SLIDE 1 Strategic Scheduling Summary
Cabrillo College
Presented by: Benjamin Davis, Software Implementation Consultant, Ad Astra Information Systems
SLIDE 2 Introduction
- This PowerPoint will serve as a summary of the
critical findings of our scheduling analysis.
- It includes highlighted sections of standard Astra
Schedule reports run on Cabrillo’s data. These slides will emphasize key data elements that benchmark Cabrillo’s current standings and call attention to areas for improvement.
- We conclude with strategies to use these reports
to build and monitor policy around more efficient scheduling.
SLIDE 3 Objectives
- To guide your institution towards more efficient and
effective academic scheduling policies and practices
- Two-part learning exercise:
– Capacity Analysis
- Strategy 1 – Spread class offerings out during the primetime week
- Strategy 2 – Reduce unused seats in rooms by scheduling classes into
appropriately sized rooms
– Course Offerings Analysis
- Strategy 3 – Minimize class offerings that use non-standard meeting
patterns
- Strategy 4 – Evenly utilize prime hours by subject/department
- Strategy 5 – Reduce the offering of unnecessary sections
SLIDE 4
Strategic Approach
1. Drill down from high-level metrics to granular, measurable success drivers for each course offered and room used 2. Benchmark granular success drivers 3. Understand relevant institutional goals and priorities (enrollment growth, cost savings, student outcomes, etc.) 4. Identify and quantify opportunities 5. Select strategies that best meet institution's goals and culture 6. Implement and refine policy supporting strategies
SLIDE 5 Area Business Problem Metric Growth Capacity How much can we grow? How quickly can we grow? When will we run out of space?
- Space Utilization
- Seat Fill Rates
- Standard Week
- Enrollment Ratio
Space Bottlenecks Where are the problem areas? How do we build policy that is relevant? What kind of space to build/renovate?
- Prime Time Utilization
- % of Sections Scheduled in
Prime Time
- Utilization by Room Type
- On-Grid Meeting Patterns
Course/Student Demand Analysis Are we efficient with our course
- fferings?
- Reduction Candidates
- Low Enrollment Courses
Strategic Study Metrics
SLIDE 6 Capacity Analysis
Introduction
Key Concepts
enrollment that can be supported in the current room inventory without compromising quality
- Efficiency – the extent to
which space, course
allocated to effectively align with student and institutional needs Strategies
- Strategy 1 – Spread class
- fferings out during the
primetime week, and over the entire scheduling week
- Strategy 2 – Reduce unused
seats in rooms by scheduling classes into appropriately sized rooms
SLIDE 7
Average Utilization does not reflect capacity or inform space management
Space Bottleneck Concept
Room Type Campus “A” Primetime Util. Campus “B” Primetime Util.
Classrooms (2) 50% 50% Science Lab (1) 50% 10% Tech Auditorium (1) 50% 90% Average Util. 50% 50%
SLIDE 8 Key Parameters Used
– Fall 2014 (September 2 to December 20) – 15 full weeks
- Campus used: Cabrillo College
- Standard Week Definition:
– 8:00 am – 10:00 pm, Monday – Friday – Total Hours: 70
– 9:00 am – 2:00 pm, Monday – Thursday – Total Hours: 20
SLIDE 9
Capacity Analysis
Strategy 1: Spread Class Offerings during the Primetime Week
SLIDE 10 Identify your Bottlenecks in Primetime
Percent of Rooms in Use by Day and Time for Selected Room Type
Identify Primetime Identify Bottlenecks (>80% utilization) Report Parameters
Policy should
Primetime and Bottlenecks
SLIDE 11 Determine Primetime Utilization
Space Utilization by Room Type and Size with Primetime
Look for Room Type/Room Size Combination Bottlenecks Prime Ratio – Monitors spread balancing over week
Use Data to Create Spread Policy
Reporting
- Prime Ratio
- % of Offerings In/Out
Primetime
Optimization Bottleneck Level Report Parameters
SLIDE 12
Capacity Analysis
Strategy 2: Reduce Empty Seats in Rooms by Scheduling Classes into Appropriately Sized Rooms
SLIDE 13 Determine Seat Fill Utilization
Space Utilization by Room Type and Size with Seat Fill
Report Parameters Additional capacity exists where seat fill based on actual enrollment is low
Use Data to Create Seat Fill Policy
- Enforce with Optimizer
- Monitor with
Reporting
SLIDE 14 Capacity Analysis
Opportunities
- Consider use of underutilized rooms during primetime.
Although the Smart Classroom Room Type is the highest utilized, there are a number of Classroom room types at varying levels of utilization across the 70-hour standard week and the 20-hour primetime. Equitable scheduling across all Classrooms will help alleviate bottlenecks felt in specific high-demand rooms.
- Improve seat fill. Even at bottlenecked times of day, many
Classroom room types have a significant percentage of seats left unfilled. Better matching of section capacities to actual enrollments will aid in scheduling appropriately- sized rooms to sections.
SLIDE 15 Course Offerings Analysis
Introduction
Key Concepts
- On-Grid Meeting Patterns –
the standard grid of times to offer lecture-style courses
- Enrollment Ratio – the ratio
- f enrolled students to
seats offered in a given course Strategies
- Strategy 3 – Minimize class
- fferings that use non-
standard meeting patterns
- Strategy 4 – Evenly utilize
prime hours by subject/department
- Strategy 5 – Reduce the
- ffering of unnecessary
sections
SLIDE 16
Course Offerings Analysis
Strategy 3: Minimize Class Offerings that Use Non-Standard Meeting Patterns
SLIDE 17 Scheduling “On Grid”
Meeting Patterns in Use
All Meeting Patterns in Use Sorted by Most Frequently Used
Use Data to Create Meeting Pattern Policy
- Enforce with Optimizer
- Monitor with Reporting
Top on-grid meeting patterns Conflicting (off- grid) patterns during primetime
SLIDE 18
Course Offerings Analysis
Strategy 4: Evenly utilize prime hours by subject/department
SLIDE 19 Identify Subjects with Greatest Primetime Preference
Prime Time Usage Ratio
All Subjects, sorted alphabetically % of sections scheduled during primetime
Use Data to Encourage Evenly- Spread Scheduling by Subject/Department
- Enforce with Optimizer
- Monitor with Reporting
Subject # Sections % Prime Subject # Sections % Prime SPED 12 100% PS 10 79% PHILO 16 98% GEOG 5 77% SOC 13 92% ECON 7 75% ADAPT 20 89% BUS 8 73% READ 5 84% KIN 96 72% JOURN 5 80% DMCP 27 69% ESL 4 79% PHYS 23 68%
Top Subjects offering 3+ sections with highest Prime Ratio In Classroom - Smart Rooms
SLIDE 20
Course Offerings Analysis
Strategy 5: Reduce the Offering of Unnecessary Sections
SLIDE 21 Determine Low Course Demand
Low Enrollment Course Analysis For Selected Term
Number of Sections Offered Total Empty Seats Across all Sections Shows enough Empty Seats to Cut one Section Identifies Courses with <10 Enrollment and <50% Enrollment Ratio
Review Trends Analyze action candidates for impact
SLIDE 22 Potential Reduction Candidates
Low Enrollment Course Analysis For Selected Term
Course # # Secs Current Avg. Enroll
Enroll Excess Seats # Secs to Reduce
ADAPT 93 11 21.73 315 76 2 ANTHR 2 6 28.67 264 92 2 ART 80SB 8 0.75 65 59 7 ART 80SC 7 0.29 152 150 6 BIO 201 15 22.33 464 129 4 BIO 80SB 7 0.71 63 58 6 CG 51 19 23.68 615 165 5 CG 52 2 0.00 60 60 2 ENGL 100 19 24.68 551 82 2 ENGL 100L 25 15.60 671 281 10 ENGL 1A 26 24.77 754 110 3 ENGL 255 10 12.60 290 164 5 KIN 27A 9 16.33 385 238 5 KIN 27B 9 2.56 385 362 8 KIN 37B 7 4.43 280 249 6 KIN 50A 4 12.75 154 103 2
SLIDE 23 Enrollment Ratio (enrollment fill) Report Parameters On-Grid Class? Offered in Primetime?
Use Data to Create Class Cancellation/Primetime Policy
Low Demand Sections
Low Enrollment Ratio Sections by Subject For Selected Term
SLIDE 24 Low Demand Sections
Low Enrollment Ratio Sections by Subject For Selected Term
*Crosslist Enrollments and Max Enrollments were use where applicable
Course (Sec#) Act. Enroll Max. Enroll Enroll Ratio (%) Course (Sec#) Act. Enroll Max. Enroll Enroll Ratio (%) ACCT 151A (84375) 23 43 54% ART 51L (84498) 11 60 18% ACCT 151A (84379) 14 30 47% KIN 43B (85305) 5 32 45% ACCT 54A (86219) 10 43 23% KIN 43B (85306) 8 32 27% AP 9A (84454) 12 26 46% MATH 12 (85438) 21 36 58% ART 31A (84472) 6 25 24% MATH 12 (85442) 22 39 56% ART 31B (86593) 6 25 24% MATH 12 (85447) 21 39 54% ART 50L (84491) 143 250 57% SPED 210 (85832) 6 25 24% ART 50L (84492) 61 150 41% SPED 210 (85833) 5 25 20% ART 50L (84493) 29 100 29% SPED 210 (85834) 8 25 32% ART 50L (84495) 30 0% SPED 210 (85835) 13 25 52% ART 51L (84496) 10 200 5% TA 27 (85853) 3 30 10% ART 51L (84497) 16 100 16% TA 29 (85859) 5 30 17%
SLIDE 25 Course Offerings Analysis
Opportunities
- Reduce scheduling conflicts during primetime. Cabrillo
has numerous conflicting meeting patterns in Classroom room types during primetime, which impacts student and faculty scheduling conflicts, as well as room scheduling conflicts.
- Revise enrollment capacities to better align with
expected enrollments, to aid in efficient scheduling to appropriately sized rooms.
- Scrutinize undersubscribed courses. Focus on courses
with multiple section offerings and excess seat count greater than an entire section capacity to potentially reduce, and better align with student need.
SLIDE 26 Strategies to Evaluate
Capacity Bottleneck Strategies:
- Optimize Rooms – enact the suggested scheduling
preferences as recommended by Ad Astra
- Prime Ratio – maximize the use of rooms during primetime
hours, and throughout the scheduling week
Course Offering Efficiency Strategies:
- Meeting Patterns – consistent meeting patterns support
ideal utilization of rooms, and minimize faculty and student conflicts
- Evaluate Reduction Candidates for degree requirement
impact
- Select Reduction and Elimination Candidates to remove or
rotate out of the schedule
SLIDE 27 Action Plan
What We’ve Done
Astra Schedule 7.5
Scheduling Summary
“Smart Room” Room Types into one Room Type
Schedule 7.5 for scheduling Events Next Steps
– Utilize optimizer to place sections with space “turned-
– Continued Enrollment Growth
SLIDE 28 Solutions that Fit
Professional Services Strategic Checkup
- Capacity Analysis
- Course Offerings Analysis
- Performance in Key Areas
- Academic Scheduling Policy
Recommendations
Platinum Analytics
Course Need Analysis
- Historical Trend Analysis
- Student Specific Degree
Program Analysis
Astra Schedule
Optimization
- Event Management
- Resource Management
Workflow
- Analysis and Utilization Reporting
- Enterprise Calendaring
Capacity and Financial Modeling Schedule Development Consulting Policy Development and Enforcement Advanced Product Use Schedule Development Sandbox
Simulated Registration Timetabling Faculty Modeling*
