As we discussed in previous entries, academic program capacity management relies on a thorough understanding of the course needs of your students. The following institutions have begun to make progress with this new, but highly promising approach:

Eastern Connecticut State University: Eastern has appropriately branded itself as Connecticut’s liberal arts university. This brand relies on relatively small classes and considerable course variety for its students. Obviously, these attributes make it especially challenging to efficiently and effectively manage course offerings and program capacity. For this reason, Dr. David Carter (then Eastern’s President, now the Connecticut State University System’s Chancellor) began exploring ways to make more informed decisions when building their schedules. His team (consisting of degree audit and student information system experts) has played a huge role in the evolution of our Platinum Analytics Suite. Eastern is currently leveraging newly available analytics information to identify course bottlenecks (hard-to-get courses) in their various academic programs. They plan to roll out the academic planner to solicit direct student feedback on course needs this spring.

Kwantlen University College: Kwantlen is a large and growing two-year/four-year institution in suburban Vancouver, BC. Kwantlen has struggled to deliver courses efficiently to its commuter students who frequently attend classes on more than one of their four primary campuses. Additionally, Kwantlen’s provincial funding is tied to enrollment levels and student success outcomes. For these reasons, Kwantlen joined six other institutions on our innovators group (advisors and early adopters for our Platinum Analytics Suite). Kwantlen is beginning to utilize analytics data to improve the efficiency of their course offerings and faculty assignments. Furthermore, they are studying how student-specific information can be used to increase the average course load of its students and thereby increase their FTE enrollment levels tied to funding.

Other institutions, some of which are on our innovators group with Eastern and Kwantlen, have embarked on similar exercises in additional related areas. Plans have been made to support the modeling of faculty allocation and faculty hiring to support course offerings.

This concludes our series on academic program capacity management. We would love the opportunity to discuss these concepts and how they may apply to the strategic mission and business challenges of your institution.

Since the last post in this series, most of our team and I have been heavily involved in hosting our annual Users’ Conference. This year’s conference was an excellent opportunity to catch up with early adopters and prospective users of the approaches referred to in the last post. Unanimously, the feedback on rolling out these solutions focused on the following points:

• There is limited available information regarding the specific course needs of active students
• Mission-critical efforts to improve student outcomes (retention and graduation rates) are compromised by a this lack of information
• The significant strategic opportunities and potential cultural ramifications of student-specific course needs information

Since the first two points have been addressed in previous posts, let’s focus on the strategic and cultural issues related to academic program capacity management.

Strategically, the availability of student-specific information creates the following opportunities:

• Decision-support information for academic departments regarding course offerings for an upcoming term
• Support for short and long-term faculty hiring plans
• Identification of course bottlenecks (required courses with the fewest available seats) for each academic program
• The understanding of the capacity of each academic program to effectively accommodate new students (derived from the capacity of its bottleneck courses)

The feedback that we have received is that the following cultural implications should be considered:

• Campus initiatives to improve student services or become more student-centered get a major, tangible boost
• Expectation management regarding the speed and magnitude of change (e.g., only a small percentage of the academic schedule representing "high-impact moves" will be addressed each term) is critical to promote faculty buy-in
• An institution-wide, versus department by department, perspective and senior administrative buy-in are critical in creating a “culture of evidence”

Join me again next week when I’ll discuss early adopters of these approaches and the future of academic program capacity management.

Both of the common approaches to Academic Program Capacity Management (mentioned last week) can be effective. They provide a partial picture of the need for courses, faculty to teach those courses and the resulting capacity of the programs that use those courses. However, both approaches have drawbacks. Specifically, historical demand analysis only gives a limited, potentially skewed picture of student demand for courses. Templated scheduling is either overly restrictive or not reflective of student needs and wants.

What approaches might be more fruitful? We believe that the introduction of student-specific course demand analysis is a key step. This approach features an analysis sample of active students likely to participate in an upcoming term and simulated students likely to join progressing students (e.g. Freshmen, transfers, returning students). While this method is complex and data-intensive, it is the only way, short of polling your students, to determine unmet course needs.

Rather than using templated or even lock-step scheduling, we favor student-specific academic career plans. These plans can incorporate partial course templates, but also serve many additional purposes. For the student and advisor they become an interactive roadmap to career completion. For the institution, they become an invaluable source of information. Specifically, data is collected regarding each student’s career intent (major, minor, goal graduation date, etc.) and preferences (desired courses, desired terms and times of week, etc.)

Next week, we’ll discuss best practices in the deployment of these two approaches.

While attempts to address academic program capacity issues are almost always worthwhile, the best practices adopted by our industry over the past few years have significant drawbacks. Last week, I discussed the most popular of those practices—historical course demand analysis and templated scheduling. This week, I’ll discuss their limitations.

The analysis of course demand in historical schedules is a powerful tool, one that we use in our Platinum Analytics Suite. Relying completely on this form of analysis, however, is problematic. The most significant issue is that historical scheduling practices can dramatically skew the results. For example, offering a limited number of seats or scheduling during unpopular times can curtail course demand, while opposite practices can increase demand. Additionally, historical analysis does not account for the recent changes in the curriculum or student demographics.

Templated and/or block scheduling is viewed by many as overly restrictive. Plus, even when pure block scheduling is deemed acceptable, it only works for the minority of students that manage to stay perfectly on the cohort (no transfers, withdrawals, failures, part-time load during any term, etc.) actually benefit from the course access that this approach is designed to promote. Regarding template schedules, we like the idea of offering a variety of templates reflecting student need and interest. This approach is a compelling alternative to block scheduling, but its deployment is dependent upon a thorough understanding of that need and interest. Since templated scheduling is typically a response to a lack of such understanding, a chicken and egg dilemma emerges.

Check in again next week to learn about new approaches that overcome these limitations allow institutions to take control of their academic program capacity.

Many institutions react to program capacity issues when they become a crisis status (often only a week or two prior to the start of an academic term). For those institutions, options are limited (e.g., adding a handful of sections that can be taught on an adjunct basis). Other institutions have had better success by planning for strategic changes in course offerings and reducing uncertainty by using templated schedules or lock-step cohorts. The reactive approach and the pain resulting from it don’t need to be explained or amplified. Therefore, I’ll focus on efforts in the market to anticipate change and improve predictability of student need.

Some institutions have invested heavily, often in their institutional research offices, in the historical analysis of student demand for courses. Using this approach, courses with increasing enrollments and consistently full sections can be isolated as candidates for increased seats and/or more sections. Alternatively, courses with declining enrollments and consistently unfilled seats may create opportunities to reassign needed faculty to courses in the first group.

Other schools looking to reduce last minute surprises during registration have started implementing approaches that “funnel” students into a select group of courses. Common examples include templated freshmen schedules (which emphasize a handful of core curriculum courses) and highly simplified program requirements. The most effective way to minimize surprises is the “cohort scheduling” approach in which all students in a cohort follow a template that satisfies simple program requirements with no electives. While these approaches fly in the face of a “traditional” liberal arts education, they have been effective in allowing some institutions (especially for-profits) to efficiently deliver courses when they are needed.

Visit again next week to learn how institutions could address their academic program capacity challenges in new ways that would yield greater benefits for their campuses.

Most colleges and universities implicitly make a promise to students during the admissions process. That promise is that they will receive the help that they need to attain their academic career goals. Even the best-intentioned school, however, is hindered in keeping that promise by a fundamental lack of information regarding future enrollment trends in each program and the capacity to support those trends. This is why academic program capacity management is so vital to higher education.

Institutions generally focus on an overall admissions goal when recruiting incoming classes. This approach doesn’t address the following key needs: predicting the percentage of that new class that will ultimately select each program at the school, and the capacity of those programs to effectively support those new students. The reality is that many institutions have academic programs with little room for additional students.  As new students choose these programs, their “gateway courses” become more severe bottlenecks to everyone in that program. A more systematic approach of “enrollment management” versus focusing on a global admissions goal gives an institution and its students better odds for success.

In addition to delivering on the “promise,” proper management of academic program capacity allows for informed faculty hiring. In the short term, fewer enrollment surprises mean fewer last-minute, frantic searches for adjunct instructors to teach courses with higher-than-expected enrollments. In the long term, institutions can focus on pinpointed hiring and allocation of available funds to add faculty of strategic importance. Knowing the projected enrollment of a program for future semesters also allows institutions to perform proactive facilities planning, eliminating the need to renovate or reconfigure space on the fly.

Check back in next week to learn how academic program capacity management is currently being addressed in higher education.

In this series, we’ll discuss a capacity issue that is related to but even more important than facilities capacity management – academic program capacity management. The phrase “academic program capacity management” or even the general concept may be unfamiliar to you. But, even if you have not spent much time considering the “capacity” of your academic programs, it is important to recognize that effective academic program capacity management allows institutions to deliver on its promises made during the admissions process.

Most institutions approach admissions in a way that targets an overall number of new students entering during an academic term. Academic program capacity management, however, considers the projected academic career path of each student and the institution’s ability to make available the courses and teaching resources that they need. It’s a way to model each student’s proposed route to completion or graduation and the academic road blocks that he or she may face.

Essentially, those roadblocks – lack of available seats in required courses (typically caused by lack of available teaching resources) – are to the course offering management process what space bottlenecks are to the space management process. Note: Please refer to my previous series of blog entries for more information on space management.

Next week, we’ll dive into why the effective management of academic program capacity management is a vitally important issue for higher education.

In this, the final post in this series on bottlenecks and their impact on campus capacity, I’ll highlight some examples of the successful use of our approach. The important thing to note is that only the framework is consistent across these institutions. The actual allocation strategies and formalized scheduling policies are derived from an analysis of each institution’s unique challenges. Additionally, this framework assumes that the statistical analysis used to attack their bottlenecks will need to be rerun over time to address new bottlenecks and resulting changes to strategies and policies to attack them.

University of British Columbia:

Reports from UBC’s bottleneck study (our first study of this type) showed that their primary scheduling issue was large-capacity rooms being booked by low-enrollment sections. Interestingly, the concentration of scheduling during primetime for these rooms was a virtual non-issue (since the demand for large rooms had already pushed heavy usage outside of primetime hours). Since the study, UBC has shown the need to require that their academic departments have at least a 70 percent fill rate in large classrooms. To the surprise of their central scheduling office staff, the reports from the study convinced their departments to unanimously approve this standard with little discussion.  UBC is now considering other recommendations from the study to support continued growth without new construction.

California State University Long Beach:

CSULB had a long-standing bottleneck in their large capacity lecture rooms, some of which were coming on and offline for renovation. CSULB had already – out of necessity – developed allocation strategies for their much sought-after lecture theatres. Therefore, the focus of their study was to refine their allocation strategies by developing reports to document their space constraints and enforce strategies. These reports are now being used to manage their updated academic scheduling policy, which includes the four identified scheduling strategies from the study. This effort, which started with the Fall 2007 class schedule, has already yielded impressive results. Deviations from the approved meeting time matrix have decreased 40% and the combined efficiencies from bottleneck allocation strategies led to 43% fewer classes left unscheduled by the departments.

University of Missouri—Kansas City:

UMKC’s bottlenecks were its technology-enhanced classrooms. The bottleneck study showed a wide range of usage levels of bottlenecks from each department. For example, one department was scheduling 80 percent of its offerings into these classrooms, even though many offerings did not require the technology. To equitably use the rooms and allow for goal enrollment growth, our study showed that UMKC could create and enforce a policy where each department could schedule only 40 percent of its lecture sections in the enhanced rooms. Discussions between the Registrar’s office and Provosts office are now focused on formalizing an academic policy that will ensure strategic enrollment growth potential and equity between departments.

Pacific Graduate School of Psychology:

PGSP offered many courses that were scheduled in non-standard meeting patterns. For example, one-hour meetings that started and ended “off the grid” were conflicting with two standard one-hour blocks (not just one), making it harder to build conflict-free schedules for PGSP students, faculty and classrooms. Since standard meeting patterns allow better fit and utilization of scheduled space, our bottleneck study urged PGSP to reevaluate its meeting patterns to make them more standard. Additionally, a PGSP survey was incorporated into the study showing potential changes to afternoon and evening timeslots that might increase student availability to certain courses.

Johnson County Community College:

JCCC has primetime scheduling periods in the day and evening, when small and mid-sized classrooms (16-25 and 26-40 seat categories) were very hard to find. In the short term, a well timed construction project adds several of these prime rooms. To continue to support their steady enrollment growth, however, JCCC plans to use the study’s reports to monitor primetime/non-primetime scheduling ratios by departments and the impact of departmentally controlled classrooms.

As I bring this topic to a close, I hope that reading about space management and other institutions’ success stories will inspire you to attack bottleneck challenges on your own campus. Your comments and questions about this topic are always welcomed and encouraged. Please contact me at tshaver@astraschedule.com.

It’s a major challenge to effectively manage your space, but it is a challenge that is well worth the effort. The individuals listed in this entry are leaders in the field. They have achieved great results with their innovative solutions.

A simple, but effective approach to spreading offering times across the scheduling week is the “zone model.” They key aspect of the zone model is that it divides the week up into zones whereby maximum and minimum usage levels can be enforced on a department-by-department basis. Herb Chereck, University Registrar at the University of Oregon, led his institution in a development effort of an academic scheduling policy that uses such an approach. Herb was part of a panel who presented their policies at a recent AACRAO meeting.

Bruce Cunningham, University Registrar at Duke University, identified enforcement as a key challenge to deploying an effective policy. Duke created a homegrown tool, the departmental schedule validator (DSV), that allows Duke to define and enforce allocation strategies. Specifically, 1) departments are limited to a maximum of 50 percent of their offerings that are held during primetime, and 2) departments are required to keep a relatively even distribution of offerings across approved meeting patterns and days of the week.

John Marshall Law School modeled various academic room renovation plans in our bulk scheduling/optimization tool. Jodie Needham, director of Academic Services, was able to identify the specific renovation plan that most effectively reconfigured their highly constrained downtown Chicago facility to support their specific course offering mix.

Another approach, less common in the United States, but highly effective, is often called timetabling. In this approach, some or all of the course offerings in a schedule are placed in a meeting pattern and room in a single optimization run. Since the offering times are variable within room, instructor, and perceived student availability, this approach typically supports much higher usage levels in a fixed amount of space than pre-assigning meeting patterns.

In my next and last post on space management, I will highlight a few case studies from some of our client institutions that have battled space bottlenecks using the recommended methods that I have described in this series.

The few institutions that have implemented a formalized academic scheduling policy would almost unanimously report that the biggest challenge, after politics and culture have been addressed, is measuring and enforcing adherence to the policies. This simply can not be done without a series of rather complex, automated reports that must be run each scheduling period.

What specifically should these reports address? While there will be variations depending on the specific allocation strategies that make up any given policy, reports should address some of the following:

• Equitable allocation of bottlenecks across departments: This is usually done by capping each department’s allocated weekly hours that correspond to a department’s pro rata hours of instruction in the overall schedule. For example, department X offers 10 percent of the weekly lecture hours in an overall schedule. Therefore, it is given up to 10 percent (or 30 weekly hours) of high-tech classroom space during primetime.

• Minimum seat fill of large capacity bottlenecks: Seat fill is frequently calculated as enrollment capacity of a section to room capacity. More sophisticated reports might measure actual enrollment in historical “like” terms as a ratio to room capacity. The latter approach is more effective in that it “weeds out” sections with superficially high enrollment caps, but traditionally low actual enrollments. In either case, many policies concerning large capacity bottleneck rooms require a minimum ratio (e.g., 70%) to even request this type of a room during primetime.

• Objective section or instructor criteria: The allocation of bottleneck rooms that have specific technology or other equipment often focuses on the objective need for such equipment and technology. For example, some institutions have developed faculty training and certification programs for use of technology. Such institutions have successfully required that only certified instructors be allowed to use such rooms during primetime. Other examples include special needs of faculty, students, etc.

Next week, I’ll highlight leaders in the field who are using the space management techniques (some that I’ve discussed and some that I have not) to remove bottlenecks and improve utilization on their campuses.

Most institutions want a formally approved academic policy, but few have implemented one. What, then, are the steps to put a policy into a practice? Specifically, how can a policy be implemented without cultural and political upheaval? The only effective approach to building a formalized academic scheduling policy is to start with a set of equitable allocation strategies (see earlier posts).

The beauty of an academic scheduling policy is that it formalizes the rules of engagement in an otherwise messy and emotionally charged process. Rooms are no longer allocated exclusively by informal and unwieldy processes – such as the squeaky wheel or “the land grab” (the first department to get a stake in the ground wins). Instead, good policies promote equitable and objective allocation models and take the scheduling office out of the often contentious role of room arbiter.

To do this, a policy must be conceived of and promoted as a way to grow “through” obvious space bottlenecks without the favoritism often present in other models. Equity and objectivity need to be key factors in measuring and enforcing an academic scheduling policy.

Next week, I’ll give specific examples of how policies can be measured and enforced as enrollments and space inventory change.

Colleges and universities can’t magically create more prime space or prime time slots during the week. They also can’t fix a space shortage solely by measuring their utilization. So, what can they do to resolve their academic space problems?

They must strategically manage the allocation of prime space during prime timeslots – which we call bottlenecks. The key to bottleneck allocation is governing the accepted bottleneck requests down to available bottleneck timeslots. Bottleneck allocation strategies need to be evaluated on an institution-to-institution basis – they are not “one size fits all.”

For instance, spreading utilization into non-prime time hours is the most obvious strategy, but its effectiveness is surprisingly varied across institutions. The strategy of setting objective criteria for the requesting of prime rooms during prime hours works well for large capacity rooms and technologically-enhanced rooms. For example, activities with low enrollment capacity or low historical enrollments should not be able to request large capacity bottlenecks. Sections not requiring technology should not be permitted to request technology-enhanced bottlenecks.

Other proven strategies include enforcing standard meeting patterns in bottlenecks, reducing room ownership by departments, and correcting data regarding bottlenecks in the space inventory. The key, again, is that you can prove that the strategies selected are sufficient to resolve the space crisis on your campus. Once you can do that, it is much easier to gain needed support for implementing these changes.

Next week, I’ll discuss the benefits of transforming these allocation strategies into a formalized academic scheduling policy.

We have noticed, over the years, that schools and vendors frequently confuse the proper role of space utilization reporting. Specifically, they attempt to position reporting as a viable method to improve efficiency. It’s not. It is only a tool to measure efficiency. Such reports calculate the statistical result of schedule load divided by available instructional space (available rooms or seats multiplied by hours the campus is open).

So, what is the value of these reports and how can an institution actually improve their space utilization?

Utilization reports are vital for benchmarking existing efficiency and (if they are detailed enough) shedding light on what types of rooms might limit your ability to grow enrollments. The important ideas regarding the identification and management of these rooms (your bottlenecks) will be addressed in upcoming posts. For now, however, it is important to focus on the role of reporting in understanding your situation and your growth constraints.

Utilization can improve in two ways: when you add more activities and/or students to a fixed amount of space; or, when you maintain a fixed activity level while removing instructional rooms from your inventory. Good reports can’t make this happen, but they can track your progress.

Next week, I’ll start to deal with the best way that we have discovered to actually facilitate improved efficiency.