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Scenario for Using SVP

This topic gives one example of how SVP may be used. You may use SVP in a number of different ways, depending on your business model.

An SVP administrator for a large beverage manufacturer knows that her company is entering its annual planning period as of September. To generate SVP, she must perform several tasks. First, she must identify the source for planning sales volume data. This source may be shipment or consumption data from previous periods. After it is identified, this data needs to be reviewed to determine its relevancy for future SVP periods. As a result of the review, the SVP administrator chooses to skip certain account-product periods because there are discontinued products or inactive accounts that need to be considered.

Next, she uses the data to establish a baseline for all products and accounts over the specified planning periods. She has the option of modifying the data directly or using it as a basis for populating the baseline planning field. In this case, the SVP administrator chooses to copy the values into the baseline planning field for the same period and, while doing so, she uses the percentage change algorithm to increase the number by 5%. Now that the baseline planning column is populated, the SVP administrator alerts the senior managers and region managers that they can manually adjust the figures.

With this data now available, the senior managers modify it and allocate these changes down the account-category-product hierarchy. The SVP administrator then alerts the subordinate managers and key account managers that the data is available.

The key account managers then modify the baseline data based on their knowledge of their local accounts and markets. They use this information to plan trade promotions for these accounts, and they enter the incremental volume that they anticipate as a result of these promotions. Finally, at the end of the planning cycle, the SVP administrator reaggregates the baseline and incremental data and exports it to a demand planning tool to be used in the consensus forecasting.

Siebel Consumer Goods Guide