In recent years, the idea of data-driven decision making has been propelling much of the higher education narrative. As many industries work to incorporate data and analytics into their organizational processes, education providers are also tasked with adopting a more thoroughly informed management approach. A 2013 report titled Building Organizational Capacity for Analytics highlighted that “enhanced analytics is critical to both optimizing student success and achieving institutional effectiveness.” Undoubtedly, a data-driven mindset should penetrate all levels of higher education decision making, from program development to student retention and graduation.

In an increasingly competitive higher education environment, the benefits of advanced data collection and analytics permeate all aspects of both student success and institutional success. Yet while higher education has been flooded with calls to adopt a data-driven mindset, the adoption of this ethos is proving difficult for many institutions to implement in practice. In an attempt to understand how higher education institutions have actually incorporated the use of data and analytics into their decision making, Helix Education and UPCEA (the University Professional and Continuing Education Association) have partnered to conduct a study of the use of metrics and the creation of a data-driven environment.

The primary goal of this research was to outline the current landscape of decision making among higher education providers and assess the role of data in management and leadership. While many institutions have introduced some data analysis activities to inform some decisions, this research reveals that for a majority of education providers, data science and analytics are being underutilized when making decisions about program development, marketing, enrollment, and retention services—a reality leading to a waste of both financial resources and staff time. For example, almost half of those surveyed indicated that they have no formalized system in place to determine which new programs are developed, and the majority of institutions don’t know their estimated conversion rate from inquiry to enrollment. While higher education is slowly adopting technologies and processes that drive data integration and analysis, the majority of institutions are hamstrung by a lack of data integration or capacity for data analytics.

A secondary goal of this research was to assess how colleges and universities are mitigating barriers to the data-driven mindset. Many embrace the idea that experience and intuition are not enough to make efficient and effective decisions at all institutional levels. For those institutions that acknowledge gaps in their capacity to be data-driven, this research shows that many are looking to outsourced partners for help.

Snapshot of Key Findings

• Eighty-three percent of respondents indicated no knowledge of the cost-per-inquiry of their most effective marketing channel for undergraduate inquiry, and more than half made the same indication for graduate inquiry.
• Sixty-eight percent of respondents don’t know their estimated overall conversion rate from inquiry to start.
• Less than half of respondents have a formalized system in place to determine which new programs are developed.
• Only thirty-eight percent of respondents reported close integration between marketing, enrollment management, and advising teams.

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