How Many Scanners Do You Actually Need? Let Your Past Events Tell You - Fri - Aug 21, 2026 - 10:09am

Stacy Chapman
Updated: Fri - Aug 21, 2026 - 10:09am ⚬ 0 Comments Barcodes & Scanning
---
How Many Scanners Do You Actually Need? Let Your Past Events Tell You


Most venues size their gate crew by feel. You remember the year the line got ugly, so you add a person. You remember the year three staff stood around with nothing to do, so you cut one. Then attendance shifts, or you add an early-entry night, and you are guessing all over again.


If you have run the event before, you do not have to guess. Every barcode you have ever scanned carries a timestamp, and those timestamps describe your arrival curve precisely. This post walks through how to pull that history, turn it into an hourly arrival pattern, and convert the pattern into a staffing plan.


We would also like to hear how you do it. Discussion questions are at the bottom.

Where the data lives


In ThunderTix. Run the Barcode Report for any past event, including expired ones. Export to CSV. The columns that matter are:


• Scanned (1 or 0)
• Updated At (your scan timestamp)
• Scanned By (which staff account processed the scan)
• Name (the ticket type, useful for segmenting later)
One important note on Updated At. The barcode export does not carry a dedicated "scanned at" field, so Updated At is your best available proxy. For a scanned barcode it almost always reflects the moment of scan, but it will also move if the record is edited afterward. Sanity check your export before trusting it: if the timestamps cluster on your actual event dates and hours, you are fine. If you see a batch sitting on some random Tuesday in August, those rows were touched post-event and should be dropped.


From a previous ticketing system. Any export with a per-ticket scan timestamp works. If your old platform only gave you gate counts by hour, that is enough for this exercise too. You lose the ability to segment by ticket type, but the arrival curve is the whole point.


From no data at all. If you are running the event for the first time, borrow the pattern from a comparable event and validate it live. Have someone log gate counts in fifteen-minute blocks on the day. Next year you will have real numbers.



Building the arrival curve


1. Filter to scanned barcodes only. Unscanned rows are unused tickets, not arrivals.
2. Group by date, then by hour. Do this per year, not pooled, so you can see whether the pattern is stable or drifting.
3. Separate your arrival days. Multi-day events rarely have one peak. Early-entry or camping-arrival nights often carry a third or more of total admissions and produce the sharpest single hour of the whole run.
4. Then go down to 30 minutes. This is the step people skip, and it is the one that matters. Hourly averages smooth away the exact burst that creates your queue.

Why the 30-minute view changes the answer


Gates open on the hour. People are waiting. The first half hour after opening routinely runs 40 to 70 percent above that hour's average, which means an hourly figure understates your true peak load badly.


A real example from a three-day festival with nine years of history: the Thursday early-entry hour averaged around 230 scans, which sounds manageable. The busiest 30-minute block inside that hour ran at a pace equivalent to 400 per hour. Staffed against the average, that gate queues immediately at opening and stays backed up for 45 minutes. Staffed against the burst, it never forms a line.


Size against the burst, not the average.



Converting load into people


Here is the part where most guidance hands you a made-up number. Do not use ours. Derive your own, because your throughput depends on whether you are also wristbanding, checking bags, checking ID, or handling will-call at the same window.


If you have run the event before, your own history gives you the answer. Take a past event where the gate ran smoothly with no complaints. Find the peak 30-minute load. Divide by the number of scanning positions you had open. That is your demonstrated per-lane throughput, under your real conditions, with your real staff.


Demonstrated throughput = peak 30-min scans ÷ 2 ÷ lanes open

Lanes needed = projected peak 30-min scans ÷ 2 ÷ demonstrated throughput
If that past event did queue badly, the same math still tells you what you were short by. Run it for the year that went well and the year that went poorly, and the gap between them is your answer.


If you have never measured it, time twenty entries at your next event with a stopwatch, front of the line to cleared. Ten seconds per patron is a fast, single-purpose scan lane. Thirty seconds is a lane that is also wristbanding and answering questions. The difference is a factor of three in headcount, which is exactly why you should measure rather than assume.


Add one floating position beyond the calculated number. Scanners fail, batteries die, someone needs a break, and a patron will always show up with a ticket problem that takes four minutes to sort out. Without a float, that one patron becomes everyone's queue.



Cross-check: your scan rate


While you are in the report, look at what share of issued barcodes were ever scanned. Anywhere from 65 to 85 percent is common and usually reflects genuine no-shows.


If yours is well below that, ask why. Sometimes it is a comp block that was never distributed. Sometimes it means staff waved people through un-scanned during a rush, which tells you the gate was under-resourced and that your measured peak load is lower than the real one. That second case is worth catching, both for planning and for revenue protection.



What shifts the pattern


Compare year over year rather than pooling everything, and watch for:


• Early entry growing. Once patrons learn that arriving the night before means a better campsite or a shorter line, that day grows every year. Check whether its share is trending up.
• Schedule changes. Moving the first headline act earlier pulls the whole Friday curve forward with it.
• Ticket type mix. Camping and weekend passes arrive early and all at once. Single-day and general admission arrive close to showtime. If your mix changes, your curve changes.
• Weather and travel. A single bad year is noise. Three consistent years is a pattern.

• Sign up today and start selling tickets Login