What's a normal void rate for a restaurant?

The number people quote is 1–2% of gross sales. It's not wrong, but it's the wrong question — because a "normal" void rate is a store-level average, and leaks don't live at the store level. They live at the name level.

The better test is the one we run in production: build a peer band. Take stores doing comparable volume with a comparable service model, find the median void rate, and flag anything running above roughly 1.5x that median. In the networks we reconcile, healthy full-service stores commonly sit anywhere from 0.3% to 0.7% — and a store at 1.2% against a 0.5% peer median is a finding even though it would pass the "under 2%" folk rule with room to spare.

Then break the flagged store out by employee. A store's excess void rate is almost always concentrated: one or two names carrying void counts far above their shift-mates on the same stations. That's not automatically theft — in the 87 days of data that started this company, 38% of voids were process noise, 27% were comps rung as voids, and 19% were untracked employee meals. But concentration by name is where the conversation starts.

So: don't benchmark against a magazine number. Benchmark each store against its own peers, flag the band-breakers, and attribute by name. That's the whole method, and it's what Void Hunter runs on a Toast, Square, Clover, or PDQ export in about 30 seconds at never86.ai/trial — free, no card.