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Module — Forecast

Forecast pulls data from multiple sources and keeps on learning.

Combine historical occupancy, revenue, reservations, weather, events and your own signals. The model learns per location and per moment, so the forecast keeps getting sharper.

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Staffing forecastExample Ltd. · Centrum location14 days · hourly · last updated 3 min ago
Live model
Expected demand1,284 hours+8.4% vs last week
Accuracy94.2%MAPE 5.8%
Open shifts23peak Sat Aug 16
ActualForecastConfidence interval
110%82.5%55%27.5%0%TODAYSat Aug 1696% · +6 staffersmadiwodovrzazomadiwodovrzazo
Signals in model24-month historyReservationsWeather 26°CEvent · 12k visitors

Module — Forecast

Combine historical occupancy, revenue, reservations, weather, events and your own signals. The model learns per location and per moment, so the forecast keeps getting sharper.

Book a demoView the platformStaffing forecastExample Ltd. · Centrum location14 days · hourly · last updated 3 min agoLive modelExpected demand1,284 hours+8.4% vs last weekAccuracy94.2%MAPE 5.8%Open shifts23peak Sat Aug 16ActualForecastConfidence intervalSignals in model24-month historyReservationsWeather 26°CEvent · 12k visitors

What does Staffyou Forecast do?

Pulls data from multiple sources — history, revenue, weather, events — and keeps learning per location. We combine your own history (shifts, hours, check-ins) with external and internal signals such as revenue, reservations, ticket sales, weather, events and manual input. The more relevant sources, the sharper the model.

Trusted by companies across the Netherlands

How it works today

Without this module, someone solves it by hand.

Most forecasts only look at last year. Staffyou Forecast combines multiple data sources and adapts every day.

Data sits in silos

Revenue, reservations, weather and occupancy live in different systems. The planner has to combine it all in their head.

Locked to history

One-off peaks, events or new locations aren’t recognised if you only look at the past.

Doesn’t learn from outcomes

What actually happened isn’t fed back into the next forecast. The forecast becomes outdated.

What the module does

Staffyou Forecast in features, not promises.

  1. Multiple data sources

    Combines your own history with revenue, reservations, ticket data, weather, events and manual input.

  2. Continuous learning

    Every scheduled shift, check-in and no-show becomes feedback for the model. The forecast keeps getting sharper.

  3. Per hour, location and department

    Not just a daily total, but a forecast at the level you actually schedule at.

  4. Straight into euros

    Translates staffing into labour costs and compares it against budget or a revenue percentage.

  5. Draft shifts

    Turns the forecast into shifts that can go straight into the scheduling process.

  6. Scenarios side by side

    Compare a lean, a neutral and a generous staffing level before publishing.

How it works

From setup to daily use.

1Step 1

Connect data

We connect your occupancy history, revenue, reservations, weather, events and other relevant signals.

2Step 2

Model learns per location

The model trains on the combination of sources and learns which signals matter most for your location.

3Step 3

Keeps learning

After every scheduled and worked shift, the model refines the forecast. The feedback loop runs continuously.

The difference

Forecasting isn’t a snapshot, it’s a feedback loop.

The best forecast doesn’t come from one spreadsheet. By combining data from multiple sources and learning from what actually happens, staffing keeps getting better matched to tomorrow’s demand.

Multiple sourcesContinuous learningPer hourPer locationFeedback loopStaffyou WFM

One platform for your permanent team, your flex pool and your agencies — Staffyou Forecast is part of it.

One platform

This is how the modules work together.

Staffyou Forecast isn't a standalone product. It's a building block of Staffyou WFM.

ModulesComplianceIDForecastAgentAlgoritmeEngagePillarsForecast

Determines how many people you need, per location and per moment.

Algorithm and Agent

Fill the shifts and keep them filled, even on the day itself.

Compliance and ID

Make sure every shift is correct and demonstrable.

Hours and self-billing

Hours, approval and invoicing flow automatically through to payroll.

Staffyou WFMOne platform underpinning all modules and pillarsView the platform

Questions planners also ask

Frequently asked questions

Questions about Staffyou Forecast.

We combine your own history (shifts, hours, check-ins) with external and internal signals such as revenue, reservations, ticket sales, weather, events and manual input. The more relevant sources, the sharper the model.

From day one, Forecast makes a prediction based on available data. After every scheduled and worked shift the model is updated, so predictions keep improving.

Yes. Via API or import we connect revenue, reservations, visitor numbers or other signals that matter for your organisation.

You can build a forecast even with limited history. We use benchmarks per activity, location characteristics and external signals. As more data comes in, the model learns to take over those patterns.

The proposed staffing level is translated into labour costs and compared against budget or a percentage of revenue.

Accuracy depends on the quality and quantity of data. Because the model keeps learning, you generally see the forecast getting better over time.

Book a demo

30 minutes, your staffing as the starting point.

We'll go through your volumes, locations and suppliers and show how Staffyou Forecast fits your scheduling process.

  • No generic product demo
  • €0.15 per scheduled hour, first 500 hours free
  • Volume-based discounts, not per user
  • Support 7 days a week, 7am to 7:30pm