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CIO Enrollment Management Presentation

April 17, 2015

What Do We Need to Be Effective Enrollment

Managers?

Today’s Objectives

Identify gaps in our enrollment strategy

Predict FTES With a Support System

Managing Low and High Enrollment Courses

Identify Course Taking Patterns

Enrollment Management Survey

We Asked A Few Simple Questions:• 30 RespondentsAnswers:• We all need new technologies• Nobody is really there yet

What else do you want/need?

Managing student pathways, particularly in Gen Ed areas.

Tools for managing class sizes that support the Completion Agenda within current funding formulas

Making EM changes without contention

Multi-year planning tool

Practical strategies for maintaining productivity and increasing enrollment

What does a comprehensive enrollment management plan look like? It should include elements of

attendance accounting, successful outreach efforts, and management strategies.

Scheduling software that integrates facilities useBest practices in scheduling of accelerated courses for student completion

Predicting FTES with a Decision Support System

Bob HughesDirector, Enterprise Application Systems

Mt. San Antonio College

We have the data;

the problem is timeliness

Timeliness

Plenty of reports showing how we did at the end of the term esp. CCFS-320

Plenty of reports showing how we are doing during the term with regard to FTES

Not enough actionable data during registration - the critical period when we can meet students needs (and capture more FTES) by meeting demand before classes start

A Decision Support System

Custom built in-house using Oracle Application Express

No additional license fee (covered by our existing Oracle license)

Resides in the same database as Banner

Built by a researcher temporarily re-assigned as a programmer

Received the Excellence in College Planning Award in 2015 from the RP group

Three Horizons

1. What can we do in the current term to better meet student demand?

2. What can we do in the upcoming term to better meet student demand (during registration)?

3. What can we do next year to better meet student demand (schedule build)?

Horizon 1:The Current Term

Each Dean gets a view specific to her division. The landing page shows a graph containing all classes in the division in four categories of fill rates.

Clicking on a color of the graph brings you to a list of sections in that category.This example shows the 45 classes in the 60% - 74.99% range.

Built in actions allow you to add or remove columns, add additional filters, and download to Excel

5 standard report formats are available

An example of the FTES report by Department. Shows Current FTES vs Projected FTES (4 year weighted average) vs Potential FTES (all sections at 100%)

Similar comparison between Divisions

Horizon 2:The Upcoming Term

What are our ‘hottest’ classes? This report shows classes with fill rates of 90% or more,ordered by how quickly they filled. All 47 sections of ENGL 1C filled in the first 4 days of registration.

What demand are we missing? After the classes are full and waitlists are full, we can measure intensity of demand by looking at attempts to register after the class has closed.

What classes are lagging or exceeding in their demand? This report shows a comparison offill rates by day during registration vs prior years and projected fill rates (weighted average).Philosophy is meeting projections.

Sociology is lagging both historical demand and projected fill rates.

Horizon 3:Next Year

FTES Distribution for the year by Division.

FTES Distribution for the term by Division.

FTES Distribution for the year by Departments in a single Division. Do we need to change the offering pattern (for example – more offerings in Fall vs Spring?)

FTES Distribution for each term by Departments in a single Division.

Sandbox – a place to experiment with course scheduling decisions before the schedule is built.

Start from a baseline of what was offered last year.

This section of AMLA 21S didn’t fill as expected. We know why – we expect it to do better next year.

Default is projected fill rate. We’ll enter 85%.

We can increase this to the projected fill rate (4 year weighted average), or enter our own prediction.

User updated courses now show at the top of the list

We’re going to add some additional sections. We choose courses where the demand is the greatest. One option is where there was most demand after all sections of the course filled.

Second option is where all sections of the course filled quickest during registration.

We added another section of PHIL 15.

We can also add brand new courses, or courses that are beyond the ‘top three’ in terms of demand.

Note that this is listed as ‘User Created’. We can delete these if necessary; the schedule will revert back to the historical schedule.

Three changes resulted in a projected increase of 8.3 FTES. We can do several models. Each user has their own “sandbox” to simulate schedules.

The Result?

Fall 2013 – demand began to softenUsed the Decision Support System during registration for Spring 2014 to add/cancel classes where warranted, and identify areas where more marketing was needed

Met FTES targets in 2013-14Mandate to grow 3% from Funded FTES in 2014-2015

Currently on target to be up 4% for the year

Enrollment and Efficiency

Santanu BandyopadhyayCypress College

Nuts & Bolts: The Data Points

Trend information

Enrollment/FTES by division

Fill rate by divisionWSCH/FTES by divisionUnmet demand

(unduplicated) by CourseDemand/Supply analysis

by course levelGrowth opportunities

Previous semester

Classroom availability# Full-time Faculty by

departmentClass sizeDeficit in extended day

budget by division

Demand Analysis – Trend

Unmet demand (unduplicated) by course: # Unduplicated students who attempted to register for a section PLUS # waitlisted students

After adding 8 sections (240 seats), demand for SOC 101 declined by 213 in 2015. For Math 101, after adding 4 sections (120 seats), demand increased by 18.

Implications for future planning? Increasing v. flat demand?

Demand Analysis – Trend

• Demand/Supply analysis by course level: # seats offered v. seats occupied for levels of courses

Availability of seats and waitlisted students in each level indicate potential for better alignment between demand and supply

At 201 to 250 level, nearly 1,200 seats are available although 648 students are waitlisted

If perfect alignment is achieved, demand will exceed supply for only 100 level classes

Demand v. Contribution

Four Quadrants

Green (Q1): High demand, High capacity

Amber (top left) (Q2): High demand, low capacity

Red (Q3): Low demand, low capacity

Amber (bottom right) (Q4): Low demand, high capacity

Using 4-Quadrant GridFocus on Q1 and Q2 courses for growthCaveat: Q2 courses may increase deficit in extended day

Q3 are likely 3rd and 4th sem classes or new programs: needed for completion and/or transfer. Schedule in alternate semester/year

Potential to grow: Q4 – Outreach Plan?

Tying it all together

Demand

• Focus on Unmet Demand• Student need upper level

classes

Capacity

• Evaluate Physical Capacity• Balance online growth with on-

campus

Efficiency

• Build capacity by improving efficiency

• Factor in cost: 4-quadrant guide

Schedule Analysis and Marketing for Growth

Craig Justice and Kathi Swanson

Student-centered Scheduling

Student choices as consumers focus on day of week, time of day, cost, work schedules, transportation issues among others

ACE Survey

American Council on Education (ACE) survey indicate that the main forecasting tools used for scheduling are historical course enrollment information and local knowledge rather than indicators of future student demand

Newer Tools

Predictive Analytics

Wait List Data

Student Education Plan Data

Social Media Survey Tools

Strategic Marketing

Capstones, Math & English

Predictive Analytics

Wait List Data

Student Education Plan Data

Social Media Survey Tools

Section Cancellation Analysis

Section Cancellation Analysis

Curriculum Analysis

Capstones

Sequences

Bottlenecks

Curriculum Analysis

Using Data and Tools to PlanThe Challenge: Less Nordstrom Style Scheduling, More Student-Centered Scheduling

Shifting the Course Scheduling Culture

Use good analytical data to inform the plan

Plan the Schedule First, Staff It Second

Marketing: Inform the Customers

Completion Dashboards

Integrating with Degree Audit to Change Student Behavior and Predict Course Needs

JoAnna Schilling, Cerritos College

JoAnna Schilling,

Frank Mixson,

Frank Mixson,

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Frank Mixson,

Frank Mixson,

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Debra Moore,

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