Same hours, better hours
Moving hours out of the quiet morning and into the rush can capture more sales without adding a single hour of payroll.
Case study · Part 1 · Retail labor
Staff to the customer, not the clock.
A case study from my years at Lowe's: put people on the floor when customers are there, and watch payroll as the day happens instead of after it.
The story · Lowe's, 2011–2021
Hours follow traffic.
A lot of my work at Lowe's came down to one question: are the right people on the floor when the customers are?
Intraday payroll hours analytics. I designed a system that let Store and Field management manage payroll expenses in real time, a first for Lowe's.
Staffing to demand. Hours should follow customer traffic, hour by hour, so the busiest hours get the most help and the quiet ones don't carry extra payroll.
The demo below is not that system and uses no Lowe's data. It's one small example store day, built to show the idea: customer traffic shapes the schedule, and the schedule drives sales captured and payroll.
Once stores were staffed right, the next question was what was being sold and by whom. That's Part 2: Sales performance.
Interactive · Example data
Schedule an example store day.
Pick a preset, then drag the bars or tap an hour and use + and −. Every number is an example assumption you can change below.
Customers per hourForecast · example
AssociatesCovered Short Extra Needed
Sales specialistsDrag a bar, or tap an hour
Example assumptions
How it works: customers split into general shoppers and specialist customers (big-ticket projects). Each associate or specialist can help a set number per hour. Helped customers buy at the higher conversion rate, unhelped ones at the lower rate. "Needed" is the fewest people who can help everyone forecast for that hour, with at least 2 associates and 1 specialist while the store is open. Sales per specialist-hour is the forecast specialist sales for that hour (customers × helped conversion × ticket) divided by the specialists on the floor. The traffic curves and every assumption are examples, not Lowe's or any retailer's data.
Beyond the store
Why this matters.
Labor is usually the biggest cost a manager controls. Spending it in the right hours matters more than spending less of it.
Forecast first
A schedule is only as good as the traffic forecast behind it. Get the hourly shape right and the rest of the plan follows.
A better customer experience
Customers notice when nobody is around to help. Coverage in the busy hours is service, not just sales.
Payroll in real time
Seeing hours against sales during the day lets a manager send someone on break or call someone in while it still matters, not on next week's report.
Short is expensive too
Under-staffing looks cheap on the payroll line, but the lost sales from customers who never got help often cost more.
Beyond retail
Call centers, clinics, delivery hubs, field service: anywhere demand moves by the hour, the same forecast-to-schedule chain applies.
Example data only: the hourly traffic shapes and all assumptions are illustrative and editable, not from Lowe's or any retailer. Built by me with AI. Updated Oct 2026.
You're reading · Part 1 of 3Staffing to demandThe right people on the floor at the right hours.
Next · Part 2 →Sales performanceWhat was being sold, and by whom.Talk shop