Making Innovation In Higher Education Work
February 28, 2018 | Dr. Robin Colson, Director, Research & Evaluation
Innovation is a hot topic in higher education today as colleges and universities continue to search for the silver bullet for student success, an acknowledgment that the way they are currently doing business is not working. A combination of public and legislative demands for better student outcomes and more accountability are the biggest indicators of the perceived lack of effectiveness of colleges and universities. The perception of ineffectiveness is not completely accurate given all that institutions of higher ed deliver to the academic community, their local communities and economies, and to society at large. The problem is that the vast majority people consider such contributions as secondary to the primary responsibility of higher ed, which is to produce competent, critically-thinking, communicative, workforce-ready graduates and that is where higher ed struggles. Indeed, if the overall success rate for producing the fundamental deliverable of any other industry hovered around 60%, which is higher education's 6-year average graduation rate (Digest of Education Statistics, 2016), that industry would have disappeared long ago. In fact, many colleges and universities have disappeared in recent years, with more closings on the horizon (Woodhouse, 2015) due to a combination of lack of perceived effectiveness, a shrinking population of college-age youths in the U.S., and reductions in state funding for higher education.
Hence, the cry for innovation - and fast.
But the hard reality is that innovation does not happen fast. Innovation is a structured problem-solving process that encompasses three major steps: ideation, development, and implementation. The ideation and development phases are led by skilled facilitators who employ a process called design thinking to guide multi-disciplinary, unconventional teams through collaborative research, design, and pilot-testing activities conducted over a period of time. The goal is for the team to have "Aha!" experiences that yield novel, often unconventional ideas, and approaches.
The term design thinking originated in 2003 at IDEO, a leading design and innovation firm. IDEO defines design thinking as "a human-centered approach to innovation" (IDEO, 2018) meaning that its approach to innovation is focused on the user's experience with a product of service, rather than on the product itself. The philosophy of design thinking is that the most effective products or services are those that drive the optimum user experience, not necessarily the ones that are the most technologically advanced or sleek. It is the fundamental tenet of human-centeredness that sets design thinking apart from other traditional problem-solving approaches. The goal of the human-centered approach is to create understanding and empathy for the end user by observing, interviewing, and walking a mile in the shoes of that user. In turn, the designer creates products and services that not only meet the user's needs, but also delight, inspire, entertain, and/or engage them.
For example, Nike, a longtime user of design thinking's human-centered approach to innovation, has become the dominant force in athletic wear, not by placing its emphasis only on creating the optimum shoe, but by creating the optimum athletic experience (Kumar, 2013) that encompasses shoes, apparel, fitness software, and the inspiring charge to "Just do it!". Apple has become the giant in its industry by using design thinking (Fortune, 2017) not simply to create cool products, but an entire customer experience, available to Apple users through its proprietary software that links all Apple products owned by the user and provides capabilities users don't yet know they need.
Like Nike and Apple, many higher ed institutions are relying on design thinking to find ways to improve the student experience and promote academic success. There are still many skeptics, however, and the innovation centers springing up in colleges and universities all over the country will have to demonstrate their value in order to become a lasting part of the institution. According to the director of the Kirwan Center for Academic Innovation at the University System of Maryland, MJ Bishop, if innovation centers cannot demonstrate a calculated return on investment, they are vulnerable when times are tough in the institution (Chronicle of Higher Ed, 2018, Jan 26).
One of the greatest challenges that innovation centers in higher education face is that many of the most vital participants are faculty who are part of a culture that may not readily embrace design thinking as a valid methodology for research and development, due to its focus on customer needs and feelings, rather than on quantitative date. In particular, the "blue sky" part of design thinking which is the non-judgmental, crazy thinking, brainstorming sessions that encourage participants to share even their wildest ideas, may seem like a less than rigorous approach to the development of new ideas. Academics, after all, are created in a culture of defensible data and established knowledge, rules, and structures that create new theories and products through rigorous research. Faculty members' entire careers are based on their credibility and their ability to defend their work, so asking them to brainstorm a new idea and then 'run it up the flagpole to see how it flies' is not a practice they wish to embrace.
Fortunately, the field of design thinking is beginning to acknowledge the role that quantitative data must play in effective design. For example, Fjord, a global design and innovation firm that is part of Accenture Interactive, acknowledges the importance of marrying its design practice with data. Even individual practitioners are speaking out about the need to step back from the innovation craze sweeping the country and acknowledge that we must take a more critical and data-supported approach to the practice of design thinking. Innovation centers in higher education would be well served to heed these messages and make sure the practices they use, consider both qualitative data they collect from their observations and conversations with students, as well as quantitative data derived from tracking student usage, engagement, and outcomes related to courses, resources, and services.
So where do higher ed innovation centers find quantitative user data?
Higher ed innovation centers should begin their journey toward more data-informed practice by partnering with their institutional effectiveness departments. Institutional effectiveness departments collect data from all over the institution, yet in all of the articles on design thinking and innovation in higher education, I have rarely (never?) seen mention of a relationship between an institution's innovation center and its institutional effectiveness department. Why is that? Indeed, if good and bountiful data is a cornerstone of effective design, then it makes sense to marry the innovation center with the institutional effectiveness function. In fact, given that a primary reason for being of both the innovation and effectiveness functions is to continually identify, analyze, and solve performance problems, perhaps they should be collapsed into an overarching umbrella of organizational performance (or some such global term).
Another challenge to innovation is the implementation of the innovation into the organization. During implementation, the greatest and most common organizational obstacles to innovation are encountered: siloed structures; deeply entrenched culture; and staff skepticism and resistance to change. Yet successful implementation of innovation is paramount because, without it, the innovation does not become a solution that produces results and adds value; it simply remains an expense that many throughout the campus might resent.
To drive successful implementation of student success innovations, higher education design centers must expand their practice beyond design thinking and innovation to also include change management practice. Change strategies must address organizational factors including culture, organizational structure, and staff dynamics, far ahead of the actual opening of a design center or rollout of its innovations. Coordinated communication and training activities must provide clear, data-supported business cases for the problems the design center is intended to solve; articulate how design thinking and innovation will yield better solutions to those problems; and provide faculty and staff the opportunity to process each new innovation as it occurs, asking many questions and airing their concerns.
In terms of execution, innovation change strategies must be executed through comprehensive, detailed implementation plans that consider all functions and personnel divisions that will be affected by the innovation, which often include not only faculty, but student services, administration, institutional effectiveness/analytics, IT, finance, and policy, as well. Many design centers fall short in the area of change management; many fail to appreciate the gargantuan effort that is required for successful implementation, thinking that the heavy lifting is over once an innovation is developed. An example is the recently-closed Institute for Transformational Learning at the University of Texas System, created in 2012 by the Texas Board of Regents to improve student success (Chronicle of Higher Ed, 2018, Jan 26). According to the article, the center failed because it was driven from the top down, without gaining faculty and staff buy-in for either the center or its proposed projects; its business model was never adequately defined and, therefore, was perceived as only a major expense to the system; and its agenda was broad and vague, never clearly articulating the specific problems it was intended to solve.
While higher education is wise to be forward thinking and embrace innovation practices in looking for ways to improve student success, lack of attention to the change aspects of innovation practice often results in failures that can eventually lead to a lack of organizational confidence and support. Failure to partner with institutional effectiveness units and their vast amounts of institutional data further limits the integration and adoption efforts of innovation centers. As higher education continues to pour more and more dollars into the creation of innovation centers, it must also be sure to address the organizational issues that are vital to successful implementation of its innovations.
Chandler, C., Nusca, A., Yong, D., Lev-Ram, M., Fry, E., Kowitt, B., & Gallagher, L. (2017, December). Business by design. Fortune. Retrieved Feb 15, 2018 from http://fortune.com/2017/12/22/business-design-apple-airbnb-tesla/
Digest of Education Statistics, U.S. Department of Education, National Center for Education Statistics. (2016). Graduation rates (Table 326.10). Retrieved from https://nces.ed.gov/programs/digest/d16/tables/dt16_326.10.asp
IDEO. (2018). How we work. Retrieved from https://www.ideo.com/about
Kumar, V. (2013). 101 Design methods: A structured approach for driving innovation in your organization. New Jersey: Wiley & Sons.
McMurtrie, B. (2018, January 26). The hope and hype of the academic innovation center. The Chronicle of Higher Education, p. A14.
Woodhouse, K. (2015, Sep 28). Closures to triple. Inside Higher Ed. Retrieved from: https://www.insidehighered.com/news/2015/09/28/moodys-predicts-college-closures-triple-2017