There is a tendency in some organizations to regard those who work in Institutional Research (IR) as just the “data people.” The data people generate numbers, reports, and provide links to Power BI or other dashboards where users can slice and dice.
However, how frequently do IR staff emerge from behind their computers to engage in robust discussions about these data with users? Unfortunately for some organizations, this does not happen often enough. I have recently discussed this issue with a colleague and we have turned to wonder, how much of this is due to how IR people think about themselves as opposed to how they are perceived by others?
The focus of this post is about how IR staff perceive their role and in turn, how that shapes the perceptions of IR in other parts of the organization. IR offices are good at data extraction and report production, but they are capable of so much more if they understand and leverage their worth beyond data extraction.
Based on over 40 years of experience in the field of IR, I have a number of recommendations for Institutional Research staff regarding how they might make themselves more valuable to their organizations and how they might change how others perceive them. Following are approaches that worked for me as I grew in my career and, as I and my staff led disciplined and focused discussions at all levels of Richland College.
Build a culture of organizational data literacy.
Present and document data discussions as part of employee professional development.
Lead rich data discussions contributing to increased data literacy across the organization, better informed strategic action plans, and improved employee and student success.
Silence really isn’t golden
IR staff should set an example for others during data discussions by speaking up when they hear or see incorrect interpretations of data. My staff knew that speaking up in a meeting was non-negotiable. Silence gives the perception of agreement when that may not be the case.
Define your role as IR professional
Remember that any report generated using data supplied by IR ultimately reflects on the department either positively or negatively. Therefore, do not respond to requests that ask the staff to do something incorrect or inappropriate.
Build a strong bench and cross train
IR leadership should include all IR staff in meetings that allow them to obtain a better understanding of how the organization operates, thus creating a strong bench in the event of turnover or employee absence. My staff attended all of our monthly report card reviews with senior leadership as well as the annual strategic planning retreats.
Crosstrain staff to ensure continuity of operations and employee growth opportunities. Each of my staff members had the ability to do the other person’s job, therefore, there was no downtime if an employee had to be absent.
Be like Socrates
Encourage discussion participants to think critically about the data.
Encourage diverse opinions and ideas, and focus on next steps and what actions might be taken based on the data.
Reflect on the validity of the questions being asked and whether the data being examined align with the research questions.
Sometimes being like Socrates can be difficult, as history has shown. You may occasionally be met with silence when questions are asked. When this happened to me, my approach was to call on a person or two who I knew would be able to get the discussion going. Separating discussion participants into groups also works well and then have them report out by group. Anything to get the conversation started and treat all questions and comments as worthwhile.
Paint an accurate picture
Be certain that the data points in trends are appropriate.
Make sure that excel charts are not misleading or skewed due to values used on the horizontal or vertical axis.
If the IR staff is asked to display data in a way that you know is not valid or accurate, it is important to say that and to explain why. This contributes to data literacy. If you are pushed to do it anyway, I recommend adding a disclaimer or a comment that indicates your concerns to the reader.
Context is everything
What are the comparisons?
At what level should the organization be performing?
Are there differences in the data based on demographics, schedule modality, etc.?Sometimes there can be pushback from leadership at various levels regarding data context. In these instances:
Be sure that your comparisons are valid and explain the reasons for this particular comparison.
Explain why expected levels of performance is an important contextual element during data discussions. During one data discussion at my college, a department was outperforming other colleges comparatively, but still well below the level the college needed to be. This resulted in a robust discussion and ultimately an improvement plan despite the favorable comparisons.
Explain that segmentation of results begins the process of peeling back the layers to look more closely at the results. At Richland College, we referred to it as “Peeling the Onion.” Results may be analyzed by student demographic, schedule modality, or by faculty, etc. It is important to have these discussions, but they must be done with consideration and thoughtfulness as the analysis moves from zooming out to zooming in.
In 2017, Neil deGrasse Tyson stated, “In school, rarely do we learn how data become facts, how facts become knowledge, and how knowledge becomes wisdom.” Institutional Research has an opportunity to play a major role in leading organizations through the transition from Data to Wisdom, if they just know their capability and leverage it. I was fortunate enough to work for an organization that allowed me and my staff to grow professionally and to increasingly add value to the organization. We were never thought of as just the “data people.” Various software products such as Zogotech, Power BI, Tableau and now AI are making the process of data extraction and reporting more automated and standardized. Now more than ever, IR needs to more clearly define its professional capabilities and value added.
