Integrate analytics & forecasting in Power BI

Organizations employ a diverse array of forecasting techniques catering to the unique needs and priorities of different departments and business functions. The sophistication and maturity of these forecasting methods vary across areas such as sales forecasting, financial forecasting (encompassing revenue, expense, and cash flow projections), headcount planning, inventory planning, demand forecasting, and sales and operations planning (S&OP).

A frequently utilized approach to forecasting involves distributing a forecast template, allowing individual line managers to submit their projections. The firm then consolidates these projections to arrive at the forecast for the entire organization. This method is known as the Sales Force Composite method in the context of sales forecasting. Such participative or collaborative forecasting methods are also standard in Finance, where users enter financial projections in templates.  

Let us take a quick look at crucial forecasting capabilities delivered by Inforiver.

Create a blank template and enter values by simply double-clicking a cell and typing in the formula bar.

Create a forecast based on actual performance (from past periods) and make finer adjustments.

Create periodic forecast trackers to compare actual performance to projections. Format columns, rows, and cells just as you can do in Excel.

Create custom forecast templates with custom fields like text, single-select, multi-select, check box, date, and person columns.

Enter data manually in the Power BI reports and collaborate with peers and stakeholders.

Combine actual data for elapsed periods and forecast data for future periods in a few clicks. In the image below, user is creating a new projection by merging actual data from Jan – Mar and forecast data for the rest of the year.

Add periods that are missing in your Power BI data model directly in the visual for quick projections. Inforiver reconciles these in the future as these periods become available in the data model.

Enter forecasts at the top level and distribute to descendants (departments, teams, geographies, months, etc.) or based on weights of other series.

Copy values across other rows and columns, and apply percentage trends if needed.

Lock a range of cells and prevent changes while forecasting. Block specific cells or entire hierarchy branches.

Implement quick forecasting techniques such as the 3-month moving average forecast.

Create and compare multiple forecast versions using ‘scenarios’ and write them back. Scenarios can be created in both the edit and read modes and shared publicly or only with specific users in the organization. You can write back all or particular scenarios.

Save the current state of the report as a static snapshot at month-end accounting/financial close. Compare multiple snapshots to see how forecasts have evolved over time. Snapshots preserve original data and are not impacted by source data changes and dataset refreshes.

Perform a one-click variance analysis between various versions of forecasts and actual performance​ using IBCS templates.

Add context to your reports, such as cell, row, column level comments, and comments column. Save comments securely to the database along with author and time stamp​ details.

Use the @ symbol to tag other stakeholders and reply to comments posted by other users.​​ Assign and track task status as needed. Receive instant email notifications when someone responds to you, mentions you, or assigns a task to you.

Audit and explore changes made to the report (who-what-when) using the audit log. Export audit details to an Excel file.

Inforiver allows you to write your forecasts, other custom fields, and comments to Microsoft Fabric OneLake/Lakehouse, Fabric Data Warehouse, Microsoft Dataverse, and several other destinations, as shown in the following image.