What-if parameters for running scenarios and performing scenario-type analysis on your data. What-if parameters let you look at previous data and examine possible outcomes if a different scenario had happened, which makes them powerful additions to your Power BI semantic models and reports. Furthermore, you can use what-if factors to project or foretell potential future events.
To create a what-if parameter, please follow these steps:
Please follow the below steps to while entering the parameters in numeric Range
- On the What-if parameter window, configure the new parameter.
- For this example, change the parameter name to Sales Forecast Percentage.
- Select a fixed decimal number as the data type list because you are using currency in your forecast.
- Set the minimum value to 1, the maximum value to 1.50, and the increment value to 0.05, which is how much the parameter will adjust when it is interacted with in a report.
- Set the default value to 1.00.
- Leave the Add slicer to this page check box selected so that Power BI will automatically add a slicer with your what-if parameter to the current report page.
- Select OK.
The current report page will display the updated slicer visual. You can adjust the slider so that the numbers rise in accordance with the settings you have chosen. In the Fields pane, you should also notice a new field for the Sales Forecast Percentage table. When you expand that field, the what-if parameter ought to be chosen.
The parameter and the measure that you produced while creating a what-if parameter will now be a part of your model and can be utilized on additional report pages as well as throughout the report. You can also remove the slicer from the report page because it is a component of the model, along with the parameter and measure. You can change the visual type to a slicer and drag the what-if parameter from the Fields list onto the canvas to get it back.
Using a what-if parameter in calcuation:
Once you’ve generated the what-if parameter, you’ll need to construct a new measure whose value is adjustable using the slider if you wish to use it. You can design intricate and distinctive measurements that enable users of your report to see the what-if parameter’s variable. To maintain simplicity in this example, however, the anticipated percentage is applied to the overall sales amount as the new measure.
The Month Name field will be on the axis of the clustered column chart, and the measures for gross sales last year and sales forecast will be the values.
The bars are comparable at first, but as you adjust the slider, you’ll see that the sales prediction percentage amount is reflected in the Gross Sales prediction column.
You can improve the visualization by including a continuous line that shows you exactly how the company is doing in comparison to a given goal or threshold. You will add a constant line in this example, with the threshold value being USD 2 million. Next, you’ll utilize the slider to determine how much gross sales must rise each month in order to cross that level. To cross the USD 0.5 million mark in the following image, the gross sales must rise by 1.25 percent.
Conclusion:
To allow users throughout your organization to access more information relevant to their teams and work environments and to ask more questions, you improved the reports and dashboard that you had previously established. You explored your data with Power BI, producing a statistical summary to highlight trends and important takeaways as well as outliers that might need to be addressed right away. You saw how your data changed over time by performing a time series analysis, which allowed you to forecast behavior and make observations.
You were able to extract new insights from the data of your firm and examine it more closely to find patterns, trends, and outliers that you were unaware of thanks to the sophisticated analytical tools you used. Your corporation will be able to make more reliable business decisions, strategies, and projections thanks to the findings of your in-depth investigation.
Thanks for reading my post. I hope it helps you work on what-if parameter analysis!!