Chapter 4 deals with the mechanics of forecasting and specifically the methods behind the development of an integrated set of financial forecasts that reflect the company's expected performance.
Firstly, a dashboard-like control panel is designed with the proper financial indicators that need to be monitored according to the specific problem the model is required to solve. For example, in order to deal with liquidity issues one needs to focus on working capital parameters. Secondly, the basic statistical methods used to forecast sales are examined. Almost all financial statement models are sales driven, in that they assume that many of the balance sheet and income statement items are directly or indirectly related to sales. So forecasting sales is one of the greatest challenges for the business modeller. Regression analysis (a statistical method that enables one to fit a straight line that on average represents the best possible graphical relationship between sales and time) is used in order to extrapolate future sales based on the past sales trend. Moreover regression analysis is used to look at the relationship between any 2 measures, say, sales and CAPital EXpenditures (CAPEX), sales and costs, and so on. These relationships can be the best possible proxies for many P&L and balance sheet figures when combined with sales, especially in the absence of any analytical working about these figures.