Using advanced analytics can help higher educations institutes have successful development
The amount of data collected by higher education institutes is now huge and covers a large scope of subject, making it a precious resource. However, institutes often remain unsure of how to use this data in their operations.
In this article, Marc Krawitz gives some guidelines of what can be achieved using data to take decisions – and good ones.
Leaders in higher-education institutions generally understand that using advanced analytics can significantly transform the way they work by enabling new ways to engage current and prospective students, increase student enrolment, improve student retention and completion rates, and even boost faculty productivity and research.
By interviewing a lot of senior leaders at colleges and universities that made their transformation a success, this article aims at sharing some insights to finally answer this question: What really works?
Data Helps Understand the Right Challenges
The report highlights the importance of changing the idea of the company concerning data – and all the rules that come with it. Some of these rules gives as examples are the following:
Being overly focused on external compliance. Many higher-education institutions’ data analytics teams focus most of their efforts on generating reports to satisfy operational, regulatory, or statutory compliance.
Isolating the analytics program in an existing department. In our experience, analytics teams in higher-education institutions usually report to the head of an existing function or department—typically the institutional research team or the enrollment-management group.
Failing to establish a culture of data sharing and hygiene. In many higher-education institutions, there is little incentive (and much reluctance) to share data. As a result, most higher-education institutions lack good data hygiene—that is, established rules for who can access various forms of data, as well as formal policies for how they can share those data across departments.
Lacking the appropriate talent. Budgets and other constraints can make it difficult for higher-education institutions to meet market rates for analytics talent. Colleges and universities could potentially benefit from sourcing analytics talent among their graduate students and faculty, but it can be a struggle to attract and retain them.
Student Analytics Make It Easy to Set Up Effective Plans
Articulate an analytics mandate that goes beyond compliance. Senior leaders in higher education must signal that analytics is a strategic priority. Indeed, to realize the potential of analytics, the function cannot be considered solely as a cost center for compliance. Instead, this team must be seen as a source of innovation and an economic engine for the institution.
Establish a central analytics team with direct reporting lines to executive leaders. To mitigate the downsides of analytics teams couched in existing departments or decentralized across several functions, higher-education leaders must explicitly allocate the requisite financial and human resources to establish a central department or function to oversee and manage the use of analytics across the institution.
Win analytics buy-in from the front line and create a culture of data-driven decision making. To overcome the cultural resistance to data sharing, the analytics team must take the lead on engendering meaningful communications about analytics across the institution. To this end, it helps to have members of the centralized analytics function interact formally and frequently with different departments across the university.
Strengthen in-house analytical capabilities. The skills gap is an obvious impediment to colleges’ and universities’ attempts to transform operations through advanced analytics—thus, it is perfectly acceptable to contract out work in the short term.
Do not let great be the enemy of good. It takes time to launch a successful analytics program. At the outset, institutions may lack certain types of data, and not every assessment will yield insightful results—but that is no reason to pull back on experimentation.
You’ll See Quickly The Impact Of Using Data
It is easy to forget that analytics is a beginning, not an end. Analytics is a critical enabler to help colleges and universities solve tough problems—but leaders in higher-education institutions must devote just as much energy to acting on the insights from the data as they do on enabling analysis of the data. Implementation requires significant changes in culture, policy, and processes. When outcomes improve because a university successfully implemented change—even in a limited environment—the rest of the institution takes notice. This can strengthen the institutional will to push further and start tackling other areas of the organization that need improvement.
The next wave of advanced analytics will, among other things, enable bespoke, personalized student experiences, with teaching catered to students’ individual learning styles and competency levels. To realize the great promise of analytics in the years to come, senior leaders must focus on more than just making incremental improvements in business processes or transactions. Our conversations with leaders in higher education point to the need for colleges and universities to establish a strong analytics function as well as a culture of data-driven decision making and a focus on delivering measurable outcomes. In doing so, institutions can create significant value for students—and sustainable operations for themselves.