to be able to increase both operational efficiency and customer satisfaction. Data analytics can assist.

Identifying analytics opportunities

Beyond the overall need to utilize the new data available to improve the utility's enterprise capabilities, companies' specific data analytics needs and approaches are as individual as the utility itself. Operational reporting and tracking of key performance indicators are a must, of course. Beyond this, there are a number of key opportunities in which analytics can play a pivotal role in improving a utility's overall focus on its mandate.

Here are a few:
• Improved customer satisfaction through segmentation and communication personalization.
• Improved reliability through monitoring and proactive maintenance.
• Improved operational efficiencies through better planning and execution.
• Improved safety through understanding and mitigating risks.

From meter operations, billing support and call center support to revenue protection, demand- side management and distribution operations and planning, analytics offers utilities abundant opportunities to better manage their businesses, and their customer relationships, across the enterprise.

To take advantage of these opportunities, utilities must begin to pick up the pace of their big data usage to engender a new culture of data-driven decision-making.

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