The top ten ways businesses can influence analytics education

A few weeks ago I participated in a Deloitte-sponsored “TweetChat” on how best to work with universities to advance your analytics objectives. We had a great group of participants—both faculty and external tweeters. The faculty, in addition to me, included Pete Fader, a professor at the Wharton School and the co-director of the school’s Customer Analytics Initiative; Randy Bradley, a professor of Information Systems and Supply Chain Management at the University of Tennessee, and Michael Rappa, a professor at North Carolina State and the founding director of the Institute for Advanced Analytics there. All three professors are closely involved with programs that develop analytically oriented students, and all work closely with the companies that hire those students.

Tweets are, of course, limited to 140 characters, but I have the luxury here of a few more letters and words on this issue. I’ll describe my own views of the top ten ways that businesses can exert an impact on analytics education. I think my views are consistent with those of the other academics, and at times I will quote them or some of the other participants’ tweets. But no one but me is ultimately responsible for these ideas and their ranking (and they are really all equally important):

1. Make clear to universities what you want and need in analytical skills. This topic had the most activity in the TweetChat. Various ideas were advanced about what skills it is necessary to equip students with. One key point, for example, was around communication skills with regard to analytics. I argued strongly for them, as did some other faculty. And other participants supported that idea too. Claudia Imhoff, for example, a well-known expert in business intelligence and data management, said in a tweet, “Analysts must be able to communicate their findings to CXOs—storytelling, data interpretation mandatory skills!” Some other tweeters argued for a focus on specific tools. Pete Fader at Wharton tweeted, “But it's not enough just to "talk the talk": I want my MBAs comfy with R, SQL, and Tableau.” Imhoff also argued for the importance of business skills in addition to analytics skills. But whatever you believe about the skills that are needed in your quantitative analysts, data scientists, or any other analytical role, make sure you let universities know what you need and that you will hire some students if they have those skills.
2. Work with a variety of programs. There are, of course, many different analytics programs in the United States these days, and even in other countries. There’s no reason to focus on just one, though you should limit the number. Beyond that, you’ll find that once you pick a university, there still may be multiple programs to address. Universities have analytics and data science-oriented groups in multiple departments and schools. They may be in a business school, an engineering school, arts and sciences, and so forth. The relevant degrees may be undergraduate, masters, or PhD. They may be online programs or face-to-face ones. Some schools have multiple degree programs with "analytics" or "data science" in their names. Some are integrated, some less so. Michael Rappa notes about his Masters in Advanced Analytics at North Carolina State: “The curriculum is fully integrated and not laid out as a series of courses.” But even at NC State, I’ve known of companies that have done well by hiring the university’s PhD students in statistics. It will probably take you some time to figure out just where all the best analytics students can be found.
3. Make universities an extension of your analytics staff. It’s not widely known, but universities can not only supply full-time students, but also offer direct assistance in solving your analytical problems. That’s one of the primary activities, for example, of the Wharton Customer Analytics Initiative. Faculty and students work with sponsoring companies to help solve tough customer analytics problems. Similar activities take place at Central Michigan University, and at least through informal arrangements at many other schools.
4. Help students get business acumen while in school. There are many ways to do this. One is to visit the campus often and give talks or discuss case studies while you are there. As Pete Fader of Wharton tweeted, “Gotta come to campus early and often.” Another is to provide data or analytics problems from your company for students to work on. A third means is to allow students to come into your organization and help with important problems while there—through internships or university-related consulting projects. Michael Rappa of NC State tweeted, “@AnalyticsInst we work close with industry with our student practicum.” The more students learn about your business and that of other organizations, the more prepared they’ll be when they actually start working for you.
5. Allow for specialization by function, industry, and analytics type. Analytical methods and tools vary, of course, by function and industry. Many schools are beginning to focus their curricula on particular types of analytical problems. Some schools, like Wharton, focus on customer and marketing analytics. Tennessee specializes in supply chain analytics; Randy Bradley from there tweeted that schools should “develop tracks of specialization within their programs.” Others may specialize by industry, such as financial services or health care analytics. Whatever your needs for specialization are, identify a school with strengths in that area and help them flesh out specialized programs.
6. Pony up some dollars. Universities are always short of money. You’ll forever (or at least for a couple of years) endear yourself to a university if you provide support for student aid, software and hardware, student travel, and so forth. Our academic guests on the TweetChat were far too well-mannered to mention money outright, but all of their programs have been the beneficiaries of corporate and alumni largesse. As Randy Bradley of Tennessee put it delicately, “Be willing to invest time, energy, and resources to help shape programs.”
7. In exchange for favors, ask for favors. If your organization has been highly supportive of a school, you can ask for favors in return. Ask who the best students are, for example. Request a prominent position in the recruiting calendar. Academics know that support and relationships are a two-way street.
8. Build a relationship with a professor or two, not the entire school. Your company may want to say you are supporting and engaging the entire university on analytics issues, but the real relationships are person-to-person. Find out who is working closely with an analytics program at a university—a program director or key faculty member—and talk with them directly about relationships of mutual benefit. You’ll get to something valuable much faster than if you go through some bureaucratic “Industry Liaison Office” or something similar.
9. Hire some students. The purpose of a university is primarily to train students and get them jobs; the purpose of corporate relationships is primarily to facilitate the hiring of students. The closer you are to a university analytics program, the higher your chances of influencing the content that is taught, identifying the best students, and persuading them that you are an appealing employer.
10. Don’t forget executive education! I tweeted this during the TweetChat, and it was retweeted by MIT Executive Education. I teach executive education programs at Babson, MIT, Harvard Business School, and elsewhere, and they are just as important as undergrad and graduate programs. The resource in shortest supply for analytics and big data is executive awareness and understanding. Enroll your favorite executive today!