Data analytics buying guide part 1: What's in Big Data for you?

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In the electric utility world, Big Data is a Big Deal. Attend just about any industry conference and you’ll hear folks talking about the data deluge swamping utilities as smart grid technologies like smart meters and sensors and Phasor Measurement Units (PMUs) go live.

 

And here's why it's such a big deal: Utilities are starting to use advanced analytics software to turn that data into actionable business intelligence. If market forecasters have it right, the industry is just getting started down that path. Utility spend on data analytics – less than half a billion dollars in North American in 2011 – is expected to swell 29% a year to $2 billion in 2016, according to the Utility Analytics Institute. Worldwide, Pike Research expects cumulative spending on smart grid data analytics to total over $34 billion by 2020.

 

So if exploring data analytics options is on your agenda, this five-part buying guide – created with valuable input from analytics experts at Origin, BRIDGE Energy Group, Space-Time Insight and Opower â€“ is designed to help you get started and know the right questions to ask.

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The saying "be careful what you wish for" may resonate with IT folks in electric utilities who suddenly find themselves on the receiving end of vast quantities of raw data streaming in from smart devices – and who have no clue what they're expected to do with it.

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That's where data analytics enters the picture – or should anyway. In this article we'll highlight benefits and challenges that utilities will discover when they make the decision to drill down on data. And elsewhere in our buying guide, experts will explain:

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·         How to prepare your workplace

·         Where analytics can take you

·         How to manage the procurement process

·         How to measure your progress

 

Like a gold mine

Utility analytics experts will tell you that the volume, velocity and variety of data streaming in from smart meters, transformers and substations are like gold mines waiting to be tapped. They can help you, among other things:

·         Predict equipment failure and outages

·         Forecast financial trends

·         Improve customer relationships

·         Optimize operational efficiencies

·         Identify patterns of revenue leakage and theft

·         Drive energy efficiency and dynamic pricing programs

 

But equally compelling may be the opportunity to dig into data to discover new insights. As BRIDGE Energy Group points out, with advanced analytics software you have the ability to perform strategic 'what if' scenario planning on where capital investments should be made as well as profit/loss planning.

 

The challenge of "social" data

The volumes of data coming into utilities, originating in everything from AMI to social media, are dictating the use of new, more advanced analytics technologies, says Jeremy Oosthuizen of Origin. "Data warehouse principles have largely remained the same for structured data," he says. "But unstructured data from social media challenges traditional data warehouse design, because it – along with what is being measured – can constantly change."

 

Newer technologies, Oosthuizen explains, allow the "mashing up" of data from different sources and easier display of data on maps which allows insights not possible with more basic analytics software.

 

And social media may be just the tip of the iceberg when it comes to the unstructured knowledge enterprises will need to integrate into their data pool. Steve Ehrlich of Space-Time Insight says emails, corporate communications, documents and external Internet-based information sources will also figure in when it comes to "driving corporate objectives around risk awareness, operational effectiveness, customer relationships and resource optimization."

 

Bottom line benefits

There are a lot of different ways to slice and dice analytics – asset optimization, operational effectiveness, customer engagement, etc. – so the return on investment will likely vary depending on the specific initiative.

 

Opower, for instance, has a data-driven customer engagement platform used by more than 75 utility partners and their customers. Carly Baker Llewellyn says the lifetime cost-effectiveness of the program is roughly $0.03/kWh (compared to $.10/kWh for an in-home audit and $.14/kWh for a weatherization program) and it consistently delivers energy savings between 1.5-3.5%.

 

In its big data initiative with Oncor, the largest electric delivery company in Texas, IBM points to a list of benefits. Among them:

·         Oncor now has pinpoint access and insight into billions of data measurement points, from advanced meters and networking devices, to transmission sensors, power lines and generation plants

·         The solution receives data every 15 minutes from Oncor’s currently installed 3 million advanced meters and pushes relevant information to and from Oncor offices and customers' personal, interactive web portals

·         Many Texas households have noted a 10 percent decrease in energy usage since the implementation

·         The new outage management system that automatically reports power issues and outages within seconds, and flags emerging, potential issues in the grid has detected more than 20 percent of outages before customers called

 

In Missouri, Vertex Business Systems implemented a new debt collection strategy applying advanced analytics to collect more outstanding debt from customers of the Metropolitan Sewer District (MSD) in St. Louis. In the initial 10 months of the project, Vertex reports MSD had:

 

·         Collected $8,463,203 within 10 days of the targeted phone calls

·         Achieved a 35.5% payment response rate

·         Seen between a 12-20% reduction in accounts reaching 45,60,90 and 120 days in arrears

·         Seen a 22% reduction in accounts assigned to an agency

 

Still another perspective comes from a Capgemini white paper titled Smart Analytics accelerates the realization of value for utilities, which addresses some of the business value they've seen utilities realize by adopting analytics solutions. Among them:

·         A significant reduction in regulatory compliance reporting lead time

·         Marked improvements in corporate collections via improved analysis of Commercial & Industrial (C&I) accounts and their invoicing

·         Reduced analysis time from one week to less than one day for revenue assurance analysis and identification of non-recording meters to meter investigation.

 

Perhaps the bottom line with data analytics in most scenarios, says Oosthuizen of Origin, is that "utilities get their ROI because of the efficiencies they gain in processes, as well as the monetization of data."

 

Analytics = answers

So what's in Big Data for you? In a nutshell, answers:

·         Answers to the biggest and most important questions that face utilities

·         Answers about your equipment, its condition and its need for upgrade

·         Answers about your operations and how to optimize your grid

·         Answers about your customers, their needs, and their preferences

 

But you'll only get the answers you need if you do Big Data right. And the first step is creating an analytics-friendly workplace.

ADDITIONAL RESOURCES

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From industry sources…

2012 Utility Industry Survey on BI, Analytics and Big Data– BRIDGE Energy Group

California ISO: Bringing State-of-the-art to California's Grid– Space-Time Insight

An Introduction to Situational Intelligence– Space-Time Insight

Managing big data for smart grids and smart meters- IBM

Data validation for smart grid analytics– Utilicase

6 Big Data Lies– InformationWeek

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From Smart Grid News…

Strategic Asset Management: A Primer for Electric Utilities

Everybody's talking Big Data, but Echelon gets to the point

Smart grid data analytics: Looming gap will force major expenditures

Smart grid data analytics in the real world

Smart grid Big Data: Survey confirms utility opportunities, but spots blunders as well

Top 5 signs you need Operational Intelligence for smart grids

Just 3 simple steps to drive business value from smart grid data?

Smart grid analytics: Why you should fire your coders (and hire solvers instead)

Smart meters and Big Data: A clear case for governance best practices