August 22, 2017 | Higher Education, Institutional Analytics, Data Governance

    Best Practices in Data Governance: Lessons Learned at the RTM Higher Education Congress

    I had the opportunity to attend a timely session at the RTM Higher Education Congress a few weeks ago focused on “Data Governance and its Implications on Student Experience and Institutional Strategy.”  Given that I spend the majority of my time speaking with institutional leaders and stakeholders exploring paths for institutional analytics, across a broad set of colleges and universities, this is a very interesting topic to me.  Turns out that it’s also of great interest to leaders across IT, Enrollment Management and Academic Affairs as it was a packed house during the last session on the last day of the conference.

    For some context,  The Data Governance Institute defines “data governance” as “a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.” In other words, data governance helps institutions manage and define data. And while it is critically important for institutions to be on the same page with regard to their data, many institutions don’t currently have data governance.  In fact, in the room of more than 100 institutional leaders, less than 10 raised their hands when asked if they had data governance on their campuses.

     I’ve summarized highlights from the session below, including insights from the three panelists.

    • There are two important goals for approaching data governance:
      • 1: It’s the Institution’s Data, Not an Individual’s Data: No one is allowed to have their own private data or their own definitions.  It is the institution’s data, not their data, and therefore the institution owns the data. Defining what constitutes a full-time student, for example, is critical so everyone is on the same page when drawing insights from the data. This goal is beginning to manifest itself across higher education as we see references from data “owners” to data “stewards”.
      • 2: Trust is the Foundation for Success: For there to be trust in the central organization, so everyone is confident in the institutions central source of truth. There needs to be this shared ownership and understanding of the data so everyone can trust it. Without this, you cannot have data governance.
    • Leadership as Independent Actors: Sage advice from panelists
      • “I don’t make any decisions. I get people in the room and make sure that some decision gets made.  I don’t claim to be the owner of data or the person who has all the data.  I’ll get the people in the room to talk about it and determine where to go next.” - Jason Fishbain - Chief Data Officer, University of Wisconsin-Madison (WI)
      • “Many executives don’t actually know what questions they want answered.  Chief Data Officers work as a group that is able to abstract knowledge from the data sets from the business units.”  - Dr. Gerry McCartney - Chief Information Officer, Purdue University (IN)

    As the interest and engagement in the room indicated, the climate seems to be shifting toward a recognition that data governance is an important undertaking across all sectors of higher education. A common thread across the session was that higher education seems to be moving from the idea of data owners to data stewards.  It’s not an individual decision anymore but instead a business decision that’s made in the best interest of the institution. As the thinking around data and data governance changes, it becomes easier, and more critical, to have a plan to ensure the effective use of data to solve institutional challenges and impact strategy decisions.

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