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Strategic Checkup Central Michigan University Presented by: Sarah Petsis, MBA Senior Consultant Ad Astra Information Systems.

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Presentation on theme: "Strategic Checkup Central Michigan University Presented by: Sarah Petsis, MBA Senior Consultant Ad Astra Information Systems."— Presentation transcript:

1 Strategic Checkup Central Michigan University Presented by: Sarah Petsis, MBA Senior Consultant Ad Astra Information Systems

2 CMU Strategic Checkup Goals Alignment to CMU’s strategic plan: Focused on student success and student retention Visibility into academic space utilization and management opportunities (Fall 2012 data used) Address current, reported scheduling challenges: Limited Classroom availability in primetime Understand course offerings inefficiencies directly impacting budgets and capacity Understand course offerings warning signals that potentially impact student access to required courses and graduation Solution framework to leverage data from the SIS in future terms

3 Overview

4 Typical Strategic Issues Academic schedules are vitally important –Means of allocating faculty and space –Means of providing students with a path to completion Academic schedules are created in a decentralized process that is difficult to measure or manage Strategic opportunities to efficiently and effectively allocate academic resources are rarely realized

5 Typical Schedule Building Process 1.Course offerings are based on a historical schedule, typically a roll-forward of a “like” term 2.Departments refine offerings in silos (distinct processes and decision makers, limited collaboration and decision-support tools) 3.Student Information System is updated 4.Room assignments are made/refined 5.“Final” schedule is posted (changes still occur after registration or even after classes start) The goal is commonly completion v. improvement

6 Course Offering Complexity What is the impact of… Students from other departments who need our courses? Curriculum changes? The incoming freshman class? Increasing retention rates? Changes in my department’s headcount? Changing course eligibility requirements? Improving graduation rates? Changing classroom availability and capacity to add sections at certain times? Changing transfer student enrollment? Faculty load and capacity?

7 Scheduling for Student Success Noel Levitz 2011 National Student Satisfaction & Priorities Report Identified key challenges for institutions Student Response: “Ability to get the courses I need with few conflicts” was the top challenge for 4-Year Public institutions Institution Response: “Ability to get the courses I need with few conflicts” was not ranked in top 25 for 4-Year Public institutions

8 Strategic Checkup Approach 1.Drill down from high-level metrics to related, and more granular and manageable, success drivers 2.Benchmark existing efficiencies of granular success drivers 3.Integrate relevant institutional goals and priorities (enrollment growth, cost savings, student outcomes, etc.) 4.Identify, quantify and prioritize opportunities 5.Select strategies that address opportunities and fit institution's culture 6.Implement and continually refine policy supporting strategies

9 Course Offerings Analysis

10 Course Offering Analysis Concepts General Terms and Concepts Seats – Seats offered in the term being analyzed Blended Demand – Average of trend of historical course enrollment from like terms (Fall 2008, Fall 2009, Fall 2010, Fall 2011 and Fall 2012) and enrollments from last like term (Fall 2012) Enrollment Ratio – Course-specific fill rate calculated as average enrollments divided by average enrollment caps (last like term) Balanced Course Ratio – Courses wherein Enrollment Ratios are between 70% and 95% (last like term) Overloaded Course Ratio – Courses wherein Enrollment Ratios are over 95% (last like term)

11 Course Offering Analysis Concepts Analysis Term Disconnects Statistical Excess Seats – Seats offered in excess of Blended Demand Statistical Additional Seats Needed – Blended Demand in excess of Seats Reduction Candidates – Potentially superfluous sections of courses that can be removed Elimination Candidates – Courses that can potentially be removed from a schedule entirely Addition Candidates – Potentially needed sections of courses that can be added to a schedule Candidate Example CourseSeatsDemand Enrollment Ratio Sections Sections Needed ReductionAAA %63 EliminationAAA %10 AdditionAAA %1012

12 Course Offering Analysis – Fall 2012 Undergraduate Only MeasurementPercentNumberCoursesPercentile Enrollment Ratio87.17% Avg. Enroll / Avg. Enroll Cap / th Percentile Balanced Course Ratio 35.80% 435 of 1, st Percentile Overloaded Course Ratio 27.33% 332 of 1, th Percentile Average Enrollment / Average Enrollment Capacity CMUMean 4-year Public Institutions Mean MinMax / / / / / 52.87

13 Course Offering Analysis – Fall 2013 Undergraduate Only MeasurementPercentNumberCoursesPercentile Statistical Excess Seats18.65% 16,359 of 87,703 seats nd Percentile Statistical Additional Seats Needed 16.61% 14,566 of 87,703 seats nd Percentile Additional Seats Needed (Fall 2013 courses only) 5.85% 5,135 of 87,703 seats th Percentile Reduction Candidates4.86% 135 of 2,779 sections 97 th Percentile Elimination Candidates3.20% 89 of 2,779 sections 75 th Percentile Addition Candidates17.81% 495 of 2,779 sections 68 th Percentile Addition Candidates (Fall 2013 Only) 2.84% 79 of 2,779 sections 69 th Percentile

14 Course Offering Analysis – By Level Level Baseline Sections Enrollment Ratio Enrollment Enrollment Cap Sections per Course 000 Level % Level 1, % Level % Level % Level % Undergrad 2, % Level % Level % Level % Level % Graduate % Totals 3, %

15 Course Offering Analysis – By Level Level Fall 2013 Sections Addition Candidates Addition Candidates, Fall 2013 Only Reduction Candidates Elimination Candidates 000 Level Level 1, Level Level Level Undergrad 2, Level Level Level Level Graduate Totals 3,

16 Course Offering Analysis By Sections per Course Undergraduate Only Findings vary by Sections per Course: Sections per Course Courses Average Enrollment Enrollment Ratio Balanced Course Ratio Overloaded Course Ratio %28.55%25.81% %47.00%29.00% 3 to %52.17%27.33% 6 to %40.35%36.84% %50.00%36.67% Totals 1, %35.80%27.33%

17 Course Offerings by Enrollment Ratio Tier Undergraduate Only Enrollment RatioCourses% of Total Average Enrollment Average Enrollment Cap 0 Seats % % % % % % % % (Balanced) % > 95% (Overloaded) %

18 Course Offering Opportunities Improved graduation rates from additional seats offered in “gateway” addition candidates (focus on required courses) Reduction of inefficiency/expense from reduction and elimination candidates (224 total candidates; 8.06% of all sections) Increased scheduling flexibility and capacity Reallocation of faculty, moving from reduction candidates to addition candidates Identification of unused faculty capacity (limited opportunity, CMU has already exceeded 85% enrollment ratio goal)

19 Course Offering Analysis Dashboards

20 Capacity Analysis

21 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% Science Lab (1)50%10% Tech Auditorium (1)50%90% Average Util.50%

22 Capacity Management Process 1.Identification of enrollment capacity for analysis term (Fall 2012): a.80% primetime utilization and/or b.95% effective utilization of any of the most dominant primetime meeting patterns 2.Analysis of strategies to maximize quality/capacity 3.Selection of scheduling strategies/policies 4.Scheduling policy refinement/enforcement (ongoing) 5.Strategic renovation/new construction planning

23 Capacity Management Findings 1 Average utilization of all instructional rooms: 65-hour standard week (8am – 10pm M-R; 8am – 5pm F) – 37.44% 32-hour prime week (9:00 am – 5:00 pm M-R) – 53.74% Utilization is significantly higher in certain room types: Classroom utilization during the standard week is Moderately High (69 th Percentile) Classroom Prime Ratio (percentage of all usage in primetime) is High (13 th Percentile)* – 69.71% – Mean is 58.13% * Even spread would be 49% (32 of 65 hours) Classroom (CR & DS) (163) Other Rooms (196) 65-hour Standard Week51.80%25.49% 32-hour Prime Week73.35%37.43%

24 Capacity Management Findings 2 CR - Classroom utilization varies by size category during the 32- hour primetime: SEATSROOMSPRIME ROOM HRS.PRIME UTILIZATIONPRIME RATIO 16 – %71.39% 26 – , %72.33% 51 – , %71.23% %80.61% Total 1273, %72.51% DS - Department Scheduled Classroom utilization varies by size category during the 32-hour primetime: SEATSROOMSPRIME ROOM HRS.PRIME UTILIZATIONPRIME RATIO 1 – % 16 – %56.83% 26 – %58.07% 51 – %61.91% %66.88% Total %58.72%

25 Capacity Management Findings 3 Classroom (CR & DS) utilization varies by region: Top Ten Classroom (CR & DS) regions by highest primetime utilization: REGIONROOMS OVERALL UTILIZATION PRIME UTILIZATION PRIME RATIO CR - Academic Advising and Assistance %98.33%83.03% CR - Earth and Atmospheric Sciences %98.33%80.00% CR - Finance and Law274.69%93.70%61.76% CR - Management274.67%92.08%60.71% CR - Accounting, School of268.31%91.35%65.84% DS Hum and Soc & Behav Sciences %89.06%85.67% CR - Mathematics %88.42%76.50% CR - Chemistry352.10%86.08%81.33% CR - Broadcasting and Cinematic Arts, School of/Psychology %85.83%62.42% CR - Computer Science353.20%84.90%78.57%

26 Capacity Management Findings 3 Classroom (CR & DS) utilization varies by region: Bottom Ten Classroom (CR & DS) regions by lowest primetime utilization: REGIONROOMS OVERALL UTILIZATION PRIME UTILIZATION PRIME RATIO DS Non-Departmental212.13%0.00% CR - MSA Program112.26%24.06%96.65% DS Education & Human Services %46.70%56.56% CR - Engineering and Technology, School of %48.75%77.16% CR - Biology236.10%58.33%79.55% CR - Business Information Systems250.82%60.68%58.78% DS Communication & Fine Arts142.36%61.35%71.31% CR - Human Environmental Studies441.09%61.38%73.54% CR - Psychology539.77%62.90%77.85% CR - College of Business242.51%64.06%74.19%

27 Capacity Management Findings 4 Seat fill ratios in Classrooms (CR & DS) vary by capacity: Classroom Seat Fill (Enroll) ratio comparison: 27 th Percentile Classroom Seat Fill (Cap) ratio comparison: 18 th Percentile CR - Classroom seat fill ratios: SEATSROOMSCAPACITYENROLLFILL (ENROLL)ENROLL CAPFILL (CAP) 16 – % % 26 – % % 51 – % % % % Total % % DS - Department Scheduled Room seat fill ratios: SEATSROOMSCAPACITYENROLLFILL (ENROLL)ENROLL CAPFILL (CAP) 1 – % % 16 – % % 26 – % % 51 – % % % % Total % %

28 Capacity Management Findings 5 MEETING PATTERN TOTAL USAGE TOTAL UTILIZATION OFF-GRID USAGE OFF-GRID UTILIZATION MWF 9:00 - 9: % % MWF 10: : % % MWF 11: : % % MWF 12: : % % MWF 1:00 - 1: % % MW 2:00 - 3: % % TR 9: : % % TR 11: : % % TR 12:30 - 1: % % TR 2:00 - 3: % % Total 3, %1, % On-grid Primetime Meeting Pattern usage in Classrooms (CR & DS rooms) varies by Pattern: *Denominator = 489 total weekly hours

29 Capacity Management Findings 5, continued (summary) There is Moderately Low off-grid meeting pattern usage in Classrooms (CR & DS rooms) during primetime meeting patterns: 30.76% (69 th percentile) of usage for all Classrooms (CR & DS rooms) There is a Moderately Low off-grid “waste factor” 441 hours or 11.69% of all Classroom (CR & DS) capacity is wasted (71 st Percentile)

30 Capacity Management Opportunities Evenly utilize all CR & DS Classrooms at 60% across the 65- hour standard week Result: Balance scheduling across all Classrooms (15.83% capacity increase, or 3,246 students) Graph category label: “Optimize Rooms” Limit Off-Grid scheduling waste in CR & DS Classrooms from 11.69% to 5% Result: Eliminate waste inherent in off-grid scheduling (6.69% capacity increase, or 1,372 students) Graph category label: “Meeting Patterns” Reduce primetime scheduling in CR & DS Classrooms to 60% Result: Move activities outside of primetime to reduce prime ratios of 69.71% (13.93% capacity increase, or 2,856 students) Graph category label: “Prime Ratio”

31 Capacity Management Dashboards

32 CMU Strategy Options to Evaluate Course Offering Efficiency Strategies: Evaluate Elimination Candidates for degree requirement impact Select Reduction and Elimination Candidates (224 total candidates; 8.06% of all sections) to remove from Fall 2013 schedule Course Offering Student Access Strategies: Evaluate Addition Candidates for degree requirement impact Consider implementation of Platinum Analytics (uncover key Addition Candidates to improve student completion rates) Capacity Bottlenecks Strategies: Optimize Rooms (15.83% potential capacity) Meeting Patterns (6.69% potential capacity) Prime Ratio (13.93% potential capacity)

33 Develop a schedule review team and process –Senior leadership and academic department representation –Focused on leveraging and sharing schedule analysis Develop data-driven scheduling policies –Course offering efficiency and effectiveness –Meeting pattern and room assignment efficiency Integrate other academic planning processes (curriculum planning, academic space planning, student success initiatives, etc.) CMU Potential Next Steps

34 Which Category Describes Your Institution? Category 1: Motivated to aggressively improve student outcomes and address inefficiencies and capacity issues Mobilized to implement change (a schedule review team is in place that includes senior administrative and academic representation) Category 2: Interested in understanding how to improve student outcomes and address inefficiencies and capacity issues Considering needed process changes (candidates exist for a schedule review team, including senior administrative and academic representation) Category 3: Discussing and considering a need to improve student outcomes, address inefficiencies and capacity Not ready to discuss needed process changes (no candidates identified for a schedule review team)

35 Questions? Sarah Petsis Senior Consultant


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