One shop, tracking staff hours is straightforward. The rota is one document, the shifts happen in one place, and by Friday you have a clear picture of what everyone worked. When you add a second Shopify location, that simplicity disappears overnight — not because the maths gets harder, but because the data starts living in two separate places that nobody is responsible for joining together.
The hours problem is not dramatic. Nobody sits down and decides to stop tracking properly. What happens is slower than that: someone covers at the other shop and the time gets logged on a WhatsApp message nobody retrieves. A manager updates one rota and forgets the other. Overtime creeps in through cross-location shifts that neither location's manager was counting. By the time payroll comes round, you're spending forty minutes on a task that should take five, tracing hours through a trail of messages, tabs, and half-updated spreadsheets.
This article explains the specific ways tracking breaks across multiple Shopify locations, and what a working system actually looks like — with and without scheduling software.
The hours tracking problem in a multi-location setup is not complexity — it is fragmentation. Each complication is small. Together they turn a straightforward admin task into a weekly headache.
Your data lives in two rotas, not one. Shop A has its own schedule. Shop B has its own schedule. Neither rota captures the full picture of what any given staff member has worked across both locations. You have to combine them manually, and that combination step is the one that always falls through the cracks.
Cross-location cover changes the picture without anyone noticing. When someone covers a shift at your second shop to handle an absence, their hours for that day need to go somewhere. If the manager at the shop they covered updates the rota there, the home shop's rota will not reflect those hours. If nobody updates anything — which happens more often than it should — those hours disappear from your records entirely until payroll surfaces the discrepancy.
Overtime is invisible until it has already happened. Overtime risk in a single-shop operation is easy to see: you look at one rota, add up the week, and flag anyone approaching their limit. In a two-shop operation, the hours at Shop A and Shop B sit in separate documents. Nobody is adding them together in real time. An employee can work 20 hours at Shop A and 22 hours at Shop B in the same week, and neither manager knows the total is 42 until payroll goes out.
Payroll reconciliation takes longer than it should. When you sit down to process payroll for two shops, you are comparing two sets of records that were maintained independently, by different people, at different times. Small inconsistencies that would be obvious in a single rota — a missed clock-out, a shift recorded at the wrong time — are much harder to spot when the two halves of the picture are in separate files.
Before you build any system, it helps to know exactly what information you are trying to capture. For a multi-location Shopify operation, there are four distinct things that matter:
Hours worked at each location, separately. Not just total hours — location-level hours. If you allocate wage costs by shop, or pay different rates for different locations, or simply want to understand which shop has the higher labour cost, you need the location detail. Combining everything into a single total loses information you will want later.
Cross-location shifts, flagged clearly. Every time someone works at a location other than their home shop, that shift needs a note. Not because it affects their pay, necessarily, but because it affects your cover availability data, your cost allocation, and your ability to trace anything back if a discrepancy surfaces. A note saying "Cover from Shop B" takes five seconds to write and saves fifteen minutes of detective work later.
Running weekly totals per person. Hours do not just matter at payroll — they matter during the week, so you can see overtime risk building before it arrives. A column that updates automatically as shifts are logged gives you a live view of who is approaching their limit. In a multi-location setup, this column needs to sum across both locations, not just one.
Absences and cover together. Absence cover and hours tracking are connected. When an absence is covered at a different shop, hours shift between locations. If your absence records and your hours records are in separate documents, keeping them consistent requires a manual sync step that frequently does not happen. Keeping them together is simpler and produces a more accurate picture.
For two Shopify locations with a team of ten to fifteen people, a single shared spreadsheet can handle this — if it is set up correctly and the update discipline holds.
The structure is straightforward. One workbook, two tabs: one per location. Each tab has the same columns: date, staff member name, shift start, shift end, hours worked (auto-calculated), location, and a notes field. At the top of each tab, a summary row per employee showing their total hours for the current week.
The weekly totals need a third tab — a summary sheet — that pulls the hours from both location tabs and sums them by staff member. This is the overtime-watch view. It should show every employee, their hours at Shop A, their hours at Shop B, and the combined total. If you only look at one tab, you will miss cross-location hours. The summary tab forces the combination to happen.
Update cadence matters as much as structure. The right moment to log a shift is at the end of that shift, not at the end of the week. End-of-week logging from memory produces gaps. Same-day logging takes thirty seconds per shift and is accurate. If both managers have edit access to the shared spreadsheet, each can update their own location in real time without waiting for anyone to consolidate.
The three-minute daily check is worth building as a habit: at the end of each day, glance at the summary tab and confirm that the hours logged look right. This catches obvious errors — a missed entry, a shift logged at the wrong shop — while they are still easy to correct. Left until Friday, the same errors take twenty minutes to trace.
The spreadsheet approach works until it does not. The failure modes are predictable, and knowing them in advance helps you decide when to move to something more robust.
Cross-location shifts fall through the cracks. A staff member covers at Shop B on Tuesday. The Shop B manager updates the Shop B tab. The Shop A manager does not know it happened. The summary tab now shows that person working at Shop A for Tuesday when they were actually at Shop B. The hours total is correct; the location split is wrong. If this happens once, it is a minor error. If it happens three or four times a week, your cost allocation data is unreliable.
The summary tab goes stale. The summary tab only works if both location tabs are being updated consistently. If one manager falls behind by two days, the summary shows an inaccurate picture. The person responsible for payroll has no way of knowing the summary is incomplete unless they check both source tabs manually — which defeats the purpose.
Scale tips the balance. A team of twelve with two locations is manageable in a spreadsheet with discipline. A team of eighteen with three locations is probably not. The number of cross-location interactions grows faster than the team size, and each one is a potential data quality problem. At some point the maintenance overhead of the spreadsheet exceeds the overhead of a proper system.
The core problem with a spreadsheet is that it is a passive document: it only contains what someone puts into it. If someone forgets to update it, the gap sits there silently until payroll.
Scheduling software built for multi-location retail solves this differently. The schedule and the hours record are the same thing — when a shift is created and filled, the hours are already in the system. When a cross-location cover happens, the system records who worked where. When a shift is modified or cancelled, the hours update automatically. Nobody has to manually sync two separate documents because there is only one.
StaffHub handles multi-location hours at the location level by default. Because it runs inside Shopify, it already knows which staff are assigned to which shops. Hours are tracked per location, cross-location shifts are flagged automatically, and the weekly total per employee is visible in real time across all locations without any manual summary tab. The overtime-watch view that takes fifteen minutes to build in a spreadsheet is just the default dashboard.
The practical difference is that with scheduling software, the five-minute weekly hours check becomes a genuine five-minute check — you open the dashboard, look at the totals, flag anyone approaching their limit, and close it. In a spreadsheet setup, that same check is a five-minute check only if everything was updated correctly throughout the week. One missed entry and it is a thirty-minute investigation.
If you run two or more Shopify shops and currently track hours across separate spreadsheets, the point where the system saves you the most time is not in the big reconciliation once a month — it is in the small accumulations during the week. Ten minutes here, fifteen minutes there, tracing a cross-location shift nobody recorded properly. StaffHub is free for up to 5 staff, with paid tiers from $12.99 per month and a 14-day free trial, and replaces the manual hours tracking entirely.
Install StaffHub on Shopify — 14-Day Free Trial
Need a quick start? The free Multi-Location Rota Template Builder generates a printable weekly rota for up to 5 shops with built-in hours tracking columns. No signup required.
A single shared spreadsheet with one tab per location works at small scale. Each row is a shift — date, staff member, start time, end time, location, any notes. The key discipline is filling it in on the day, not at the end of the week from memory. A weekly five-minute check every Friday before payroll catches most errors while they are still easy to trace. The system breaks when someone covers at a different location and neither manager updates the central sheet — that is the failure mode to watch for.
Add a running weekly total column to your hours tracker that sums across both location tabs. When it crosses your threshold, flag the name. In a multi-location setup, overtime risk is invisible until you combine the hours from all shops — which is exactly what a summary tab, or scheduling software, does automatically.
Record the hours under the location where they actually worked, not their home location. Add a note — "Cover from Shop B" — so you can trace it back if needed. The important thing is that total weekly hours are correct and attributed to the right location for cost purposes.
Split the entry. One row for the hours at Shop A (e.g. 9am–1pm), one row for the hours at Shop B (e.g. 2pm–6pm), both under the same date and name. This keeps location-level data accurate while giving you the correct total. Most scheduling tools that support multi-location will do this split automatically when the staff member clocks in and out at each site.
Once a week, every week — not the night before payroll. A Friday end-of-day check catches small errors while they are still easy to trace. For most small multi-location retailers, the week is fresh enough on Friday that anything unclear can be queried before Monday.
Related reading: Multi-location staff scheduling for Shopify: the practical guide · How to handle last-minute staff absences across shops · How to handle cross-store shift swaps · Free vs paid scheduling tools for Shopify multi-location · StaffHub vs manual rotas.