Workforce scheduling

Labor Demand Forecasting

No more over- and understaffing. Get accurate forecasts, monitor events and calculate required staffing levels

BENEFITS

Higher accuracy by Machine Learning

A realistic forecast includes the full range of demand drivers, ranging from sales, promotions, price changes, local events, seasonality to weather. OnShift uses Machine Learning to take into account both employee preferences and historical data to automatically detect trends and outliers.

Calculate required headcount

Calculate optimal labor hours and get the number of employees you need from each role to meet demand by combining our ML-driven forecasts with your labor standards. Make decisions on temporary work, hiring and layoffs to increase revenue when demand is high and reduce labor costs when demand is low

Location-dependent forecasting

Use different methods for each location to make accurate forecasts. Each location has different demand drivers, such as transactions, major events and sales, that must be taken into account. Identify peak and off-peak periods at 15-minute, daily and weekly levels forecasts with OnShift.

Uncover future labor demand by predicting how many people with the appropriate skills your organization will need several weeks from now.

Demand signals

By using various demand signals such as sales, visitors, bookings, promotions, price changes, local events, we can accurately predict how many people you will need at any given time. We account for the season or the weather patterns that influence customer behavior and staff demand. In addition, you may know which employees are better at up-selling or work better under pressure - these are all data points you can just plug into OnShift to do the hard work for you.

Learn how to boost your forecast accuracy 22% higher with our best-in-class demand forecasting solution that uses advanced supervised machine learning techniques.

  • Machine learning is a powerful forecasting tool. It is able to surpass traditional methods such as moving averages, historical predictors by more than 22%.
  • Machine learning, in contrast to traditional statistical methods, is faster and more adaptable. Since new data can quickly be incorporated, machine learning can be used to calculate labor demand with higher accuracy.
  • By using machine learning, our forecasting algorithm can automatically adjust to changing customer needs and trends.
key features

Up to 98% accuracy

Forecast with high accuracy your future demand
  • Consider all possible demand variables and priorities.
  • Make accurate predictions and simulations to understand your future demand.
  • Use you historical and current workforce data and staffing requirements.
  • Granular prediction capabilitie from interval forecast as granular as 15 mins to daily, weekly, monthly or yearly forecasts
  • All forecasts consider trends and seasonality, but also consider events that don't follow a smooth pattern (eg: new product introduction, weather, equipment failures or other factors).
  • Compares all forecast models in a single generation and then the AI picks the best performing model for the specific objective relative to its environment.
Solution details

How it works

Drawing from historical and real-time data, you can now predict the number of visitors or customers to different locations and departments based on demand patterns, price changes, and other factors. You'll be able to see the impact of events like holidays and local events on your locations and know exactly who you need to meet the demand where and when.

Use Cases

Optimize your workforce

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