The Capacity Math Behind Load Smoothing

Scheduling theory has a core conclusion: **for the same total workload, a smoothed distribution yields higher completion rates than a peak-heavy one.** Toyota’s Production System turned this into a method called *heijunka*—flattening peaks and valleys to raise both output and quality. Toyota applied it to assembly lines; you apply it to groomer stamina curves—same math, different context.

Run the numbers for a pet-grooming day. Assume a groomer’s effective daily work time is six hours:

**Mixed scheduling (random orders):** slot misjudgment (large dog estimated at 1 hr, actual 2 hrs) → cascading delays → compressed afternoon → stamina drop slows work further → actual output ≈ 6 hrs × 70% ≈ **4.2 effective hours**

**Breed-based scheduling (grouped by size):** consecutive similar services (skill repetition rises) → predictable load (precise buffers) → stamina curve respected (large dogs not back-to-back) → actual output ≈ 6 hrs × 90% ≈ **5.4 effective hours**

Gap: 1.2 hours/day. At NT$1,000 per service-hour, that’s **NT$1,200/day, about NT$31,000/month** (26 days). Same staff, same hours—only the scheduling method changed. (The 70% and 90% figures are illustrative; measure your own actual output before and after implementation.)