Once upon a time, if you wanted to buy a new car, the only people who would know about it were you and the car salesman.
But oh, how times have changed.
Now, consumers post about their purchases on Facebook before, during, and after they swipe their credit cards. They browse online, painting an intimate picture of their shopping habits and aspirations. They upload pictures to Instagram and tweet about their adventures in consumerism.
And it's all been a boon for big data and analytics.
"In the past you could just see the transaction from the customer," says Rick Watson, a professor at the University of Georgia’s Terry College of Business. "Now you can see a posting on Facebook about what the person intends to do, or see movement in the store for face recognition or something like that. You can see the transaction, and the events after the transaction."
With this plethora of information now available about products and consumers, fields ranging from finance to marketing to operations management are increasingly relying on numbers and data to navigate this new world.
"Especially in marketing, because of the availability of greater data on consumers and activities and different channels of data available to firms, and because of advances in analysis firms--all of those have helped to create a situation where regardless of which job you're going into, there's going to be an opportunity to use analytics," says Manish Tripathi, director of the Marketing Analytics Center at Emory University’s Goizueta Business School.
This means that more and more companies are practically begging for students who have the skills to make sense of these numbers.
"The world actually has a shortage of people with analytics skills," Watson says. "The demand just continues to grow, even to the point where Walmart has a billboard in San Francisco advertising for data analytics people."
Officials at schools like Goizueta, Terry, Carnegie Mellon’s Tepper School of Business and the Queen's School of Business in Canada, which are top-ranked for analytics, say that students who study analytics go on to work at companies like FedEx, construction and mining equipment company Caterpillar, General Electric, or at large retailers advising about topics like price setting.
"I think there's lots of excitement with the kinds of problems that can be solved [through analytics]," says Alan Montgomery, associate professor at Carnegie Mellon University's Tepper School of Business.
"Some students go into management consulting, others will do technology and work with technology companies. We have a lot that go to Microsoft and Amazon, and others that go into financial services, at companies like Bank of America."
Tina McGlynn, who's currently enrolled in Goizueta’s MBA program, is just one businesswoman who realized that analytics are an essential part of modern business. McGlynn worked in consulting before business school, where she noticed that every decision she made was rooted in data.
"That's where I realized that there's incredible value in knowing how to do various types of analytic work, because every recommendation or strategy that our firm presented to our clients was really rooted in some sort of analysis," says McGlynn, who worked in a marketing strategy role at Delta Airlines last summer and hopes to continue working in market strategy after she graduates in 2016.
McGlynn says that in her experience, analytics skills are crucial during the job search.
"[Analytic skills are] something that can really set you apart," she says. "Whenever you're up against a comparable colleague, if you have the ability to perform various types of analytics and not only do it but make the connection and say, this is the result of the analysis, this is what it means in terms of the recommendation-- it's really a big differentiator when it comes to career advancement."
An explosion in business analytics program offerings
The increased importance of analytics in business has translated to an increased interest in analytics among business students--and a corresponding increase in the number of programs that focus on this discipline. Montgomery says more and more Tepper MBA students have enrolled in the school’s analytics track over the past three years.
At Goizueta, Tripathi says he now incorporates analytics into the core marketing classes that he teaches. And more and more schools are rolling out MBA programs with a focus on analytics or even one-year master’s programs in business analytics.
At these programs, students learn how to analyze data in four different ways, says Terry’s Watson. First, students learn data management, the time-consuming process of gathering data and organizing it so that it can be analyzed. Second, they learn data analysis, which involves presenting data in tables, reports or other easily digestible forms and explaining the significance of the data.
The next step is predicated analysis, which involves trying to explain what will happen if a company changes something.
"What happens if we change a policy? If we give a different discount? Do we attract more customers? How well does this promotion work? Does changing the placement of the search bar on the website make a difference in the number of people we convert from browsers to buyers?" Watson says.
Predicated analysis is one of the main areas transformed by technology. Watson likens the digital revolution to a wide-angled camera, allowing data experts to view transactions from all angles and thus expanding the tools for predicated analysis.
The final step is prescriptive analysis, where data experts try to advise a company or government about best practices based on the numbers. For example, Watson says a recent project in Singapore advised the government about how to manipulate and change 900 traffic lights in order to reduce traffic congestion.
To accurately and efficiently perform these different analytical tasks, students must learn various technological skills, including analytics computer programs such as SAS, R, Microsoft Excel and Tableau. And, as in so many fields, students also need broad general computer knowledge.
"You need a stronger technology base," Watson says, "just to be able to put all the pieces together. Just starting off with getting the data, gathering multiple data streams with different formats, and bringing them together with different formats. Sometimes [data is gathered] hourly, in other cases daily, and you have to get them on the same time scale. Then you have to go through the process to visualize them."
He added, "The needs are much deeper now."
Image credit: DARPA.