Revenue driver explained
What is a revenue driver?
A revenue driver is what drives the revenue of a department. For example, if more guests are staying at a hotel, the restaurant can expect to generate more revenue. There is often more than one driver that impacts revenue in a department.
A driver-based forecast uses these drivers to forecast for the department. For example, a restaurant may use Guest nights as a driver to forecast the number of covers.
How to review and update the driver
If set-up has selected to use PMI machine learning algorithms, the driver detection will be automated based on seasons and day of the week. It will create different drivers per segment and, if units/covers are used, separate drivers for these. This is recommended for properties with at least 1 year of historic data in PMI. It is possible to use ML (Machine Learning) drivers with only 5 weeks of history, but the accuracy will increase as the amount of historic data available increases.
To view the drivers being used:
- Go to tools. Select ’Driver based’
- Use the graph to review the results and evaluate the usefulness of the drivers. You cannot make any edits to drivers when ML drivers are activated. Consider if your department could achieve a more accurate forecast with a manual driver.
- ML drivers are detecting correlations between the department’s historical covers/units/revenue and other departments/segments (sources). There can be more than one source per day of the week which can make it difficult for humans to understand the correlations. We therefore recommend using the graph for a general evaluation of the accuracy of the drivers, instead of checking the sources in the table.
Manual drivers are usually used for new properties with less than 1 year of historical data available, or for properties that have recently been through significant changes that make historic patterns an unreliable source for future.
To create a manual driver:
- Go to Tools and select Driver based
- Use the drop-down menus to define which segment (if enabled) you want to build a driver for.
- Choose the source. You can also define which segments within the source you want to build the driver from.
- Choose if you want the calculations by weekdays or just as a total (unticked radio box).
- After you have defined settings, click on the + sign and the rule for this segment is moved up in the rate grid list. You may build several drivers for one segment or department.
- After all the rules have been created, choose if you want the entire forecast to be based on the rule. 100% means everything, but if you want to revise e.g., 30% of the revenue manually, change the cell with percentage to 70. If you have a positive change in the revenue with 10% on specific days or in total, you can change the percentage to 110%.
- Applicable for covers only: Define capture ratio for both cover/units and rates. You may untick both these buttons if desired.
- Applicable for covers only: An easy way of letting the system help you is by clicking on one of the two blue buttons, From Budget or From History. From Budget means that PMI splits the budgeted data per day based on last year’s actual figures. It will suggest the same average check, but different number of covers each day. In other words, PMI calculates the budgeted capture ratio of occupancy; e.g., if your budget is 100 covers and guest nights are budgeted at 1000, the capture ratio would be 10%. This is usually recommended to new hotels that don’t have any historical data.
- Applicable for covers only: From History means that PMI calculates each departmental segment individually, giving you different averages for each segment, and different average rates, based on last year’s actual figures. For example, if you had 10 guests on average, last year on Mondays, and the guest night occupancy was, on average, 100, PMI will calculate 10% of guest nights as the capture ratio for this period.
- You may calculate for just some of the rules as well. Use the radio button next to the rule to activate or deactivate for calculation.
- You may manually revise the ratios directly in the cells at any time. You can also make a New Period for different seasons that influence the average revenue. For example, summer is a slow season with guests spending less money, on average, in the restaurant, than in the autumn with conference guests on average spending more.
- Make sure that you save the changes.
Troubleshooting tips
This section provides additional troubleshooting advice for readers experiencing specific issues. While it’s packed with useful insights, you may skip it if you’re not facing any related problems.
Why is the hours total different in the table and the graph?
The difference in hours comes down to the type of forecast being displayed:
- Management Forecast (Table): This is the forecast set manually by management, based on their expectations and strategic goals. It reflects planned hours to meet operational needs.
- SMART Forecast (Yellow Bar in Graph): Generated by PMI’s SMART system, this forecast uses machine learning and historical data to provide a dynamic suggestion. It factors in monthly productivity goals and current hotel activity.
The variation between these two forecasts highlights the difference between static planning (Management Forecast) and data-driven predictions (SMART Forecast). Use this insight to adjust plans as needed for better alignment with real-time performance and goals.
Understanding zero OTB in Flash report
In PMI, the Flash Report provides a daily overview of revenue figures, both actual and forecasted, across all departments. Users may encounter situations where the Flash Report displays zero On the Books (OTB) data for specific dates leading to concerns about data accuracy.
Clarifying OTB in Flash Reports
It’s important to note that the Flash Report does not directly display OTB figures. Instead, it presents actual revenue data up to the current date and relies on the Live Forecast for future dates. The Live Forecast incorporates OTB data, which represents revenue from existing bookings or sales for upcoming dates. Therefore, if revenue actuals are zero for specific dates, the OTB for those dates will also be zero, reflecting no current bookings or sales recorded.
Manual changes overwritten at Live forecast import
Legacy PMI System
- Issue: Pickup column doesn’t “gray out” when importing Live forecasts.
- Cause: This is the design of the legacy PMI system.
- Effect: Manual changes in the pickup column will be overwritten with each import.
New PMI System
- Preserving Manual Changes:
- Enable Editing: Click the robot icon (if auto-forecasting is enabled) or the import icon next to the day you want to edit.
- Edit Value: Enter your desired value in the pickup column (only editable column for future days).
- Save Changes: Press “Save”.
- Result: Your changes will be preserved even after a new import, indicated by a person with a pencil icon.
How to change covers on historical dates
If you need to update covers on a past date, use the Flash Report instead of Live Forecast. Follow these steps:
- Navigate to the Flash Report.
- Select the historical date you wish to edit.
- Click on the Edit tool (Pen icon).
- Manually adjust the covers as needed.
- Save your changes.
Note:
- Live Forecast is designed for adjusting future covers.
- Flash Reports handle updates for historical data, such as revenue and actual figures.
Excluding segments from driver-based calculations
It is not possible to stop Machine Learning (ML) from including an existing segment in the driver-based calculation. If the ML Live Forecast doesn't align with your expectations, you have the option to manually override it or construct a custom driver to make necessary adjustments.
Enhancing forecast accuracy: Leveraging PMI’s auto forecasts
Discrepancies in the imported Room Night live forecast can impact the generation of live forecasts for arrivals, departures, and stayovers. To address this, it's recommended to utilize PMI's auto forecasts. These forecasts are typically more accurate as they rely on machine learning and historical data. Ensuring the accuracy of the imported Room Night live forecast is crucial, as it directly influences the precision of your live forecasts. Regularly review and adjust your forecasts to maintain their reliability and effectiveness.
Different hours for similar revenue on different dates can vary!
Recommended hours for similar revenue on different dates can vary due to a combination of factors including the monthly productivity forecast, historical staffing patterns, and other factors recognized by the machine learning capabilities of the SMART forecast.
Difference Between Live Forecast and PMI Prediction
If there is a recalculation of the PMI Prediction due to season generation, new file import, or manual calculation, it takes time for the ML algorithms to fully update. The Live forecast values will only update once all dates in the viewed period are completely updated. Thus, there might be a delay, and the Live forecast might not immediately match the PMI Prediction.
Changing revenue for today & tomorrow in PMI
Key Points to Remember:
- Budget & Forecast Module changes totals on a monthly basis only.
- Flash Report allows you to edit historical values.
- Live Forecast allows you to edit future values (including today and tomorrow) by switching to “manual.”
Steps to edit revenue for historical dates (Past)
- Open the Flash Report.
- Expand or select the past date you want to edit; click the plus icon.
- Click the pencil icon (if available) to override the revenue value.
Steps to edit revenue for future dates (Today & Tomorrow)
- Go to the Live Forecast.
- Expand or select the specific date (e.g., today, tomorrow).
- Switch the date to “manual” if required.
- Enter the new revenue value in the editable field.
Can you activate a Live forecast accuracy report in Power BI?
The PMI system integrates Live forecast accuracy into its PMI Index calculations. Although Live forecast accuracy contributes to the PMI Index, it is not explicitly shown as a separate report in PowerBI.