Technology works best when it is integrated into an institution's strategic vision. Our deployment of analytics coincided with a strategic plan outlined four years ago by University President Stephen Spinelli that called for aggressive growth and innovation. We needed 24x7 data access and decision support tools to support our growth.
Philadelphia University's strategic plan calls for developing a model for professional education that gives graduates not only the competencies in their professions, but also lifelong learning skills in communications, problem solving and critical reasoning. Our students have the breadth of liberal education to be problem solvers and the professional focus to lead in their chosen fields.
To accomplish this, we are growing undergraduate and graduate programs and facilities, advancing research and collaborating with industry leaders to create active, real-world learning opportunities for our students. We have also consolidated our schools into three colleges, including the creation of a new college that fully integrates the curriculum of design, engineering and business majors. The ambition of this plan called for a new approach to how we make rapid, informed decisions.
We also want the university to be a center of innovation. This means building flexible classrooms and modern research facilities and locating specialized labs, student lounges and study centers in close proximity to one another. The university is so serious about innovation that it created a new position of executive director of innovation, believed to be one of the first positions of its kind in higher education.
Meeting these goals means that we have to work more collaboratively, sharing information in real time. What became clear is that the static reports we use no longer suffice. We need to deliver executive dashboards to the president's cabinet, top administrators and department heads so they can make faster and more effective decisions. We took our analytics proposal to President Spinelli, who provided buy-in and full support for the concept. In a very short time, we were under way and have already deployed key dashboards across campus. Based on our experience over the last two years, here are some recommended best practices.
Show top management tangible benefits to the bottom line. To institute the broad organizational change that creating a data-driven culture entails, it's essential that the project receive full administration support. We were fortunate that we had that support, but it also helped that we were ready from an IT infrastructure perspective. In addition, we recognized that it's very difficult to justify an investment in analytics simply based on making faster and better decisions, as it's very hard to quantify. We focused on what we thought would be the most tangible impact in the short term: better utilization of existing resources.
100% The growth in portal offerings based on business analytics at Philadelphia University since April 2011
SOURCE: Philadelphia University
We showed the labor consumed by the status quo of manual reporting and how that could be repurposed by automating reports, as well as how analytics could help us make better decisions on our class offerings and resource utilization. For example, we run about 1,000 course sections per semester. A portion of those sections could be consolidated or modified without impacting educational outcomes. It is our expectation that by consolidating enrollments we could save money on space and human resources. That's the kind of bottom line data that provides the most concrete justification for investing in analytics.
Gain support by winning over the departments. It's really important to meet with your constituents. We always start by telling a group or department that this is what a dashboard could look like. We never dictate. We always invite them to tell us how they would envision the new business process and ask them to outline the workflow. For analytics to work, the people using the tools have to feel that it's their dashboard and their data, and that there is no loss of data control.
It's also important to understand each group of stakeholders. For top management, the primary drivers are return on investment and transparency. At the department manager level, the ability to keep tabs on the group's progress is what's important. And at the staff level, it's automated reporting that sells analytics. Then we show them that moving forward, the information will be available at any time, as opposed to having to spend many hours a week on reporting alone.
One important win for our team was with the athletics department, which used to do a lot of manual data searches to respond to compliance requirements. Now, the information is on the dashboard in an easy-to-use graphical format whenever they need it. Other early successes were in the advancement office and international student office, where they learned how we could significantly reduce reporting time.
Look for ways to leverage existing technologies. Start by assessing the institution's readiness for analytics and dashboard tools. One of the most important decisions we made took place about 10 years ago when we deployed an integrated enterprise resource planning system built around a common database. Once we did that, we moved to an SQL database, which meant we finally had a nonproprietary database that could support collaboration tools such as Microsoft SharePoint. We had licenses for SQL and SharePoint, so the analytics and data mining operation were built on technology we already had.
Establish a user's group. Never underestimate what a big change the analytics effort represents to the rank-and-file departments and staff. Many of our people had been working with the same systems for several years. The user's group helped mitigate the resistance and cultural barriers and served as a consistent place for all parties to address concerns and work through any problems or issues. We couldn't have succeeded without it.
By taking these ambitious steps, we have successfully developed the support tools and culture of data-driven decision-making to advance Philadelphia University as a high-performance organization.