Why Con Edison Selected C3 IoT for the Largest Active Deployment of Smart Meters in the U.S.
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By Sue Walsh, RTInsights
RTInsights explains why one of the largest utilities in the United States – Con Edison and Orange & Rockland Utilities – recently selected the C3 IoT Platform to facilitate the company’s digital transformation.
According to RTInsights, “Data from smart meters is increasingly being used by utilities for a variety of use cases: pinpointing outages on the grid to restore power faster to specific areas; as demand response to reduce energy use; prevention of energy theft; dynamic pricing based on time of use; and to assist in the planning of distribution grid assets. The C3 IoT Platform in particular is becoming a popular choice among large utilities – the tech company’s customers include two of the world’s largest electric companies: Enel, based in Rome, and ENGIE, based in France.”
In partnership with C3 IoT, “Con Edison, which provides power to New York City and Westchester County, will operationalize data from 5 million smart meters to ensure the health of the sensor network and provide products and services that leverage artificial intelligence and machine learning. The companies estimate data volumes will exceed 115 terabytes, growing by 104 gigabytes per day, from 480 million meter reads each day.”
This is the largest smart meter deployment currently under way in the U.S.
By Derrick Harris, Founder/Editor/Writer, ArchiTECHt
ArchiTECHt’s Derrick Harris has published an in-depth Q&A-style article with Tom Siebel that reveals the C3 IoT CEO’s inspiration for building the C3 IoT Platform, the new technologies that have made such computational power possible, and the business problems being solved today with next-generation AI and IoT applications.
Why Thomas Siebel made the move from CRM to industrial IoT (and back again?)
Derrick Harris, ArchiTECHt, Feb. 3, 2017
Thomas Siebel is best known for his namesake CRM company Siebel Systems, which he co-founded in 1993 and sold to Oracle in 2005 for nearly $6 billion, but these days Siebel is focused on the Internet of Things.
I spoke with him recently about his latest venture, C3 IoT, and how cloud computing and big data are making IoT a possibility—at least for the large enterprises he’s currently targeting...
Constellation Research has published an independent, in-depth report recommending that enterprises shortlist C3 IoT for IoT platform selections and next-generation application use cases.
Constellation provides a thorough overview of the C3 IoT Platform and explains the benefits of key differentiators, including the C3 Type System and integrated AI / Machine Learning capabilities. Constellation also assesses C3 IoT’s partnerships and alliances, pricing strategy, and management team – all in terms of customer value. Excerpts include:
The “time to go live” and “time to insight” metrics were crucial design criteria for C3 IoT. The platform has demonstrated the ability to deliver value to enterprises in a matter of days, in contrast to the few quarters traditional platforms can take. Being able to achieve more with less resources (time and talent) is a proposition that is very attractive to enterprises at a time when software is a strategic differentiator.
C3 IoT has practically created the “mythological system of systems” through the combination of a data-first platform approach, the type-based system architecture, and the exposure of new automation via APIs. This combination of capabilities allows customers to bring all information together on the C3 IoT Platform, not only for insight and Machine Learning processes, but also to make the C3 IoT Platform the central system of record and the base for nextgen applications.
C3 IoT successfully addresses a number of challenges that have plagued enterprises in the past with respect to traditional approaches to Machine Learning. With C3 IoT, data remains in place, gets automatically updated and refreshed, and thus Machine Learning capabilities are no longer the domain of a small clique of advanced users.
All these capabilities of the C3 IoT Platform have been created with the idea of empowering a few users to do a lot of work, while at the same time broadening the potential user base by requiring more business acumen than technical knowledge from platform users.
Source: Holger Mueller, Vice President and Principal Analyst, Constellation Research, Inc., 2017.
By Isaac Brown, Lux Research
Independent research and advisory firm Lux Research positions C3 IoT at the top of its list of companies that raised significant funding in 2016. As Lux explains, “While total funding may be slowing down, the size of the individual rounds is, if anything, ramping up. Investors threw huge piles of cash at several companies developing innovative technologies centered on devices, connectivity, applications, and analytics – these companies target a wide range of use cases, including energy, manufacturing, commercial buildings, and connected products.”
According to Lux:
C3 IoT – $70 million Series D / September 2016 – Founded in 2009 by software veteran Thomas Siebel, originally focused on application and analytics platforms for energy organizations, C3 recently rebranded to focus more broadly on the IoT. The firm has developed a platform for connecting sensors, IoT devices, and enterprise systems to an environment that offers pre-built AI and machine learning applications, an application development environment, and analytics tools. This round, led by TPG Capital, brings the firm’s total funding up to $131 million. In addition to attracting this investment, C3 IoT won some big deals in 2016, including enterprise contracts with Engie and the U.S. State Department.
C3 IoT was a notable presence this week at the Amazon Web Services (AWS) user conference, AWS re:Invent 2016, held in Las Vegas. From the opening Partner Summit keynote, which featured C3 IoT customer successes as well as a video interview with CEO Tom Siebel, to being recognized as a leading AWS IoT Competency partner, to receiving the 2016 “Best New Sponsor” award for our stand-out event presence and show-floor experience, C3 IoT was highly visible at one of the industry’s most important events – with 32,000 attendees – dedicated to advancing digital business transformation. Media mentions from the week include:
TheCUBE's video interview with AWS Global Partner Ecosystem GM, Dorothy Copeland, captured onsite at re:Invent, explains that C3 IoT is an AWS partner as well as an AWS customer. At minute 11:50, Dorothy says: “One of our newer partners, C3 IoT, which provides a predictive analytics solution (and espresso, as you can see right behind us!) as well as an IoT solution, built their solution from the ground up on AWS. But they became an AWS partner only earlier this year because they found that telling their enterprise prospects that their solution was on AWS helped them win the deal. They’re in well over 20 enterprises with over 70 million endpoints today. So we see a lot of success in terms of partners being able to really promote the fact that they’re an AWS partner and they’re built on AWS.”
A Forbes exclusive interview with AWS CEO Andy Jassy about the future of the enterprise cloud boldly positions C3 IoT at “the beginning of the IoT wave.” As Jassy explains, “IoT is a generational opportunity that’s just exploding. IoT is one of the fastest-growing and adopted types of new paradigm shifts that you’ve seen in a long time. … most of the big implementations on top of AWS are coming in the form of IoT.”
ZDNet noted that Terry Wise, AWS vice president of channel and alliances, “touted the innovation of AWS customers, such as C3 IoT’s work in the Internet of Things space … ‘It’s up to us to provide the foundation for innovation and agility.’”
A TechCrunch article about AWS re:Invent stated, “Amazon seemed to be especially excited about the possibilities of bringing more IoT solutions to AWS,” and then highlighted C3 IoT as a premier member of the new AWS IoT Competency program via this video interview with C3 IoT CEO Tom Siebel, which is also available on YouTube.
An AWS news announcement, AWS Extends Amazon Aurora with PostgreSQL Compatibility, features C3 IoT: C3 IoT provides a high-productivity enterprise machine learning application development platform with their applications applying advanced machine learning to recommend actions based on real-time analysis of petabyte-scale data sets, dozens of enterprise and extraprise data sources, and telemetry data from hundreds of millions of endpoints. “Amazon Aurora with PostgreSQL compatibility provides C3 IoT with the opportunity to scale relational-based workloads in the C3 IoT Platform to much higher levels, providing better performance and higher availability at lower costs,” said Houman Behzadi, Chief Product Officer, C3 IoT.
Overall, AWS re:Invent 2016 was successful in emphasizing the value and innovation C3 IoT and AWS bring to the market with an end-to-end development platform for enterprise IoT and big data applications.
“Tom embodies the attributes of exceptional leadership – strong values, clear vision, innovation, integrity, and community contribution. We are proud to honor his talent and passion for building strong, vibrant organizations and inspiring employees to ever-higher performance,” said Publisher Mary Huss.
An editorial profile, “Siebel Aims to Do It All Again,” about Siebel’s leadership, industry contributions, and vision for C3 IoT, published in the November 11th edition of the newspaper, offered these insights:
Standing on the brink of another potentially world-changing industry, [Siebel] aims to “become larger than the sum of all competitors combined.”
With C3 IoT, Siebel now finds himself vying for market position in an industry projected over the next decade to be worth $250 billion as companies race to equip buildings, homes, cars, and all manner of “things” with sensors and software analytics suites.
“C3 IoT is well positioned within the evolving ‘Big Data stack’ sought by companies in a variety of industries with ever-growing volumes of operational data to parse,” said investor and board director Nehal Raj, a partner with TPG Capital.
Once again [Siebel] is on the ground floor of an industry that’s poised for exponential growth.
His ambitions remain untamed. Siebel’s not aiming for a mere slice of the IoT market, or even the most profitable one. His stated objective is global dominance in the Internet of Things: to “become larger than the sum of all competitors combined.”
Siebel has a track record of beating multinationals to new markets. “In emerging markets, these behemoths don’t tend to do so well,” Siebel said. “Large companies tend to miss transitions.”
“When you’re in emerging markets, the leader gets to set the rules,” Siebel said, citing the examples of Siebel Systems and Oracle. Staying ahead of the herd is crucial to establishing enduring models for pricing, licensing, distribution, and other pillars of future deals in the space.
[Pat] House describes day-to-day life inside Siebel’s companies as “a high performance culture.” She said many talented employees have bought in over the years, following Siebel from Oracle, to Siebel Systems, and, now, to C3 IoT. “Much of our team has remained consistent across those three companies,” House said. “That tells a lot about a person, doesn’t it?”
Patricia House, Siebel’s long-time colleague, collaborator, and friend, presented the 2016 Most Admired CEO Lifetime Achievement award to Siebel during the publication’s ceremony on Thursday night. She noted, “Tom leads by example in all regards – his work ethic, quality of work product, commitment to customer success, and high levels of professionalism. Tom’s leadership at Oracle, Siebel Systems, and now C3 IoT is characterized by his unwavering commitment to building global companies known for excellence, quality, integrity, and performance.”
Interview with Emily Chang, Host
On Nov. 1, C3 IoT CEO Tom Siebel appeared on Bloomberg Technology TV to discuss the IoT market with host Emily Chang. Their discussion ranged from the hype and reality of the Internet of Things, to C3 IoT’s early leadership position in this dynamic market, to the benefits of cloud computing in an era of increasing cybersecurity threat.
Siebel’s observations include:
“It is clear that the next generation of computing is all about smart connected devices and the Internet of Things. This is an entire replacement market for enterprise software.”
“All value chains are being sensored: healthcare, financial services, telecommunications, transportation, the energy industry, you name it.”
“When we started Oracle, we took on all the big software companies and we did pretty well. When we built Siebel Systems, we took on all the large software companies – Oracle, SAP, IBM – and we did pretty well. In each of those markets, we established and maintained a market leadership position globally. We have about 100 million sensors under management today, which is 100 million more than anyone else in the market. So far we’re doing pretty well.”
“Cybersecurity is a critically important issue to which we do not pay enough attention, especially when you look at the threat that critical infrastructure is under. There is a myth, however, that somehow data are more secure behind our own firewall than they are in cyberspace. I would argue that the opposite is true. Data used to be secure in our own data rooms when it took a forklift to move a storage device. It no longer takes a forklift. I would suggest the only opportunity where we can really secure data – using encryption in avoiding penetration – is in cyberspace.”
Fortune wrote about the new Siebel Center for Design at the University of Illinois at Urbana-Champaign – author Adam Lashinksy’s alma mater, as well as Tom Siebel’s.
The article states, “Siebel is funding a new, $50 million design-thinking-focused institute at the university that he hopes will be a place many disciplines can come together. ‘The big trend at universities is interdisciplinary efforts,’ says Siebel, noting that graduate and advanced research programs like medicine and bioengineering have benefited from the trend. ‘The design school is the undergraduate version of interdisciplinary thinking.’”
Lashinksy praises Siebel’s business acumen throughout his career: “Being nimble enough to go from ‘customer relationship management software’ to energy monitoring to keeping track of sensors connected to the Internet is quite a feat. So is giving back to a public university in the Midwest that gave him his start.’
The Chicago Tribune’s Blue Sky Innovation, a special section dedicated to innovators and entrepreneurs, profiled the new Siebel Center for Design at the University of Illinois at Urbana-Champaign.
The article states:
A $25 million donation from tech entrepreneur Thomas Siebel will help build the new innovation-focused design center at the University of Illinois at Urbana-Champaign. It is meant to bring together disciplines from around campus.
The two-story building will feature a variety of spaces, including workshops for things like 3D printing and laser cutting, digital media studios for audio recording, and immersive technologies for virtual reality.
Siebel is chairman and CEO of C3 IoT, a Redwood City, Calif.-based software company that lets companies design and operate Internet of Things applications. In 1993, he founded Siebel Systems, a global software company that merged with Oracle Corporation in 2006.
This is not Siebel’s first naming gift to U. of I. In 2000, six years before his company merged with Oracle, he gave $32 million to the university to build the Thomas M. Siebel Center for Computer Science.
Siebel is an alumnus with three degrees from U. of I.: a bachelor’s in history from 1975, an MBA from 1983 and a master’s in computer science from 1985.
Siebel said he expects companies and inventions to grow out of the Design Center that will have an impact on Chicago and Illinois. “It’s going to make change happen, and it’s going to make changes happen for the better.”
The University of Illinois at Urbana-Champaign has unveiled the Siebel Center for Design – a new state-of-the-art facility that will be a campus-wide hub to cultivate interdisciplinary design thinking and innovation – funded in large part by a $25 million lead gift from the Thomas and Stacey Siebel Foundation.
Experts have heralded Siebel’s vision for bringing students together from various fields (e.g., computer science, history, biology, business, mechanical engineering, and fine arts) to work on groundbreaking projects, solve real-world problems, and make significant impact in the world.
Building a fully scalable cloud platform for IoT is much more difficult than it sounds. One company has managed to build the only full-stack IoT platform that has succeeded in scaling in production.
C3 IoT is a one-stop-shop for businesses that need an IoT platform.
C3 IoT is enabling … the “fourth IT wave” which utilizes all the technologies we have been getting excited about lately.
In order to understand just how incredibly capable the C3 IoT platform is, you only have to look at how it’s being used presently by their clients.
Here’s a very powerful statement that shows just how scalable their platform is: “For one multi-billion dollar global corporation, C3 IoT’s platform ingests 7 trillion rows of data, with 550 billion sensor and device reads, processing at 1.5 million writes per second in a petabyte-scale data cloud, running more than 2,500 analytics in near-real time to generate 8 million predictions per day, with greater than 95% accuracy.” Can you imagine the sort of infrastructure you need to have in place to accomplish that?
These implementations are saving tens of millions of dollars annually from improved fraud detection and reduced equipment failure; increasing customer engagement; and significantly lowering energy costs and greenhouse emissions (that’s the whole “making the world a better place” part).
C3 IoT is going to be cranking away and analyzing trillions of data points to make companies across all industries more efficient.
When you visualized a world where everything was connected and being analyzed by artificial intelligence to constantly get better over time, what you were visualizing was a platform offering like C3 IoT.
One of the most influential media outlets covering innovation in payments and commerce, PYMNTS has written a compelling profile of C3 IoT, the company’s technology, and its ability to help financial services, healthcare, and manufacturing organizations exploit big data and predictive analytics to tackle fraud detection and other challenges.
According to Ed Abbo, president and chief technology officer of C3 IoT, fraud detection is paramount in the global power industry, which is a $30 billion–$40 billion industry.
C3 IoT is a leading IoT development platform that initially focused on the energy sector but is now tapping the lucrative spaces of fraud detection, healthcare and banking.
Back in April, ZDNet predicted that C3 IoT was scaling and would soon expand. It wasn’t wrong. On Sept. 2, 2016, the company raised $70 million in Series D equity funding.
CEO Tom Siebel has a knack for predicting when to scale IoT deployment. Before C3 IoT, he headed Siebel Systems, a CRM startup, which he later sold to Oracle. C3 IoT was formed when Siebel saw the potential convergence of cloud, Big Data, machine learning and mobile sensors in solving business problems.
Has Seibel’s vision materialized in C3 IoT? According to Abbo, C3 IoT has the only full-stack platform that has succeeded in scaling in production. C3 IoT manages 70 million sensors and has over 20 customers who report significant ROI because of fraud protection, predictive maintenance and improved energy efficiency.
The C3 IoT platform was built from the ground up over the last seven years and is the only comprehensive and cohesive technology stack.
According to Harbor Research: “C3 IoT is clearly miles beyond its established competitors” in terms of product development, devices under management, customers and scale of deployments.
The McKinsey Global Institute estimates the total potential impact of digitally transformed business processes to be $3.9 trillion–$11.1 trillion per year in 2025 — digitally transformed meaning those companies able to harness and apply advanced analytics and machine learning to Big Data in real time and produce results. And, according to Abbo, C3 IoT’s track record on this score is impressive.
One customer credits C3 IoT applications with $20 million in annual savings from smarter fraud detection. Another company reduced equipment failures between scheduled maintenance by 50 percent, lowering costs and downtime. One large enterprise lowered energy costs by 10 percent, and another reduced greenhouse gas emissions by 14 percent. A large manufacturer in the U.S. cut energy costs 16 percent across all of their plants, saving millions of dollars and achieving 230 percent return on their investment.
The payments industry is also undergoing a digital transformation and replacing traditional rule-based systems with sophisticated Big Data and machine-learning technology. These processes detect patterns in real-time data and recognize cases of theft or fraud. According to Abbo: “Financial services organizations will increasingly apply predictive analytics to transaction data to improve fraud detection, predict customer churn, reduce customer acquisition costs and deliver next-generation product and service offerings.”
Abbo sees a burgeoning market for connected, low-cost sensors, adaptive systems, a new generation of smart applications and a renaissance in business process reengineering. “This new generation of smart business processes and applications will ultimately replace the current enterprise software applications stack. IoT is essentially an entire replacement market in global IT.”
Lux explains, “There are hundreds of Internet of Things (IoT) platform products on the market today. Platforms exhibit a wide range in technology strength and product maturity – picking the optimal platform is no easy task.”
Excerpts from Lux Research’s assessment of C3 IoT’s platform strengths and feature sets include:
Technology & Differentiators
C3 has developed a solution for connecting sensors, IoT devices, and enterprise systems to a platform with pre-built IoT applications, an app dev environment, and a comprehensive analytics engine. The Platform begins with inputs from a variety of data sources, including sensors, SCADA systems, asset management solutions, CRM platforms, and ERPs. It feeds this data to its transformation engine, which processes the data and pushes it to its app and analytics environment.
Users can select from a set of pre-built applications, which the firm claims are broadly applicable across multiple industries. Beyond the pre-built applications, the C3 platform provides a development environment for building custom IoT applications similar to ThingWorx. C3 has integrated machine learning / analytics tools into its applications and development environment. The analytics tools provide reports, dashboards, visualizations, and actionable insights. C3 hosts the solution in AWS, but can deploy the solution in private clouds, as well as on-premises as an appliance.
Strategy & Markets
C3 operates from offices in seven countries across North America, Europe, and Asia with most of its customers in North America and Europe. Given the firm’s genesis in the utilities space, most of its customers are still energy organizations (mostly electricity providers), but it has won a few big deals outside of the utilities space. 80% of its customers leverage the pre-built applications for managing their internal operations; some customers are building custom applications through C3, which they then resell as part of a bundled solution to their customers. The pricing model is tied to the specific pricing of Amazon’s storage and compute fees, which C3 says keeps billing simple and allows customers to pay as they grow.
Lux Take: Strong Positive
With proven value and scale, C3 is a leader in IoT application and analytics platforms. The firm’s founder and CEO, Tom Siebel, is a mogul and will be able to get in front of execs and drive growth.
One of the most influential technology publications for senior enterprise executives in France, Journal du Net (JDN) has written a comprehensive profile of C3 IoT, its vision and distinguishing capabilities, and its pioneering work with industry-leading organizations.
The company specializes in the processing of data sent by connected devices. It is headed by one of the icons of high tech, Thomas Siebel, the inventor of CRM.
Compared with unicorns growing by the dozens in the collaborative economy or finance sectors, Internet of Things startups are still at the fetal stage. But there is one exception to the rule: C3 IoT. This California company, founded in 2009, has developed a platform to manage the data generated by connected objects. It offers its clients (large organizations) a series of applications to process this information.
"Many companies that are trying to take a position in this market segment manage little data. Their customers, still in the 'proof of concept’ stage, have only installed a few hundred or thousands of connected devices. C3 IoT manages in real-time industrial quantities of data, generated by more than 70 million sensors,” said Julien Groues, senior vice president EMEA of the company. This argument rings true in the ears of investors, who paid $70 million as part of a funding round in early September 2016, to support the commercial development of the young company. The company has collected $110.81 million since its inception, according to the U.S. site Techcrunch.
This investor confidence is due to C3 IoT’s CEO, the self-made billionaire Thomas Siebel. Known to all in the high-tech field, he founded Siebel Systems in 1993, the company that created the first CRM software. The company was acquired for $5.8 billion in 2006 by Oracle (where Siebel was one of the first employees).
With 40 years of experience in the technology sector, this pioneer has a clear vision for the IT market and can detect sources of growth before anyone else. As early as 2009, he had sensed the potential of the Internet of Things. Utilities, which already had begun to connect their meters at the time, put him on the right track. These companies were the first customers of C3 IoT.
"We have collected and analyzed more than 750 terabytes of data for the Italian electricity provider Enel, generated by sensors installed on almost all of its industrial assets. We are now performing the same work with the French company Engie," said the C3 IoT CEO last June, who came to Paris to announce the signing of a partnership with the French group.
The company is also developing rapidly in other vertical markets, such as Industry 4.0. It processes the data sent by machines equipped with hundreds of sensors, which allow, for example, the measurement of temperature, vibration, engine power ... "These sensors send us information, often several times a minute. We combine all of it with static data, such as maintenance history or the date of installation of the device on the production line. Our machine learning system analyzes these data. It determines if the machine has a high, moderate, or low risk of failure,” explains Julien Groues. When they find it relevant, plant managers send a technician to repair the equipment before it fails. They also invest more wisely in equipment, by evaluating priorities better.
The C3 IoT predictive analytics system, which learns from its mistakes, also interests companies from the world of finance (in particular, it helps to detect fraud). The start-up has more than 20 customers, such as Cisco and the U.S. Department of State. The start-up does not disclose its financial results, but the Harbor Research analyst firm estimated its annual revenue to be $50 million.
By Chris Preimesberger, eWeek
eWeek looks at C3 IoT's emerging leadership in the IoT market, with its powerful platform, suite of SaaS applications, impressive customer base, and recent infusion of $70 million, which will be used to expand C3 IoT's product footprint, invest in customer service and satisfaction, and accelerate the expansion of its customer service capacity globally.
RTInsights explains how C3 IoT's platform approach is solving enterprise IoT challenges, such as interoperability among IoT devices, data integration with enterprise applications, ingesting and analyzing data, handling data volume and velocity, clarifying business returns, complexity, and cost. It also address a critical question for enterprise IT executives: "How does C3 solve the time-to-value problem?"
It's generally not a large leap from the energy industry into other verticals, Siebel said. For example, managing the health of sensors, which the C3 IoT Platform provides, can be applied across any industry using sensor data. Identifying energy theft, meanwhile, isn't fundamentally different than identifying banking or insurance fraud...In all cases, it's a matter of teaching the system to recognize anomalies in data.
It's also not a leap to go from predicting whether a distribution transformer will fail to predicting whether a part will fail on a Boeing 787 airliner or Caterpillar tractor. And in some respects, healthcare can be thought of as a predictive maintenance problem. Health insurance companies also "have a great wealth of information about medical history and lifestyle" of their customers, Siebel said. "It's a classic machine learning problem and a predictive problem -- to analyze this data and identify which segment of the insured population will be battling diabetes seven years from now."
Siebel said his business approach with C3 is no different than what he's done before at Siebel Systems with CRM -- to establish and maintain a leadership position in the market. C3 is starting from a position of strength: it currently has a 40 percent share in the global smart meter market, which is miles beyond its competitors GE and Siemens, notes Harbor Research in a July 2016 research report.
“It looks like an entire replacement of the existing software stack that’s out there,” [Siebel] said. “It’s very fast-moving, and challenging.” But with IoT, he predicts, “the economic and social benefits will be more significant than previous ways of computing.”
Business Insider asserts the “next Industrial Revolution is happening as we speak. It’s so big that it could mean new revenue streams for your company and new opportunities for you. The only question is: Are you fully up to speed on the IoT?”
This question sets the stage for BI’s analysis of C3 IoT and how the $70 million equity financing, led by TPG, will be invested to fuel the company’s growth.
This article explains how “Silicon Valley luminary Thomas Siebel … founded C3 IoT in 2009 to help business organizations maintain operational efficiency and productivity. The platform offers a powerful suite of tools to enable IoT development, including cloud computing, predictive analytics and machine learning.”
The article goes on to say that “C3 IoT is able to process seven trillion lines of data at a speed of 1.5 million writes per second in a petabyte-scale data cloud. It can also carry out more than 2,300 analytic calculations in near real-time to generate eight million data predictions per day, with near 100% accuracy.”
Silicon Valley Business Journal covered C3 IoT’s $70 million funding round. The article quotes C3 IoT CEO Tom Siebel: “This partnership with TPG, a leading investor in high-growth technology markets, enhances C3 IoT’s industry leadership and our ability to assure our customers’ success.”
Having a well-known founder can go a long way towards helping a startup attract investors. The latest example of that is C3 IoT Inc., the platform-as-a-service provider led by Silicon Valley billionaire Thomas Siebel, which today raised $70 million in a funding round led by TPG Growth.
The cash infusion follows a series of major customer wins for the outfit that included a $25 million contract from the State Department and a deal with French utility ENGIE SA, one of the largest companies in Europe. Both organizations were drawn to C3 IoT’s cloud-based development toolkit by its focus on machine-generated data. The main component is a platform-as-a-service stack specifically geared towards powering workloads that process information from connected devices, particularly industrial equipment.
Bloomberg offers a detailed look at C3 IoT’s $70 million equity financing, led by TPG, a premier equity investor in high-growth companies.
Excerpts from the article include:
Billionaire Thomas Siebel has raised $70 million for his data analytics startup C3 IoT as investor enthusiasm for the so-called Internet of Things begins to wane.
Siebel founded the company in 2009 under the name C3 Energy. The Redwood City, California, startup initially targeted energy companies before expanding to other industries and eventually rebranding itself earlier this year. C3 IoT helps businesses collect and analyze data from internet-connected sensors, including thermostats and electrical transformers, and other sources.
C3 IoT won a $25 million contract this year to track energy use by the U.S. State Department at more than 22,000 facilities around the world.
C3 IoT has estimated annual revenue of $50 million and about a 40 percent share of the global smart meter market, according to Harbor Research.
By Matthew Littlefield, President and Principal Analyst
LNS Research, a leading analyst firm covering Digital Transformation and the Internet of Things, published a blog post explaining their positive outlook on C3 IoT. Highlights from the LNS Research review include:
Although C3 IoT provides a platform that is industry agnostic, given its early start in the utilities industry, the company has a leg up on some newer entrants to the market with industrial cred.
Because utilities were early adopters of smart connected devices, C3 IoT has a platform that claims more connected devices than any other I have heard. To date, C3 IoT has signed some of the largest utilities in the world with currently 70 million total connected devices.
Using C3 IoT’s embedded ML [machine learning] capabilities, the utility was able to increase the success rate [of theft identification] to over 90%. The wow factor isn’t just the remarkable improvement, but the “how.”
One of the areas of challenge/experimentation for many IIoT Platform providers is the licensing model. C3 IoT has wiped all that complexity away.
Following an in-depth interview with C3 IoT CEO Tom Siebel, and referencing independent research conducted by Lux Research and Harbor Research, InformationWeek Editor at Large Charles Babcock writes about C3 IoT’s leadership in the Industrial IoT market. “From where IT professionals sit, these are early days for industrial IoT. Still, the software, hardware, and network ecosystems required for delivering on the promise of IoT will eventually transform the way enterprises think about running everything.”
Babcock continues, C3 IoT “is considered by most research firms to be a current leader in the industrial IoT market.”
InformationWeek’s Editor at Large Charlie Babcock recently visited C3 IoT headquarters in Redwood City, CA, and sat down with CEO Tom Siebel for a far-reaching conversation about industrial-scale Internet of Things applications and C3 IoT’s competitive position in this dynamic market.
They discussed the company’s roots in the global energy industry, where C3 IoT has installed “the largest set of IoT production applications on earth” and “more than 80% of European smart meters are under management by the C3 IoT Platform,” according to the InformationWeek article. They also discussed demand for the company’s development platform for IoT applications from additional industries, including manufacturing, healthcare, and financial services. InformationWeek also cites independent analysis by Lux Research and Harbor Research, noting Harbor's conclusion that “C3 IoT is clearly miles beyond its established competitors.”
The InformationWeek article concludes, “Siebel knows he previously enjoyed a big opportunity in launching salesforce automation on the mainframe, and the IoT opportunity is much larger than that. ‘We did something important at Siebel Systems and at Oracle, too,’ Siebel said. But if C3 creates a platform that becomes a leader in IoT applications, or sets a cross-industry standard for how to create IoT applications, that ‘would be a lot more important.’”
On the heels of its C3 IoT Market Leader Profile, Harbor Research president Glen Allmendinger published a blog post about the evolving competitive landscape and vendor ecosystems that are enabling Smart Systems and the Internet of Things. One of the critical defining forces and trends for IoT platforms, Allmendinger writes, is "a unified end-to-end 'managed' services offering to support the shift from predominantly OEM adopted solutions to true end customer managed 'owner/operator' solutions that go beyond just a narrow function platform story."
In this context, Harbor's Allmendinger asserts that ENGIE's selection of C3 IoT as their platform "validates the vast scale and range of capabilities inherent to C3 IoT's enterprise application development offering. C3 IoT provides a full-stack application development platform that leverages big data and connected devices and systems to drive greater insights into business processes and productivity, operational efficiency, and customer and product behavior." He also summarizes C3 IoT's partnership with Amazon Web Services (AWS) "to enable faster deployments and go-to-market initiatives designed to facilitate customer success with large-scale IoT implementations."
This is the federal government's first enterprise-wide contract to deploy predictive analytics and energy management technology globally, which will help achieve and maintain statutory, executive order, and department energy and sustainability goals.
Enterprise-wide contracts like this one will allow the Department of State to enhance operational efficiencies by taking advantage of real-time access to all telemetry, enterprise, and extraprise data across 22,000+ Department facilities worldwide and leveraging predictive analytics on a global scale.
With C3 IoT's machine learning-based platform and software application suite, the State Department can predict impending failures of critical facility equipment, automatically monitor, analyze, and manage energy usage across all assets, and assess the health of the sensor and device infrastructure.
World-leading organizations are using C3 IoT and AWS IoT technologies to enable smarter, data-driven offerings ... applying IoT capabilities and solutions to challenges and opportunities to improve government services including transportation, public safety, and city services. From parking to officer safety to water management, agencies can achieve cost savings, efficiency, and improved innovation.
C3 IoT is an Advanced Technology Partner in the AWS Partner Network (APN). In June, the companies announced an increased level of cooperation with new development and go-to-market initiatives to deliver a tightly integrated, end-to-end platform as a service that accelerates organizations' success with Industrial Internet of Things (IIoT) applications and other big data initiatives.
By Isaac Brown, Lux Research
In an article called "IoT Partnerships That Make Sense," Lux Research analyst Isaac Brown evaluates the strategic technical and commercial synergies inherent to the C3 IoT and Amazon Web Services (AWS) alliance, as well as the Cisco Jasper and AT&T alliance.
Visit the Lux Research website to download the article and learn why Lux calls the C3 IoT + AWS partnership a "home run."
By Michael Alba
Excerpts from Engineering.com’s article about C3 IoT’s contract win with the U.S. Department of State include:
The U.S. State Department recently awarded C3 IoT a contract to provide the department with the C3 IoT platform for application development. The multi-year deal, worth up to $25 million, is focused on using the Internet of Things (IoT) for energy management and aims to help the department meet sustainability goals.
The agreement hopes to leverage data from IoT sensors in the State Department’s more than 22,000 facilities in over 190 countries. The machine-learning IoT platform promises to deliver actionable data insights by monitoring and analyzing energy management across the department’s assets.
The C3 IoT platform is set to be deployed in AWS GovCloud, an Amazon Web Services region that is isolated in order to host sensitive government data. This is necessary to comply with U.S. government requirements including International Traffic in Arms Regulations (ITAR) and Federal Risk and Authorization Management Program (FedRAMP).
The State Department hopes the deal will allow it to increase efficiency and make it a frontrunner in utilizing IoT technology, all while helping the environment.
Tom Siebel was interviewed by Press:Here host Scott McGrew, USA Today’s Jon Swartz, and Pando’s Sarah Lacy about C3 IoT, trends in the Internet of Things industry, and the tech economy. The show aired Sunday, June 26, 2016 on NBC Bay Area TV.
Watch the first Press:Here segment: “Tom Siebel: The longtime entrepreneur and cofounder of Siebel Systems knows where he’ll make his next billion: the Internet of Things.”
Watch the second Press:Here segment: “Siebel on Startups: In the second half of our interview, the CEO of C3 IoT talks about whether the bubble is bursting.”
By David Curry
The Department of State has announced plans to deploy an Internet of Things (IoT) energy platform to conserve more energy, identify potential issues quicker, and monitor the department’s sensors.
It will be working with C3 IoT (formerly C3 Energy) to deploy the IoT platform to hundreds of thousands of “data points” over the coming years. This may include foreign embassies and treaty rooms, which the State Department control.
Internet of things platform-as-a-service specialist C3 IoT revealed June 23 that Paris-based energy provider ENGIE has selected the company's platform and applications as the tech foundation for its global enterprise-wide transformation plan.
C3 IoT will provide ENGIE with the necessary power, scalability and flexibility to apply machine-learning and advanced real-time analytics to very large petabyte-scale data sets, C3 IoT founder, CEO and Chairman Tom Siebel told eWEEK.
When everything gets up and running, this will become one of the largest—if not the largest—IoT management deployments in the world, Siebel said. It expects to process about a petabyte of data per day and possibly more, he said.
C3 IoT, headquartered 30 mi. south of San Francisco, was founded in 2009 offering a number of IoT applications, including predictive maintenance, sensor network health and supply chain optimization. It has undertaken projects with airframe manufacturers and OEMs in areas such as anticipating supply chain delay, IoT solutions for manufacturing, and predictive maintenance applications across aircraft systems and line replaceable units.
Ed Abbo, C3 IoT president and chief technical officer, says aviation has been proactive in IoT adoption. “Aerospace is embracing IoT as a paradigm. Adoption is being led by airframers and OEMs who understand that this technology will allow them to improve operational efficiencies and offer more competitive product service agreements that could potentially disrupt the market in their favor.”
“As fleets modernize and adopt newer aircraft that produce orders of magnitude more data, the need for advanced machine-learning analytics will be at the core of system characterization and performance analysis. These technologies will be essential to aircraft system anomaly-detection capabilities and vital maintenance troubleshooting efforts.”
Abbo, meanwhile, sees opportunity for C3 IoT across the entire aviation value stream, including maintenance planning, and says the only impediment to greater aviation industry adoption lies within the industry itself. “The biggest hurdles to IoT adoption are the speed with which the sector is capable of embracing the amount of change that IoT technologies signify in terms of business process reengineering,” he says. “As with other sectors, such as manufacturing and energy, innovative companies are much better positioned to take full advantage of the benefits IoT has to offer.”
Internet of Things platform supplier C3 IoT this week announced two sweeping contracts, one with ENGIE, a huge energy company in Europe, the other with the U.S. Department of State, adding to the eight-year-old company’s roster of big IoT wins …
Although C3 IoT started off in the energy sector, Siebel says IoT has implications for everything from transportation to manufacturing, healthcare and insurance. Common early use cases, he says, are predictive maintenance and fraud detection, but that is just the tip of the iceberg. “I think this is a complete replacement market for the enterprise software market,” he says. “In 10 years all applications will be IoT applications.”
IoT Journal recaps three C3 IoT announcements from the past two weeks, including a strategic alliance with AWS, a contract with the U.S. Department of State, and a strategic technology partnership with ENGIE, a global energy player. Excerpt:
C3 IoT, an IoT platform provider that earlier this year transitioned from serving only the energy industry to targeting its software to a wide range of companies, ranging from manufacturers to healthcare to financial services, has signed three different deals during the past two weeks. On June 16, it announced a strategic alliance with Amazon Web Services through which the C3 IoT platform is now fully integrated with AWS IoT, a managed cloud service that connects devices to the cloud and provides sensor status and network health data. The C3 IoT Platform uses AWS’s infrastructure and services to provision, manage and scale network components.
On June 20, C3 IoT announced that the U.S. Department of State had awarded it a multi-year contract, of a value up to $25 million. Through the contract, C3 IoT will provide the State Department its machine learning-based platform and software application suite, which the department will be able to use, in collaboration with networks of sensors, to automatically monitor, analyze, and support energy management systems across more than 22,000 State Department facilities in more than 190 countries.
Thirdly, on June 23, C3 IoT announced that ENGIE, a Fortune 500 global energy company, has selected the C3 IoT platform for a three-year minimum licensing deal, as part of ENGIE's new Digital Factory initiative in order to improve its operational performance and predictive maintenance across all of its 24 business units across the world. Through this program, ENGIE will also develop IoT-based programs to offer new products and services to its residential, business and industrial. ENGIE will use the C3 IoT platform to power its IoT initiatives across its entire enterprise.
...any deal that brings the so-called Internet of Things to market is notable. The latest example of IofT emerged from the State Department, which has awarded C3 IoT a contract to build an analytics platform to manage energy use and sensor health in real time across 22,000 buildings in more than 190 countries. CIO Journal’s Steven Norton has the story.
Soon, the State Department says, automated recommendations will free up engineers to tackle more complex projects, and make it easier to track and document savings.
C3 IoT said ENGIE, a global energy company, will use its cloud platform in a three-year plan to track and analyze its infrastructure. The deal comes after C3 IoT won a $25 million enterprise application contract from the U.S. Department of State.
… CEO Tom Siebel has said that C3 IoT was looking to land big deals.
The U.S. government is slowly acting to catch up with much of the world in terms of IoT implementation, and in a recent announcement, the Department of State has taken a big step in the right direction.
C3 IoT has announced that the U.S. Department of State this week awarded the company a multi-year contract up to $25 million to provide its IoT enterprise application development platform for energy management and predictive analytics. This will be the federal government’s first enterprise-wide contract of this type, which is designed to help achieve and maintain statutory, executive order, and department energy and sustainability goals.
The State Department has awarded C3 IoT a contract to build an analytics platform to manage energy use and sensor health in real time across 22,000 buildings in more than 190 countries.
The platform will collect and analyze hundreds of thousands of data points, using machine learning and cloud-based infrastructure, in an effort to support energy management, predict failure of equipment and monitor the health of sensors and other devices, C3 said in a statement.
Founded by Tom Siebel in 2009, C3 IoT, formerly C3 Energy, provides an application development platform and software-as-a-service apps for things like predictive maintenance, fraud detection and supply chain optimization. It started out producing technology aimed at the energy sector, but has expanded to other industries.
“We will be able to identify and address outliers across our global buildings portfolio, learn how to improve upon previous embassy designs and operations, and … lower utility and maintenance costs,” Landon Van Dyke, a State Department senior adviser for energy, environment and sustainability, said in the statement.
The C3 platform and related applications run on Amazon Web Services’ GovCloud, an isolated set of servers designed to host sensitive data or computing workloads subject to government regulations such as the International Traffic in Arms Regulations and the Federal Risk and Authorization Management Program, or FedRAMP.
Cloud-based analytics is an expansion of the State Department’s existing smart meter initiative, called MeterNet. The department expects to have more than 150 of its 275 posts — which can encompass hundreds of buildings, apartments or large facilities — equipped with meters and reporting data to the C3 platform by the end of this year. It plans to have more than 200 posts equipped by 2017, and full deployment by 2020.
C3 IoT, which provides an enterprise Internet of things platform, said it is bolstering its existing partnership with Amazon Web Services to create an integrated enterprise stack for deployments.
The company, led by Tom Siebel, has landed a series of large utility deployments and is branching out into new verticals. C3 IoT has more than 20 public sector and enterprise customers. The compute for these enterprise machine learning deployments at companies like Endesa, Enel and Pella has typically been provided by AWS.
As a result, AWS and C3 IoT were already strong partners. Now C3 IoT will be an advanced technology partner for AWS and be fully integrated with AWS IoT. AWS IoT is a managed cloud service designed to track sensors and networks. C3 IoT also said it will be integrated with AWS EC2 and provide auto scaling and spot pricing optimization.
Six months ago, C3 Energy, the IoT platform provider that enterprise software pioneer Tom Siebel launched in 2009, broadened its focus beyond the energy market. IOT Journal spoke with him about the transition and why he thinks every system—even the human body—is becoming part of the Internet of Things.
Jun 16, 2016—Silicon Valley stalwart Tom Siebel has spent four decades developing enterprise software, beginning as an early executive at Oracle and later founding CRM software company Siebel Systems, which Oracle acquired in 2006. In 2009, he launched C3 Energy in order to help utility companies and grid operators better manage data and systems as they transition to smart grid technology. As such, C3 Energy was an Internet of Things company before such a term was in wide use.
Earlier this year, with nearly two dozen clients under its belt, C3 Energy relaunched itself as C3 IoT. While its core software platform remains largely the same, C3 IoT has a much wider purview, serving oil and gas, manufacturing, transportation, financial services and other industries.
IOT Journal spoke with Siebel about his company, how the IoT is evolving across all value chains and why heart attacks are really just another problem that can be solved with predictive maintenance.
Tom Siebel recently visited CBS Interactive’s office in New York. Editor in Chief of ZDNet, Larry Dignan, has this to say in his video summary of their conversation:
“When I caught up with Tom Siebel to talk about his plan to build Internet of Things systems across multiple industries, I wasn’t quite sure what to expect. I had never met Siebel before. I was familiar with his C3 IoT company, but I knew much more about his namesake CRM company that was gobbled up by Oracle back in 2006. Oracle bought Siebel after the acquisition of PeopleSoft to build out its applications business. What I found in Siebel was an engineer’s engineer. He thinks in systems and he thinks in architecture. He’s a billionaire, but he seems to be driven with his latest venture to do something big. He’s driven by his legacy. Siebel will have to think big because he’s running against GE, IBM, and a bevy of others in the Internet of Things market. What sticks out most to me about my talk with Siebel is that he said 2000 people can’t build good software. AWS, Oracle, and Siebel were initially built with 10-20 people. That’s a very interesting quote given that C3 IoT is going against giants. That quote is also interesting to note when you ponder big software deployments. In the software deployments I’ve seen, in-house software that has been built by big teams usually just falls apart. So Siebel is out to make his technology legacy. This should be fun to watch.”
By Brien Sheahan, Elizabeth McErlean, and Anastasia Palivos
Are Regulators’ Heads in the Cloud? Primary Challenges to Utility Adoption of Cloud-Based Solutions
While companies like Amazon, Google, Netflix and Uber are using the cloud and IoT to disrupt entire industries, offering dynamic pricing and services, utilities are lagging behind. As the energy landscape evolves, regulators must consider whether the technical and functional merits of the cloud can create value for utilities and ratepayers.
Increasingly, unregulated businesses are adopting cloud-based information technologies to improve service while leveraging back-office scale and security to generate greater value for consumers and shareholders. Burdened by outdated accounting rules that incentivize investments in legacy technology, cloud adoption by public utilities is relatively low due in large measure by the failure of regulators to consider forwarding looking policies. As the electricity grid evolves, cloud-based services will become necessary to manage a smarter, more efficient, and more distributed network and regulators will have to overcome antiquated views regarding how we think about rate-base and cybersecurity.
By Steven Norton
The Wall Street Journal explains how Eversource Energy has integrated data from about a dozen legacy systems to better understand how individual customers consume electricity and natural gas. It soon hopes to start analyzing data from Internet-connected thermostats and other devices to help those customers optimize their energy use. Companies like Eversource see in this explosion of real-time data — part of the so-called Internet of Things — a way to collect and analyze more data from customers in order to improve services. Eversource worked with platform vendor C3 IoT to integrate the data, analyze it and make it available for customers to use. The C3 platform uses data integration software to create a unified data image, basically a snapshot of data across all those systems at a given time. That information is correlated in a standard format, allowing Eversource to match customer information with particular meter readings, billing systems and other data. The result has been a more granular breakdown of energy use among its more than 3.6 million customers.
Broadening its potential market opportunity, C3 Energy has changed its name, and somewhat its focus. The new company is now called C3 IoT. While the name change might seem to indicate a significant change in the company, the functional focus is still on assembling and analyzing large amounts of operational and customer data into information and action. Most of the technology vendors, like Itron, GE, Schneider, Siemens, ABB, etc, have steered their offerings towards the Internet of things (IoT) market. For companies with existing analytical and Big Data offerings, a focus on IoT typically doesn’t require a large investment in new products. With IoT’s most valuable component being taking large amounts of data from diverse sources and deriving insight and direct actions, it makes sense for C3 to broaden its approach to the market and take it beyond energy markets.
C3 IoT sees the future as a more horizontal approach and is taking what it has learned and developed in the utility space and applying it to other industries, like manufacturing and retail. Manufacturing, especially, is becoming a crowded space for IoT. Traditional manufacturing companies like PTC have invested heavily in staying at the forefront of the manufacturing IoT market. In a vacuum, it would appear to be a tough market for C3 IoT to penetrate. But C3 has an established track record in the utility space that can provide immediate and successful references. In contrast, Some vendors, like EnerNOC, seem to be heading in the opposite direction. EnerNOC competes with C3 in areas around Demand Response (DR) in the utility market. EnerNOC is doubling down on its specialty and core, electric utility DR programs. What Energy Insights sees is energy grid and analytics companies either trying to broaden their appeal to the larger IoT market or going even deeper into energy markets.
C3 IoT can bring its data and analytical capabilities to the adjacent markets quickly. With Tom Siebel’s name at the head of C3, name and brand recognition should be established rapidly. The key for C3 IoT, and any company trying to establish itself as an IoT player, is to get real-world use cases and references lined up as soon as possible. User executives are developing heavy amounts of skepticism towards technology vendors focused on IoT. Those executives want to understand what is different about IoT than what they have been doing for the last 20 years. They want to see how the advancements in device connectivity, analytics, data science, and customer engagement come together under the banner of IoT. To really establish itself, like they did in the utility space, C3 needs to take a functional area like New Product Introduction (NPI) and show how they can take all the information from multiple silos and present information that can help a company prioritize investments and deliver new products faster. That is just one example in one market of the multitude of these business processes that span the organizational silos of end user companies. If C3 can help companies cross the silos, they can bring the IoT message they have built in the utility market to other industries.
For customers of C3 Energy, there should be little reason to feel uneasy. Any change in focus for a technology supplier can be a cause for concern. But in C3 IoT’s case, the investment is relatively light from a technology standpoint. The IoT foundation is there from the C3 Energy building blocks. There will have to be a shift in sales and support, but C3 has the resources and the investment available to support a broader push. The short of it is that current and future companies should rest easy that C3 will not become distracted. In fact, it’s IDC Energy Insights’ opinion that utility customers of C3 will benefit from developments that come about from C3’s expansion into other markets.
By Klint Finley, Wired
Tom Siebel has a history of placing winning bets. He was an early employee at Oracle, which is still the most widely used enterprise database in the world. He later founded Siebel Systems, a business software company that inspired followers such as Salesforce and Microsoft Dynamics. He sold that company to Oracle in 2006 for $5.8 billion.
His latest bet is that the much-hyped Internet of Things is finally going to take off. But he’s not interested in the plethora of “smart” gadgets aimed at consumers. Siebel wants to connect manufacturing equipment, medical devices, and all the other commercial equipment used by the world’s largest companies. Maybe the way the Internet of Things really grows isn’t so much by letting you control your thermostat with your smartphone; it’s by connecting the physical infrastructure of businesses to help them turn a profit.
This week, Siebel’s latest company, C3 Energy, changed its name to C3 IoT and branched out from its focus on energy utilities to commercial enterprises such as manufacturing, mining, transportation and health care.
“We’re solving problems that have never been solved before.”
If you’re into technology, you’ve probably heard of Tom Siebel.
He first rose to prominence as an executive at business software giant Oracle before setting off on his own to start Siebel Systems, a customer relationship management software, or CRM, company. In 2006 he sold his eponymous company to his former employer for $5.85 billion and started a new one, C3 Energy, focused on data analytics software for the so-called smart grid.
But “clean tech” has fallen out of favor. What’s in? The so-called Internet of things.
On Tuesday C3 Energy rebranded itself as C3 IoT, a sign that the electricity grid is just one application for technologies that improve the efficiency and functionality of Internet-connected devices. The Redwood City, Calif. company now covets customers from all industries in a bid to bring its sensor-driven smarts to bear.
(The list of target industries on C3’s website is exhaustive: oil and gas, manufacturing, aerospace, automotive, chemical, pharmaceutical, facility operations, telecom, retail, insurance, and financial services, not to mention government, defense, and intelligence agencies.)
To find out more about his plans for the company—and his thoughts on an industry that IDC estimates will be worth $1.7 trillion in 2020—I spoke to Siebel on the phone.
C3 Energy has released the next generation of its C3 Customer Analytics application suite with significant enhancements that advance interactions between utilities and energy retailers across residential, commercial, and large enterprise customers on one fully integrated platform. With this release, utilities and energy retailers can provide their customers a compelling self-service user experience with higher levels of transparency, simplicity, and control than ever before – resulting in increased customer satisfaction, loyalty, and participation in utility-sponsored programs.
“By transitioning from call center and paper-based communications to a comprehensive digital customer experience, utilities can develop cost-effective, targeted engagement strategies that increase participation in utility-sponsored programs, achieve energy efficiency targets, and improve customer satisfaction, acquisition, and retention,” said Ed Abbo, C3 Energy President and Chief Technology Officer. “C3 Energy’s software applications bring together data integration, predictive analytics using machine learning techniques, and customer engagement on a single operating platform to generate insightful and, just as importantly, actionable outcomes.”
C3 Customer Analytics Enhancements
With this announcement, 10 new modules are now available for C3 Residential, C3 Commercial, and C3 Enterprise applications:
Revamped user experience eases customer engagement – now with three clicks or less. More intuitive navigation, improved user task flows, and responsive design allow customers to interact with utilities and complete major actions in less than one minute.
Predictive billing analytics allow proactive energy monitoring and spend management. With support for billing prediction and alerting, customers can see what their bill is likely to be well before the billing cycle ends and be alerted to rising energy usage, projected costs, and tips to improve energy performance. Individually-tailored reports and enhanced charting give customers an accurate view of bill charges and contributing factors.
Three new advanced analytic tools drive customer engagement and more effective energy efficiency programs.
Robust and scalable energy disaggregation algorithms deliver optimally tailored energy efficiency recommendations to customers across millions of homes and businesses. Built by world-leading experts at C3 Energy, the algorithms have achieved industry and academic benchmarks of 98 percent accuracy levels using 15-minute smart meter data, compared to “ground truth” where sensors were put on appliances and equipment to measure accuracy of predictions.
With its universal rate engine C3 Energy now supports all rate types with intuitive visualizations, enabling enhanced analytic outputs, charts, and insights. This gives users the ability to understand rate-specific usage and bill components, and to select the best rates for their needs. The first deployment of this feature was for a leading utility, enabling the utility to manage all rates including time of use, net metering, generation, capacity reservation, demand charges, and demand response events.
Enhanced energy efficiency project integrations enable C3 Residential, C3 Commercial, and C3 Enterprise to surface all projects and actions a customer has completed in the past, such as rebates applied for, with the ability to set goals and track progress. Customers also gain access to commissioned audit reports, ENERGY STAR score management, and Green Button access to energy use data, creating a comprehensive picture of their usage and energy efficiency efforts.
Pre-built loyalty programs make it fast and easy for utilities and energy providers to allow their customers to earn points for taking actions like enrolling in energy-efficiency programs or purchasing products and services, and automatically redeem their points at 300 brands across major retail verticals.
Advanced visualization features enable power users – such as facility managers, franchise owners, residential landlords, and other customers handling multiple buildings and disparate groups of meters – to analyze and download their energy usage and costs at the level of individual meters, accounts, or user-defined groupings of meters and accounts.
Native mobile iOS and Android applications are now integrated with the C3 Energy platform, enabling utilities to use a white-label application to engage their customer for a range of common services – including bill pay, outage communication, reporting, and energy usage and efficiency. These modules can be part of a standalone application or widgets integrated into an existing utility application.
Pre-built integration with MarketoTM, an engagement marketing platform, puts messages, alerts, and notifications linked to predictive analytics in the hands of the end customer, as controlled by the utility or retailer. This makes it even easier to seamlessly deliver relevant information to the right customer on the right device at the right time.
Integration with C3 Energy Intelligence for ad hoc predictive analytics gives users in any business function and of all experience levels access to a web-based interface through which they can discover insights from all their data using compelling visualizations in order to better understand their customers, conduct internal analysis, and inform marketing campaigns.
The new release of C3 Customer Analytics applications first went live this month at AEP, Eversource Energy, and Westar. Eversource, operator of New England’s largest utility system with 3.6 million customers, deployed the applications across two states to date in order to redefine the engagement experience for its residential, small commercial, and large commercial customers and deliver customized insights across the right channels.
When analytics software company C3 Energy emerged from stealth in 2011, expectations ran high. After all, the company’s founder was veteran entrepreneur Tom Siebel, who sold his previous "startup" to Oracle for almost $6 billion.
Four years later, C3 is reporting progress among utilities, including Italy’s biggest power company Enel, and businesses such as Cisco Systems that desire far more accurate status reports about energy consumption across their facilities but don’t have the computing resources to crunch all that data efficiently.
The company has been particularly successful in Europe and Asia, which have moved more quickly to connect smart meters to the "Internet of Energy," Siebel said during a recent interview with GreenBiz. In Europe, C3’s energy analytics applications, delivered through software as a service (SaaS) subscriptions, cover about 80 percent of the market, according to C3.
"We look at the entire grid as a machine, aggregating all of the signals about consumption, billing, real-time weather data, wind, solar radiation," Siebel said. "With this information, we’re able to look at assets, [determine] what will fail next and why, and fix them before they break. The social benefit is obvious, as well as the safety issues."
C3 is one of several companies that sell energy analytics applications that are meant to replace more manual data-crunching methods, such as spreadsheets, that utilities and other organizations use to uncover trends. What differentiates these technologies from smart grid systems of the past is that they also incorporate data collected by sensors and other devices that aren’t necessarily part of the grid itself, but that are connected via the so-called Internet of Things.
"When you are dealing with data sets that are this large, you’re forced into cloud-scale computing," Siebel said.
As a private company, C3 doesn’t report its revenue but it delivered 10 substantial installations during its 2015 fiscal year, according to a June update. That includes a $64.4 million contract to manage more than 44 million smart meters for Enel across Spain and Italy. The utility is using several applications including C3’s predictive maintenance capability, which could result in an annual "economic benefit" of close to $730 million; and its residential energy management platform, which homeowners can use to track consumption information and evaluate suggested efficiency measures.
Ed Abbo, president and chief technology officer for C3, said many of his company’s utility customers use its software to engage more personally with their own customers on strategies meant to reduce power consumption. "Utilities can become much more like Amazon or Google or a consumer Web operation with their recommendations," Abbo said.
One example of a utility embracing this strategy is Eversource Energy (formerly Northeast Utilities), the largest utility in New England with more than 3.6 million electricity and natural gas customers. Eversource invested more than $500 million in energy efficiency initiatives in 2014. It will use C3’s platform to make much more specific recommendations in the future. Previously, it relied on spreadsheets.
"[The software] allows a much more sophisticated segmentation of our market. In the past, our view stopped at the meter," said Tilak Subrahmanian, vice president of energy efficiency for Eversource. It took the better part of a year to get the Eversource application up and running. The installation unifies 12 data sources, using that information to guide energy audits and energy efficiency rebate decisions.
"Energy efficiency has been a cottage industry. There was plenty of awareness at the facility level. What we have done is raise this conversation to the C-suite," Subrahmanian said.
C3 got its start selling energy analytics directly to businesses. At Cisco, for example, the service was used to gather data across about 500 facilities in order to provide the company with more uniform processes for managing its energy budget. In recent months, however, it has focused far more explicitly on utilities. Some big names it works with include Commonwealth Edison, Entergy, Hydro-Quebec, San Diego Gas & Electric, and Pacific Gas and Electric.
Plenty of technology companies are angling for a piece of the broad energy management system market, which will near $60 billion in revenue by 2022, according to an estimate by Grand View Research. Those tackling energy analytics — although not necessarily at the same scale as C3 — include BuildingIQ, FirstFuel, Retroficiency and WegoWise.
View the full article on the GreenBiz website here.
The Internet of Things (IoT) has gained momentum. Sensors are now small and cheap enough to embed in all kinds of devices, and more companies are leveraging the vast data generated. Here are some key drivers your company needs to remember as you jump into IoT.
Gartner expects 6.4 billion "things" will be connected to the Internet in 2016, up 30% from 2015. Although sensors aren't new, they're being built into more types of devices because they are considerably smaller and cheaper than they once were. More organizations, regardless of industry segment, will embrace IoT devices to lower operating costs, increase revenue, or provide more relevant customer experiences. The road to success comes with pitfalls, however, some of which can be avoided or minimized with little effort or cost.
The obvious problem is the sheer volume of data. Cramming every piece of sensor data into an existing data warehouse or a cloud environment probably isn't practical, or even wise.
"The different approaches to data management have revolved around building enterprise data models and integrating data from different places and then making them look the same. That was expensive and cumbersome, but it was doable," said PricewaterhouseCoopers (PwC) partner Oliver Halter, in an interview. "No matter how much money you throw at it, traditional data management, from a process point of view, doesn't work anymore because you get new data sources and new types of data all the time that you have to integrate very rapidly."
Moreover, many organizations have no idea what they would do with IoT data if they had it. If the potential business value can't be defined, there's little that can be gained from adopting even the coolest IoT innovations.
"Before you think about software or technology, what's the business problem you're trying to solve? If you're an executive at one of the companies we work with, you're losing 2% of revenue to fraud or sensor malfunction. And 2% of your revenue may mean $100 million," said Houman Behzadi, senior vice president of products at enterprise application software provider C3 Energy, in an interview. "If you want to be successful, you have to solve a business problem like fraud."
Here are a few of the ways the IoT can impact companies' IT infrastructures and data strategies, and the bottom line.
Machine Learning Is Likely Necessary
The greater the volume of data, the more likely it is that an organization will need to use machine learning to make sense of it.
"With the volume of data we have now, it's no longer a manual or human kind of computation problem. You need a machine to identify the correlations across a significant volume of information so you can do things like predictive maintenance on assets," said Houman Behzadi, SVP of products at hardware and software solution provider C3 Energy.
An East Coast utility company was trying to understand the health of its sensor network, and it was endeavoring to prevent fraud. Using simple analytical rules on data sources, the company was identifying a couple of hundred fraud cases a year, but the method was only 30% accurate. Using machine learning, the utility company was able to identify 20,000 cases immediately, and it eventually achieved a 90% accuracy rate, Behzadi said.
View the full article on InformationWeek's website here.
During the European Utility Week, the company received an award for its digital transformation and focus on service quality
Enel’s digital transformation and its commitment to improving the electricity service provided to its customers have been granted a prestigious acknowledgement at European Utility Week, recently held in Vienna. The global electricity company was given an award in the category “Best Digital Utility Transformation” of the Global Smart Energy Elites, a guide to the most cutting-edge smart energy projects drawn up by Metering&Smart Energy International and presented at the EUW.
“Enel’s commitment to improving grid reliability with the help of the C3 Energy predictive maintenance platform is an excellent example of a utility company that is successfully enacting a digital transformation strategy”, said Metering&Smart Energy International managing editor Claire Volkwyn, explaining the motivation of the award. “In the Global Smart Energy Elites 2015 guide we showed the wonderful work that Enel and other utility companies have performed to make the best use of smart grid transmitted data”.
Enel has developed, in a partnership with C3 Energy (US company that develops software for industrial applications), a predictive maintenance system used in 16,000 power substations in Italy, allowing Enel Distribuzione to accurately predict possible breakdowns in the medium-voltage distribution network. By integrating data from various sources (from the history of past failures to maintenance work history, from the ground and plant morphology to weather conditions), the system manages to update the ‘health status’ of the grid in real time. Thanks to the automatic updating model, a possible breakdown can be predicted and localised in a few seconds. This information allows Enel to carry out efficient inspections and solve possible problems proactively and with considerable savings.
Ed Abbo, C3 Energy president and CTO, said that “Enel is an innovator in the field of smart grids and a world leader in renewable energy. The company keeps on raising the bar in its digital transformation, which allows it to achieve objectives of greater reliability, operational efficiency and cost reduction”.
Livio Gallo, Head of Global Infrastructure and Networks Business Line, commented: ‘This award acknowledges the work we have already done to enhance the quality of our service with big data technologies. It is a welcome reward and further motivation for us to accelerate the process of digitizing our business’.
Enel’s reliability in providing electricity services is confirmed by the SAIDI (System Average Interruption Duration Index) value, the main parameter of quality in energy distribution, which puts the global electricity company at the top of the sector ranking with an average of only 40 minutes per year of interruptions.
Multinational power company Enel last week scooped an award at European Utility Week in the Global Smart Energy Elites 2015 'Best Digital Utility Transformation' category. Enel received the award as part of the 3-day trade event held in Vienna, Austria.The gong coincided with the launch of Metering & Smart Energy International's launch of the Global Smart Energy Elites, a guide to the most innovative smart energy people and projects.
Claire Volkwyn, managing editor of Metering & Smart Energy International, said: “Enel’s efforts to address grid reliability with C3 Energy’s predictive maintenance platform is a prime example of a utility effectively executing its digital transformation strategy.
“In the Global Smart Energy Elites 2015 guide, we are showcasing superb work being done by Enel and other utilities across the globe in leveraging the increasingly data-rich smart grid.”
Enel's digitised substations
Enel Italy teamed with US application software company C3 to deploy its Predictive Maintenance programme across 16,000 substations in Italy. C3 said it designed the deployment for Enel Distribuzione to accurately predict faults on medium voltage electric distribution feeders across Italy.
C3 Predictive Maintenance works by integrating data from 10 source systems: SCADA, maintenance work orders, fault protection, asset management, historical equipment failures, known network issues, power quality, lightning, terrain and vegetation, and weather.
The California-based software developer said it leverages more than 750 analytics to update the asset health score in real-time as data is received, and then uses a machine learning model to predict the probability of feeder faults and pinpoint their locations with increasing precision over time. With this information, Enel is able to conduct efficient inspections and proactively address possible problems, which will drive substantial savings for Enel.
Ed Abbo, president and CTO at C3 Energy, said: “Enel is a smart grid innovator and a leader in renewable energy. The company continues to raise the bar in its digital transformation, which enables it to achieve its goals of greater reliability, operational efficiencies, and cost reductions.” Enel has reportedly achieved high system reliability, with an industry-leading average annual interruption time (SAIDI score) of 40 minutes per customer.
Clean Power Plan Rules, but Utility Industry Faces Plenty of Regulatory Edicts in 2015
Posted By: Rod Walton, Senior Editor
The grid modernization portion was lauded by Ed Abbo, president and chief technical officer at Redwood City, California-based C3 Energy, a six-year-old startup focused on application software in smart grid analytics, cloud computing and data to improve power delivery.
Abbo's boss, C3 Energy CEO Thomas Siebel, told a House subcommittee on energy and power that as much as $2 trillion will be invested globally to upgrade the grid infrastructure throughout this decade, with half of that spent in the U.S. A crucial part of that upgrade will be the addition of sensors needed in meters and other smart grid devices, Abbo echoed. Those sensors, in turn, will cut down on the costs of line loss, energy inefficiencies and give dramatic, informed power back to both the utilities and the customers, he said.
Utilities just need financial encouragement to make those investments. Abbo predicted that the grid modernization bill, if approved, can do just that by allowing companies to move the costs of advanced analytics and cloud-based computing into the rate-paying structure. Previously, many companies have booked those new-era investments as operating expenses rather than capital expenditure costs.
"That's one of the obstacles or hurdles the bill will help remove," Abbo said. "The bill encourages regulators and utilities to treat investments in advanced energy analytics and cloud-based (services) as investments they can get rate recovery on.”
Real-time analytics and sensors can improve reliability, lead to fewer outages and help consumers save money by giving them data on rate costs and usage patterns, he added.
All in all, the modernization act can unlock $50 billion value on both sides of the utility-customer equation, or $300 per meter per year, in C3's estimation.
"There's no need for subsidies," Abbo said. "These are investments that pay off in net positives."
View the full article on Electric Light & Power's website here.
By Barbara Vergetis Lundin
As the "Internet of Things" (IoT) expands, reaching 25 billion connected devices by 2020, according to Gartner, utilities will face an unprecedented volume of data generated from new digital equipment, systems, devices, and sensors on the grid and at their customers' premises. Gartner also predicts that the proliferation of IoT will bring significant new application and data integration challenges as the number of new connections for IoT devices will exceed all other new connections for interoperability and integration combined.
Historically, application and data integration costs -- both first-time and those associated with ongoing maintenance -- have been significant and frequently underestimated, according to Zapthink. The more differences there are in application architectures and different approaches to integrating applications, the more costly the overall integration effort becomes. Both the proliferation of new data sources and the vastly increasing volumes of data being generated by IoT further exacerbate the integration effort, causing these costs to rapidly escalate over the next several years, says Gartner research.
With a platform approach, utilities deploy an integrated-family of cloud-based, smart grid analytics applications built on a common, enterprise data platform. In contrast, utilities could use multiple, independent, on-premise or cloud-based, point applications to address individual, specific use cases.
Taking an enterprise, cloud-based platform approach results in significant cost savings. To estimate the magnitude of these savings, consider a large utility with 10 million customers and three different operating companies. In order to create a comprehensive smart grid analytics capability across the value chain, the utility might need to procure and deploy five different analytics applications. Examples are:
Revenue protection to detect electricity theft.
AMI operations to optimize smart meter deployment and network operation.
Predictive maintenance to prevent asset failure and enhance operational and capital planning.
Voltage optimization to reduce overall system voltage.
Outage management to enable faster response to and better recovery from system outages.
The following analysis illustrates that the cost savings of deploying and maintaining an integrated family of applications built on a common, enterprise, cloud-based platform is up to $189 million over five years. The models and assumptions have been validated with IT operational and financial executives across numerous global utilities.
These cost savings accrue from four areas:
Data integration and implementation.
Hardware and software infrastructure and services.
Hardware and software maintenance, support, and operations.
Procurement of the solutions and support hardware and software.
Data integration and implementation
Gartner has forecasted that, in the coming years, companies will spend more on application integration than on new application systems. A platform approach minimizes these integration costs. Deploying an integrated family of applications that share a common data architecture and cloudbased platform enables a utility to perform a single initial integration without having to repeat the work with the addition of new applications. A platform approach also provides the benefit of being able to flexibly deploy applications either at one time or sequentially over time with little to no incremental effort or cost.
Recent experience has shown that deploying a single smart grid analytics application, whether on a platform or not, requires approximately 25 data source extracts. Adding four more applications on a platform typically requires only an additional 25 data source extracts for a total of 50. Many data sources are shared by different applications on the platform and all of the data are available to all applications deployed on the platform, which results in the minimal number of total extracts.
Recent experience has shown that deploying a single smart grid analytics application, whether on a platform or not, requires approximately 25 data source extracts. Adding four more applications on a platform typically requires only an additional 25 data source extracts for a total of 50. Many data sources are shared by different applications on the platform and all of the data are available to all applications deployed on the platform, which results in the minimal number of total extracts.
Hardware and software infrastructure and services
The platform approach delivered as Software-as-a-Service (SaaS) provides a single complete and fully functional hardware and software infrastructure at no additional cost. The infrastructure and services included in the SaaS model encompass all necessary facilities, equipment, technologies, and administrative personnel needed to run the system, including security, data center, power, hardware, storage, backup, monitoring, maintenance, and support resources.
The SaaS platform approach also provides ongoing maintenance, support, and operations at no additional cost. The incremental internal utility IT personnel requirements are minimal because the applications share the same infrastructure, data model, analytics platform, and user interface.
Further, deploying an integrated family of cloud-based applications across multiple operating companies requires only a single procurement process for the platform. The procurement cost is directly proportional to the number of applications. The scaling factors B and D described in Figure 2 determine the degree of interdependency between individual point solutions, and therefore the extent to which data integration and ongoing maintenance costs grow as the number of applications grow. Mathematically, they determine the strength of the growth as a function of the square of the number of applications.
The scaling factors A, A', and C determine the degree of synergy between the applications within an integrated, cloud-based, enterprise platform, and, therefore, the extent to which data integrated for one application can be used for another application. Mathematically, they determine how quickly the total cost of each additional application decreases relative to the previous application.
Imagine two scenarios in which a large energy company deploys smart grid analytics applications across three utility operating companies with approximately 10 million customers. In one scenario, the company deploys an integrated family of smart grid analytics solutions built on an enterprise, cloud-based platform. In the other, it deploys five independent, on-premise smart grid analyt-ics applications from different vendors, each with its own hardware and software infrastructures.
Table 1 compares the five-year costs (not including the software licensing fees of the applications themselves) between the two scenarios and shows a difference of approximately $189 million.
Additional costs accrue due to the much higher execution risk for each individual application deployment relative to the platform deployment. Assuming a 25 percent risk of failure for the point solutions collectively, compared to a 5 percent risk of failure for the enterprise platform, the value of the lower risk is approximately $49 million, yielding a risk-adjusted total cost savings of $238 million.
Comparison of costs of deploying an integrated family of cloud-based, smart grid analytics applications built on a common, enterprise data platform with that of deploying and maintaining multiple, independent, on-premise point software applications.
On-Premise vs. Cloud
The analysis here compares the costs of deploying and maintaining a family of cloud-based applications built on a common data platform with that of deploying and maintaining independent on-premise applications. A large fraction of the total cost savings is due to avoided hardware and software expense because of a cloud-based solution. However, even if the individual point solutions are provided through a cloud-based model that includes all of the supporting hardware and software infrastructure (but not certain supporting application functionality provided by a platform solution), the cost savings of a platform approach are still significant -- reaching approximately $69 million. (See Table 2)
Significant up-front and ongoing costs, in the range of $69 million to $189 million over five years, can be avoided by taking the platform approach, as a result of lower cost application and data integration costs; avoided hardware and software infrastructure costs; lower ongoing maintenance, support, and operations costs; and avoided procurement expenses.
This estimate is not just theoretical. Examples of cloud-based smart grid analytics applications built on a common, enterprise data platform exist in large-scale production today at utilities such as Pacific Gas & Electric (PG&E), Exelon and Enel. By expanding the use of these enterprise platforms, utilities stand to reap significant cost savings as they simultaneously capture value from the increasing volume of data on the grid.
By Tom Siebel
The “Internet of Things” (IoT) is creating a buzz across industries. It describes the integration of an advanced, interconnected infor-mation backbone into the functioning of physical devices, systems, and infrastructures. It is the convergence of the virtual and the physical. At a basic level, IoT applies the Internet
as we know it to wirelessly connect machines, devices, systems, and other “things.” IoT will be transformational, and Gartner predicts that, by 2020, 25 billion things will be connected in industries ranging from automo-tive to food and beverage services.
In the energy industry, the momentum of IoT is having a tremendous impact as the grid becomes sensored, connected, and smarter. The “Internet of Energy” applies the premise of IoT to the infra-structure of the grid and is driving the acceleration of the dynamic smart grid.
The Advent of the Smart Grid Nearly 40 years ago, a Harvard sociol-ogist predicted the advent of the Infor-mation Age. Years before the invention of the Internet, minicomputer, personal computer, and smart phone, Daniel Bell authored “The Coming of Post-Industrial Society.” He predicted that information and communications technology would cause a fundamental change in the structure of the global economy— a change as signiﬁcant as the Industrial Revolution.
The Information Age, as we know it today, describes the free, nearly instantaneous transfer and access of data. It predicated the preeminence of the “knowledge worker” and resulted in the emergence and continued growth of information technology (IT). It drives ubiquitous changes in the ways we communicate, with lasting effects on professional and leisure activities.
With the genesis of the smart grid, Bell’s predictions from four decades ago are having a direct impact on today’s energy systems. The National Academy of Engineers identified the electric grid as the
most significant scientiﬁc achieve-ment of the 20th century. The smart grid will be the largest and most complex machine ever conceived and will likely prove one of the most significant scientific achievements of the 21st century.
It is estimated that as much as $2 trillion is being invested this decade in upgrading the power infrastructure globally to add sensors to the devices throughout the grid, creating part of what has come to be known as the IoT. These newly sensored things or devices are the basis for the physical infrastructure of the smart grid and include smart meters; thermostats; home appliances; heating, ventilation, and air conditioning equipment; factory equipment and machinery; transformers; substations; distribution feeders; and power generation and control compo-nents. Once sensored, these devices become remotely machine addressable, meaning information can be sent and received across a computer network.
Taking smart meters as one exam-ple, it is clear that the smart grid is advancing apace. As of 2014, nearly 400 million smart meters have been installed globally, according to Navigant Research. That number will more than double in the coming decade. Repre-senting a fraction of the sensors on the grid infrastructure, smart meter installations serve as a proxy for the penetration and growth rate of the smart grid.
The “smart” sensored devices in and of themselves provide little utility. They simply provide the capability to remotely sense and/or change a device’s state. For example, is the device operative
or inoperative? If operative, at what temperature, voltage, or amperage?
It might allow us to know the amount of energy that the device has consumed or recorded over some period of time or is consuming in real time.
Collectively, these devices generate massive amounts of information—an increase of six orders of magnitude from before the connected grid. As utilities adapt from managing a relatively small number of non-communicating devices to connecting hundreds of millions of diverse sensored devices, data volumes are expanding exponentially. To effectively aggregate and manage this inﬂux of data, utilities require next-generation technologies to integrate, process, apply analytics, and intuitively visualize the data and analytic results in a way that drives business outcomes through a common data- and intelligence-driven solution.
By applying technologies and techniques commonly used by Google, Amazon, Netﬂ ix, and Twitter in the consumer industry, utilities can collect and aggregate the sum of increasing volumes of data to correlate and scientifically analyze all of the information generated by the smart grid infrastructure in real time. Computer science techniques, including elastic cloud computing, machine learning, and social human-computer interaction models, are now being applied to challenges utilities have faced for years, such as managing the operational health of advanced metering infrastructure (AMI) assets and preventing revenue loss due to theft and meter malfunctions.
Utilities can apply the same technology concepts that Twitter uses to process 15 million tweets per second or Netﬂ ix uses to stream more than one billion hours of videos per month to integrate, aggregate, and analyze the massive amounts of incoming data. One such powerful computer science technique is machine learning, or the ability for computers to learn without being explicitly programmed. Machine learning simply uses mathe-matical equations known as algorithms that can learn from data. The algo-rithms are trained on historical data to make predictions. After predictions are made, actual conﬁ rmed results are fed back into a machine-learning algorithm to reﬁne it. As a result, over time, it “learns” and evolves so that the analyses generated are increasingly accurate, reﬂecting real-world conditions specific to the utility.
Machine learning is used to classify assets at high risk of failure, segment customers for targeted marketing campaigns, identify non-technical loss (which includes measurement errors, recording errors, theft, and timing differences), and predict future load, among many other applications. For example, like a credit card company can use historical spending data to ﬂ ag potential fraud, utilities can use a variety of historical and real-time data to identify cases of energy theft. Baltimore Gas and Electric Company (BGE) proved this use case when it deployed the C3 Revenue Protection™ application across its full two-million-meter service territory. In six months, the solution identiﬁed more than 8,000 new cases of potential theft, higher than its original goal.
Leveraging not only machine learning but also a full stack of tools asso-ciated with the science of big data, analytics enabled by the smart grid provide efﬁciencies across the energy value chain. Examples far outreach revenue protection and include:
real-time pricing signals to energy consumers;
management of sophisticated energy efﬁciency and demand response programs;
conservation of energy use;
reduction of fuel necessary to power the grid;
real-time reconﬁguration of the power network around points of failure;
instantaneous recovery from power interruptions;
accurate prediction of load;
efficient management of distributed generation capacity;
rapid recovery from damage inﬂicted by weather events and system failures;
reduction of fuel needed to power the grid;
and substantial reduction in adverse environmental impacts.
Data Analytics Solutions
Data analytics solutions for utilities must integrate massive amounts of disparate data, apply sophisticated multi-layered analytics, and provide highly usable portals that generate actionable real-time insights. Utilities need end-to-end system visibility across supply-side and demand-side smart grid operations.
Data analytics enable grid operators to realize dramatic advances in safety, reliability, cost efficiency, and environmental benefits by correlating and analyzing all of the dynamics and inter-actions associated with the end-to-end power infrastructure as a fully interconnected and sensored network, including current and predicted demand, consumption, electric vehicle load, distributed generation capacity, technical and non-technical losses, weather reports and forecasts, and generation capacity across the entire value chain. In another example from BGE, the utility used the C3 AMI Operations™ application to identify 3,600 meter health issues with 99-percent accuracy in order to stream-line critical maintenance on AMI assets.
The growth of the smart grid and the necessity for next-generation analytics solutions are not limited to the United States. The European market is seeing strong drivers for analytics, including the increased number of smart meter deployments in Italy, the United Kingdom, France, and Spain, and the European Union’s recommendation
of 80-percent smart meter penetration in member countries by 2020. Enel, a leading integrated player in the world’s power and gas markets with the largest customer base (61 million) among its European peers, is deploying data analytics solutions to enable smart grid and smart city services. A smart grid pioneer, Enel was the ﬁrst utility in the world to replace traditional electromechanical meters with digital smart meters, a major operation carried out among Enel’s entire Italian customer base. By 2006, Enel had installed 32 million smart meters across Italy; Enel has since deployed a total of approximately 40 million smart meters in Europe, representing more than 80 percent of the total smart meters on the continent.
To optimize the monitoring of energy ﬂows, Enel has deployed one of C3 Energy’s data-analytics applications across one million meters in Italy. Implemented in less than eight months, the solution ultimately identified 93 percent of Enel’s already-known operational issues through the initial deployment.
For Enel, C3 Energy integrated, normalized, and aggregated more than 50 billion rows of data from 11 Enel sources, including the customer information system, billing system, work order system, outage management system, producer system, meter data management system, validated theft-case data, external weather data, and Google for address veriﬁcation.
Leveraging investments in analytical algorithms, machine learning, data integration, and cloud-scale infrastructure, Enel deployed 55 unique and sophisticated energy ﬂow analytics to identify anomalous meter activity. The company is leveraging these analytics to execute rule-based and machine-learning algorithms to unlock insights from both batch and streaming data, and to generate increasingly targeted and accurate results.
The initial deployment proved that the data-analytics solution could readily handle Enel’s smart grid data processing and aggregation needs. Based on the results from the one-million-meter demonstration, Enel and C3 Energy are working to expand the deployment of this solution more widely across the group’s distribution network. Enel also is installing additional applications to expand on what will be the largest deployment of software-as-a-service smart grid analytics in the world.
Leading utilities are driving innovation toward the Internet of Energy. They are at the cutting edge of technology advancements and are realizing significant returns by applying data-analytics solutions that combine the sciences of cloud-scale computing, advanced smart grid analytics, and machine learning to the benefit of their communities, consumers, stake-holders, and the environment.
By Ed Abbo
The rapid growth of hardware investments in smart grid opens up a new opportunity for utilities to take advantage of next-generation information technology, such as cloud computing, to fully unlock the insights and value that a modern grid has to offer. However, outdated state rate regulations and accounting rules, have not kept pace with, and actually impede, the ability of utilities to benefit from the new IT models that will substantially improve system performance, reduce capital and operating costs and hardware risk, and produce substantial economic value to utility customers and shareholders. Under current guidelines, utilities may classify investments in legacy hardware and supporting on-premise software as a capital expense, which can be included as part of the rate on which it can receive a return. Counterintuitively, if a utility wants to invest in state-of-the-art cloud-based technologies that both enhance the performance of legacy and new hardware systems and that eliminate the need for continual procurement of more expensive new IT hardware, a utility typically must treat the investment as an operating expense for which it does not receive a rate of return. This difference in treatment creates a perverse incentive to pursue more costly, less effective, and riskier on-premise technology investments and deprives rate payers of the immense performance and economic benefits of the more advanced technology innovations that many other sectors are now experiencing. A simple update of rate regulation and accounting rules can fix this problem.
This decade, utilities are investing billions of dollars to make the devices in the power grid remotely IP-addressable, including, for example, the nearly 1.1 billion smart meters that will be installed by 2022, according to Navigant Research. While representing only a fraction of the sensored devices on the grid, the number of smart meters provides a good indication of the growth rate of the smart grid.
All of these hardware advances, however, are of limited usefulness without the cloud-based software innovations that will actually make the smart grid 'smart.' As the grid increasingly becomes sensored, an unprecedented amount of data are produced, which can only be addressed using the most state-of-the-art information technology. IT offerings have rapidly evolved to today's innovative cloud computing models, including Software as a Service, Platform as a Service, and Infrastructure as a Service. With these, come opportunities to leverage numerous capabilities essential to fulfilling the promise of the smart grid - continuous access to increased processing speeds and power, more flexibility and mobility, elasticity/on-demand surge capacity, and lower costs through scale.
However, the U.S. regulatory and accounting treatment of cloud computing models has not kept pace to take advantage of this technology opportunity, and utilities are faced with undue consequences when they select a cloud computing offering because cloud computing and on-premise software solutions are treated quite differently. The existing guidelines are based on 20-year-old business models, which classify last-generation on-premise software licenses as a capital expense, and modern cloud computing arrangements as an operating expense. The classification as a capital versus operating expense influences a utility's ability to obtain rate-base coverage consistent with other capital expenditures and incentivizes investments in antiquated technology.
In order to accelerate the goal of a modern electric transmission and distribution system, advanced cloud-based IT offerings are necessary. Regulation should respond to remove illogical barriers and provide the same incentive to deploy cost-saving, highperforming software systems that a utility already receives for investing in other technologies or smarter equipment.
The traditional software model provides a physical copy of the product on-premise under a license agreement. The license allows the vendor to restrict use of the software, for example by limiting access to a certain number of users or installation to a certain number of servers, and preventing reverse engineering.
These licenses are typically structured as 'perpetual' or 'term' arrangements. A perpetual license is a right to use software for an unlimited period of time - it is paid for once and does not have to be renewed. A term license is a right to use software for a specified period of time and requires renewal of the license at the end of the term for continued use.
Both perpetual and term licenses typically include an annual maintenance arrangement to support updates, ongoing customer service, and other incidental activities, but the responsibility for the application upgrades, patching, administration, and hardware infrastructure operation and management is left to the utility. The distinguishing feature for utility IT teams is that the software vendor grants the use of a copy of the software under the license arrangement, but the teams must manage the operation of the software.
Over the last decade, a rapidly growing number of companies have shifted from buying these on-premise software components under perpetual or term licenses, to leveraging software built, managed, and continually improved by someone else. These companies are replacing traditional on-premise software applications and platforms - even underlying IT infrastructures - with the same kind of cloud-based solutions, or cloud computing. Cloud computing refers to the use of Internet-based computing to deliver a variety of product offerings. Under cloud computing arrangements, the customer has a right to use or benefit from the functionality of software but does not receive a copy of it. These arrangements are typically structured under subscription models.
Under a subscription, the software vendor agrees to deliver one or more of its software products at the time of contract, and unspecified additional software updates during the term of the subscription. A subscription differs from a perpetual or term license in that it provides customers with a turnkey solution that includes application management, monitoring, patching, and upgrades as well as hardware infrastructure and operations. While these software applications can provide similar solutions to on-premise software, they have the added enhancements and benefits of the mobility, scalability, and elasticity of the cloud.
The most common cloud computing models for utilities are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (laaS). With a Saas model, utilities pay to use an Internet-based software product hosted by the Saas solution provider. Saas solutions used commonly by utilities today include applications such as C3 Energy for smart grid analytics, Esri ArcGIS for geographic information systems, and SmartGridCIS for billing and customer information systems. Typically, Saas solutions are service-based, scalable and elastic, and metered by use. By 2016, IDC estimates that Saas solutions will constitute about 14.2 percent of all software spending and 18 percent of all applications spending, with a compound annual growth rate of 21.3 percent.
PaaS models are more commonly used by developers. With these solutions, utilities pay to use a web-based platform hosted by a software vendor or a third party to design, develop, and test their own applications. The most common examples of PaaS solutions in use today include Salesforce.com and Microsoft Azure. Specific to big data and the energy market, C3 Energy's data analytics platform has also been designed as a PaaS solution.
Finally, laaS allows utilities to pay to use a virtualized service environment such as computers, systems, hardware, network bandwidth, etc. maintained by a vendor. Utilities can rent (rather than own their own) servers or operating systems to run their choice of software solutions. According to a KMPG analysis, implementation of laaS can save 30 to 60 percent of IT infrastructure costs. Amazon Web Services is the current leader in this area.
In each of these models, the solutions are basically rented by a utility instead of purchased outright. This allows utilities access to the latest advances in technology, mobility, elasticity, and scalability to realize operational efficiencies. Without having to invest in hardware and software to meet their maximum requirements upfront. For example, utilities can increase capacity on-demand to meet specific timelines and requirements and then scale back as appropriate. However, regulation has not kept apace, and despite the efficiencies available, utilities are disincentivized to invest in these solutions and are conversely motivated to continue with obsolete technology investments.
Accounting for the Cost of Cloud Computing
Currently, U.S. generally accepted accounting principles (GAAP) do not have specific guidance that addresses accounting for cloud computing arrangements, so utility regulators have no clear roadmap. This results in differing representations of on-premise and cloud computing arrangements in financial statements.
With no explicit guidance, utilities are following 20-year-old business and technology models, with the following disparate result:
Perpetual software license: Capital expense
Saas license: Operational expense
Term License: Operational or capital expense, depending on the arrangement
One-off treatment as an approved regulatory asset: Capital expense
These differences in accounting classifications are inconsistent, given the similarities of the solutions. Both arrangements are similar in:
the rights conveyed and restrictions imposed;
the benefits derived;
the nature of the arrangements whereby a customer is granted the right to use software over a specified time; and
the maintenance, upgrades, enhancements and support often included in both types of contracts.
On-premise license arrangements treated as a capital expenditure are recognized as intangible assets at inception of the arrangement and amortized over the life of the arrangement. Cloud computing arrangements are accounted for as executory contracts by a majority of utilities and recognized as operating expenses over the term of the arrangement. The resulting difference in accounting treatment is prohibiting utilities and their customers to access the added benefits and technology innovation inherent in cloud computing.
If a utility licenses software in conjunction with investment in operating equipment (meters, substations, sensoring on distribution system, etc.), then both the hardware and software investments are typically capitalized as a bundle. For example, if a utility purchases smart meters that have an analytics layer bundled into it both the hardware and software are categorized as a capital expense. However, if a utility wants to license software that improves performance of existing operating equipment, independently of a hardware purchase, than the utility must go through a non-optimal path to achieve capital treatment of the software investment.
In addition, an on-premise software license model also requires a significant capital investment in IT hardware (servers, storage, etc.), which rapidly becomes obsolete, but in the Saas model the acquisition of IT hardware is not necessary as it is bundled in the Saas model, and can take advantage of continuous advances and investments in higher performing IT hardware owned and managed by cloud service providers.
The work-around for some utilities wishing to capitalize Saas arrangements has been to characterize the arrangement as a term license and justify capital treatment by analogy, using capital lease rules. This approach is not as clear as it would be for a perpetual license, and in many cases not optimal for the utility.
Instead of utilities being burdened with confusion and inconsistencies on their balance sheets, rate regulations should catch up with software innovations in order to accelerate the goal of a modern transmission and distribution system. Regulators must understand the issue at stake and create regulations that support utilities in ways that deliver even greater benefits to their customers.
Utilities should not be penalized or discouraged from investing in technology advancements. Instead, utilities should be leading the way to a more modernized electric system. In order to do so, they need simple clarifications on rate recovery rules on a national or state by-state basis to support a model rule for capital treatment of cloud computing solutions.
To move forward, utility regulator agencies and GAAP should recognize Saas license arrangements as a capital expenditure rather than an operating expense. This change would accelerate the adoption curve and accessibility of today's innovative computing models and unlock the scalability, elasticity, performance power, integration speeds, and cost benefits for utilities and their customers. The classification of Saas as a capital expense would also reduce the current, unnecessary barriers towards technology advancement in the utility industry, which is an essential step in the transformation to a smarter, more efficient, and more sustainable energy system.