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Student Poaching, Predictive Analytics, and Changes to the NACAC Code of Ethics

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By Earl Sires

The admissions process is soon likely to become significantly more competitive: 35% of enrollment officers are considering poaching students now that the National Association for College Admissions Counseling removed guidelines regarding the practice.

At its annual meeting, the NACAC struck several provisions from their code of ethics due to antitrust pressure from the Justice Department, ostensibly to create a more open marketplace for students shopping around for the school of their choice.

The NACAC guidelines no longer recommend against:

  • Continuing to recruit a student who has already committed to another school
  • Offering exclusive early decision enrollment incentives
  • Unprompted solicitation of transfer applicants from the previous year’s applicant pool who are enrolled at another school

These changes to the NACAC code of ethics create a lot of uncertainty in the world of Enrollment Management. Early Decision is no longer the guarantee it used to be. While you could previously count on having 25-30% of your class locked in, you can’t make that assumption any longer.

Since you may soon be less able to rely on real data (your actual early admits), it’s wise to seek the next best thing: predictive data.

Predictive analytics offers several ways in which you can reintroduce a measure of certainty into your enrollment management efforts after the changes to the NACAC code of ethics.

If you aren’t using predictive analytics yet:

It’s time to put this powerful technology to use so you can gain some much needed security and stability. There are several ways that predictive analytics can introduce a degree of certainty back into your process:

  • Inventory, compile, and clean up your data. Often, institutions store data in different formats by different departments, with no easy way to collate it and view it all in one place. This makes it very difficult to assess your strengths and weaknesses or put together an informed plan. Data preparation is the first step on the path to reestablishing certainty in your enrollment management process.
  • Model your enrollment. Based on your historical data, you can make projections about what the makeup of your incoming class is likely to be. Using what you learn from these projections, you can shape your incoming class to ensure that you’re meeting KPIs. You can also target your recruitment efforts to use resources as effectively as possible.
  • Rank and prioritize search names and inquiries. Use predictive models to discover which search names are likely to enroll, then prioritize outreach to them. Adapt your outreach methods based on likelihood to enroll and other factors. Build a model to assess the value of different lists to make more-informed purchasing decisions when buying lists in the future.
  • Predict attrition risk and monitor student success. Build a model to detect factors that tend to lead to attrition and use it to flag students who would benefit from intervention and support.

These are just some of the improvements in your enrollment management procedures that you can see when you implement predictive analytics.

If you’re working with a consultant or using proprietary predictive models:

You’re on the right track and you’re already benefiting from the power of predictive modeling. Consultants and proprietary models offer quick, easy solutions to very specific questions you have about your enrollment process. The right consultant also offers experience in the field and can lean on case studies when analyzing data for you.

But here is what consultants and proprietary (“black box”) models don’t offer:

  • Freedom and flexibility. With consultants and proprietary models, you can answer very specific questions, but you can’t change the question you’re asking on the fly. An in-house modeling platform allows you to build an unlimited number of models to answer as many questions as you’d like at no additional cost. For example, you can build a model to assess in-state vs. out-of-state students, as well as a model that compares students receiving financial aid to those who pay full tuition. A model can be built to assess and address whatever your urgent needs may be.
  • A streamlined, fluid user experience. Working with a consultant tends to be slow, or you’re limited to a set number of scheduled reports. When you use an in-house analytics platform, you can pull reports as often as you want, and can even automate them to be pulled on a regular schedule. This puts data in your hands much more quickly and makes for a more responsive enrollment management program.
  • Cost savings can be very significant if you bring predictive modeling in-house. For a proprietary, purpose-built model, you could potentially pay tens of thousands of dollars for limited functionality. Consultants tend to charge $40-$50 an hour, which adds up quickly. An in-house analytics platform is considerably more affordable and offers greater functionality

If you’re already building predictive models yourself:

Congratulations! You are ahead of the industry curve and are using the best method of predictive modeling. Still, it’s important to consider which modeling platform you’re using, as there are definite advantages to choosing the right platform. Here’s why we think you should choose Rapid Insight:

  • Our modeling platform makes collaboration across departments simple, even for people who aren’t trained on the platform. Our drag-and-drop visual interface makes it easy for anyone to follow a job’s logic or build a dashboard to view live data. This encourages collaboration and democratization, and you can factor in input from other departments.
  • We include free training and support with the purchase of a license. Our team of analysts is ready to assist you in setting up your model and resolving any issues you may have. The product is easy to learn, and you will be up and running on your own in no time.
  • Our analysts also have expertise in higher education, and the majority of our clients are in higher ed. We have our ear to the ground and are in consistent communication with our users, learning from their experiences and sharing solutions to common problems.
  • You’ll be part of our user community network, made up of experts in the fields of Enrollment Management, Institutional Research, Student Success, and many more. Reach out to them for advice! We also host an annual conference to get everyone together for two days of education and collaboration.

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