A number of technologies and practices have great potential to impact postsecondary data and analytics adoption

4 scenarios for the future of postsecondary data and analytics

A number of technologies and practices have great potential to impact postsecondary data and analytics adoption

Current technologies and practices have big implications for the future of postsecondary data and analytics.

The 2022 EDUCAUSE Horizon Report: Data and Analytics Edition profiles trends and key technologies that are impacting data and analytics. The report also outlines various scenarios and implications based on perspectives and expertise from a panel of higher-ed leaders. These implications will drive institutional decision-making and strategic planning for the future.

Horizon panelists identified 15 trends, across five categories, as post important in shaping the future of postsecondary data and analytics.

• Institutions are increasingly asked to support decisions with data.
• Many big data methods reinforce social inequality.
• A focus on creating equitable learning and work environments is increasing.

• Existing data infrastructures are outdated and disorganized.
• Institutions still struggle to implement data governance systems.
• Data literacy and AI skills still lag behind the rapid adoption of big data analytics products.

• Free or inexpensive certificates from nonaccredited platforms are becoming more common.
• The value and ROI of a college degree are being questioned.
• Tech salaries are growing at an unprecedented rate.

• Institutions are rethinking the use of their physical spaces.
• Commuting patterns are changing due to the pandemic.
• The demand for green IT services is growing.

• Data privacy laws are getting more complex around the globe.
• There is increasing political involvement in public education.
• AI technology is being used for policing.

Panelists also identified the most critical technologies and practices that they think are poised to have a significant impact on the future of postsecondary data and analytics.

Those technologies and practices include:
Data Management and Governance
• Unifying Data Sources
• Modern Data Architecture
• Data Literacy Training
• DEI for Data and Analytics
• Assessing and Improving Institutional Data and Analytics Capabilities

As the panelists considered the potential for each of these technologies and practices individually to have an impact on overall institutional data and analytics adoption, they also highlighted the interdependencies between these technologies and practices.

Those considerations led to four potential scenarios for the future of postsecondary data and analytics.

1. Growth: “Only measurement matters” has become a common catchphrase in higher education as institutions are increasingly being asked to adhere to data-driven
decision-making processes.

2. Constraint: Institutions have been forced to operate on dwindling budgets, and data and analytics teams in particular are understaffed and overwhelmed.

3. Collapse: Public opinion on the value and ROI of a traditional college degree has continued on a downward trend, and underfunded and understaffed institutions lack the data and analytics capabilities for measuring and reporting compelling evidence of their value to skeptical consumers.

4. Transformation: Efficiency is driving value around the world, and higher education has taken on the challenge of improving the health of our global ecosystems by
redefining the purposes and uses of physical spaces.

Find the full report and detailed perspectives here.

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Laura Ascione