Perceptions of leadership sentiments toward analytics are largely optimistic. A majority of respondents (79%) indicated that their institutional leaders have proactive/optimistic sentiments toward analytics (see figure 1). A plurality (45%) said that leaders at their institution are fully committed to and actively investing in analytics, while 34% said their leaders are interested in analytics. Only 10% of respondents reported that their leaders felt neutral or skeptical/cautious toward analytics.

Perceptions of leadership sentiments vary by respondent role and area of responsibility. Executives (57%) were more likely to say that institutional leaders are fully committed to and actively investing in analytics, compared to directors/managers (42%) and professionals/staff/faculty/other (40%) (see figure 2). Interestingly, respondents whose primary area of responsibility is data and analytics were the least likely to say that their institutional leaders are fully committed to/actively investing in analytics (38%), compared to those whose primary area of responsibility was technology (49%), education, scholarship, and research (46%), or cybersecurity and privacy, business operations, other (41%).1 Presumably data and analytics staff are the most knowledgeable in this area and are therefore more likely to be aware of the gaps, challenges, and areas for improvement and more likely to be critical of current practices.

Data are deemed to be accurate and useful at many institutions. A majority of respondents said that data are somewhat or greatly accurate and useful for analytics as their institution (see figure 3). Student success data (81%), academic data (83%), financial data (74%), operational data (74%), and learning data (70%) were all reported to be somewhat or greatly accurate and useful for analytics. Notably, very few respondents reported that data were not at all accurate/useful for analytics at their institution (less than 5%). Respondents reported greater accuracy/usefulness of student success data (46%), academic data (45%), and financial data (43%) compared to operational data (34%) and learning data (29%).