Abstract

Managers need to be comfortable with financial statement forecasting. Forecasts allow managers to plan properly by weighing consequences and preparing for outcomes. A less-recognized but equally important benefit is that the act of forecasting forces managers to make explicit the many links that exist between decisions, possibly drawing attention to constraints that otherwise might have been overlooked. This is particularly important since financial statements integrate the financial and operating decisions of a firm. This note focuses on forecasting in the context of decision-making. Aspects of forecasting explored include: revenue growth estimates, sources of error, assumptions, typical ratios, and the T-account approach. It also includes a detailed example of a typical financial forecast. The concepts are applied to the hypothetical firm Morgan Industries, a setting that has been integrated across all the Financial Analytics Toolkit series of technical notes.While this note focuses on financial statements, the forecasting techniques described herein are readily transferred to related contexts, such as building cash-flow forecasts and using ratios to evaluate financial performance. Excerpt UVA-F-1928 Dec. 4, 2019 Financial Analytics Toolkit: Financial Statement Forecasting Managers need to be comfortable with financial statement forecasting. Forecasts allow managers to plan properly by weighing consequences and preparing for outcomes. A less-recognized but equally important benefit is that the act of forecasting forces managers to make explicit the many links that exist between decisions, possibly drawing attention to constraints that otherwise might have been overlooked. This is particularly important since financial statements integrate the financial and operating decisions of a firm. While this note focuses on financial statements, the forecasting techniques described herein are readily transferred to related contexts, such as building cash-flow forecasts and using ratios to evaluate financial performance. Furthermore, while forecasts can be generated for many reasons, this note will focus on the use of forecasting in the context of decision-making. Thus the two most important criteria for forecasts are that they be unbiased (neither optimistic nor pessimistic) and consistent (rationally constructed from all the available information). The need to be unbiased follows directly from the role of financial statements in decision-making: biased forecasts lead to biased decisions. Consistency is the ultimate measure of forecast quality. Growth Estimates and Consistency . . .

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