Academic Analytics in Higher Education: Barriers to Adoption

The analysis of big data points and the use of data analytics have proven successful in improving corporate business efficiencies, growing profits, and increasing competitive advantages. The theory of academic capitalism, which holds that institutions of higher education are becoming more like corporations due to declining operating funds and the need to become more efficient, transparent, and competitive, guided this study. Despite the positive outcomes that analytic tools may produce in advanced efficiencies and competitive growth, college academic administrators have not yet adopted these tools, due in part to barriers facing the administrators. The purpose of this phenomenological study was to explore the nature of those barriers in a community college. Ten academic managers in 6 community college divisions who reported accountability for criterion-based key performance indicators were interviewed on their perceived use of academic analytic tools and barriers in adopting these tools. The interviews were collected and analyzed through preliminary grouping, reducing and eliminating outliers, clustering descriptions into categories, and constructing themes. The managers' narratives suggested that there were 4 perceived barriers that prevented the adoption of tools such as organizational bureaucracy (climate), restricted organizational data (policy), training, and infrastructure. An important area for further research involves identifying the strategies managers could use to overcome these barriers. The findings of this study will assist college administrators in implementing analytic tools. Such tools will improve key performance indicators, resulting in a more cohesive and cost-effective academic experience for students, faculty, administrators, and the community