Ratios and forward assumptions.

Here we see both historical ratios and forward assumptions. The first two columns show historical ratios. That's Year -1 and Year 0. These are based on the figures reported by the company and are therefore referred to as actuals, shown with the letter A. The five columns on the right show us forecast assumptions. That's years 1, 2, 3, 4, and 5. And these are based on analyst forecasts, and they're therefore referred to as estimates, shown with a letter E. Looking at the historical actual data, I can see that revenue growth in the past has been 6.2% and 6.6%.

Looking at this data helps us to understand the business. It shows us how the business has been performing, and why the performance has been good or bad. This helps us to understand trends within the company to compare the company's performance with peers, and to compare the company's performance with the markets and economies that the company operates in. This analysis helps us to make predictions about where the business is going. For example, if we see a company is performing better than peers, this might mean that we expect the company to continue to perform better than peers in the future, or if the company has performed particularly badly during an economic downturn, which is expected to continue next year, this helps us better predict how the company will perform next year. If our analysis reveals unusual trends or variations in the ratios. For example, revenue growth in the last year jumps to 20% from 6.2%, and that's because the company has made an acquisition in the last year, it's really helpful to explain this variance in a footnote or a comment, so that someone else using your model can understand the reason for the variance, and knows that isn't just an error. These forward assumptions will drive your forecast figures. It's very common for models to provide explicit forecasts for somewhere between five and 10 years into the future. The forecast usually need to be far out enough for the effects of any business and economic developments to stabilize. So the number of years of forecast is very dependent on both the company and the industry.