The Advanced Scheduling product provides easy access to add forecasts, schedule employees, and to see how a business is performing. This article will show how to navigate through Advanced Scheduling from the Home Dashboard, and provide information on the Demand Forecasting algorithm.
For a list of all available Advanced Scheduling articles, please visit: WFM - Advanced Scheduling: Getting Started
- Go to Home - Dashboard & Alerts
The homepage gives a selection of charts and graphs to provide an overview of the business.
- The pie chart shows sales figures, split by revenue stream if desired. Hovering over the pieces of the chart will show the amount of sales month to date for each revenue stream
- The line graph to the right shows a comparison of forecasted sales vs. actual sales month-to-date. This gives a quick snapshot at how accurately the business is forecasting on a day to day basis
- Labour cost % month-to-date is also shown in the bar graph. Once a schedule is set to Approve, the system uses snapshot functionality to compare and see consistency between Forecasted vs. Actual Labour costs
- Weather forecast information specific to the selected site's postcode is displayed
Fig.1 - The Home tab
- Sales Forecast - Forecast future sales
Forecasted sales can be edited and viewed here, through a weekly, daily and monthly viewpoint. Total sales, actual sales, budget sales and last year’s sales can also be viewed.
- Schedule - Plan & manage your rota
Update, edit and view employees’ hours and view financial information on wage costs, available for wages, wage budgets and actual sales
- Reports - Performance Analysis
Useful reports to supplement the Advanced Scheduling Solution can be accessed from here.
Understanding the Demand Forecasting Algorithm
The Demand Forecasting algorithm uses recent and historical site-specific historical and recent sales data to derive forecasted sales values, taking into consideration national events, any logged local events and weather conditions.
- The first data point used is from the previous year’s equivalent date. The system looks at the same day for 8 weeks both forwards and backwards
- The previous year's forecast is calculated by taking an average of the relevant data after excluding any outliers. An outlier is any day that falls outside of the business’ day-to-day sales trend
The next key data point is recent trends.
- Equivalent days in the 8 weeks prior to the date will be used to make the recent trend calculation. This is done site-by-site, by time slot, sales category, sales value and number of sales items, all fed over automatically from the till system
- Seasonality changes are also taken into account when moving from one week to the next. For example when moving from December to January significant changes in sales would be expected
The next data point used is weather.
- Weather forecast information is obtained by looking at each sites’ postcode or GPS coordinates
- Using all available historical data the system can generate a forecast purely based on weather. This is based on how precipitation levels and temperatures have impacted on sales in the past
The last data point the system takes into account is national events.
- Standard UK national events are configured within the system. These include all Bank Holidays, and special days such as New Years’ Eve and Valentine’s Day
- The system will understand the change in holiday dates. For example, if a Sunday in April is Mother’s Day, instead of looking at the equivalent day for last year, the system will look at the data for Mother’s Day last year. Likewise, if the Sunday this year is a normal Sunday, but the equivalent day last year was Mother’s day, the data from last year will be treated as an outlier
To generate a forecast 8 weeks into the future, the system will use its own historical forecasts to produce an optimum ratio for each site-specific business
The data points mentioned above are combined using this optimum ratio. This gives the business an accurate forecast based on live data.