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How can I forecast demand with Section Demand Analytics?

Coursedog's Demand analytics is a powerful reporting tool that uses historical enrollment data to forecast the number of seats and sections an institution should offer for future terms. 


Demand analytics require historical enrollment data to create any forecasts. If an institution has provided such data, then all that is required is to turn on the permission to view the analytics. This permission is found under the "Course Editor" permission group:

Once this permission is turned on, there will be a "View Section Analytics" button next to every section:

And a Course Analytics button within every course:

Note: Once historical data is loaded into the Coursedog system, it will take about 1 week until the initial forecasts are complete. After that, forecasts will be available at any time, and will be updated on a weekly basis. 

Viewing Demand Analytics

After clicking the "View Section Demand Analytics" button, a modal containing all analytics information for that section is shown

The Section Demand analytics modal contains the following information: 

  • A stated recommendation if applicable - this is shown if there is a discrepancy between the forecasted enrollment for the current scheduling term and the max enrollment. In the example above, the term is Fall 2020, and the max enrollment is set as 45. However, the forecasted enrollment is 35 so we recommend decreasing the max enrollment capacity. 
  • A graph with a line differentiating historical from forecasted data
  • A table with the underlying data from the graph including:
    • Term
    • Enrollment
    • Max Enrollment Capacity
    • Waitlist

The Course Demand Analytics modal is similar, except it shows information aggregated across all sections of that particular course. 

Best Practices

Demand analytics work best when scheduling data is rolled over from term-to-term. This process creates an audit trail that makes it easy to track a section's particular history through various scheduling terms. By engaging in a rollover-based process, your institution will have access to the most accurate forecasts possible. 

We suggest viewing the forecasted enrollment trends before any room scheduling takes place at your institution and making modifications to the values of max enrollment and room preferences to ensure your space is utilized as efficiently as possible. 

Demand analytics use the course's id and the section's id to create the audit trail term over term and year over year.  In case no recurring section id is found in the historical data the engine will use the section number section.sectionNumber.

Nick is the author of this solution article.

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