Sinclair Community College in Dayton, Ohio has been a leader in the use of data and analytics for years, thanks to the efforts of Karl Konsdorf, Sinclair’s director of research, analytics, and reporting. Konsdorf leads a team responsible for database administration, institutional research, report development, and data quality. His group helps Sinclair understand and gain insight into student success and student outcomes.
Recently, Konsdorf deployed a new data-visualization strategy that allows users to conduct interactive reporting, visual data discovery, and self-service analytics. Enrollment managers, department heads, deans, and advisers can interact with reports, collaborate on insights, and slice and dice data to make proactive decisions about enrollment, retention, performance, and degree completion. For example, what is enrollment this year compared with the same time last year?
Based on his data-visualization success, Konsdorf offers the following five tips for colleges and universities hoping to increase self-service access to reports so that decision-makers can quickly get the answers they need.
1. Secure buy-in at all levels of management. Data and analytics programs need to have executive sponsorship at the highest level—someone who fully understands the value the initiative can bring to the institution and has a vision for using it to improve school, program, and student outcomes.
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The endorsement and support should extend down to mid-level managers, too. They talk to employees regularly about using data for decision making and model using it in meetings and other contexts. This total management buy-in from the top down is vital, as non-data people are often intimidated by working with data and analytical reports, which can hinder adoption.
2. Modernize your data and analytics platform to handle large amounts of data quickly. Konsdorf worked to modernize Sinclair’s system because the college’s users wanted to be able to use the data to quickly visualize patterns and trends. According to Konsdorf, in-memory environment for interactive reporting, visual data discovery, and self-service analytics addressed those needs.
The data-visualization initiative effort kicked off with a single node deployment of SAS Visual Analytics but, due to some exceptionally large data sets, Sinclair moved to a distributed environment. Using this environment, the response times have been amazing. For example, for one of the largest reports, incorporating 15 years of census data, they are able to load the data, process the data, and calculate statistics with a response time of less than five seconds.
3. Develop a consistent, intuitive visual interface. The interactive interface includes list boxes, drop-downs, and other user-friendly elements that have made training easier for Sinclair. Reports are deployed to the community, as opposed to users creating their own reports or explorations. Sinclair adopted development standards so that reports have the same basic look and feel. If someone begins using the enrollment report, he or she can seamlessly transition to reports on degree completion, course success, degree audits, performance funding, payroll, or finance.
Konsdorf compares the new reports to the iPhone phenomenon. The reports are so intuitive that little training or documentation is required. Simple, easy-to-use reports have made servicing basic requests much easier. Consolidating information into consistent, frequently updated reports that answer the most common questions has allowed Sinclair to dramatically reduce the amount of overall reports from 1,600 to 20!
4. Encourage a culture of trusted data usage. Make sure that the data is of high quality so people believe in it and trust it. Konsdorf promotes a culture of data usage through bi-monthly training sessions at Sinclair’s Center for Teaching and Learning. He has found that these one-hour classes further increase usage and adoption of the data visualization reports. Currently, he has more than 1000 users.
Konsdorf also started an annual summit on data and analytics. Nearly one-third of all full-time employees of the college, including the president, vice presidents, deans, directors, managers, and some faculty, have attended. This level of engagement, particularly with leadership (see tip #1), is critical to fostering a culture in which data is valued and used for data-informed decision making. The summit emphasizes how important and useful data is and how it is being used at Sinclair to help students succeed.
5. Be prepared for more sophisticated users and questions. Konsdorf admits that empowering users has not freed up his team’s time. As users become more sophisticated and interact with the data, they generate more questions. As such, Konsdorf’s team is now being asked to do more sophisticated analyses. Konsdorf plans to tackle intelligent scheduling to help Sinclair determine the ideal number of courses to offer, when and where to offer them, and the number of faculty members needed for instruction.
Konsdorf is encouraged by this deeper dive into the data, as it means his group is moving away from being just a reporting department to a true research and analytics department.
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