Data Analytics: Outlining Student Enrollment Strategies In Higher Ed

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A survey shows that enrollment rates in the US have been on a decline for the last six years. In 2018, Indiana University Northwest saw enrollment for degree-seeking students drop by 3.7%. Also, two private colleges in San Francisco have been affected by declining enrollment rates. Problem!

Location and demographics are few reasons affecting enrollment numbers. Many public colleges and universities receive funding from the state based on their enrollment numbers and any amount of decline is a major concern for such institutions. Deans, presidents, and provosts are all worried about how their institution can improve strategies to increase the enrollment rates.

Where Does the Problem Lie?

Data in institutions are housed in disparate sources and systems such as CRM, Excel spreadsheets and PDFs. This is then imported into a multitude of crowded pie charts and scattergrams, making insights hard to fetch. Also, whenever student and organizational data increases, it becomes difficult to track things. If we look from the enrollment and recruitment point of view, one of the biggest concerns that comes across is administrators not being data savvy; hence lacking the ability to leverage the same for overcoming setbacks like difficulty in retaining students, enhancing student experience, and helping graduates to succeed in their careers.

Data Analytics Propelling Higher Education Industry

Last decade has thrown a major light on the technology inclusions in the higher ed institutions. However, data analytics stood out without a doubt. Data analytics has pushed higher ed to improve the education quality strategically.

Higher educational institutes are moving towards the analytics bandwagon and leveraging its benefits by making student experience better than ever. Analytics holds the key to solve the problem of declining enrollment numbers. I read in a report that Wichita State University’s placement model showed 96% accuracy after analytics intervention in identifying students who could perform well in placements.

Smart Ways How Universities and Colleges Are Using Data Analytics:

1. Targeting Student Scholarships

Data analytics help higher ed institutions to attract students who are more likely to stay in a college or university for scholarships, instead of moving towards the students who are likely to stay as prospects only. This helps in achieving higher student retention rates and ROI on scholarships leading to best return for the investment.

2. Improving Student Admissions ROI

Data analytics help institutions target the potential prospects by analyzing demographics, academic history, and other related factors. This can help the institutions to target the desired prospects and meet their enrollment targets.

3. Identifying At-Risk students

Data analytics make it easy for the faculty to identify the students who are at risk by analyzing the students’ performance in the past. Henceforth, it can help in amending the class schedule for those students and they can focus more on the subjects or lessons they need help with.

4. Evaluating, Developing and Formulating Curriculum

Curriculum evaluation is another area where data analytics can be of help. If any course or class is facing more than usual drop-out rates, then administrators can dig deep and identify the root cause with the help of data analytics. They can analyze the reasons like quality of lesson delivery, engagement rate of the students, etc.

5. Reducing Expenses & Save Operational Costs

Institutions can cut on costs by deploying data analytics. With the help of real-time data around dynamic pricings, institutions can produce performance models accordingly and reduce the overall operational expenses.

The Bottom Line Is:

As we know that higher ed space is evolving faster than ever, it is imperative for the institutions to keep up with the changing student needs. There is a need to embrace technology to deliver on modern student needs and eventually develop successful strategies to meet institutional requirements. Data analytics can help institutions outline realistic as well as favorable targets to strategically tackle inefficiencies and overcome hurdles like declining student enrollments or high drop-out rates. How are you leveraging data analytics in your institution?