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This is the second time Siebel has been honored as Entrepreneur of the Year. As Chairman and CEO of Siebel Systems, he was cited as Ernst & Young’s 2003 “Master Entrepreneur” for founding and managing one of the most successful software companies in history and pioneering the customer relationship management (CRM) market.
Between 1999 and 2003, Siebel received several accolades as the leader of one of the fastest-growing and most influential companies from BusinessWeek, Deloitte & Touche, Fortune, Harvard Business School, Investor’s Business Daily, and other industry observers. In 2016, Siebel received the Most Admired CEO Lifetime Achievement Award from the San Francisco Business Times.
As C3 IoT CEO, Siebel is once again working on a market leadership position in one of the fastest-growing software markets in the history of information technology. The market for AI and IoT applications is projected to reach $250 billion by 2025, driven by CEO-led mandates for digital transformation initiatives.
C3 IoT is aiming at this growing demand by enabling large industrial and commercial organizations to build and deploy next-generation software applications that exploit big data, predictive analytics, AI, machine learning and IoT across the enterprise for productivity improvements, new business creation and competitive differentiation.
Under Siebel's leadership, C3 IoT claims it has built the industry's only platform as a service (PaaS) for AI and IoT applications--with 14 patents pending globally--that is proven at enterprise scale with large-scale deployments worldwide.
Siebel told eWEEK in that his company already has nearly 30 working installations of his company’s platform, including a multimillion-dollar system sold a year ago to Paris-based energy provider ENGIE. ENGIE selected the company's platform and applications as the tech foundation for its global enterprise-wide transformation plan.
C3 IoT is providing ENGIE with the necessary power, scalability and flexibility to apply machine-learning and advanced real-time analytics to very large petabyte-scale data sets, Siebel said.
C3 IoT: A Leg Up on Bigger Competitors?
The company claims it has a lead in working industrial installments over larger competitors.
It’s true Predix has been treading water for a while in the market, but there are also signs that it is now getting some customers. The platform’s new Allsites energy management system, for example, has been installed in about 4,500 of banking giant JPMorgan Chase's U.S. branches, and the financial services company says it is saving energy and dollars right off the bat.
GE thinks AllSites will do for factories what Apple's iOS and Google's Android did for smartphones. It uses sensors, software and lighting controls to curb electricity and gas usage at Chase branches by 15 percent, projecting the savings of about $200 million over 10 years.
Such is the potential power of the IoT, and C3 IoT is right in the middle of it all.
C3 IoT also has provided significant customer projects for financial services consumer spend prediction, discrete manufacturing dynamic inventory optimization and supply network risk, healthcare chronic disease prediction, oil and gas predictive maintenance, renewable and thermal power generation and optimization and data lakes.
The company offers C3 Ex Machina, a visual analytics and machine learning development tool that simplifies and speeds big data exploration and predictive analytics modeling. C3 Ex Machina empowers data scientists and business analysts to extract actionable business insights quickly--without writing any code. It also offers native support for Python and R, allowing data scientists to leverage the programming language of their choice and push their code back to production in the C3 IoT Platform without rewriting any code.
Siebel’s firm is expanding on the AI and machine learning capabilities currently integrated in its platform with additional deep learning technologies and more advanced analyses that increase the precision and accuracy of predictions. C3 IoT also added: image processing for object and facial recognition at the edge; natural language processing (NLP) for analyzing text-based data such as handwritten notes and work logs; expanded support for libraries of machine learning algorithms; and a machine learning pipeline that makes it faster and easier to develop and deploy machine learning models and publish them back to the platform.
C3 IoT results for fiscal year 2017, ended March 31, 2017, included 600 percent year-over-year bookings growth, 65 percent revenue growth year over year, and cash-positive operations.
So the early returns are in: Little C3 IoT is carving out a leadership role in the first inning of the IoT era, and a lot of the big guys find themselves chasing it.
Tom Siebel is the main reason for this. We’ll continue to keep a close eye on this sector at eWEEK.
Thought leader Esteban Kolsky takes on the big question: What will data platforms look like now that big data's hype is over and big data "solutions" are at hand? This is the second part beckoning.
Last week, I ran my friend and thought leader Esteban Kolsky's first part on how to think about data in a post-big data world -- and it was a hit. Now, to end the suspense, we have part two, where EK looks at how data impacts B2C and B2B differently and what has to be done with that data. All this came as a result of research Esteban was asked to do by Radius, as I mentioned last week. Kudos to them for inspiring this excellent piece.
So, now, Esteban, onto part two.
What did you think of the last post on evolution of data?
If you know where you came from, you know where you are going. And to see where we are going, we need this second part: How have data platforms evolved?
Data has been the "blood" of business since the early days of computing in the 1960s. Along the way changes brought different tools to collect, store, process, and manage data, all the while not asking the essential questions: Why are we doing this? Why do we need data? What are we doing with it? How do I know if we are doing the right things?
There is a difference in how data affects traditional mass market (B2C) organizations and those that sell to other businesses (B2B). There are issues related not just to the potential size of the market (a B2C company targeting hundreds of millions of potential customers versus a business targeting a few hundreds to a few thousands of other organizations) but also the complexity of the data models used.
We've had data aggregation happen in mass market organizations (buying and aggregating credit card information, for example, or collecting and sharing loyalty information about customers' needs and actions) for a long time -- we call that segment differentiation in B2C organizations. While this aggregation is interesting for those organizations, it is also far simpler than doing it for B2B worlds. And the tools necessary to solve those problems are focused on managing large quantities, not in focusing on the best data.
In a B2B world, the problem becomes more complex and requires better tools and processes to be resolved. We cannot say that, for example, 120 of our 200 potential targets belong to the same segment. It becomes impossible to differentiate and very hard to serve properly.
We need better data models that are more focused on our sales processes and our customers' intents.
The amount of data is not a problem in B2B, as in B2C markets, because the potential markets are far smaller, making the data easier to find, but the quality and aggregation of the data represent a bigger challenge. This is where data platforms began to shine.
A combination of easy access to the right data for multiple purposes and generating effective insights is what makes data platforms and insight engines so powerful -- not just the data aggregation. It is not the amount of data stored and potentially used, but the necessary data that is used at the appropriate time. We need to rely on aggregated data to optimize processes and on the and insights generated from those transactions.
The chart shows the evolution of data platforms and data storage over time, including the pros and cons of each. It also includes guidelines as to what each model can accomplish and how it works best.
Matching these tools to the planned outcomes from using data is the first step in generating insights and this is not without problems.
1. Trusted data aggregation: When organizations have too much data from too many sources, some of the datum may overlap and even conflict. Using insights as the outcome of aggregating data in platforms differentiates between trusted data sources based on the outcomes of the processes and those that should not be used as much.
2. Simple access and updates: Just because the data was collected, aggregated, and stored does not mean that the data is never going to change. In our always-on-the-go world, data changes as often as many times a day (in case of operational data) to every few weeks (in case of segmentation or identifying data).
3. Optimized data use: Business functions rely on having the most accurate and most current data to make the proper decisions. Businesses in the digital era demand the right data at the right time, to make the right decisions.
Until now, organizations have used most of the tools described in the chart to aggregate, consolidate, and centralize data in different versions of platforms used by myriad processes and functions. While this has given them a starting point and the illusion of movement and progress, the reality is that for B2B organizations making data-based decisions in real time requires not just more data but better-quality data and insights. Tools that simply focus on aggregating data regardless of the use of it don't understand what's needed and can't do the job.
Master data management, for example, is a discipline and set of tools that focused on aggregating as much data as possible. This is done for creating a better centralized store of data that then becomes "the single source of truth." While it creates massive, optimized data stores, there is no purpose or knowledge of the outcome, thus it misses the mark on knowing or highlighting what data to collect, store, and use for each different process.
Customer data platforms are a more modern model and intends to solve the problem of MDM systems by going beyond simply creating a single source of truth to focus on uses for that data. It consolidates data, provides access to many different systems, and ensures that data flows freely from A to Z and is used appropriately in between for known processes. While it does a good job of creating an ODS (operational data store) on the cloud, it fails in the same places where huge data stores failed: It does not know what happened to the data once it was used, whether it was good or needs to be updated or improved, and what were the outcomes.
Very often, data-use initiatives are focused on achieving one or more KPI change: Increase revenue, decrease costs, generate more customers, and many others. Traditionally, methodologies already exist for achieving these simple outcomes. For example, to acquire more customers, the steps are simple: Identify a target segment, understand what they need, create an offering that fulfills that need, generate marketing to match the need and identify customers, implement high-pressure sales tactics, and close the deal.
Thus, the next time more customers are needed, a variant of the above will be implemented, and results will be there. It has proven to work well so many times, it will continue to be repeated -- usually the same way as before. With data platforms and aggregated data, the system can optimize the above model so that it reflects both real-time needs as well as lessons learned and insights from past occurrences.
If an organization wanted to optimize or transform based on lessons learned, it would create some sort of report post-event and analyze what could've been done differently. This is a way to generate delayed insights (or post-facto insights). It works but does not help optimization since by the time we learned what needs to be done, the event is over, and changes cannot be made anymore.
Learnings and changes can be made in near real-time using real-time insights, artificial intelligence, and advanced analytics. Optimizations happen quickly, and results are captured dynamically, creating the insights that help improve the event this time and every other time. Campaigns can be optimized with a better message, sale cycles can use updated pricing and even bundling, marketers can use better content that has seen results, and so forth.
Instead of waiting until the end and potentially the next event to see if changes worked (and in the process ignore the fact that conditions changed already between events), an organization can use insights from aligning the right data, the right processes, and the right outcomes to improve operations on the fly.
Of course, to do this requires not just a different set of tools (not focused on storing and aggregating data only) but also a different mentality. And a different methodology.
And for that, we have a framework -- but you will have to download the paper to see what it is.
Back to you, my friend.
Thank you, Esteban. This was awesome. Come back if you want to expand on this -- anytime.
NOTICE: The CRM Watchlist 2019 registration and the registration for The Emergence Maturity Index Award for 2019 is closing on Sept. 30 with no extensions possible. So, if you want to make sure that you are part of these (see the links in the names for the details), then you have roughly two weeks to go (a little less). I'd do it, if I were you, though I'm not. You, that is.
To request the registration form for either of them, please email me at mailto:[email protected].
Reactive, real-time applications require real-time, eventful data flows. This is the premise on which a number of streaming frameworks have proliferated. The latest milestone was adding ACID capabilities, so let us take stock of where we are in this journey down the stream -- or river.
Making sense of the vast amounts of data gathered by businesses is a problem for business that Iguazio says it's cracked.
Two comic books out this week from DC Entertainment are poking fun at the upcoming United States elections, but in "bittersweet" ways that one of the writers says will "play to a range of emotions."
It's perhaps fitting that the mudslinging nature of this year's presidential election, which will be decided on November 8, has provided fodder for a satirical story in The Flintstones #5 by Mark Russell and Steve Pugh. It's also coinciding with Russell's reunion with Prez (and artist Ben Caldwell), for a short in Catwoman: Election Night.
Self-described "semi-neutral" Canadian writer Meredith Finch and artist Shane Davis will provide some Gotham City-based metaphors for this year's presidential election in the lead story of Catwoman: Election Night, with the Penguin standing in for Donald Trump and a new character representing Hillary Clinton as the tworun for mayor.
Newsarama talked to Finch and Russell about their stories, how they're portraying the two presidential candidates in new ways, and how Catwoman and the Flintstones react to the world of politics.
Newsarama: Mark and Meredith, the election is rarely a fun topic for people, but are you guys attempting to make it more entertaining?
Mark Russell: Yeah, that's the idea.
Nrama: Where did the idea come from? Obviously, Mark, you've played with this before in Prez, but how did Catwoman come into the equation?
Meredith Finch: I was talking about a Catwoman story with DC and the option of doing something to do with the election came up, and I loved it. I'm Canadian, so I get to do it from a third party perspective. So I get to sit back and watch what's happening. So I thought it would be fun to take the approach and try to be as neutral as you can be, because we're ultimately, we're not neutral up here. Whatever happens south of our borders affects us. But initially, the idea was to take a semi-neutral approach and present both candidates in kind of a caricature.
Nrama: Where does Catwoman stand in all this?
Finch: Catwoman stands where she always stand, which is for No. 1. She always takes care of herself, and in this particular instance, the election is really secondary to the fact that somebody's trying to mess with somebody who's important to her. And she will blow it all up if she has to, to protect the person that she cares about.
I think people can really get behind that, because it's not very often that you get to read about a character that Catwoman has a real affinity for. We know she has a relationship with Batman, but one of my favorite things about doing this story was that I got to add a person of meaning to Catwoman into her lore.
Nrama: But this is not the election that people might suspect - Catwoman isn't dealing with presidential candidates. This is in Gotham City, right?
Finch: Right, it's the election for the mayor of Gotham. And we have Penguin, who's running as our Donald Trump-esque character, and then we came up with a completely new character to represent Hillary Clinton, and her name is Constance Hill.
So we tried to be reflective of the bad, or the weaknesses, of both candidates within the characters in the issue. And in the end, we show that, for Catwoman, what it's about is not Gotham City, but her and the people that she loves.
Nrama: So Mark, how did you get in on this, and where did the ideas that you're utilizing in The Flintstones come from?
Russell: Well, DC just told me that, for the November issue, they wanted something a little election-themed for The Flintstones, which was no problem for me, because I think everything I do in The Flintstones at least has a little bit of political or social commentary embedded in it.
My election allegory was kind of split between a general election in Bedrock for the new mayor, and the mayor is a scion of a more powerful person, and then also the middle school elections at the school - the class elections - in which the leading candidate is Ralph the bully, who's a not-too-subtle reference, of course, to Donald Trump.
So I really just sort of tried to parody what I think the problems and frailties of our electoral process are in those elections.
It basically boils down to people's gullibility. People are willfully misled, and they kind of follow their excitement at the expense of their reason, which I think is the big failing in democratic politics, is that people are easily tittilated and misled.
Nrama: Interesting. So I take it that the characters in The Flintstones are easily manipulated and misled?
Russell: Yeah, generally. You know, civilization is new to the people of Bedrock, so they have an excuse that we do not. But yeah, generally, they're chasers. They're all about what the new flavor of the week is. Or whatever the new promise is. There's a new mall that opens up, and everybody's all about the mall. Someone makes a big promise in an election that sounds good to them, and they abandon their reason and their experience of past mistakes that have been made by that sort of rhetoric to embrace it wholeheartedly.
In a lot of ways, people of Bedrock are just an amplified version of the American public.
Nrama: And this Catwoman: Election Night also returns you to the character from Prez.
Russell: Yeah, it's just sort of an additional Prez story. It doesn't really wrap up the storylines from the original Prez, but it does give readers and fans one more Prez story.
And it shows Beth Ross a little further on in her progression as a politician. She's a little more savvy now. She's a little more calculated, and she knows how to, like, turn disadvantages to her advantage. I think that's what you see in this special election issue, is a Beth Ross who is no longer an ingenue, but somebody who knows how to work the system to her favor.
Nrama: Yet the way that she was elected is representative of what you were talking about before with Bedrock. Beth Ross was the hot new thing and got elected president, right? People were just following a trend?
Russell: Yeah, exactly. But in her case, it just happened to have some good outcomes, in that she turns out to be a capable president.
But it's all predicated on this idea that people are fickle and they don't really think things through when they're considering their votes.
Nrama: What about the artist on these stories? What can you tell us about their contribution to the stories?
Finch: Well, if you give me a chance to talk about the artist, I'm going to gush on and on. Shane Davis is the artist on the book, and he did phenomenal work. His use of shadows - I guess this comes from living with an artist, but those are the things that I pay attention to. But he does some really cool things with shadows. And I know he was heavily influenced by Tim Sale and the way he used Catwoman's tail and her whip.
For me, as much fun as it is writing the book, it's almost more fun seeing it realized in the artwork. People should definitely pick it up just for the art. I think the story's good too, but the art is amazing.
Russell: I totally agree with that sentiment as far as The Flintstones goes too. My favorite part of each month is getting the artwork back from Steve Pugh, who's the artist on The Flintstones, and it always cracks me up. He finds nuances and all kinds of funny little background details that I didn't put in the script, and it's been a real joy working with him.
Same with Ben Caldwell, who returns to the art for the Prez special elections story. I've been incredibly lucky getting to work with two amazing artists who have, like, such a humor and vision of their own. It really helps sort of flesh out my work as a writer.
But yeah, I think that in both issues, they're a little bittersweet. I hope people find them funny, but also a little sad. They play to a range of emotions.
Nrama: Kind of like elections themselves.
TAMPA, Fla. — Within one month, someone splashed four cars with an acid-like liquid in busy Tampa parking lots.
Deputies are not sure if the incidents are related. The most recent happened in a shared parking lot near the AMC Veterans movie theater and Starbucks off Anderson Road.
The scenario is the same in all of these situations. Some sort of corrosive liquid is poured onto the doors of the cars which damages paint, metal and plastic on the car.
Two panels on Gary Schaff’s 2015 white Mercedes had to be repainted. He was parked in the lot off Anderson Road two nights in a row as he and his family caught up on the latest Marvel movies at AMC.
As his family got closer, they realized the white paint had bubbled up. By the time they got home a lot of it had flaked off and exposed the metal underneath.
"I don't even know what I would say to someone who thinks it’s a good idea to do something like that,” Schaff said. "What does it accomplish exactly?"
Hillsborough County deputies say a 2007 BMW was vandalized the same way in a Publix parking lot off N. Dale Mabry on April 11 and a 2017 Porsche SUV was damaged by a corrosive liquid in the Heath Integrated parking lot on April 23. All three attacked occurred within a few miles of each other.
The Tampa Police Department responded to a 2011 Audi with similar damage at International Mall on April 15.
"It's just to me a completely random thing, and it's really hard to prevent,” Schaff said. "Have insurance on your car."
While Schaff must pay a $500 deductible, his insurance company will cover the rest of the amount needed to repair the damage.
He asked the movie theater about security cameras but believe the ones on the building catch the area of the parking lot his car was in.
"I hope the person gets caught, and brought to whatever justice there would be from this and learns a lesson not to do this,” said Schaff.
Scripps station WFTS in Tampa reached out to the property owners of this parking lot to see what type of security they have and is waiting to get an official response.
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