To take full advantage of analytics, a college or university must first develop a data-enabled institutional culture.
The mantra "data-driven decision-making" is one that institutions of higher education are adopting at an increasing clip. More than three-quarters of colleges and universities say institutional analytics is a priority. However, as more projects get off the ground, some initiatives are falling flat. What's happening? Data are being kept in the periphery. For an analytics program to be useful, leaders must build an institutional data culture that sets analytics as its modus operandi.
Culture is easy to overlook. Undervaluing its role, however, can hinder any institutional analytics effort. More conversations are starting to take place around an analytics culture in higher education. Notably, this year the EDUCAUSE Top 10 IT Issues crystalized the idea by identifying "data-enabled institutional culture" as the number 4 issue. The shift from last year's related theme of "data-informed decision-making" is a subtle but significant difference, particularly in terms of the possible impact of data and analytics.
As the challenge of cultivating a data culture emerges, there is no clear blueprint for doing so. Lessons can be learned from early successes, however, including the importance of insisting on governance and data fidelity, making investments in people, establishing two-way communication, and recognizing that building culture is a process. Those are just some of the lessons we learned as we launched data initiatives, first at the University of Maryland University College (UMUC) and then at other institutions through HelioCampus.
In 2012, UMUC began to experience unprecedented enrollment volatility. The university's president, Javier Miyares, made the decision to form the Office of Analytics, which I led until the unit was spun off into a private company, HelioCampus, in 2016. Our charter was to compile and analyze the information from our many systems, yet we still ran into small hurdles that slowed our momentum. We started looking at how we were operationalizing analytics on campus and realized that making decisions based on the data was only half of the challenge. A separate challenge was facilitating meaningful conversations using data and changing the way the institution thinks as a whole.
To foster a data-enabled institutional culture, we knew our institutional practices and leaders had to evolve purposefully. We did that by identifying five best practices.
Establish One Source of Truth
Individual departments or teams often use data to inform decisions. This can create conflicting information, making it harder to have a meaningful impact across an institution. A better route is to establish a hub-and-spoke method in which power users in different areas use common data models to create their own analysis and key metrics from a core platform. This model allows for customization and flexibility while setting up data governance to reaffirm the principle that the data belong to the institution, not an individual.
Form Cross-Functional Teams
Higher education can be full of silos and separations. To build an effective data culture, there cannot be 18 different ways of operating. Cross-functional teams create bridges that bring together finance, enrollment management, academics affairs, and other key stakeholders. Together, individuals from these groups can see how data points, patterns, and trends intersect and influence each other. In these cross-functional teams, communication and focus are key. Recurring meetings, with standardized, data-centric agendas can help keep efforts on track. For example, daily meetings can be held to disseminate key information the team needs, weekly meetings to show how the efforts are tracking to goals, and monthly meetings to conduct a business review or as a precursor to an executive committee meeting. This level of transparency additionally helps with the ongoing process of securing buy-in from all levels of the institution.
Appoint a Data Czar
Although a data culture must be embraced by all, having one person lead the charge is essential. After all, if everyone is responsible, then no one is responsible. Enter the data czar, or chief data officer (CDO). Right now, only a handful of institutions have a CDO in place. But, this person is vital to supporting data governance and data stewardship models. As EDUCAUSE writes, these experts are the people who ask questions in meetings about the meaning, application, or validity of data, as well as how an institution will keep improving. To be effective, the data czar should have a direct reporting line to the president of the institution or to another senior administrator, allowing the data czar to maintain independence.
Data stewards do not have to be internal appointees. Sometimes they can be external, independent actors. According to Gartner, "In the absence of strong leadership and/or resources, institutions need a provider that can serve as that change agent, independent actor, and neutral third party." Third-party, unbiased, external data czars might be more open to surprises because they don't have a stake in the data. These people can help institutions uncover truths in their data and debunk or validate assumptions.
Make the Effort Bi-Directional
Creating a data culture will never work as a one-directional effort. It is a top-down and bottom-up approach. Data are not "owned" by a single individual or department, and, as a result, communicating the importance of data isn't solely housed within one skill set. Colleges and universities need the right combination of experts at all levels to create an effective data culture. From the bottom up, institutions should start small and let success go viral. Those wins accumulate — as one department or person sees traction, that will provide the best publicity for data efforts as everyone else will want that same level of impact. On the opposite end of the spectrum, leadership needs to provide air cover and autonomy from the start of efforts to allow data culture to flourish.
Commit to an Ongoing Analysis Agenda
Creating a data culture is ever evolving and ongoing. Like any culture, data culture is dynamic and living and so requires persistence and commitment. Institutions must keep analyzing their efforts and using data to ask questions and inform actions. Data will not get better left unattended, and data won't automatically tell a story. A dedicated team of business intelligence and analytics professionals are needed to be custodians of the data and to be experts in the metrics that run the institution.
Effectively integrating data into how an institution thinks and acts is essential — now and for the foreseeable future. From funding to new competition and to questions about the ROI on a college degree, downward pressure on the higher education community will continue. Paying attention to data culture will help institutions avoid being caught flatfooted as the ground shifts beneath them. To be able to deliver quality education to students and nimbly adapt to external changes, institutions must encourage a culture that values data analysis to reach their potential.
Darren Catalano is CEO at HelioCampus and was formerly Vice President of Analytics at the University of Maryland University College.
© 2018 Darren Catalano. The text of this work is licensed under a Creative Commons BY 4.0 International License.