How to make campus life better with AI technology

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In many organizations, business intelligence is the exclusive province of IT specialists and business analysts. However, those of us at Michigan State University (MSU) have a different approach.

At MSU’s Division of Residential and Hospitality Services (RHS), we put IBM Watson Analytics into the hands of our operations managers. Its ease of use gives them the confidence to interact with their data, build their own analyses and get immediate insights. This helps them fine tune operations while sticking to a tight budget.

Watson Analytics also benefits our workplace culture. Managers across the enterprise can easily share their analytical models, increasing collaboration among teams that previously found it difficult to work together. And “widesourcing” analytical decisions from those on the front lines raises our business IQ.

Furthering the mission

Why would a university residence and hospitality service depend so heavily on AI-powered analytics? RHS’s broad responsibilities means we have diverse analytical needs. In operating 27 residence halls, 10 dining halls and 21 convenience stores for the 14,000 students who live on campus, we work hard to create spaces that satisfy students and help them succeed socially and academically.

In addition, we operate commercial ventures such as a conference center, a hotel and two golf courses. We have to run these efficiently to produce enough revenue to provide essential services. That’s why we need to know how students and guests use our facilities, how they spend their dollars, how they feel about their time on campus and how we compare with our off-campus competition.

Analytics are essential to answering these questions. In fact, we have 33 different data sets from housing, culinary services, finance, commercial transactions, student surveys, social media and other sources. We need to help all our managers discover the insights that matter most to them.

Watson Analytics is so easy to use that student interns can quickly train managers—no need to learn SQL or data science. Then the team can dig into their data to discover real-time trends, opinions and sentiments that reveal where they excel and where they can improve. This hands-on relationship with data eliminates the middleman, helping managers quickly make decisions backed by science.

Generating live insights

Consider this example from a live demo of Watson Analytics to our executive board. As we analyzed students’ survey responses, demographics and social media sentiment about their experiences in moving into our residence halls, we discovered that students in one hall hadn’t received needed information—a gap that might otherwise have remained buried in the survey data. The data’s business owners in the room understood the implications and corrected the problem.

Employees in our housing division experience positive results, as well. They interact with thousands of students to help them change residence halls, adjust roommates and explore moving closer to classes. Watson Analytics taps into the underlying data to inform decisions that are best for the students.

The tool also helps improve our marketing on social media. Say we run a campaign encouraging students to eat at a specific dining hall. We can analyze social media to check for an uptick in posts mentioning the hall and the sentiments of the responses. Such insights help refine our efforts to create successful campaigns.

In the university setting, as in business, managers need tools for resource optimization. Watson Analytics does this for RHS, helping us shape a campus experience that exceeds expectations and keeps students and guests coming back for more.


Watch Michael Dawisha and Troy Stroud discuss putting Watson analytics into the hands of operations personnel at Michigan State University:


Chief Information Officer

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