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Realizing your investment in Technology through Analytics

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Paul Fratellone's picture
Director Software Products, Tesco

Paul Fratellone’s career in quality assurance and product management began in the mid-1980s and has spanned multiple industries and domains. Through the years, Paul has recognized certain...

  • Member since 2019
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  • Dec 2, 2020

This item is part of the Data Analytics & Intelligence - Winter 2020/21 SPECIAL ISSUE, click here for more

Energy and utility companies are in an unfamiliar territory in which they must integrate alternative energies, expand situational awareness across the system and deepen their relationships with customers. Organizations that want to grow their business are adopting analytics and business intelligence to increase responsiveness, reduce operational costs and improve asset integrity. Business intelligence / analytics are crucial to solving key business problems for all organizations. For utilities, it can turn information from smart meter and smart grid projects into meaningful operational insights and understandings about their customer’s behavior.  

The analytics opportunity for utilities is clear, but there continues to be a lack of real investment to enable this initiative. What is holding utilities back? Many companies have been concerned about the high costs and complexity of data. To reduce those concerns, organizations simply need to take a structured approach. This change begins with a realistic review of their analytics maturity levels: where they want to get to, and what they want to achieve. That framework gives a baseline for key investments and initiatives. Utilities can then identify the right data sets and the smart systems they need, invest in the right skills and put in place the right data governance model. Within this structured approach, utilities should be on the side of pragmatism. 

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By using the data already in their possession, utilities can see comprehensive information about each of their assets, such as rejected shipments, RMA devices, installation history, and maintenance records. This information can be combined in new ways with other conditional data to provide insights to help improve purchasing, planning, operations and maintenance practices. If a certain meter form/program ID and firmware version combinations are proving to be more problematic versus other combinations, a utility will investigate this further as to what is the root cause and not purchase or install these devices in such a way. Such innovations will help utilities shift from traditional and costly time-based asset management, where network repairs are done on schedule regardless of how much useful life is left in an asset, to a more informed reliability-based approach of making repairs when they are actually needed. Moreover a coordinated cross-enterprise vision can help reduce IT costs. Utilities are finding new uses for the data they are collecting as they expand the data received across the enterprise. This data is enabling utilties to roll fewer trucks for emergencies as well as early identification of potential weak spots in the infrastructure. 

The data is allowing utilities to perform increased reliability in purchases as well as the long term planning for maintenance. The data gives them the tools to predict, measure, and identify inefficient and ineffective operations, in a meaningful and actionable way. 

With AMI Devices, utilities are made privy to problems they never would have been able to identify in the past. The faster data can be analyzed and an actionable event created, the greater the potential for revenue recovery or loss prevention.

Matt Chester's picture
Matt Chester on Dec 2, 2020

With AMI Devices, utilities are made privy to problems they never would have been able to identify in the past. The faster data can be analyzed and an actionable event created, the greater the potential for revenue recovery or loss prevention.

How quick is the process from identification to solving? I assume those are still pretty manual processes, right? 

Paul Fratellone's picture
Paul Fratellone on Dec 14, 2020


Thanks for your inquiry. Trying to wrap up 2020 on a good note, 

It depends on the appetite to invest in a an analytics engine. There are many to choose from, but for those with small pockets, they can get their feet wet by doing some rudimentary data analysis on the data they already possess. So yes, without a platform there would be more manual efforts to slice the data.  



Paul Fratellone's picture
Thank Paul for the Post!
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