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Integrate analytics & forecasting in Power BI

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Create a forecast using a blank template

Start with a blank template and input your forecast

Create a forecast based on actuals

Use prior period data or an existing forecast as base, and make further changes

Create a periodic forecast tracker

Compare actual performance to projections using a forecast template

Create a forecast template with custom fields

Add remarks, drop-down, date, and user fields to your template

Allow users to input forecast data in the reading view

Allow multiple users to enter forecast data for items they own

Create, manage, and compare forecast versions

Utilize scenarios to create and compare multiple forecasts in a few clicks

Create and compare forecast snapshots across time

Review how forecasts have evolved over a period of time

Audit changes to forecasts

Understand who made changes, what changes were made, and when

Write back & save forecasts

Save forecast data to Fabric, DataVerse, Azure, Snowflake, OneDrive, SharePoint, and many other destinations

Why 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.  

The baseline data for forecasting usually originates from the latest performance data extracted from analytics tools like Power BI, Tableau, Qlik, Spotfire, and Cognos. As these tools offer limited built-in forecasting capabilities, analysts often export data from these tools to Microsoft Excel or enterprise planning software to create forecast templates.  

Challenges in Forecasting in Power BI

Power BI’s built-in forecasting capability is restricted to creating time series forecasts using its line charts. However, you can forecast only one series at a time, and the chart will need a date field on the x-axis. Power BI’s table and matrix visuals do not support collaborative forecasting using templates where users can enter data.

Line Chart Time Series Forecasting Powerbi

Consequently, there are two ways to enable forecasting right inside Power BI (and avoid replicating the data elsewhere):

  1. Forecasting using Power BI + PowerApps:

You can build forecast templates in PowerApps and integrate them with Power BI using the PowerApps visual. However, this approach is limited in terms of what it can do. Note that PowerApps is an entirely different skillset from Power BI, with minimal overlap between the two. In fact, most Power BI developers are NOT PowerApps developers.

In an earlier analysis, we concluded that the combination of Power BI + PowerApps is not for everyone, as it is relatively harder than it should be for casual business users and yet too restrictive for very advanced scenarios.

      2. Forecasting using a third-party visual:

Another option is to use a third-party editable table or matrix visual for forecasting. However, almost all solutions in the market today (except Inforiver) are IT-centric, with the following issues:

  • For each forecasting requirement, you must work with IT to set up the backend infrastructure, including creating database schema, tables, and service URLs for writing back forecasts. If a manager wants to create a quick & dirty forecast, this approach does not work.
  • These solutions are typically rigid, making change management difficult. For example, adding a column to an existing forecast template is effort-intensive. Changes must be made at all levels, including the database, data model, and Power BI report.
  • Many users want to run simple forecasts without the added hassle of managing an end-to-end writeback solution. They are fine creating and saving forecasts in the .pbix file or exporting them to an Excel file. This gives them complete independence from IT. Unfortunately, third-party visual based solutions enforce a writeback infrastructure on such users.

Using Inforiver for Forecasting in Power BI addresses all the above issues

With Inforiver, you can deploy a business-friendly, robust, and flexible writeback solution in Power BI with minimal dependency on IT. You can:

  • Run forecasts right from within the visual without setting up a database, server, or writeback service. This allows managers to run forecasts on any report casually in minutes. Choose Inforiver Matrix if this appeals to you.
  • You only set up the backend infrastructure if you need to write back your forecasts. Even there, you need not create database tables in advance. Inforiver automatically triggers appropriate create/update SQL queries based on the design and updates to your writeback template. Choose Inforiver Enterprise if you want to perform forecasting with writeback.
  • Change management is more straightforward with Inforiver. Add a column in an existing forecast template, and the writeback engine will identify the change and trigger queries to update the DB schema automatically.

Inforiver allows your line managers to create forecasts whenever they want, with minimal involvement from IT. The business productivity and cost savings can be huge, considering that many line managers create and submit forecasts across the organization.

Read More

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

Featured Webinar

Microsoft Power BI to Fabric Data Writeback (LIVE DEMO)- Replay

Microsoft Power BI to Fabric Data Writeback (LIVE DEMO)

Learn how to save forecasts from Power BI to Microsoft Fabric and other destinations.

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1. Create a forecast using a blank template

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

Create Forecast Blank Template

2. Create a forecast based on actuals

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

Create Forecast Based On Actuals

3. Create a periodic forecast tracker

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

Create Periodic Forecast Tracker

4. Create a forecast template with custom fields

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

Forecast Template With Additional Fields

5. Allow users to input forecast data in the reading view

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

Input Forecast Data Reading View

6. Blend actual and forecast data

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.

Blend Actual Forecast Data

7. Add forecast for periods not available in your data model

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.

Forecast Future Periods Not In Data Model

8. Allocate forecasts to children equally or based on weights

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

Forecasts Equally Or By Weights

9. Copy data across periods or apply a trend

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

Copy Values Apply Trend

10. Lock/unlock cells, cell ranges, and hierarchies from editing

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

Forecasts Specific Categories Lock Unlock Cells From Editing

11. Create moving average forecasts

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

Three Month Moving Average Forecast

12. Create, manage, and compare forecast versions

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.

Manage Multiple Forecast Versions

13. Create and compare forecast snapshots across time

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.

Create Periodic Forecast Snapshots

14. Perform one-click variance analysis

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

One Click Variance Analysis Of Forecasts And Actual

15. Add cell, row, and column-level comments

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.

Enter Data Level Comments

16. Initiate threaded conversations with replies and notifications

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.

Collaborate With Team Over Forecasts

17. Track changes to forecast with audit log

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

Track Changes Audit Forecasts In Power Bi

18. Write back & save forecasts to a destination of your choice

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.   

Writeback Save Forecasts

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Forecasting multiple items with seasonality

Learn how you can quickly forecast multiple items with seasonality right inside Power BI!

 

forecasting-multiple-seasonality

Featured blogs

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About Inforiver!
Inforiver is the fastest way to do everything in Power BI. It enables citizen developer productivity and unleashes true self-service with our intuitive and interactive no-code data app suite for Microsoft Power BI. The product is developed by Lumel Technologies Inc, who are #1 Power BI Visuals AppSource Partner serving over 3,000+ customers worldwide with their xViz, Inforiver, and ValQ offerings.
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About Inforiver!

Inforiver is the fastest way to do everything in Power BI. It enables citizen developer productivity and unleashes true self-service with our intuitive and interactive no-code data app suite for Microsoft Power BI. The product is developed by Lumel Technologies Inc, who are #1 Power BI Visuals AppSource Partner serving over 3,000+ customers worldwide with their xViz, Inforiver, and ValQ offerings.

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