5 Steps for Data-Informed Strategic Enrollment ManagementReading time: 5 minutes
Data-informed strategic enrollment management combines the objectivity of data with the subject matter expertise of you and your team. A data-informed approach recognizes that you know your institution’s enrollment process better than anyone else, but it also recognizes that incorporating data can lead you to better, more strategic decisions.
In this post, we’ll discuss 5 steps you can follow when building a data-informed enrollment management strategy for your institution!
1. Establish your Goals
This first step is crucial for mapping out a course to your end goal. Try to envision where you’d like to end up and formulate a specific set of goals to help get you there.
Your goals might include:
- Reducing your prospect outreach budget
- Increasing the accuracy of enrollment yield predictions
- Meeting diversity objectives
- Increasing your retention rate
It’s critical to note your specific strategic enrollment management goals because data will help you objectively understand if you’re achieving them.
2. Get to Know your Data
The first step to getting to know your data is gaining access to your data, which is trickier for some people than others. If you have to go through IT to access your data, it helps to have a clear goal in mind and a good idea of what fields or tables you’ll need.
You’ll then need some time to get well-acquainted. A good starting point is to make sure you understand what each field represents and how things are coded. If you have questions about how data is being recorded or stored, this is the time to ask. Once you have a handle on what your data represents, you’ll want to give it a thorough review.
A few suggestions:
- Spot-check your data. Double-checking the mean, min, and max for each variable is a quick way to verify accuracy. If you spot any data quality issues, do your best to resolve them sooner than later.
- Check for missing values. If you have a variable with a high number of missings, you’ll need to decide whether or not to use that variable and if there’s a way to fill in the blanks.
- Brainstorm ideas for new variables. For example, if you have access to a prospect’s zip code, you could calculate that prospect’s distance from campus fairly easily. This might be a much more useful metric than a zip code. If you can’t create new variables from what you have on hand, spend some time thinking about things that might be worth tracking going forward.
3. Analyze your data
At this stage, you’ll want to see if fields in your dataset can give you some insight that you can relate back to your initial goal(s).
- Look at correlations within your dataset. Are they positive or negative? Large or small?
- Look for the differences between your target and non-target population, variable by variable.
- Visuals help! Graphs are a great way to get a feel for the relationships between your variables.
- Try building a predictive model. The results you get will be more directly applicable to informing decisions.
You may get surprising results during the analysis phase – and that’s to be expected!
Sometimes you’ll find that the conclusion is the exact opposite of what you anticipated. At other times, the data will confirm what you’ve long suspected to be the truth – whether it’s that students from Montana are more likely to enroll, or that the number of first term credits impacts a student’s likelihood of attrition.
Embrace these contradictions and confirmations and let them inform future strategic enrollment management decisions.
4. Turn Analysis into Insight
Keep your initial question in mind, take what you’ve learned from your analysis, and apply it going forward. The idea here is to replace anecdotal evidence with insights from data while leaving space for human judgment in final decisions.
- If your goal was to save money on prospect marketing efforts, you could use the factors that correlate to a higher response rate to inform your decisions about who will receive expensive recruitment packages and personalized email outreach.
- If you’re trying to improve your retention rate, you might flag students taking too many challenging courses in the same semester and have advisors reach out to help keep them on campus.
- Perhaps your institution has mission-driven goals that you want to prioritize because the institution sees intrinsic value in certain objectives, such as a strong arts program. A cross-cutting revenue attribution report can bring multiple departments in on decision-making! Raw data might point in the direction of making cuts, but that’s the value of a collaborative, data-informed (rather than data-driven) approach incorporating human judgment.
Even in instances where you are making decisions that skew toward the subjective, data can still inform your decisions.
5. Assess your Decisions
Don’t forget to circle back and assess your decisions. This may be where combining your own judgment and expertise with objective insight from data is most important.
- If you feel like you’re not making progress toward your prospect outreach budgetary goals, consider re-framing it or breaking it down into more manageable phases. Perhaps this year you’ll focus entirely on the digital component and dial in the physical mailers later!
- If you feel good about the progress you’re making, consider building on your existing goals. For example, you could expand your efforts at predicting enrollment yield into a wider goal of shaping your incoming class.
- If you accomplished your goals earlier than expected, add new ones!
Data helps you gauge progress against your goals and make important decisions along the way. Assess as you go rather than waiting until it’s too late to make changes!
Incorporating data into your strategic enrollment management plan while maintaining space for your team’s subject matter expertise can be a tricky balance to strike! But Rapid Insight’s user-friendly tools make it a much easier process! Our analytics software equips you to fully understand and adjust your data strategy so that it suits your institution’s unique needs.
On top of that, our expert support team is on hand to help you through build, implement, evaluate, and improve your data strategy. Over the years we’ve gathered thousands of hours of experience helping enrollment managers integrate data and predictive modeling into their processes. We’re thrilled to put that experience to use in working with you one-to-one under our free, unlimited support model.
Click the button below to schedule a demo and learn more about how we can help you build a data-informed approach to enrollment at your institution!