Data governance plays a key role in academic program evaluation and management. Strong data governance enables data integrity. This leads to timely and insightful analyses, which ultimately facilitates a full and accurate expression of the institutional story.
What is Data Governance?
Gartner defines data governance as “the specification of decision rights and an accountability framework to ensure the appropriate behavior in the valuation, creation, consumption, and control of data and analytics.”
Having a data governance plan in place can ensure the quality and security of data used in your institution and define how an action will take place based on that data.
Why Is Data Governance Important for Academic Program Evaluation and Management?
Decisions related to adding, discontinuing, or changing academic programs cannot be effectively implemented across all units of an institution unless close attention is paid to data governance. Strong data governance begins with collaboration and cross-unit communication. It is essential that representatives from various units, both academic and operational, participate in the data governance process; they know their unit’s business and data needs best.
Data governance structures that comprise active participation from relevant internal stakeholders allow leaders to be well-positioned to make better informed, faster decisions. Failure to consider input from across the enterprise can lead to confusion, workarounds, and implementation gaps, contributing to operational inefficiency and political tension.
As I mentioned in my previous blog post: The Journey: Fostering a Data-Informed Culture, our data governance structure is grounded in our Academic Program Support Team (APST), a cross-functional group of faculty, staff, and administrators who review program proposals. The APST acts as the gatekeeper of data governance and has transformed what was once a form-driven, decentralized, isolated, inconsistent process into clear frameworks that encompass collaborative and robust data governance culminating in program approval.
A Framework for Academic Program Proposals
When program directors or chairs desire to start a new program, they contact me for a market analysis and financial evaluation. I walk them through the steps outlined in the first Framework below, defining roles, expectations, deliverables, and deadlines. The proposer then proceeds to a curriculum consultation with our Center for Excellence in Learning and Teaching (CELT). This consultation is a vital data governance step because it focuses on how data related to the assessment of student learning will be captured and analyzed. Following the CELT consultation, the proposer completes and submits the New Academic Program Proposal Form that officially documents the proposal’s details from both an academic and operational perspective. The market/financial and curricular analyses are required attachments to this form.
Upon receipt of the entire proposal, the APST engages in the data governance review. Based on the market analysis, the financial analysis, the curriculum consultation, and the operational details, this group scrutinizes data governance questions related to coding, catalog requirements, billing rules, and modality, etc. It makes a recommendation on whether or not to move forward with the proposed program. This is an important step, as the proposal has been thoroughly vetted prior to the approval stage.
The framework for new academic program proposals is shown below:
A Framework for Academic Program Change Requests
The framework is similar when program directors or chairs desire to make a change to an existing program.
Examples of program change requests include adding a location, changing the number of required credits, changing the modality, or discontinuing a program. The change request process starts with the program director submitting an Academic Program Change Request Form to the APST. In this framework, the market, financial, and curriculum consultations are not required upfront. However, the APST may request any of these consultations along the way if it feels they are needed to make an informed decision. Fewer approvals are needed for program change requests, so the approval stage is condensed compared to new program proposals.
The framework for a proposal to a change in an existing academic program is shown below:
In both frameworks, once the approval stage is completed, the details of the decision, including the data governance components, are communicated to all relevant internal stakeholders, and change implementation occurs seamlessly.
In future blog posts, I will describe the steps in these frameworks in greater detail.
- Start with the market and financial consultations. This adds to the efficiency of the process. In planning the workflow, look at the market and financial data early in the process. In a few proposals, I quickly assessed that the market (i.e., student demand, low competition, employment) was not very strong, or that a program would produce an insufficient return on investment in the early years. I identified and shared these issues with the proposer, allowing either a quick end to the decision or a new proposal that addressed these deficiencies.
- Be intentional about the representation on your steering committee. I will focus on this topic in a future blog post. When we formed our steering committee, we sought a cross-functional group representing faculty and administrators from our campuses. Our faculty representatives are nominated by their peers and have rotating terms. Committee members should have specialized knowledge of academic operations and/or curriculum. This expertise is key to strong data governance.
- Find a balance between curriculum and operations. Our initial, less effective, and somewhat dysfunctional process focused mainly on curriculum. Subsequently, we minimized market and financial implications and neglected operational details. Meetings were spent clarifying long narratives and fixing spelling and grammatical errors. In other words, we had zero data governance! Once approved, there was no implementation plan. This led to confusion, frustration, and poor data quality. In contrast, today, there is a high level of engagement related to program viability, data integrity and management, and operational details.
In summary, our approval frameworks establish transparent workflows that require high levels of engagement from a cross-functional group of subject matter experts. These frameworks lead to faster and better-informed academic program decisions, seamless implementation, high data integrity, and effortless long-term program management.
Andy Dunn is the Director, Strategic Financial Planning and Analysis with Concordia University Wisconsin and Ann Arbor. He oversees Concordia’s budget process and is developing an integrated approach to academic program portfolio optimization, focusing on institutional mission, markets, and margins. He has over 20 years of experience in the financial services, health care, and higher education industries.