The age of big data is upon us.
Nearly every sector of the business world now relies on harnessing an abundance of complex information to make sense of their business, customers and employees.
Bill Amadio has witnessed these sweeping changes spurred by the rapid growth of technology over 40 years as a College of Business Administration professor. Amadio helps guide students through the opportunities and pitfalls of working in the information age through his courses on data mining, statistical analysis and other quantitative topics.
“It’s only in the very recent past that this opportunity of working with big data has arrived,” he says. “Prior to a few years ago, this kind of logical reasoning and quantitative assessment of performance hadn’t been possible for the everyday manager."
Today, mathematical analysis is vital and data literacy necessary for managers to make informed decisions and find success, says Amadio, who teaches in the school’s information systems department. The field touches on the cornerstones of leadership, from generating sales and enriching customer relationships to improving firm management and brand awareness.
Coming of age in a different era, Amadio once relied on complex mathematical equations and models that had little data to process. “Most people dealt with quantitative methods in school and were grateful to leave them to the 'experts' once they were on the job,” he says. “Now it’s very useful, and useful is the key term. Now everyone sees value in the quantitative and that leads to better management.”
Amadio was 7 years old when Sputnik launched in 1957, rousing dreams of working for NASA. “I’m the product of the government's effort to grow more math and science students,” he says. “But when I graduated in 1970, the government was shutting down space programs. There were people with more experience than I who were getting laid off. I couldn’t see following that path any further.”
Believing it would provide a more stable career, he switched his course of study to business and found himself immersed in probability and data. He earned his bachelor’s degree in mathematics from Brooklyn College and both his master’s in mathematics and doctorate in probability theory and functional analysis from Polytechnic University.
A love of math spurred Amadio to become a professor. But it’s the interaction with students and not the subject itself that has become the most satisfying part of his job. “I would say the most rewarding collection of items that I have from my 40 years here are letters, and now emails, from people who may have graduated five or 10 years ago who tell me they learned something in my class that is now really important to them,” he says.
This past semester, Amadio taught a first-year math course to incoming freshman. “Being around 18-year-old kids is a lot of fun,” he says. “It was a pleasure to go to class twice a week and interact with them.”
He’s currently working on a project analyzing research from TripAdvisor, a travel website and app that assists people in planning and booking trips. Part of a summer research fellowship grant from the University, the project will culminate in a data map that illustrates Amadio’s findings culled from customer feedback posted on the site, such as online reviews of hotels. His goal is to make sense out of the sea of information so managers can understand the feedback and meaningfully address it.
Parsing big data is promising, but relying on it carries risks, as well. “You can fall in love with your spreadsheets and models and they can become your reality,” Amadio says, adding that managers need to continually test the assumptions of their models to stay connected to the real world.
Hard-won experience may be the ultimate guide to navigating such waters, but Amadio says he can creates scenarios in the classroom that accurately reflect the types of challenges managers face in analyzing, and leveraging, complex information. For today’s managers, information isn’t enough; they require the skills to understand what it’s telling them about their business.
“Every computer model has assumptions, and you’re always going to get an answer from them,” Amadio says. “The question is: 'Do I act on it?'”