As service brands expand across multiple locations, small inefficiencies in staff scheduling can compound quickly. Overstaffing increases labor costs, while understaffing leads to inconsistent experiences that weaken retention and loyalty.
Yet most scheduling tools rely on rigid templates or outdated assumptions, making it difficult to staff around real demand. MyTime takes a different approach with Labor Forecasting, which leverages a recently upgraded AI-driven model to deliver staffing recommendations grounded in actual booking behavior.
This article breaks down how MyTime’s upgraded Labor Forecasting engine works, why demand-aligned staffing is essential for multi-location brands, and how predictive staffing helps operators reduce labor costs while protecting client experience.
Labor forecasting predicts how many staff members a business needs at any given hour based on historical booking patterns, recent demand trends, and provider productivity. The goal: avoid overstaffing (wasted labor dollars) and understaffing (poor client experience). MyTime automates this with a multi-layered, continuously updating AI model which adapts to each location’s real booking behavior.
Most service organizations—salons, spas, barbershops, med spas, fitness studios—still rely on static schedules, gut instinct, or last year’s numbers. That approach collapses quickly when you operate 3, 10, or 200+ locations.
Here’s why.
Fixed schedules often keep too many staff on slow days. Managers repeat the same template even when demand drops.
Result:
Thousands in unnecessary labor spend per month across the franchise, especially as small scheduling inefficiencies multiply across many sites.
When schedules fail to anticipate peaks, clients wait longer, appointments run behind, and experiences deteriorate across several locations at once.
Result:
Consumer behavior changes constantly. Relying on old schedules creates misalignment between actual demand for services and scheduled labor.
Examples:
Result:
Small mismatches quickly multiply across a franchise, leading to labor waste, inconsistent service quality, and schedules that go stale long before operators notice.
A downtown location might peak at lunch.
A suburban location might peak after school.
A mall location might peak on weekends.
A “one-schedule-fits-all” approach doesn’t work.
MyTime solves this with location-specific, pattern-specific forecasting.
Most staffing tools look only at recent appointment volume. MyTime analyzes multiple layers of historical demand to understand true booking rhythms across every location.
Recognizes recurring surges such as holidays, summer lulls, back-to-school, and promotional periods.
Captures periodic spikes tied to:
Identifies strong days (e.g., Wednesdays & Saturdays) and weak days (e.g., Mondays).
At the operational level, MyTime models fine-grained demand by recognizing:
Daily and hourly patterns drive the most precise staffing recommendations, ensuring operators match labor to real demand on a shift-by-shift basis.
Why this matters to operators:
Predictive staff scheduling built on multi-layer demand modeling is significantly more reliable than systems that rely only on only month-to-date or week-to-date data.
This gives franchise operators a clearer, more stable foundation for optimizing labor costs at scale.
A forecasting model is only useful if it adapts quickly.
MyTime incorporates a 90-Day Recent Demand Layer, which continuously learns from the most recent three months of booking trends.
Example:
If the last three months show Thursdays have slowed significantly, MyTime immediately adjusts staffing recommendations—even if last year’s Thursdays were busy—reducing unnecessary labor hours at every affected location.
If a weekday shows consistently zero bookings across 90 days, MyTime recommends zero staffing.
This eliminates unnecessary shifts and supports more cost-efficient staff scheduling franchise-wide.
Most scheduling systems forecast labor based on appointments alone. MyTime goes further by incorporating actual provider productivity, giving brands a clearer picture of true staffing needs.
This ensures forecasts reflect each location's real staffing capacity, rather than relying on generic labor ratios.
When labor allocation is based on real behavior—not guesswork—multi-location brands see immediate improvements across operations.
Schedules match real demand, not static templates.
Removing just 2–3 unnecessary shifts per week per location produces meaningful savings.
Peak periods are fully staffed, protecting your brand reputation.
Managers save hours each week adjusting misaligned schedules.
Every site receives forecasting tailored to its unique behavior.
MyTime’s enhanced Labor Forecasting gives multi-location brands the precision they need to control labor costs, protect client experience, and make informed staffing decisions at scale. By layering long-term patterns with recent booking signals, eliminating anomalies, and incorporating real provider productivity, MyTime offers one of the industry’s most accurate predictive scheduling tools.
Because Labor Forecasting is built directly into the MyTime Scheduler, operators can act on predictions immediately—without extra tools, spreadsheets, or manual adjustments. Even small improvements in labor efficiency translate into meaningful savings and stronger operational stability across every location.
MyTime customers can contact Support to start using enhanced Labor Forecasting. New to MyTime? Schedule a demo to see it in action.