Logic of the Model

The model is designed to be used in a number of ways:

1. "generating a forecast" - as a simplified business planning model which will produce financial projections based on a limited framework and number of assumptions. It is Intended for possible use by smaller associations in need of a simple planning model.


2. "reconciling a forecast" - to replicate the financial projections produced by an association's own business planning model, via a standardised input format, to facilitate a) full analysis to a standardised format and b) flexing of the forecast. The standardisation enables the generation of the full range of the model's financial/graphical/capacity analysis.
   
   From the data input the model exactly replicates the association's own (unflexed) financial projections via a complex set of "reconciliation factors". The model can, furthermore, be used to flex key assumptions and, hence, the financial projections, independent of the association's own business planning model.
   
   The flexed forecasts will not be as "accurate" as those produced by the association's own model because the capacity model is built around a simplified, "one-size-fits-all" logic.


3. as a comparative analysis model which can accept standardised financial projections from housing associations' own business planning models, together with the set of simplified, standardised assumptions. It is intended to facilitate comparison of associations with quite diverse ranges of activities and planning models to a standard format eg for funding purposes by the Housing Corporation. Projections can also be flexed to a standard set of assumptions.


4. the National Housing Federation and Housing Corporation may also use the model to produce aggregate data and comparative sector statistics.
   
   To facilitate the various objectives and uses described above the model had to be sufficiently detailed to catch many of the key variables which drive associations' businesses, allowing for the varying mix of business activities across different associations. But the model had to be much simpler and less detailed in its structure than associations' own existing, detailed models to ensure its applicability to all associations while keeping the input data requirements to a manageable size.