When creating financial models, often overlooked errors can occur. I've reviewed over 3000 financial models and watched numerous tutorials on creating them. Here's a list of five overlooked errors frequently made in financial modeling.

1. Parameters Beyond Control 

Using parameters in the model that the team doesn't control. A common example is forecasting competition. Such parameters are often linked to the external environment, aiming to incorporate environmental changes for business development. While understanding how the market will change is good, basing the model's achievements on these factors is risky, as the team's influence over these external parameters is minimal. I elaborated more on the concept of responsibility in my article "Only Be Responsible for What You Can Influence." 

2. Unsubstantiated Growth Parameters 

One of the most common errors is using unsubstantiated growth parameters in the model. Growth rates, such as growing by 10.00% per month or a customer churn rate of 5.00%, are frequently chosen arbitrarily without justification. The main issue with this approach is that any model is a set of probabilities converging into one final probability of project success. Any error in the model parameters leads to an increased overall error in calculating the project's success probability. It's unclear why one would knowingly introduce errors by initially selecting unjustified parameters in the model. 

3. Team and Model Parameters 

This error is a consequence of the previous ones. Building a model results in a set of business parameters that the team must adhere to. However, we overlook whether the existing team is sufficient to achieve or maintain the business parameters obtained. For instance, if our model predicts around 100,000 clients per month, but there's no team in place to handle customer support, account management, etc., we fail to consider that some clients may encounter issues or lose documents, leading to potential problems for the business. Moreover, achieving many business parameters requires not just any staff, but the best talent from the market, which comes at a cost. This too should be reflected in the model, as the expenses for such a team capable of executing the model may exceed the business's revenues. 

4. Fixed Time-bound Business Parameters

This error is also related to the first two mistakes, where fixed-time parameters in the business are used. For example, assuming a 10.00% monthly increase in the number of new clients that remains unchanged over time. But is this really the case? Are you ready to ensure such growth every month from the project's inception? What if you can't sustain it? 

5. Incorrect Use of Churn

I've seen models using a fixed churn parameter incorrectly. However, this parameter relates to cohort properties, referring to specific groups of clients, such as those who joined the product in January. Therefore, each cohort will have its churn rate. Moreover, the churn rate within a cohort may change every month of the cohort's lifespan. Additionally, for some business models, predicting churn is quite challenging, such as in commerce, where clients may purchase items sporadically and return to make purchases after months of inactivity. Churn rate is ideally suited for subscription models, where subscription cancellation is a distinct event. 

Minor Errors 

I've covered five subtle errors, but there are many others made in model creation. While they may not be as critical as those mentioned earlier, they're still worth noting.

Constants in Formulas

Using constants in formulas, where you set a parameter value, such as the cost of workplace equipment, and then use this number in cost calculation formulas without referencing the cell where you set this cost value, is not ideal. Eventually, if you want to change the expense amount, you'll have to correct this parameter in all formulas. 

Color Formatting

Though not a direct error, arbitrary cell formatting can cause confusion and waste time when dealing with a large number of models. There are three types of cells: input, calculation, and input containing formulas. However, model creators often use arbitrary configurations of colors and fonts to highlight cells. For example, input data cells may have a yellow background, or sometimes just an italic font is used. I recommend using the FAST standard for financial model formatting. Input data cells have a gray background, and input values are formatted with blue font color. If an input cell contains formulas (sometimes necessary in complex projects), green font color is used. Calculation results have black font color on a white cell background. 

These suggestions are recommendations, as there's no single formatting standard. However, if you work with a large number of models and expect others, such as investors, to work with your models, it's advisable to create models that are easy to understand for the reader.