How colleges and universities can use analytical resources to better serve their missions
By Jonathan S. Gagliardi and Philip Wilkinson
As vital drivers of social mobility, economic growth, and community development, U.S. colleges and universities have long been regarded as among the best in the world. However, in light of national test scores falling behind our international peers, some stakeholders have begun to question whether or not that will remain true in the future.
Over the last decade, this uncertainty has led to the creation of a series of aspirational educational attainment goals known collectively as the completion agenda. The completion agenda serves many purposes. For lawmakers and employers, it is a human capital development strategy aimed at promoting social justice, economic prosperity, and community development. Institutions, particularly in states that are in the midst of a demographic winter, often see it as a way to fulfill their dual promise of access and opportunity, and as a strategy for campus sustainability.
Academics, by necessity, are reconsidering their fundamental identities and operations in light of the emerging focus on attainment goals. As leaders prepare their campuses institutions for the process of transformational change, many have begun by assessing whether or not institutional structures and arrangements get in the way of student success. These efforts entail identifying ways to improve student outcomes while promoting diversity, equity, and inclusion. Other efforts seek to optimize resources to support the values and missions that are at the institution’s core. Doing this successfully requires four key ingredients: data, insight, leadership, and action.
We are smack-dab in the middle of an analytics revolution. The term “big data” describes the types and scale of data that are being generated in ways and amounts that have never been seen before. Over the last decade, data analytics has evolved from a buzzword to a multibillion-dollar business, and it has begun to permeate higher education.
Among the many uses, some institutions have employed data analytics to create more personalized approaches to advising. Others have leveraged predictive analytics to estimate the likelihood of student progress through courses and majors. Still others have used such analytics to combine data with teaching and advising to help improve student outcomes, particularly among underserved students.
Strong leadership and a recognition of the value of data-informed decision making are key factors in the planning and successful implementation of analytics solutions at the campus level. Still, data savvy presidents who have successfully tamed the groundswell of data and analytics tools remain the exception, not the rule. One only has to look to the retail sector to find examples of leaders who refused to or were late to harnessing their data and evolving their operations to find organizations that are withering on the vine.
But there are colleges and universities who have learned to strategically harness data in order to improve student outcomes, especially as external stakeholders place a premium on degrees and jobs. The last few years have seen institutions such as the University of Texas System develop creative data-sharing agreements with state and federal agencies that sparked the development of groundbreaking analyses and visualization tools at the intersection of student success and workforce outcomes. As the U.S. population continues to change and diversify, colleges and universities are also using data to identify ways to promote diversity, equity, and inclusion. As a result of an effort to develop analytics platforms that began in the early 2000’s, Georgia State University has increased graduation rates by over 20 percent and closed equity gaps for low-income students and students of color.
While higher education works to increase equity and improve student outcomes, campuses are anticipating a plateau in the number of recent high school graduates, as well as a continuation in the decline of financial support from states. As this occurs, colleges and universities have begun to use data to optimize the investment of time, talent, and resources, including assessing the use of facilities, monitoring the performance of academic programs and student services, and identifying optimization opportunities. Hundreds of campuses have participated in the Delaware Cost Study, the only national study that provides campuses with a clear picture of teaching loads, direct instructional costs, and other academic activities relative to cost.
To even begin methodically collecting and interpreting data requires infrastructure, which many campuses lack. Standing in the way of building a smarter campus are challenges related to data quality and standardization, a lack of data integration across key functions, the complexities of executing more predictive analytics, and a lack of both financial and human resources.
Cultural issues can also stop efforts to modernize analytics dead in their tracks. Initial efforts to create an analytics-informed campus often raise concerns among key administrators and faculty. If efforts to use data are not effectively rolled out, campus stakeholders worry about the possible harm that irresponsible or unethical data use can cause to students, in addition to the possibility of program cuts or job losses.
These concerns are not unwarranted. Historic tensions between functions like institutional research, information technology, budget and finance, and student affairs over the ownership of data and competition for scarce resources can bog analytics down in a political quagmire.
Leadership is needed to build a data-informed campus and to modernize analytics infrastructure. Campuses need to begin treating their data as importantly as their financial assets. Having access to good, relevant data resources is as important as access to financial resources for leaders to be able to strike while the iron is still hot—to make more informed decisions quicker and capitalize on opportunities.
For starters, college and university presidents must blend the science of data with the art decision-making. A president who can inform their campus about how data was used to guide the decision-making process and communicate their commitment to using data provides both a path and a safety net for others to follow. Only then can administrators and faculty be expected to use data in role-specific ways that augment teaching, learning, and advising. That requires a long-term data strategy that is tied to a vision for the future that honors the identity and history of the campus. Presidents need to work collaboratively to ensure consensus around the intent of harnessing data analytics to do that effectively.
A sound and flexible data governance framework is a must in order to increase and improve the opportunity for and the use of campus-wide data use. Such a framework should make clear that the data belongs to the entire campus instead of a select few departments or units. Doing so helps remove some of the political barriers to using data across the institution, and it is an important first step in neutralizing conflicts that stem from issues around data ownership and use. This framework should be malleable and adapt to the needs of the users as projects, data collection techniques and technologies, objectives, and priorities mature. At the same time, ethical guidelines related to the use of data also must be clearly outlined.
The rate of technological innovation and use has and will always outpace the creation of policies and laws that restrict or attempt to rein in those technologies. The last decade has exposed this gap more than ever before as concerns have arisen about how data governance is created and how data are being collected and used by governments, police and security agencies, social networking companies, hospitals, and internet services and service providers.
It is essential for privacy and security protocols to be developed to account for the growing volume of unstructured data and network-connected devices on a campus that already provide vast amounts of data. Higher education institutions can limit the risk for both themselves and their digital resources by collaborating with other like-minded institutions to establish a series of standards and best practices for privacy and security policies. In time, such agreed-upon policies and practices can be presented to governmental agencies and other bodies to create laws and even more formal policies that will further reduce the risk and uncertainty in creating and adapting data governance and use policies at the campus level.
Becoming a data-enabled executive is easier said than done, and the process of creating a campus-wide culture of data use is often more fraught than it seems. Real barriers stand in the way, and we need to better understand what they are.
But if the time to begin using data and data analytics better is not now, when is it? How will those who choose delay or ignore the data revolution on their campuses fare in the future? How will their campuses remain either relevant or even viable as they watch the higher education ecosystem adapt around—and without—them? These are serious questions, and now more than ever, serious leaders are needed to point the direction forward.