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madhumitabanerjee2019
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SAP Analytics Cloud is continuing to bask in the glory of being the disruptive cloud solution (https://bi-survey.com/product/sap-analytics-cloud) that allows us to do planning, predictive analytics and business intelligence in a simple and intuitive solution. It brings a simple, powerful and quick-value-delivery tool for analysing the data.

When it comes to analytics, Key Performance Indicators (KPI) play a very important role. It is a measurable value that demonstrates how effectively a company is achieving key business objectives. Organizations use KPIs to evaluate their success at reaching targets and to have the calculations on the fly, SAP Analytics Cloud has a feature to add measures in an existing or new model which uses dynamic input variables.

In this example we will create a new measure called ‘Projected Selling Price’ which will be used in the charts in story. It will have a dynamic user input for Profit % as the decidable factor in computing the measure.

We will create a variable to capture Profit Input which will act as a placeholder for the values that can be changed while analysing the data.

In the modelling screen, click on Data to add a new variable.



As the window pops up, click on the ‘+ ‘sign to add variables for the model.



We would enter a unique ID for the variable created, provide a description and will choose the domain which can be a fixed number or the value from one of the other dimensions in the model.



We can also define a default value for it.

Once the variable is created, we can use it in the formula to create a new measure at the model level namely Projected SP.



Projected SP is the estimated selling price that can be a crucial tool to help in managing a revenue stream and the product positioning. Also, we can compute selling price variance based on this.

We will open the advanced formula tool and compute the formula. The formula used in here is:

Projected SP = [Total Cost + {(Profit Input /100) *Total Cost}]



The variable that we created before will be now available in the list of objects to be used in our formula. We can validate it by clicking on the format tab.

We can see the details of the new measure added to the model in the modelling screen under Accounts.



In the story, we can test the variable from the toolbar (Edit Prompts) or the chart details. In the pop-up window ‘Set chart variables’, we can see the variable and the option to change the default value to apply on the charts.



As we change the value of the variable, the chart will get the dynamic input and will show the calculated value.



To reset all prompts applied for a story in view mode, we can click on the ‘Reset’ button in the ‘File’ menu.

Although, as these are created on a model level, for each of the charts in the stories, it takes the default value for the created variables. This can be handled by cloning the model and doing the necessary changes as per the requirement.

 

Thanks for reading. Hope it helps!

 
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