Archive for October 2011
At last week’s Information On Demand event in Las Vegas, we heard a lot about how the Watson technology is starting to permeate the marketplace.
There was much discussion around the use of Watson by Seton Hospitals using the new IBM Content and Predictive Analytics for Healthcare solution, and also about the continued expansion of Watson into other industries.
Today, we learned that IBM is headed to Harvard with Watson. Not to go back to school, but to present a Watson symposium with the Harvard Business School and the MIT Sloan School of Management.
This event is bringing together some of the brightest academic minds to collaborate on the use of advanced analytics, like those powering Watson, to transform the way the world does business.
As part of the symposium, teams of students from Harvard and MIT will put their skills to the test in a demonstration of IBM Watson’s question answer (QA) capabilities in an exhibition game of the TV quiz show “Jeopardy!”
The commercialization of Watson technology means that today’s students will require new skill sets when they enter the job market. As future leaders in a wide range of industries and entrepreneurial ventures, students will need to combine business skills and knowledge with advanced analytical techniques to compete successfully in the world economy.
For example, when applied to banking and finance industry, Watson-like technologies can uncover hidden patterns in data that can rapidly identify market trends, and provide deep, integrated risk analysis. This provides financial services professionals a more accurate picture of their market positions, helping them better assess risk and hedge their financial exposures.
“Great technology companies like IBM are converting the seemingly impossible into reality these days, to the point that it’s hard to keep up with all the digital innovations and their business implications,”said Andrew McAfee, principal research scientist, MIT.
“So we thought it would be a good idea to devote a day to discussing them, and also seeing them in action. We’re going to spend the morning talking computer science and economics with the world’s leading experts in these fields, then cheer our students on against Watson in the afternoon. I predict at least a second place finish for the MIT team.”
Harvard Business School and MIT Sloan School of Management are the first two business schools where IBM will co-host a Watson symposium.
A team of researchers from MIT, led by Boris Katz, principal research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory, contributed code to the QuestionAnswer capabilities in Watson.
Harvard Business School’s Professor Shih recently wrote an in-depth case study of Watson that is will be used by MBA students in the School’s required first-year course Technology and Operations Management.
At Information On Demand 2011, day 3, BBC presenter showed up onstage ready to play ball with Moneyball author Michael Lewis and Oakland A’s general manager Billy Beane.
Fitting, considering we’re currently in the midst of this year’s World Series between the Texas Rangers and St. Louis Cardinals (Game 6 is tonight in St. Louis!)
Kay first asked Lewis why a book on baseball statistics, and Lewis explained that people are sometimes misvalued by markets, and that what Beane was doing with his team in Oakland in 2001 was a science experiment where “the lab rats [the players] didn’t really know they were lab rats.
Lewis went on to tell a hilarious story about first seeing the A’s players walking naked out of the showers, and how what he saw did not seem to be a gathering of muscle-ridden athletes. They were fat, misshaped, and otherwise seemingly disfigured.
When Lewis approached Beane to ask him about this, Beane explained “that’s kind of the point. We’re in the market for defective people. We’re in the market for players whose value the market does not grasp. We’re a magnet for these unattractive bodies!”
Lewis says that’s the moment it hit him: Beane’s assembled the misfit toys of baseball, the people who have been discriminated against because of their appearance and who are greatly undervalued when compared to their actual player statistics.
Lewis went on to explain, “I realized there was this discrimination going on in the market for baseball players. The way they had done it, with statistics, getting below it…the statistics though were besides the point. You had to think of it as a business. These baseball players, who do what they do, for the past 100 years, and there were all these people who considered themselves experts based on intuition instead of actual performance.”
So there they were, October 2001, the A’s v. The Yankees, and Billy Beane had some of the best players out there: Jason Giambi, Johnny Damon…but he knew he wasn’t going to be able to hold on to them, so he was going to have to throw the intuition playbook out the window.
Beane: “I remember thinking I will never have a collection of talent like this. What the heck are we gonna do? We knew they were gonna go (Giambi, Damon, etc.). We knew the whole year that was gonna happen, but we were trying to find some solution and replace in the aggregate what they did. So, we scoured guys who had A skill, not five skills. And because we had no money…we had one of the lowest payrolls…we couldn’t afford to invest in the romance of a player, but really what they could do and with no biases for or against them, just their performance.”
“Quite frankly,” he went on to explain, “if we were ever going to trust the mathematics, this was the time. We had nothing to lose!”
Cay then posed the all important question: How did you come to this way of looking at the data?
Beane responded that “we never claimed to have invented anything. Numbers are historically scary to everybody, and math doesn’t come easy and doesn’t come from sports. Sports are more about the gut. But we had to be a disciplined card counter.”
Lewis elaborated: “The fact that they weren’t actually generating themselves a whole lot of new baseball knowledge, but that a lot of it was on the web, available to any team, and they recognized it as knowledge. And the use of analytics was so critical, as it took them to another decision point in the game of baseball.”
“This is why the market was so hostile,” Lewis went on. “That there was a new and valuable way of analyzing baseball players, because it implicitly undermined their intuition and knowledge of the game. All these years you did this job, spouting out an intuitive response. So it was finding a better way to measure baseball. Baseball stats are so clean, and it’s easy to assign them in the field of play. The second thing was, sports are somewhat anti-intellectual, and baseball was really anti-intellectual. Most of the kids who go on to play the game don’t go to college, and the game itself is not intellectually challenging.”
“You can’t be too stupid to play baseball,” Lewis explained, eliciting great laughter from the audience, and what had to be the most highly-Tweeted quote from the conversation.
Then, to the heart of the matter in terms of bridging baseball analysis to business purpose: How did you get to the right numbers? asked Katty Cay.
Beane: “If you’re following metrics that have no correlation to business success, or in our case, winning games, you’re in trouble. The older the business, the more challenges and the more traditional and conventional thought.
“Baseball started in the mid 1800s. For us, it was simply put, out of necessity, if we had a dollar, where were we going to get the most efficiency from it. Bill James really started this whole thing, but he didn’t have a venue by which to test this out.
“But I was in the game, and I had the forum and the platform, and really no other choice. So, they had to be the stats that correlated the most to winning.”
Beane went on to detail his recipe: “We were able to pile all our chips to guys who got on base, and on base percentage had the strongest correlation to winning games. For us, this was the statistic that had the most impact on winning.”
Cay: In the moments, you have moments of tension with the staff re: intuition. Did you waver at all when you looked at the numbers?
Beane: “There was this perspective that it was risky, but it wasn’t, and the beauty of baseball over time is that there’s so many games you weed out the randomness and ultimately we thought we’d come out where we thought we could. We thought there was more risk in NOT doing it, in going with our guts.”
“To go with our gut would have been the most irrational thing to do.”
Cay: Michael, how do you think Billy was able to get away with this?
Lewis: “He had to be able to intimidate his staff. It was just him and an assistant who were privy to what the goals were. Re: the players, he said, we don’t tell them, it’ll just confuse them.”
“But he did get some resistance, yet it went away, because he was basically bigger than everyone else in the organization. He could beat up everybody there. There’s this law of the jungle quality to the clubhouse. The players also knew he was a better athlete than they were. It came clear to me right away where reason was being imposed by violence.”
Cay: He looked like such a nice guy.
Lewis: “He’s mellowed. He would chew tobacco, and his eyes would get red, and I would think, ‘Don’t get in his way!'”
Cay: Let’s translate that to the business environment. You have to have the confidence to go with what your’e analyzing with the data.
Lewis: “It’s sort of like, did it work or did it not worth? The confidence comes from having the information and feeling like you’re right.”
Billy: “As Michael said, the tough thing is how you give out the information, and you have to be careful. One of our directors in the back office, he said, ‘I don’t know what you guys are doing back there, but whatever it is, it works.'”
“If you were disciplined with it, you were going to be right to the end.”
Lewis: “There’s a huge amount of randomness, and you can have made a huge amount of decisions, but you can’t change the process of how you made that decision. People make decisions based on outcomes in sports all the time.”
“If you’re the casino, and you stack the odds in your favor, and you play a really disciplined game, it’s going to be an optimum strategy.”
Cay: You described it as a flipping a coin….if you flip it a million times, it will come out well.
Beane: “The great thing is that the eight teams that get there, those are usually the best teams. But then you get into a round robin series, and the best team doesn’t always win. The Phillies were one of the best teams this year, but micro events did them in.”
“So a lot of decisions are made on those random events that happen in a short series.”
Lewis: “For me, this was not just a sports story, it was a market story. It wasn’t the actual number crunching that interested me, but rather what it exposed about the world around me.”
“You could quantify a player’s value very precisely, but you could value what he’d done in the past. How can a market be so misvalued for such an obvious thing as a baseball player. What’s going on in markets is people are operating using intuition vs. statistics, and that influences their judgement!”
“People generalize from small sample sizes. People overvalue things that are flashy and easy to see, like foot speed or arm strength. And they underestimate things like plate discipline or ability to get on base. The big thing is understanding those biases and you, the business manager, are making at least partially intuitive judgments.”
Cay: Why did you let him write a book about this?
Beane: “This is a long answer. There was a momentum that was already starting to happen, and other teams were out there. Brian Cashman in NY, others, were already on their way. So the book maybe accelerated it a bit. But the information was on the Web so fans could do the same work. And technology, there was just no way to ignore the fact that technology was creating data that they could go out and analyze themselves.”
Cay: Arbitrage only lasts for a small period?
Beane: “Yeah, other people catch on, even with Wall Street. The other thing was, when my assistant came in, who was a Harvard graduate, there was now an avenue for people to come into the game who were highly intelligent. Smart people had an opportunity, and it became a meritocracy in the front office.”
“Today, the people who are running sports teams…well, I like to say, in 10 years, I won’t be employable.”
“And what really captured us about Michael, he said right away, ‘you guys are arbitraging the misevaluation of baseball players.'”
“We sort of viewed him as a resource to us as well. And he was validating everything we did. He became one of the guys.”
Lewis: “I just had a single question: How is this happening? And it was more than five minutes than I caught on, but it was the Wall Street story in the easy 1980s when a previously, not intellectual business, got complicated and people saw arbitrage opportunities in the market.”
“And in the course of the reporting, it became clear that other teams, especially the Boston Red Sox, had started learning what was going on. The Boston folks tried to talk me out writing the book, and they wanted me to try and talk Billy into coming to work for them!”
“You could already see that the market was going to move, and the opportunities I identified in the book were going to go away. So it would have been socially awkward to have thrown me out by this time.”
“So the book was all about them, and all about him [Billy], and he gets a galley, and he’s at spring training in 2003. And he calls me, and he’s upset after reading it. What’s disturbing you?”
“You had me saying ‘F—k’ all the time. And I said, ‘But you do.’ And he says, ‘My mother is going to be furious!'”
“As a coda to the story, when I’m on the book tour, and I’m doing a reading in San Diego, and there’s a lady at the back, with her arms folded like this, and I thought, ‘Oh no…that’s Billy’s mother.'”
“She comes up afterwards and says, ‘My son doesn’t talk like that.’ And I covered for him.” Lewis explained he went on to have the most awkward dinner with Beane’s mother for the next two hours.
Cay: So weren’t you concerned he wrote this blueprint for arbitrage?
Beane: “No. Because I said to Michael, “You don’t think anybody in baseball is going to read your book, do you?”
Huge laughter from the audience.
Cay: But they did. And the game changed…baseball changed…so how are they using analytics today in a way they weren’t 10 years ago?
Beane: “None of them are stupid enough to let Michael in so we don’t know!”
But seriously, Beane explained, “The Yankees now have 21 statisticians!”
Lewis: “Think about why that’s changed. 20 years ago, signed a player who didn’t perform, that was a $20K mistake. Now, that’s a $20M mistake. So all the front offices have evolved and they’ve ballooned their analysis staff.”
“After the book came out, what’s amazing was how it changed. Baseball owners were getting calls from Wall Streeters, telling them they were wasting money. But the industry left to its own devices would have not changed.”
“The lesson? If you got a business with an entrenched culture, you don’t know how entrenched it is. There are so many disincentives to not changing what they know to what they don’t know. There’s a personal resistance to that.”
Cay: So are we seeing a generational shift in the game?
Lewis: “Sure, all these 50 year olds have been lopped off, and all these 20 and 30 somethings are now running the game. There’s a book entitled The Structure of Scientific Revolutions, which explains how middle aged physicists are hesitant to embrace ideas from the younger generation coming after them.”
Lewis concluded: “Progress is a funeral at a time.”
The IBM board of directors has elected Virginia M. Rometty president and chief executive officer of the company, effective January 1, 2012.
She was also elected a member of the board of directors, effective at that time. Ms. Rometty is currently IBM senior vice president and group executive for sales, marketing and strategy. She succeeds Samuel J. Palmisano, who currently is IBM chairman, president and chief executive officer. Mr. Palmisano will remain chairman of the board.
“Ginni Rometty has successfully led several of IBM’s most important businesses over the past decade – from the formation of IBM Global Business Services to the build-out of our Growth Markets.”
“Ginni Rometty has successfully led several of IBM’s most important businesses over the past decade – from the formation of IBM Global Business Services to the build-out of our Growth Markets Unit,” Mr. Palmisano said.
“But she is more than a superb operational executive. With every leadership role, she has strengthened our ability to integrate IBM’s capabilities for our clients. She has spurred us to keep pace with the needs and aspirations of our clients by deepening our expertise and industry knowledge. Ginni’s long-term strategic thinking and client focus are seen in our growth initiatives, from cloud computing and analytics to the commercialization of Watson. She brings to the role of CEO a unique combination of vision, client focus, unrelenting drive, and passion for IBMers and the company’s future. I know the board agrees with me that Ginni is the ideal CEO to lead IBM into its second century.”
IBM Board of Directors Elects Virginia M. “Ginni” Rometty President and CEO of IBM: Samuel J. Palmisano and Virginia M. “Ginni” Rometty at IBM’s corporate headquarters in Armonk, N.Y. Rometty, an IBM senior vice president, was elected by the IBM board of directors to become the company’s president and ninth CEO on January 1, 2012. Palmisano, currently IBM chairman, president and CEO, has significantly transformed IBM. During his tenure as CEO, the company has delivered record financial performance and breakthrough innovations, such as Watson. Mr. Palmisano will remain IBM’s chairman. [Photo: Jon Iwata/IBM]
Ms. Rometty said: “There is no greater privilege in business than to be asked to lead IBM, especially at this moment. Sam had the courage to transform the company based on his belief that computing technology, our industry, even world economies would shift in historic ways. All of that has come to pass. Today, IBM’s strategies and business model are correct. Our ability to execute and deliver consistent results for clients and shareholders is strong. This is due to Sam’s leadership, his discipline, and his unshakable belief in the ability of IBM and IBMers to lead into the future. Sam taught us, above all, that we must never stop reinventing IBM.”
Mr. Palmisano, 60, became IBM chief executive officer in 2002 and chairman of the board in 2003. During his tenure, IBM exited commoditizing businesses, including PCs, printers and hard disk drives, and greatly increased investments in high-value businesses and technologies. He has overseen the significant expansion of IBM in the emerging markets of China, India, Brazil, Russia and dozens of other developing countries, transforming IBM from a multinational into a globally integrated enterprise. In 2008, he launched IBM’s Smarter Planet strategy, which describes the company’s view of the next era of information technology and its impact on business and society.
Since Mr. Palmisano became CEO, IBM has set records in pre-tax earnings, earnings per share, and free cash flow. During Mr. Palmisano’s tenure, IBM increased EPS by almost five times, generated over $100 billion in free cash flow, and invested more than $50 billion in research and development – creating over $100 billion of shareholder value since 2002 through an increase in market capitalization and dividends paid.
As global sales leader for IBM, Ms. Rometty, 54, is accountable for revenue, profit, and client satisfaction in the 170 global markets in which IBM does business. She is responsible for IBM’s worldwide results, which exceeded $99 billion in 2010. She also is responsible for leading IBM’s global strategy, marketing and communications functions. Previously, Ms. Rometty was senior vice president of IBM Global Business Services. In that role, she led the successful integration of PricewaterhouseCoopers Consulting — the largest acquisition in professional services history, building a global team of more than 100,000 business consultants and services experts. She has also served as general manager of IBM Global Services, Americas, and of IBM’s Global Insurance and Financial Services Sector.
Ms. Rometty joined IBM in 1981 as a systems engineer. She holds a Bachelor of Science degree with high honors in computer science and electrical engineering from Northwestern University.
This morning at Information On Demand 2011, IBM introduced new software for the healthcare industry to help health care providers and payers improve patient care and reduce costs.
According to the New England Journal of Medicine, one in five patients suffer from preventable readmissions, which represents $17.4 billion of the current $102.6 billion Medicare budget. Beginning in 2012, hospitals will be penalized for high readmission rates with reductions in Medicare discharge payments.
The new software offering uses content analytics similar to what is found in IBM’s Watson technology. IBM today introduced new software for the healthcare industry to help health care providers and payers improve patient care and reduce costs. The new software offering uses content analytics similar to what is found in IBM’s Watson technology.
Seton Healthcare Family is the first client to adopt and use the technology, called “IBM Content and Predictive Analytics for Healthcare.”
The solution will allow healthcare organizations to extract relevant clinical information from vast amounts of patient data to better analyze the past, understand the present, and predict future outcomes.
Calling Dr. Watson
By combining IBM’s Watson technology with industry solutions offerings, Seton intends to focus the new content and predictive analytics solution on the root causes of hospital readmissions, and ways it can decrease preventable multiple hospital visits.
Most healthcare organizations are drowning in data but are challenged to gain reliable, actionable insights from this information. In fact, more than 80 percent of an institution’s data today is unstructured. In healthcare, this is in the form of physician notes, registration forms, discharge summaries, documents and more is doubling every five years. Different from machine- ready data, this content lacks structure and is arduous for healthcare enterprises to include in business analysis and therefore is routinely left out. As a result, millions of patient notes and records often sit unavailable in separate clinical data silos. This content contains valuable information, but there’s historically been no easy way to analyze it.
IBM Content and Predictive Analytics for Healthcare enables doctors and healthcare professionals to go far beyond traditional search and analysis of unstructured data. They can advance diagnosis and treatment by accurately extracting medical facts and understanding relationships buried in large volumes of clinical and operational data.
The IBM solution transforms raw information into healthcare insight quickly by revealing trends, patterns, deviations and predicting the probability of outcomes, allowing organizations to derive insight in minutes versus weeks or months, or not at all. As a result, healthcare professionals can find more effective ways to care for high-risk patients, provide safer patient care, and develop new models for reimbursement for quality care.
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The new IBM solution gives clinical and other knowledge workers and executives several ways to interact with analyzed information including searching, exploring, mining, monitoring and reporting. It delivers a set of proven technologies that meet the rigorous standards and requirements of the healthcare community.
The software is also compatible with IBM’s Health Integration Framework, which means healthcare organizations can realize more value from existing information system investments such as data warehouse, business intelligence, master data management and advanced case management.
IBM is offering new content and predictive solution services through its Business Analytics and Optimization initiatives, which includes a new center of competence for UIMA-based text analysis solutions. This center of competence draws on resources from IBM Global Services, IBM Software Lab Services, and the IBM jStart emerging technology team.
IBM Content and Predictive Analytics for Healthcare is optimized to run on IBM Power Systems, which are designed for high throughput and complex analysis of structured and unstructured data. Built on the foundation of IBM POWER7 processor technology, Power Systems are available at many different price points and can be tailor fit for purpose and rapidly deployed for a broad range of customer environments with leadership performance, ease of management and efficiency.
For more information go here. IBM Content and Predictive Analytics for Healthcare.