Value Driver Tree in SAP Analytics Cloud Planning.

KPI Simulation using Value Driver Key :Using value drive key planner/ Business Analyst can track the impact /changes in business process and other KPI with respect to another KPI change. Even a Sales KPI impact can be measured if a Finance KPI change or vice versa.

The value driver tree is used to simulate KPI. If the business want to change a small KPI with a percentage or number how it will impact in a large NET KPI that impact revenue that we can simulate before doing the changes. This reduce the risk of planning, budgeting and forecasting error.

Let’s discuss about a scenario for which we will create value driver tree –

There are a summary level KPI that impact Revenue warning which is NET SALES which depend on different small small KPI from different department.

KIP Calculation Logic :

NET Sales :

NET SALES = GROSS SALES-DISCOUNT

Gross Sales  :

GROSS SALES = QUANTITY -  AVARAGE PRICE

Average PRICE : 

AVARAGE PRICE = TOTAL GROSS SALES /QUANTITY

DISCOUNT :

DISCOUNT = GROSS SALES * DISCOUNT RATIO.

Steps :

1.Before creating a Value driver tree or NET SALES we will create a blank Plan version version for 2024 and then simulate over the plan version.

2. Before it we simulate select the Simulation version( Plan Type) , we have created and published as public version . We have added add the calculation in the Model measure section.

3. We can automatically create the VDT( Value Driver Tree ) or create manually the nodes –

Lets do it Automatically. Business Analyst can easily used this features –

4. A Value Driver Tree  will be available for simulate to test the value –

A. Initial Blank Sales Simulation 24 version will have blank values as shows below –

B. Now if I change the value of Cross Quantity KPI and Quantity which we plan in the planning version. Then the Net Sales value will be simulate based on the gross sales and Quantity.

Net Sales will direct impact on revenue so business can take the decision  weather Discount, Quantity change will be beneficial or not and take the decisions.

Hope It will help you in your analytics planning area.