Big Data in the Big Apple

No sport has generated as much raw data as Major League Baseball. Between pitches and in-between innings there is plenty of time for the dedicated fan to record all sorts of minutiae: what sort of pitch was thrown?, how fast was it going?, where did the ball cross the plate?, did the batter swing?, where were the fielders positioned?, what was the ambient temperature? what were the wind speed and direction?

Baseball was Big Data before Big Data was even a thing.

For more than 100 years, the data just sat there, getting bigger by the game. But then came Bill James in the late 1970s. At night, James was a security guard at a pork and beans cannery. He spent many of his daytime hours poring through box scores, collecting and organizing data and then using it to make insightful observations about specific players and about broader questions of strategy. By looking closely at the data everyone else ignored, James started a movement later made famous in author Michael Lewis’s 2003 book Moneyball.

Moneyball focused on Oakland Athletics’ general manager Billy Beane and his revolutionary use of statistics to identify and acquire undervalued players. With Beane using data to guide his personnel decisions, the A’s compiled an impressive win-loss record over the years, especially compared to their much more free-spending rivals.

While the new one-year Masters of Engineering degree (M.Eng.) in Operations Research and Information Engineering (ORIE) being offered at Cornell Tech will probably not lead anyone to a General Manager’s position for a major league baseball team, the unique program will prepare graduates to be decision-makers in today’s data-rich tech world.

International consultants McKinsey and Company released a report recently called Big data: The next frontier for competition. The report concludes “analyzing large data sets will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus as long as the right policies and enablers are in place. The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of Big Data.”

Cornell Tech’s M.Eng. in ORIE is designed to provide graduates with exactly the skills McKinsey and Company say the global economy needs in order to take full advantage of all the data companies now have access to.

“This is a time when Operations Research is coming to the forefront,” says Huseyin Topolaglu, professor of operation research and information engineering at Cornell. “Companies are in a position where they need to manage both information and physical resources. It is an exciting time because a lot of these companies that have an online presence have problems that are relevant to OR. We are in a position where we can make a really deep impact.”

For many years, operations researchers had their biggest impact in the area of supply chain management. In the internet age, it is still vitally important that companies manage their inventories and supply chains well. But it is equally important that these companies manage their information well. Just like Bill James and Billy Beane sifting through a hundred years of raw baseball data, today’s decision makers need to find the value in the numbers. Unlike Bill James and Billy Beane, the amount of data being produced and managed by tech companies makes baseball’s big data seem like small potatoes.  The questions companies like Uber and Amazon and Netflix need to answer are incredibly complex and require a deep knowledge of optimization strategies and algorithms designed to help companies use the massive amounts of data they collect in order to make good decisions quickly.

To meet the special needs of tech companies in the Age of Big Data, Cornell Tech’s M.Eng. program in ORIE has been designed from scratch. It is not simply a reconfiguring of the M.Eng ORIE program that already exists on the Ithaca campus. “This is different from any other program,” says Kathryn Caggiano, senior lecturer in ORIE and director of the M.Eng. program for the past eight years. “It is smaller and more nimble. It has a unique educational approach featuring an integrated curriculum, students and professors from many areas of expertise, and valuable interactions with the tech firms of New York.”

Cornell’s Ithaca campus has from 80 to 90 ORIE M.Eng. students graduate each year. In comparison, the new Cornell Tech ORIE M.Eng. program will have between 8 and 12 students when classes start in the fall semester of 2016. The plan is to grow the program a bit in coming years, but to not let it get so big that it loses what makes it unique. “It is a different offering at Cornell Tech,” says Caggiano. “It provides an alternative environment and a different experience that will speak to a different type of applicant than we get on the Ithaca campus.”

“The types of projects students will work on at Cornell Tech are different.” Says Topolaglu. “Students will do two projects in their year-long M.Eng program. The first is a company challenge and the second is a start-up project.” The company challenge focuses on actual open-ended questions submitted by tech firms. Students read through a long list of questions and then note those they are most interested in. Cornell Tech faculty do the same thing, noting which questions seem most interesting to them. Students and faculty advisors are then assigned to teams based on their project preferences.

“What is unique about these project teams is their multidisciplinary nature,” says Topolaglu. “On a team of six students you may have OR students, computer science students, information science students, and MBA students all working together. The solution they provide the company can address all sides of the company’s question.”

The second major project-based component of the new Cornell Tech ORIE M.Eng. offering is a start-up project. Rather than working on a problem posed by a company, students come up with their own business idea for a product or software or a service. Again, students are part of an interdisciplinary team that may include Operations Research majors, Computer Science majors, Information Science majors, and MBA students.

“This is one of the most interesting differentiating aspects of the program.” says Topolaglu. “The boundaries of the program are not constrained by the boundaries of OR. We go much broader so we can actually create projects that overcome the traditional scope of the field. This to me is the most exciting part of the program.”

According to Topolaglu, another major differentiating aspect of the Cornell Tech ORIE M.Eng. degree is the underlying theoretical and technical strength brought to the program by its connection to the Ithaca campus. “When we teach courses here at NY Tech, we place quite a lot of emphasis on large-scale computation and large-scale implementation. For example, when I teach a course on optimization methods, I cover all the essential theory backed up by Cornell’s long history as a leader in the field of Operations Research, but I also show students ways they can take these algorithms and build deployable ultra-large-scale systems that will be relevant to a company today.” By “ultra-large-scale” Topolaglu is referring to companies such as Amazon, whose operations are enormous and gather incredible amounts of data that needs to be processed and analyzed quickly properly in order for the company to run efficiently.

A third characteristic of the Cornell Tech ORIE M.Eng degree that separates it from the M.Eng offered on the Ithaca campus or, for that matter, at almost any other university, is the ready access to leaders in the digital, financial, and start-up worlds. For example, student teams present their final company and start-up projects on a day called “Open Studio.” Hundreds of representatives from the tech world of New York and the rest of North America attend the event. Topolaglu describes it as a “job fair turned upside down.” Students have ten-minute slots to show their work and, at the same time, show industry people what they are capable of.  This level of access and interaction with tech industry and start-up leaders is hard to come by in any Masters program.

Topolaglu says the ideal candidate for the new program should have some prior exposure to the basics of optimization, probabilistic analysis and programming; should be passionate about bringing business intelligence to tech industry companies; and should be interested in combining operations research theory with evolving computational tools to deliver business solutions. Graduates of the program will fill roles such as business analyst, data scientist, and quantitative decision expert in companies that use computational tools, algorithms, and large amounts of data to make business decisions in uncertain environments. Of course, graduates might also choose to dive in and create their own startup, as well.