Connect the dots, see the big picture.

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We know first-hand that an institution needs to be able to answer many questions. Different questions require different techniques, from descriptive to diagnostic to predictive.

Descriptive and diagnostic analyses serve as the foundation for effective predictive analytics. Walk through our approach to tackling common challenges leveraging a variety of techniques.

Which programs are driving demand, degree production and require investment?

Describe

What are our historical trends and key metrics in yield, retention and degree production by academic program?

Diagnose

What is the breakdown of direct revenue and direct expenses? What are the indirect costs that need to be allocated to each academic program?

Predict

Through an activity-based costing model, which academic programs should we invest in or maintain?
Profitability Analysis
Enrollments to Target

Does our student population support the revenue required to run the institution?

Describe

How many new students are we enrolling at the university? What is our retention rate? How are our expenses trending over time?

Diagnose

Is there a correlation between the type of students we enroll and our retention rate? Which costs support degree completion? Do our regional demographics support enrollment targets?

Predict

What is the likelihood of financial sustainability over the next five years?

Predictive

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“When we think about the value of analytics for an institution, we approach it through the lens of the data needed to support institutional KPIs. We believe it’s important to have a balance of descriptive, diagnostic and predictive to provide the richness needed to understand the full picture and support long-term health and profitability of the education enterprise.”

- Jack Neill, Vice President of Client Services, HelioCampus

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