A financial model is often called a “model of models.” This is because there are several parameters which go through a series of complex calculations themselves. Revenue is a perfect example of one such parameter. For the financial model as a whole, the revenue number is just one of the many inputs required for the calculations to be run. However, there are a lot of calculations that go into arriving at the revenue number itself.

This article provides a detailed analysis of the complexities involved in revenue modeling.

Why is Revenue Modelling Important?

From a financial modeler’s point of view, the revenue number may be the most important input in the financial model. This is because revenues form the top line of the financial model. Expenses are subtracted from revenues to arrive at profits. Profits are then adjusted to arrive at cash flows. All investment and financing decisions are taken based on this cash flow. Hence, if a firm has made a big error while forecasting revenues, they will face a trickle-down effect of their mistake. All the subsequent calculations will be incorrect, and the company may end up making some really bad decisions since they did not have the correct information at hand.

Why is Revenue Modelling Challenging?

Revenue modeling is important. However, it is also extremely challenging. This is because there are multiple ways of arriving at the revenue number. Some examples have been listed below:

• No of Units Sold* Selling price = Revenues
• Total Market Size * Market Share = Revenues
• Previous Years Revenue * Growth Factor = Revenues
• Revenues Per Store * No of Stores = Revenue

Each of the above formulae provides a different way of looking at the same number. For instance, the first method is very production oriented. At the same time, the second way of arriving at revenue focuses on competition. This method is external oriented and brings the management’s attention to the change in market share.

The third method derives the number based on the previous year’s actuals. This method is used if the past forecasts of the company have proven to be accurate and only minor adjustments need to be made to arrive at the new number. Lastly, the fourth formula expresses the revenues as a factor of the number of stores. This viewpoint encourages the company to increase the number of stores in operation if the revenue has to be maximized.

Therefore, a financial modeler has to decide an approach which is most suitable for their specific case. This is what makes revenue modeling extremely challenging.

Different Methods of Creating a Revenue Model

The above-mentioned methods are amongst the most basic techniques which can be used for revenue modeling. In real life, companies use much more complex parameters to be able to accurately model revenue. Some examples have been provided below:

• Focusing on opening new stores in order to increase revenues would be an incorrect strategy if the size of the store is not considered. Therefore, many financial modelers distinguish between small and large stores while creating financial models. Therefore, instead of using a store as a single unit, modelers tend to use units such as square footage which provide a better estimate

• However, opening a small store in a prime location could still generate more sales than opening a big store in a remote location. It is for this reason that many companies forecast their sales using revenue per square foot from comparable stores

• Also, many companies ensure that new store calculations are listed separately. This ensures that stakeholders are made aware of whether the sales were generated by already established stores or by newer stores. This provides information about how much revenue can be expected from a new store immediately after it becomes operational.

Key Considerations to be Taken into Account While Revenue Modelling

There are some factors which negatively affect the revenue model. They need to be managed to ensure that the model and the results that it gives are accurate.

1. Influenced by Stakeholders: Many times, revenue numbers are inflated in order to massage the egos of the higher management. The higher management may put in a lot of pressure, and the ground level resources may give unreasonable forecasts under this pressure. This needs to be avoided. Companies must ensure that the numbers which get reported are accurate and realistic; otherwise, the results of the model become inaccurate. It should be understood that the process of giving sales targets is not the same as collecting data for the financial model.

2. Longer Duration: Companies should refrain from making revenue predictions about the distant future. Empirical records show that revenue is a highly sensitive number, and it varies widely over the years because of factors which cannot be predicted too far off into the future. Hence, companies should ensure that detailed revenue modeling is only done for the short term. For long term numbers, the data can simply be extrapolated. This would provide a rough estimate without actually putting in too much effort.

3. Impact on the Stock Price: Companies should refrain from giving overly optimistic revenue guidance. This should be the case, especially when their stocks are traded on the exchange. This is because when companies miss their revenue guidance, their stocks experience a loss in value. Revenue guidance should be seen as a company’s word, and attempts should be made to fulfill the promise without resorting to devious methods.