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Live @ Information On Demand 2012: Craig Rhinehart On Predictive Healthcare

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I made it back to Austin late last night, mostly no worse for the wear.

There were a number of key announcements made at Information On Demand 2012 over the course of the past few days in Las Vegas.

One of those that I mentioned in one of my keynote post summaries was IBM Patient Care and Insights, new analytics software based on innovations from IBM Labs that helps healthcare organizations improve patient care and lower operational costs by considering the specific health history of each individual patient.

This is a fascinating new capability with profound implications for healthcare providers.

The new IBM solution provides the core capabilities for devising predictive models of various health conditions, which can be used to identify early intervention opportunities to improve the patient’s outlook by minimizing or avoiding potential health problems.

It features advanced analytics and care management capabilities to help identify early intervention opportunities and coordinate patient care.

Providing Individualized Care

At the core of IBM Patient Care and Insights, developed by IBM’s software, research and services teams, are similarity analytics that help drive smart, individualized care delivery.

Born in IBM Research, IBM similarity analytics is a set of core capabilities and algorithms that allow healthcare professionals to examine thousands of patient characteristics at once — including demographic, social, clinical and financial factors along with unstructured data such as physicians’ notes — to generate personalized evidence and insights, and then provide care according to personalized treatment plans.

By way of example, physicians can make personalized recommendations to improve a patient’s outcome by finding other patients with similar clinical characteristics to see what treatments were most effective or what complications they may have encountered.

They can also perform patient-physician matching so an individual is paired with a doctor that is optimal for a specific condition. With this solution, caregivers can better tap into the collective memory of the care delivery system to uncover new levels of tailored insight or “early identifiers” from historical/long term patient data that enable doctors and others to help manage a patient’s healthcare needs well into the future.

Craig Rhinehart, director for IBM’s ECM Strategy and Market Development organization, sat down with Scott Laningham and I earlier this week to describe the challenges facing health care, and how the IBM Patient Care and Insights can help improve health care by delivering dynamic case-based, patient-centric electronic care plans and population analysis.

Go here for more information on IBM Patient Care and Insights and IBM Intelligent Investigation Manager.

Live @ Information On Demand 2012: A Q&A With Nate Silver On The Promise Of Prediction

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Day 3 at Information On Demand 2012.

The suggestion to “Think Big” continued, so Scott Laningham and I sat down very early this morning with Nate Silver, blogger and author of the now New York Times bestseller, “The Signal and the Noise” (You can read the review of the book in the Times here).

Nate, who is a youngish 34, has become our leading statistician through his innovative analyses of political polling, but made his original name by building a widely acclaimed baseball statistical analysis system called “PECOTA.”

Today, Nate runs the award-winning political website FiveThirtyEight.com, which is now published in The New York Times and which has made Nate the public face of statistical analysis and political forecasting.

In his book, the full title of which is “The Signal and The Noise: Why Most Predictions Fail — But Some Don’t,” Silver explores how data-based predictions underpin a growing sector of critical fields, from political polling to weather forecasting to the stock market to chess to the war on terror.

In the book, Nate poses some key questions, including what kind of predictions can we trust, and are the “predicters” using reliable methods? Also, what sorts of things can, and cannot, be predicted?

In our conversation in the greenroom just prior to his keynote at Information On Demand 2012 earlier today, Scott and I probed along a number of these vectors, asking Nate about the importance of prediction in Big Data, statistical influence on sports and player predictions (a la “Moneyball”), how large organizations can improve their predictive capabilities, and much more.

It was a refreshing and eye-opening interview, and I hope you enjoy watching it as much as Scott and I enjoyed conducting it!

(Almost) Live @ Information On Demand 2012: A Q&A With IBM’s Jeff Jonas

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Jeff Jonas sat down last evening with Scott and I in the Information On Demand 2012 Solutions EXPO to chat about privacy in the Big Data age, and also gave a sneak look into the new “Context Accumulation” technology he’s been working on.

You really ought to get to know IBM’s Jeff Jonas.

As chief scientist of the IBM Entity Analytics group and an IBM Distinguished Engineer, Jeff has been instrumental in driving the development of some ground-breaking technologies, during and prior to IBM’s acquisition of his company, Systems Research & Development (SRD), which Jonas founded in 1984.

SRD’s technology included technology used by the surveillance intelligence arm of the gaming industry, and leveraged facial recognition to protect casinos from aggressive card counting teams (never mind the great irony that IBM’s Yuchun Lee was once upon a time one of those card counters — I think we need to have an onstage interview between those two someday, and I volunteer to conduct it!)

Today, possibly half the casinos in the world use technology created by Jonas and his SRD team, work frequently featured on the Discovery Channel, Learning Channel, and the Travel Channel.

Following an investment in 2001 by In-Q-Tel, the venture capital arm of the CIA, SRD also played a role in America’s national security and counterterrorism mission. One such contribution includes a unique analysis of the connections between the 9/11 terrorists.

This “link analysis” is so unique that it is taught in universities and has been the widely cited by think tanks and the media, including an extensive one-on-one interview with Peter Jennings for ABC PrimeTime.

Following IBM’s acquisition of SRD, these Jonas-inspired innovations continue to create big impacts on society, including the arrest of over 150 child pornographers and the prevention of a national security risk poised against a significant American sporting event.

This technology also assisted in the reunification of over 100 loved ones separated by Hurricane Katrina and at the same time was used to prevent known sexual offenders from being co-located with children in emergency relocation facilities.

Jonas is also somewhat unique as a technologist in that he frequently engages with those in the privacy and civil liberties community. The essential question: How can government protect its citizens while preventing the erosion of long-held freedoms like the Fourth Amendment? With privacy in mind, Jonas invented software which enables organizations to discover records of common interest (e.g., identities) without the transfer of any privacy-invading content.

That’s about where we start this interview with Jeff Jonas, so I’ll let Scott and myself take it from there…

Live @ Information On Demand 2012: Smarter Marketing Analytics

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Big Data is the digital convergence of structured and unstructured data. Those organizations that can capture and analyze their data, regardless of what type, how much, or how fast it is moving, can make more informed decisions. At Information On Demand 2012 today in Las Vegas, IBM announced a new digital marketing system to help CMOs conduct smarter marketing analytics.

The news dam has begun to break at the IBM Information On Demand And Business Analytics Forum here in Vegas.

One of the highlights of today’s announcement was IBM’s unveiling of a new digital marketing system and big data software designed to help organizations gain actionable insights.

These tackle the most pressing big data challenges facing organizations today — accessing and gaining intelligence into an enormous stream of data generated from mobile, social and digital networks.

Big Data for Chief Marketing Officers 

The emergence of big data technologies is driving the transformation of marketing for every channel. Chief Marketing Officers (CMOs) are now responsible for analyzing consumer demands from social media, mobile devices, and traditional channels and align these demands with product development and sales.

The new IBM Digital Analytics Accelerator helps CMOs tap into consumer sentiment to create targeted advertising and promotions, avoid customer churn, and perform advanced Web analytics that predict customer needs.

Now, CMOs can bring advanced analytics to all their social media, web traffic, and customer communication behind their own firewall.

The industry’s first big data solution in the digital marketing arena is powered by Netezza and Unica technologies. With this integrated offering that includes the recently announced PureData System for Analytics, clients can run complex analytics on petabytes of data in minutes, and arm marketing professionals with instant insights.

CMOs can use new insights to accelerate marketing campaigns and better meet consumer needs based on the broadest range of data.

Trident Marketing: Gaining Visibility Into Consumer Behaviors

For Trident Marketing, a direct response marketing and sales firm for leading brands such as DIRECTV, ADT and Travel Resorts of America, performing analytics on big data has helped the company gain unprecedented visibility into consumers — from predicting the precise moment in which to engage with customers to anticipating the likelihood a customer will cancel service.

Working with IBM and partner Fuzzy Logix, the company has realized massive growth including a tenfold increase in revenue in just four years, a ten percent increase in sales in the first 60 days, and decreased customer churn by 50 percent.

Live @ Information On Demand 2012: Analyze This

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Jason Silva explains to the gathered IBM Information On Demand 2012 his utopic vision of a technology-rich future, one where everything is connected to everything else.

Techno DJ futurist Jason Silva (formerly of Al Gore’s Current TV) kicked off the Information On Demand 2012 event here at the Mandalay Bay Arena by telling us all to “Think Big.”

Though I’d known this was the conference theme, I didn’t realize how big big was until the small, but limber, Silva gave his big presentation.

As he kickstarted the event with a blend of hyper animations and visualizations reeling behind him on a huge video screen in post-MTV fashion, I wanted to stop him and explain that to talk about big things so rapidly would allow a lot of his big ideas to disappear into the ether and to just slow downnnnn.

Jason’s look at the big picture was an interesting one, wherein he described a world that was “hyperconnected,” where we extended sensors into everything…on planes, bridges…even our conference IDs for IOD!

But Silva’s utopian vision could easily merge into a dystopia, if proffered without regard to some of the more realistic and mundane issues presented in a Big Data universe.

Small, and petty human concerns like agendas, and greed, and lack of privacy, and bias, and the other nasty little buggers which make us human.

So, though I wanted to go along with Silva’s optimistic joy ride snowblind to those considerations, someone has to be the buzz kill at this emerging Big Data party and explain there are some very real and concerning issues that will need to be dealt with, none of which Silva seemed even to allude to.

Steve Mills explains to the Information On Demand 2012 press conference Monday morning how economics has made big data not only possible, but inevitable.

But, as techno joy rides go, his was fun even as it went by in the blink of an eye.

Once he blinked, it was IBM Software vice president Robert LeBlanc who really set the stage for the week’s tidings, explaining to the gathered audience of 12,000+ in the Mandalay Bay arena how smarter analytics would be required in the new era of computing.

As always, Leblanc started with some facts: Like how Big Analytics is what’s driving innovation and market growth in IBM’s recent CTO study.

How “technology factors” has risen to the top of the CEO agenda as the number one issue during the study’s last six years.

And how it’s no matter what part of the world you inhabit or what industry you’re in…all and everywhere will be impacted by the need for smarter analytics.  This kind of transformational change is a movie we’ve seen before, first with transaction processing in the 1960s, with Internet-enabled e-business in the mid-1990s, and now, the move towards analytics becoming foundational to computing.

Two IBM customers provided two very different, yet compelling, views into this future, one they’re each already living.

ConocoPhillips principal scientist Dr. Phil Anno explained how his organization is utilizing big data analysis to maximize the economic performance of petroleum extraction in the Arctic (and prevent damage to their drilling rigs by shifting ice flows!)

Keith Figlioli, senior VP with Premier, a U.S.-based healthcare IT provider, explained how they’re using IBM technologies to drive substantial costs out of the U.S. healthcare system (he explained that 30 cents on every dollar is wasted on unneeded care and fraud in the U.S.)

Also in the opening general session, we heard from Inhi Cho Suh, VP of Information Management at IBM, who gave an excellent, if quick, summary of the three PureData systems options.

Deepak Advani, who gave an excellent flyover of how big data analytics is bringing about the rapid integration of structured and unstructured data, also highlighted www.analyticszone.com, where you can download some free tools for conducting your own personal analytics.

As the general session concluded, I scooted on over to the day one press conference, where I heard some opening comments from IBM senior vice president Steve Mills.

Mills explained how IT economics laid the red carpet for big data, that it wouldn’t have been possible had the economics of hardware, in particular, been driven down to such an affordable level so as to enable these higher performing systems required for big data analytics.

Mills also highlighted the fact that smarter analytics is a delivery of the real promise of information technology, that now customers are “buying outcomes, and time to value,” as opposed to systems and processes, and that it made sense for them to invest in such projects.

More on the actual announcements as details emerge…

Big Study On Big Data

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Perfect timing.

In advance of IBM’s massive event next week in Las Vegas featuring all things information management, Information On Demand 2012, IBM and the Saïd Business School at the University of Oxford today released a study on Big Data.

According to a new global report from IBM and the Said Business School at the University of Oxford, less than half of the organizations engaged in active Big Data initiatives are currently analyzing external sources of data, like social media.

The headline: Most Big Data initiatives currently being deployed by organizations are aimed at improving the customer experience, yet less than half of the organizations involved in active Big Data initiatives are currently collecting and analyzing external sources of data, like social media.

One reason: Many organizations are struggling to address and manage the uncertainty inherent within certain types of data, such as the weather, the economy, or the sentiment and truthfulness of people expressed on social networks.

Another? Social media and other external data sources are being underutilized due to the skills gap. Having the advanced capabilities required to analyze unstructured data — data that does not fit in traditional databases such as text, sensor data, geospatial data, audio, images and video — as well as streaming data remains a major challenge for most organizations.

The new report, entitled “Analytics: The real-world use of Big Data,” is based on a global survey of 1,144 business and IT professionals from 95 countries and 26 industries. The report provides a global snapshot of how organizations today view Big Data, how they are building essential capabilities to tackle Big Data and to what extent they are currently engaged in using Big Data to benefit their business.

Only 25 percent of the survey respondents say they have the required capabilities to analyze highly unstructured data — a major inhibitor to getting the most value from Big Data.

The increasing business opportunities and benefits of Big Data are clear. Nearly two-thirds (63 percent) of the survey respondents report that using information, including Big Data, and analytics is creating a competitive advantage for their organizations. This is a 70 percent increase from the 37 percent who cited a competitive advantage in a 2010 IBM study.

Big Data Drivers and Adoption

In addition to customer-centric outcomes, which half (49 percent) of the respondents identified as a top priority, early applications of Big Data are addressing other functional objectives.

Nearly one-fifth (18 percent) cited optimizing operations as a primary objective. Other Big Data applications are focused on risk and financial management (15 percent), enabling new business models (14 percent) and employee collaboration (4 percent).

Three-quarters (76 percent) of the respondents are currently engaged in Big Data development efforts, but the report confirms that the majority (47 percent) are still in the early planning stages.

However, 28 percent are developing pilot projects or have already implemented two or more Big Data solutions at scale. Nearly one quarter (24 percent) of the respondents have not initiated Big Data activities, and are still studying how Big Data will benefit their organizations.

Sources of Big Data

More than half of the survey respondents reported internal data as the primary source of Big Data within their organizations. This suggests that companies are taking a pragmatic approach to Big Data, and also that there is tremendous untapped value still locked away in these internal systems.

Internal data is the most mature, well-understood data available to organizations. The data has been collected, integrated, structured and standardized through years of enterprise resource planning, master data management, business intelligence and other related work.

By applying analytics, internal data extracted from customer transactions, interactions, events and emails can provide valuable insights.

Big Data Capabilities

Today, the majority of organizations engaged in Big Data activities start with analyzing structured data using core analytics capabilities, such as query and reporting (91 percent) and data mining (77 percent).

Two-thirds (67 percent) report using predictive modeling skills.

But Big Data also requires the capability to analyze semi-structured and unstructured data, including a variety of data types that may be entirely new for many organizations.

In more than half of the active Big Data efforts, respondents reported using advanced capabilities designed to analyze text in its natural state, such as the transcripts of call center conversations.

These analytics include the ability to interpret and understand the nuances of language, such as sentiment, slang and intentions. Such data can help companies, like a bank or telco provider, understand the current mood of a customer and gain valuable insights that can be immediately used to drive customer management strategies.

You can download and read the full study here.

Update: Also check out the new IBM Big Data Hub, a compendium of videos, blog posts, podcasts, white papers, and other useful assets centering on this big topic!

Thinking Big @ Information On Demand 2012

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Nate Silver, author of the blog “FiveThirtyEight,” will be one of the featured keynote speakers at this year’s IBM Information On Demand 2012 event in Las Vegas, Nevada, October 21-25. Silver correctly predicted the results of the primaries and the U.S. presidential winner in 2008 in 49 states through his statistical analysis of polling data, and at IOD will explain how to distinguish real signals from noisy data as well as how predictive analytics is used in politics.

That annual festouche and gathering of all things data is just around the corner.

Yes, that’s right, it’s almost time for IBM Information on Demand 2012.

So in order to start the drumbeat, I wanted to take a few moments and point you to some useful resources as you prepare to make your way to the Bay of Mandalay, and to optimize your time on the ground in Vegas.

First, the new (and official) IBM Information on Demand blog, which you can find here.

The blog includes easy access to some of the social media channels that will be covering the event (including Facebook, Twitter, LinkedIn and YouTube).

Of course, never forget the official IOD hashtag, #ibmiod, where you’ll be able to follow the endless stream of tidings leading up to, during, and after the event.

The blog also has links off to the IOD 2012 registration engine, as well as to the IOD SmartSite so you can start thinking about your IOD calendar now (I do NOT advise waiting until the last minute…talk about information overload!)

We’ve got some exciting guest speakers this year, including Nate Silver, statistics blogging extraordinaire who first found fame with his “FiveThirtyEight” blog, which is now part of The New York Times family of media properties.

Silver analyzes politics the way most of us should be analyzing our business: Through data…and lots of it.

His analysis of political polling data is unparalleled, and in the 2008 U.S. presidential election, Silver correctly predicted the results of the primaries and the presidential winner in 49 states.

His recent book, “The Signal and The Noise: Why Most Predictions Fail — But Some Don’t,” explores the world of prediction, “investigating how we can distinguish a true signal from a universe of noisy data.” Silver tackles some of the big questions about big data, so we’re very excited to have him join us in Vegas for IBM’s own big data marathon event.

At this year’s event, we’ll continue our trend of including tracks for specialized areas of interest, including forums for Information Management, Business Analytics, Business Leadership, and Enterprise Content Management.

And, of course, you’ll be able to find Scott Laningham and myself down in the EXPO center, where we’ll be talking to and interviewing many of the IBM and industry luminaries on the important data-related topics being discussed at the event.

Speaking of data, this will be my seventh IOD in a row, so I’m looking forward to seeing many of you once again.

Meanwhile, keep an eye here on the Turbo blog for future IOD-relevant posts.

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