While few believe the current university model will die, profound change will occur. Those universities that best leverage their big data (aka digital assets) will see their coveted ranking from the US News and World Report rise disproportionately in the next 5-10 years. In other words, prospective students and their parents, leading scholars and skilled administrative staff will seek out the advantages to be had from the Big Data University.
Universities, like all businesses, are undergoing a period of rapid change fuelled by a changing economy, and an increasingly connected world, where knowledge is broadly available and free to consume. Evidence of these changes can be seen in declining federal and state research dollars, the appearance of massive, open, on-line courses (MOOCs) and disconcertment among students (and parents) for how they are being educated, and the cost of that education. At the same time a degree from a prestigious university counts more than ever in the workplace. Universities with their long traditions, generally conservative viewpoint and prior sense of entitlement through federal, state and public support, seem slow to adapt to the new realities. One aspect of that new reality is the need to leverage ones data to keep up with the times and grow.
Universities have traditionally been analog – courses taught with slides or overheads, course notes printed, research data on shelves in notebooks, admission applications kept in endless file cabinets and so on. Now all of that content is, or soon will be, purely digital. The problem is universities treat these data as simply electronic versions of what was maintained in hard copy. Universities have been traditionally very slow to leverage the power of the digital medium. This failure is not new in business; the music industry, the book and newspaper industry, the manufacturing industry etc. all initially responded slowly to the new digital reality and when change accelerated, old businesses died and new ones emerged.
What does it mean in today’s fast paced environment to be a Big Data University and hence leverage the data? It means to integrate data and information resources to improve ones business (universities are businesses). Once integrated it must be analyzed to make useful findings that give the University a competitive advantage in ways that would not otherwise be possible.
Moving to a Big Data University will be a challenge for many because the current organizational structure of most research universities makes such data and knowledge integration difficult. Research, education and administrative services are siloed and each maintains its own separate organizational and sometimes duplicative data and information infrastructure. Typically there are central services that provide computer networking but how that is used is a free-for-all with redundancy across schools, departments, colleges, or whatever organizational structure is in place. Breaking down the silos takes vision, leadership, and resources, but consider the gains that are in reach for Jane, a student at a Big Data University, and her colleagues.
Jane scores well in parts of her advanced on-line biology class. Professors who undertake research in the areas where Jane did well are automatically notified of her potential based on a computer analysis of her scores and background interests and Professor Smith interviews her and offers her a research internship for the summer. Over the summer, as she enters details of her experiments related to understanding a widespread neurodegenerative disease in an on-line laboratory notebook, the underlying computer system automatically puts Jane into contact with another student, Jack, in a different department whose notebook reveals he is working on using bacteria for purposes of toxic waste cleanup. Why the connection? It turns out the same gene, which they both reference a number of times in their notes, is linked to two very different disciplines – mental health and the environment. In the analog university they would never have discovered each other, but at the Big Data University pooled knowledge can lead to a distinct advantage. The collaboration later results in a patent filing and triggers a notification to a number of biotech companies who might be interested in licensing the technology. A company licenses the technology and hires Jane and Jack to continue working on the project. Professor Smith hires another student using the revenue from the license and this in turn leads to a federal grant to support further research. The students get good jobs, further research is supported and societal benefit arises from the technology. A hypothetical example for why the Big Data University makes sense.
Today there are no technical reasons why this example cannot be realized. However, cultural and resource issues imped a move towards the Big Data University. It will be interesting to see which institutions can overcome these impediments and call themselves Big Data Universities. They are where I would want to send my kids.