Fourth Analytics: Understanding the Sales Dashboard (HotSchedules)

Fourth Analytics allows users to export dashboards, reports, and graphs to further analyse and share the data within the business.

The Sales dashboard is a fundamental element of the Fourth Analytics solution available to HotSchedules customers.

Available Sales Types

Data feeds into Fourth Analytics once daily from HotSchedules.

Types of Transactions:

• Actual Sales
• Forecast Sales
• Last Year Sales

Actual Sales – HotSchedules sales data exported daily to Analytics.
HotSchedules standard reports will reflect the same as sales in Fourth Analytics.

Forecast Sales – Forecast Sales are generated and posted manually in HotSchedules by the Manager who is responsible for scheduling employees.

Last Year Sales – Last Year Sales are the actual sales for the same day in the previous year. 

Budget Sales – Budget Sales can be requested to be loaded once annually or an FTP folder can be provided, so the Budget can be loaded as necessary by your business.
Please speak to your Fourth contact if you would be interested as these options are chargeable.

(Comp) or Same-store sales - An important barometer used to compare the performance of established stores with newly opened stores. Comp locations can be requested to be loaded once annually.
Please speak to your Fourth contact if you would be interested as these options are chargeable.

Date/Time - Each tab provides sales analysis as perspective snapshots in time.
Data is shown based on the Financial Calendar provided by the customer and shows as:

• 52 or 53 weeks in each year
• 12 or 13 periods in each year, made up of 4 or 5 weeks in each period
• Weeks go in line with Payroll/Schedule week numbers

The Sales dashboard within the Fourth Analytics solution is available to HotSchedules customers.

The Sales Dashboard contains a set of Tabs:

• Daily
• Weekly
• Period
• Year
• Trend vs Last Year
• WAPE
• Alerts

Sales Tabs - Daily, Weekly, Period, Year, Trend vs Last year
Each tab has been designed to provide consistent insight and intuitive navigation

1. Sales KPIs are presented at the top of the page

2. Followed by visual representations of KPIs comparing and ranking locations using sales-based metrics as variance +/-  Sales, Guests, Forecasts

3. End capping each tab are detailed reports of the same Sales KPIs from the top of the page for all locations selected.

Sales tabs could be scheduled to users' email as it displays the previous insight into trends.

'Detail' Reports

Some reports in the Sales dashboard in the North American offering of Fourth Analytics have a 'Detail' option that expands the displayed data, providing in-depth insights via a more detailed breakdown.

The example below shows the location of the Detail button on a report, and then the detailed view with different report view options (to display the report in table (default), line, bar, or chart format).

Sales Dashboard reports with the 'Detail' option

• Sales - Weekly - By Location
• Sales - Period - By Location
• Sales - Year - By Location

WAPE - Weighted Absolute Percentage Error

This tab provides enhanced analysis and metrics pertaining to sales forecasting behaviors.

The calculations include only actual sales greater than zero and aggregates the data by location and date. This ensures accurate reporting by handling edge cases where negative sales values have been entered.

In a previous version of Analytics, all dates and locations were included, even when actual sales were zero, leading to distorted metrics.

This new calculation will be in place for customers who have migrated to the enhanced US offering for Fourth Analytics. Please see this release note for more information.

Weighted as any error in forecasting (in dollars) is equally impactful on the overall reported error value. It proportionately represents the true cost to your business. Without this, data from smaller locations or slower days could disproportionately affect the calculated error, leading to inaccurate and misleading results.

Absolute ensures that instances of over and under-forecasting do not cancel each other out. Determining how detailed you wish to measure the accuracy is also important to get the right result. For example, the error on a weekly basis per organization may be relatively small, while the daily figure by location can be significantly higher.

The WAPE tab can be used to evaluate the performance of your forecasting model while also providing a clear measure of manager forecasting accuracy across your organization.