Optimizing the schedule is a hot buzzword in Higher Ed. The idea of clicking a button, building the perfect schedule and sitting back and relaxing is quite compelling. But in practice, few schools have truly gotten an optimization to work well for them, and in a lot of cases it can be more work to set up than the benefit of running it. Especially with legacy vendors, we estimate greater than 50% of clients never run a good optimization at all.  Why is it that folks rarely actually save time and improve resource utilization with these solutions? Often, it feels like they are just a hard-to-use system to prevent room double-bookings. But can you do better?

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Legacy Room Optimizer Solutions

It’s time for a history lesson. Why are room optimization solutions so prevalent… and bad? Well, dating back to the late 1990s when some of the earliest tools hit the market, scheduling was extremely decentralized. As in, faculty & departments would just request whatever times and in some cases rooms that they wanted, and they would usually get them.  So room optimizer solutions were built to take in a bunch of crazy, unstructured preferences and then optimize them the best that they could. And the funny thing is, they actually do that pretty well. Bad data in, bad data out. 

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Recently, though, schools have begun to re-conceptualize scheduling as much more than optimization of a cesspool of diverse preferences. Universities started to 1) Think more about student success and recognize research that suggests booking all classes in primetimes, and or having a lack of understanding of course demand can decelerate degree velocity; 2) face even more of a space crunch, and in some cases become incentivized by state legislatures to improve space utilization and 3) Quite simply… administrators had less time. More projects, more integrations to manage, and did we mention… COVID? 

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Modern Scheduling Solutions

So what does a modern scheduling solution include that perhaps a legacy room scheduling system might not have? 

• Section scheduling to ensure you offer the right courses, seats and sections in tandem with space bookings
• Policy enforcement, such as timeblocks and primetime rules, to improve course access and save time
• Smart instructor forms help institutions to be more student-centric while still being cognizant of faculty needs, and to automate the tedious, manual process of gathering preferences
• Faculty workload tracking
• Enrollment heatmaps and balanced section reporting (ROI dashboard) that demonstrate the ROI of the tool.
• Automatically surface best fit rooms based on preference fit for departmental room scheduling
• Room optimizer that actually works; surfacing potential issues before optimization to prevent post-facto manual clean-up (read more below)
• Ability to customize preference weighting in optimization to take school's unique needs into consideration
• A modern user experience so that end users can build schedules more efficiently
• Rapid improvement and iteration as a company and product, rather than fixing one bug release per year…

And here at Coursedog, we’re proud to be very upfront about expectations in terms of what you can expect from an optimization. 

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Schedule Optimization Tips

Here’s some tips to consider whether an optimization is helpful for your campus: 

• Bad data in bad data out. If you don’t have scheduling policies that help you to distribute the schedule effectively, and everyone requests the same timeslot, you will have bottlenecks and the optimization will not work. 
• The value of a room optimizer increases proportionally to the size of your school and the degree of centralization of room scheduling. More rooms centrally owned = more space to optimize = more value in maximizing space utilization and more time saved optimizing. 
• The value of time and room optimization together increases proportionally to the degree that your scheduling process is centralized. More centralization = easier to consolidate preferences = easier to optimize. 
• Time optimization should really only be used by centralized schools.
• Oftentimes, you may not want to implement an optimization for your first scheduling cycle. It may slow down the implementation process and can be implemented after go-live, during the section scheduling process, but should not be a requirement prior to project go-live. 

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