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Economic Mobility: Data-Driven Responses in a Disruptive Time

Explore the importance of data-driven decision-making in higher education and discover how colleges and universities can thrive in a disruptive time. Learn effective strategies, success stories, and tips for utilizing data analytics to increase enrollment, improve retention, and identify growth opportunities.

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Economic Mobility: Data-Driven Responses in a Disruptive Time

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  1. Economic Mobility: Data-Driven Responses in a Disruptive Time Jonathan Kaplan

  2. 2100* * Based on average US female life expectancy (CDC data)

  3. This morning, I’d like to cover…. • Observations about data and decision-making in higher education • Examples of how I’ve seen data used successfully • Tips for leaders and ‘data pros’

  4. Typically in big organizations… Decisions are made based on a little data….and a lotof: • Assumptions • Prior experience • Politics • Biases • Bureaucratic inertia

  5. Higher ed struggles with data & decision-making • According to New America study, fewer than half of colleges and universities see the use of predictive analytics as a priority for improving performance (New America Foundation study, “The Promise and Peril of Predictive Analytics in Higher Education,” 2016) • Last month, 3 major higher education groups urged colleges to speed up adoption of data analytics (AIR, NACUBO, Educause)

  6. Bill & Melinda Gates Foundation Report: • The problem in higher ed is not just an unwillingness to use data, but a matter of capability • Many colleges and universities don’t hire or develop the expertise

  7. Urgent need for data analytics in higher ed • “A sharp decrease in fertility during the Great Recession will further deepen the high-school graduation trough by 2026” (The Chronicle of Higher Education, 9/9/19) • To maintain enrollments, ”the national, first-year discount rate had already crested the 50-percent mark,” an increase from 39 percent in 2008 (Chronicle; NACUBO) • Higher ed leaders have to use data more effectively going forward • to increase economic opportunity and mobility • to ensure the financial strength, and perhaps viability, of their institutions

  8. How can data analytics help colleges thrive/survive? • Increase new enrollment yield • Improve retention • Increase graduation rates • Identify growth opportunities such as successfully launching new program offerings

  9. New Program OfferingsExample of using data successfully in higher ed • Historically, programs were offered because they were areas of personal interest for department chairs • Today, colleges must be more market-oriented • Labor market data can help determine the best new program areas to enter • Data is essential to measure: • market demand… • trend lines… • Pricing/tuition…. • student ROI… • financial impact on university

  10. Tips for using data effectively at your institution • Don’t make the perfect the enemy of the good. Know when some data is enough. And focus as much on accurate data interpretation as on data gathering. • Break down siloes. Collaborate across your organization to ensure that anyone’s data is everyone’s data. • Think globally. Act locally. Gather data with the big picture in mind, and then apply the solutions to take incremental but important steps. Even if they are small steps, they can add up to have a big impact for students and your institution.

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