Model type planning considerations in Planning Business Modeler

When creating models in your Microsoft Office PerformancePoint Server 2007 application, you can choose from five model types, the Global Assumption Model, Exchange Rate Model, Financial model with shares calculations, Financial model without shares calculations, and the Generic Model.

The primary consideration when determining which model types to include in your application is how you will use the models and their data, such as whether you are creating a business model or an assumptions model. You may also find that different end-users will want differing levels of data, so it is important to include a broad spectrum of users in initial planning.

For example, the data that you want to see in scorecards or reports may need to be modeled differently than data used solely for financial reporting. A model used primarily for financial reporting may not include salesperson data or be at the correct level for salesperson level reporting; however, this data would be vital for sales scorecards. In this scenario, you may wish to design you models to provide detailed sales data that can be summarized for financial reporting.

Additionally, you can create one model of a given model type or multiple models of the same type for different purposes, so this may be alternate solution to the above scenario.

Available model types

The Generic Model is the most basic model type and can be used for any other model type needed and contains no predefined rules for accounting logic.

The Global Assumption Model can be used for baseline data that will apply throughout a business, such as headcount or price list information or for business drivers in a financial model, such as revenue and expenditure assumptions.

The Exchange Rate Model is a special-purpose assumption model that tracks foreign exchange values by period and exchange type for all currencies in your system.

One important consideration for Exchange Rate Models is whether you will want to track exchange rates by multiple time granularities, such as daily, monthly, and annually. As the Exchange Rate Model does not provide aggregation, you will need a separate Exchange Rate Model for each time granularity in your application that uses exchange rate assumptions.

To fully use assumption model functionality, all assumption models, whether an Exchange Rate Model or a Global Assumption Model, should be linked to other model types. Thus, it is useful when you plan your assumption models to identify the other models in your system that you will link with your assumption models. For example, creating an Exchange Rate Model and linking it with another financial model, such as a corporate costs model, makes it possible to both efficiently update your assumptions and easily access and consume your assumption data.

The model type, Financial model without shares calculations, includes built-in logic to perform consolidations, but does not include shares calculations. If you have one entity, or multiple entities that are analyzed individually, use this model type. For example, the Financial model without shares calculations model type could be used to create a corporate costs model or a departmental model, such as a model specifically for use by Human Resources.

Another model type, Financial model with shares calculations, includes built-in logic to perform consolidations that include shares calculations and also calculate intercompany eliminations. For example, if you have multiple entities and you will provide consolidated reporting at the corporate level or if you have multiple entities that are not 100% owned, use the Financial model with shares calculations. This model type could also be used to create a strategic planning model.

When cumulative roll-ups of your periodic data are needed, such as year-to-date values, use the TimeDataView dimension. This dimension is generated by PerformancePoint Planning Business Modeler in financial models, including the financial model with and without shares model types, and provides periodic and cumulative views of data.

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