One Data Trick to Nail Labor Forecasting

Labor forecasting can feel like trying to predict the weather—you look at the patterns, make your best guess, and hope you don’t get caught in a storm of overstaffing or understaffing. But what if one simple data trick could drastically improve your accuracy, save on labor costs, and make your managers’ lives easier?

That trick: using historical sales data tied directly to labor hours.

Why Labor Forecasting Is So Hard

For restaurants, hotels, and other shift-based businesses, labor costs are one of the largest expenses—often accounting for 30% or more of operating costs. Get it wrong, and the fallout is immediate:

• Overstaffing: payroll costs eat into profit.
• Understaffing: service suffers, employees burn out, and guests leave unhappy.

Traditional forecasting methods—like looking only at last week’s numbers or “gut feeling”—leave too much room for error. With labor costs rising and competition fierce, managers need more than guesswork.

The One Trick: Pairing Historical Sales Data With Labor Hours

Here’s where the magic happens: linking your sales history directly to the labor hours you scheduled.

Instead of just asking, “What did we sell last year this week?” you ask:
“What sales-to-labor ratio worked best last year this week?”

This simple shift gives you a labor-to-sales efficiency benchmark.

For example:

• If you did $10,000 in sales on a Friday last August and scheduled 320 labor hours, that’s $31.25 in sales per labor hour (SPLH).
• Compare that to other weeks, and you’ll see your sweet spot for productivity.

By focusing on the SPLH trend, you can build future schedules that match expected demand with the right number of hours—not too many, not too few.

Why This Works

Data-driven forecasting isn’t just about numbers—it’s about consistency and adaptability. As Forbes explains, effective forecasting should be a “continuous, flexible process” that adjusts as new data comes in.

Pairing sales and labor data gives managers a living benchmark they can refine weekly:

• Big event in town? Adjust up.
• Rainy day slump? Adjust down.
• Year-over-year holiday sales growth? Apply the new trend.

This ensures your labor plan reflects both historical insight and real-time adjustments.

A Real-World Example

A busy brewery schedules Friday nights based only on “gut feel.” Some weeks, they overschedule and end up with servers standing around. Other weeks, they’re scrambling with too few bartenders during a rush.

By switching to SPLH forecasting, they learn their sweet spot is about $30–32 in sales per labor hour. Now, if they expect $12,000 in Friday sales, they know to staff for about 375–385 hours across the week.

The result? Lower payroll waste, happier employees, and guests who get served faster.

How to Start Using This Trick

1. Pull Last Year’s Sales Data – Break it down by week (or even by day).

2. Match It With Labor Hours – Use your scheduling software (ShiftForce) to line up hours worked.

3. Calculate SPLH – Sales ÷ Total Labor Hours.

4. Find Your Sweet Spot – Look for the range that consistently delivered strong service without overspending.

5. Apply It Forward – Use that benchmark when building upcoming schedules, adjusting for known events or seasonal trends.

Why Technology Makes This Easy

Doing all of this in spreadsheets is possible—but painful. Tools like ShiftForce automate the process, giving you clear insights on SPLH trends, forecasting models, and real-time adjustments. That means:

• Less time crunching numbers.
• More time focusing on guests.
• Happier managers who aren’t scheduling by guesswork.

The Bottom Line

Labor forecasting doesn’t have to be complicated. By pairing historical sales with labor hours and focusing on your sales per labor hour (SPLH) benchmark, you can take much of the guesswork out of scheduling.

The result? Lower labor costs, improved employee satisfaction, and guests who keep coming back for great service.

And that’s one data trick worth repeating.