One of the most prominent barriers to using data for optimal resource allocation is incomplete and inaccurate department-level data. However, as institutional research (IR) and information technology (IT) departments know all too well, fixing these issues is easier said than done. It not only involves a refresh of policies on how data is collected and stored; it also involves a refresh of how key stakeholders on campus view their data stewardship responsibilities.
For most, these responsibilities are viewed as distractions. Because data management falls outside the scope of most performance reviews, data stewardship responsibilities are often neglected. This in turn leaves the burden of data quality on the IR and/or IT department(s).
In response, one university recently addressed this challenge by decentralizing the role of data stewardship from the IR and IT departments—elevating it to a formal responsibility in the job descriptions of directors, department chairs, and analysts. The following are four key lessons learned through this process.
1. Data stewards exist beyond the data governance committee
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The process of formalizing data stewardship as a job responsibility began with the university’s IT department, which worked closely with the human resources department to draft new job descriptions. IT then asked vice provosts to designate individuals in their department who interact most often with institutional data, such as directors and analysts, as formal data stewards.
Data stewards are responsible for carrying out data capture and usage policies within their own departments—acting as a liaison between the academic units and the IT department. Sponsorship from institutional executives empowered newly appointed data stewards to dedicate time and effort to data management tasks.
2. Refine your definition of data stewardship with respect to the department
There is a constant tension in having data ownership rest at the department level instead of the institution level. In the former scenario, department leaders feel empowered to exhibit ownership over their own data, but with that power, standardization of data across departments could be affected. In the latter scenario, institutional executives have a greater view of campus-wide trends, but at any point, department leaders may feel as though data improvement is no longer their responsibility. Instead, this university has found success in promoting the concept of data stewardship—under which data is viewed as an institutional asset that departments own and must cultivate.
3. Staff turnover is the greatest obstacle to achieving continued success
When starting a new data quality initiative, early contributors to data management efforts tend to be highly interested and greatly invested. Unfortunately, when staff turnover occurs, new staff members often fail to share the same interest level or understand the importance of data stewardship. At this university, the data governance committee created a tiered training program to onboard data stewards. The program focuses on the fundamentals of data governance, the importance of data management to the university and its key functions, and the resources needed to improve institutional data.
4. Begin data quality improvement efforts upstream, and plan for downstream effects
After establishing a healthy culture of data stewardship across the university, the next step was to tackle existing data quality issues in institutional source systems.
A great deal of student-level data originates with administrative offices, such as admissions and financial aid. As a result, work should begin here. However, all possible downstream effects should be controlled for prior to implementation. For example, you would want to avoid a scenario in which a small change to naming conventions within one student information system (SIS) field could lead to a series of errors from course management and communications platforms.
Improving data quality does not happen in isolation. Formalizing data stewardship—and empowering data stewards on campus—can ensure that IR departments and academic leaders have the data necessary to make informed and timely decisions.
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