How to track class and instructor utilization on Starch
Class and instructor utilization tracking is the practice of knowing, at any moment, how full your classes are running, which instructors are driving attendance, and where you have capacity sitting idle. It sounds straightforward until you're pulling booking data from your scheduling tool, cross-referencing it against instructor schedules, and trying to spot patterns across locations or time slots — all manually, all after the fact.
What this looks like in practice varies: a multi-location fitness studio cares about fill rate by class format and time slot; a yoga co-op is more focused on which instructors retain members over time; a corporate wellness operator is tracking utilization against contracted minimums. The underlying question is the same — are you getting the most out of your schedule, and do you know why or why not?
On Starch, you describe the report or dashboard you actually want — 'show me weekly fill rate by class type, flagged when any slot drops below 60%, with instructor headcount alongside it' — and it exists. You can set it up to push a summary to Slack every Monday morning, or keep it as a live view you check before making schedule changes. Either way, you're looking at current data, not a spreadsheet you built last quarter and haven't touched since.
Why it matters
Underutilized classes cost you on two fronts: you're paying instructor labor for empty spots, and you're missing the signal that something in your schedule isn't working. Overutilized classes create a different problem — waitlists that frustrate members and accelerate churn. Operators who track fill rate and instructor performance weekly can catch both before they compound. Those who don't usually find out too late, when revenue has already dropped or a popular instructor has already left.
Common pitfalls
The most common mistake is tracking enrollment count instead of fill rate — a class with 18 bookings looks healthy until you realize the room holds 30 and you've been scheduling it at peak hours. A close second is measuring utilization at the location level when the real variance is by time slot or instructor. Third: looking at data monthly when scheduling decisions happen weekly, which means you're always reacting to last month's problem. Fourth: treating no-shows as cancellations in your fill rate math, which makes utilization look worse than it is.
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