Instrumented Interconnecteds Intelligent
May, 2nd 2013
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Steve Hamm, IBM Writer

Steve Hamm, IBM Writer

By Steve Hamm

When Brenda Dietrich joined IBM with a newly-minted PhD in operations research 30 years ago, she ran into a buzz saw of ignorance about the role that math could play in business. She offered her  expertise to an IBM manufacturing group in Poughkeepsie, New York, but was rebuffed. The only way they could use her math skills, they told her mockingly, was in helping to balance their checkbooks. “We’ve come a long way in the recognition of the value of math and analytics,” says Dietrich, CTO of IBM’s Business Analytics division.

Today, math and data analytics are seen as essential elements for businesses and other organizations when it comes to understanding how the world works, predicting the future and making better decisions. In this world of Big Data, the Internet of Things and social networks, organizations use math to help improve everything from operations and finances to their understanding of customers, employees and the interactions of physical and social systems. As data about all manner of things becomes more readily available and has computers become ever more powerful, we are at last able to deal with complexity and uncertainty, and, as IBM Watson’s victory on the TV quiz show Jeopardy showed, we can create machines that think.

With all of this progress in mind, IBM Research on May 1 threw a party celebrating the 50th anniversary of its math department–which is now called Business Analytics and Mathematics Sciences. Here’s a video with insights from attendees about the past, present and future of math.

YouTube Preview Image

Rather than attempt to give a full report of what was said during panel discussions featuring past and current IBM math scientists, I’m going to bullet a series of comments and anecdotes that made me think:

Ralph Gomory, the second leader of the math department and later director of IBM Research: What we’re living through today is on the scale of the Industrial Revolution–only things are happening much faster. But, as with that earlier revolution, it’s still difficult to predict the future. “I won’t predict anything because the future of science and technology is totally unpredictable and utterly transforming.”

Sam Winograd, who led the math department in 1994, when IBM had its near-death experience: The company’s turnaround CEO, Lou Gerstner, visited IBM Research a couple of days after he started on the job. Walking the hallways,  he came upon a scientist, David Johnson, who had an IBM customer visiting him in his office. Gerstner stopped and talked to the two men. Later, in a meeting with IBM Research managers, Gerstner told him that this was the first time he had met one of IBM’s customers–and he was impressed that it was in the lab. (Many people expected Gerstner to slash the research workforce, but, instead, he recognized research as the crown jewel of the company and built it up.)

Richard Toupin, a former math department head: “One of my favorite mathematicians, Henry Poincare, said mathematics is the art of giving the same name to different things. It’s a very efficient definition.”

Alan Hoffman, another former math department leader: Most people have no idea how difficult it is for a mathematician to prove theorems. “You really don’t know what it’s like until you have done it. You isolate yourself mentally and beat yourself up. Other people don’t understand it or appreciate it.”

Bill Pulleyblank, a former math department director who is now a lecturer at the US Military Academy at West Point: In his early days in IBM Research, then-research director Jim McGroddy used to bring in executives from other industrial research laboratories. One of them, from Xerox PARC in Silicon Valley, said, “Strategy is who you hire and tactics is how they get the job done. So I always focused on hiring the very brightest people. We had to be flexible about what we pursued because things are always changing.”

Finally, a warning from Brenda Dietrich: “One of the downsides of making math and analytics so easily consumable is that people can also abuse them. You can have really bad results that are made to look really pretty on the screen. Some people slap the name ‘analytics’ on it and declare victory.”

So math is out of the societal dungeon. It’s recognized as being relevant like never before. A new generation of university students is studying math together with business and computer science with the goal of becoming  data scientists. Perhaps the profession will emerge as one of the hot careers of our era, and the next generation of math grads won’t have to face the kind of derision that Dietrich did when she introduced data analytics to one corner of the world of business.

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For an excellent introduction to the increasing role of math in business and society, check out Steve Baker’s book and blog, The Numerati.

 

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Congratulations to the math department staff and alumni … and thank you for the many significant contributions you’ve made to IBM and society during the past 50 years.


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Congratulations!

I would like to see linear programming, simplex method applied to Storage Data Sizing case: you have a Storage Data equipment with flash drives, sas drives and near line (nl) sas, these with capacity, performance, energy and cost characteristics, so you would like to size your Storage based on constraints like sizing for capacity or sizing for performance, and so on and based on business/applications rules too. Modeling such case has great value on Storage Area. The other solution is try and error and should be avoid.


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May 2, 2013
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Congratulations to the math scientists of IBM at 50! Your accomplishments are world-changing and I can’t wait to see the results as you embark on your next 50 years!


Posted by: Robert Morris
 
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