How to Validate Your Bottom Up Financial Model

Introduction

A bottom up financial model is a type of financial model that focuses on bottom line revenue by forecasting each product line separately and adding them up together. The bottom up financial model provides a more comprehensive and holistic approach to forecasting future sales and revenue. This top down financial model makes use of data and inputs to estimate these future sales numbers precisely.

Validating your bottom up financial model is essential, as it helps you identify potential errors in the modeling process and enhance the accuracy of the resulting forecasts. By validating your financial model, you are able to make sure it is able to accurately predict future revenue levels and provide reliable insights into the financial performance of a business.

Benefits of Validating Your Model

• Accurate and reliable forecasts: Validation can help ensure more precise financial modelling and thus more precise forecasts.
• Identify potential errors: Validating your financial model can help identify potential errors in the modelling process and make sure forecasting results are accurate.
• Improved accuracy of forecasts: By validating your bottom up financial model, you can make sure that the forecasts are more accurate.
• Time saver: Validation can also save you time, as you can quickly identify problems and solve them faster.

Key Takeaways

• Validation improves accuracy and reliability of forecasts
• Validation helps identify potential errors in the modelling process
• Validation improves the accuracy of revenue forecasts
• Validation is a time saver

Assessing Assumptions

When validating a bottom up financial model, it is important to assess all the assumptions that are incorporated in the model. These assumptions may include, among others, future changes in market conditions, projected growth in sales of a particular product, or profitability levels.

Identifying What Assumptions Your Model Contains

The first step in assessing these assumptions is to review the model and identify the assumptions that are included in it. For example, the model may contain assumptions about anticipated price changes for the product, projected customer growth, forecasted production costs, or given discount rates. It is important to make sure that all assumptions that are applicable to the model are identified.

Thinking Through Why You Have Included Each Assumption

Taking Into Account Potential Changes to the Assumptions

Finally, it is important to consider how these assumptions may change over time. For example, price changes may be impacted by changes in demand, while production costs may be affected by external factors. It is important to take potential changes into account when assessing the model and evaluating its accuracy.

Quality Checking Inputs

When validating a bottom up financial model, the first step is to check the inputs and data that have been used in the model. Analyzing the accuracy of inputs and data enables you to identify any potential issues and take the appropriate action to rectify them.

Checking to Ensure the Inputs and Data are Formatted Correctly

Formatting input data correctly is a crucial step of validating a bottom up financial model. If the data is not formatted correctly, then the model will produce inaccurate results. Therefore, it is important to make sure that the formats of all input data are consistent. This can be done by checking the cell formatting, values, and formulas.

Checking for Duplicate Entries

When validating a bottom up financial model, it is important to check for any duplicated entries. Duplicated entries can lead to inaccurate results. Therefore, it is important to make sure that all entries are unique. This can be done by sorting the data and then running a check for any duplicates.

Sourcing Data from Reliable Sources

The accuracy of a bottom up financial model is only as good as the data that is used in it. Therefore, it is important to make sure that all data is sourced from reliable sources. This can include government websites, financial statements, and industry publications. Additionally, the sources should be verified to ensure that the data is up to date and accurate.

Reconciling Outputs

Reconciling your model's outputs is an important step in validating the bottom up financial model and ensuring accuracy. There are a few different steps we can take to ensure the model has been built correctly and that specific output assumptions can be justified.

Verifying the data

First, it is important to verify the data that has been produced from the model. Every piece of data in the model must have an original source of origin. We can look back at these sources for reference and compare them to the data outputs of the model. To do this properly, create a spreadsheet and fill it with data from both sources. Side by side, compare the two sets of data to ensure that the figures do not significantly differ.

Cross Checking Calculations and Amounts

Cross checking calculations and amounts should be a regular step in validating any financial model. If a certain output figure is not inline with expectations, the modeler should be able to quickly cross reference the associated formulas and calculations leading to the number in order to identify where the issue is stemming from. It is recommended to document any formulas and calculations used in a model in writing as an added safety check, allowing for easier and more transferable auditing of calculations.

Agreeing Outputs with Third Party Facts

Finally, outputs from the model should be validated and agreed upon with third party facts. It is not enough to simply review the data produced from the model or double check calculations. Certain assumptions and figures used in the model should instead be backed up with reliable industry data. Examples of ideal sources for third party facts include public companies, market researchers, and industry associations.

• Comparing the data from the model and its original source
• Cross referencing calculations and amounts used in the model
• Agreeing on outputs with reliable third party facts

Determining Limitations

Developing an accurate bottom-up financial model requires consideration of the various factors that could affect projections and results. Evaluating the underlying assumptions in the model, understanding how different decisional or market dynamics may impact the results, and properly addressing existing limitations can all help increase the model’s accuracy.

Examining how assumptions could potentially change

Assumptions are an essential part of a model, as they provide the basis for testing different hypotheses and tailoring each model according to different situations. The model should be build on reasonable assumptions that can take into account a wide range of potential outcomes. For example, historical data and trends should be taken into consideration when producing projections. The results should then be tested and validated, since oftentimes relying on previous data may lead to invalid predictions.

Understanding how different decisional or market dynamics could affect the projections

Decisional dynamics are an important factor in financial modeling. Understanding the characteristics of the decision making process in the field of study can help you build a better model. Knowing how different decisions could impact the model and its outputs is essential. Additionally, external factors such as market dynamics should be accounted for when evaluating the possible impacts on the results.

It is important to keep in mind that the model’s outcomes may be affected by various factors, and that it may be necessary to adjust the assumptions in order to produce more accurate results. Taking the time to thoroughly assess all relevant factors can help you develop a more reliable and robust model.

Establishing Credibility

When it comes to validating your bottom up financial model, one of the key steps is to establish credibility for the model amongst other stakeholders. After taking the time to develop your model and make it user-friendly, it's time to turn your attention to showing other stakeholders why it is a reliable and defensible source of information. In order to do this, there are two main areas you can focus on:

A. Sharing your Model with Other Stakeholders

The first step to establishing credibility for your model is to share it with other stakeholders. If your model is more than a static report, you will likely want to walk stakeholders through the model step by step, highlighting how the inputs of the model get you to the outputs. This can help people become more confident in the model and understand the logic and assumptions behind the outputs.

B. Explaining the Assumptions and Logic Behind the Model to the Stakeholders

In addition to sharing your model, it is important to also explain the assumptions and logic behind it. This includes going through each of the assumptions that you make in terms of inputs and variables, and showing how those assumptions inform the outputs. Additionally, it can be beneficial to give a high level overview of the models key functions, such as decision tree logic or Monte Carlo simulations. Making sure that stakeholders understand the assumptions and logic behind the model can help increase the perceived accuracy and trustworthiness of the model.

Conclusion

Creating a successful financial model requires more than a simple set of calculations-- it requires validation. Establishing a bottom up financial model is a complex process that needs to take into account not only the current financial figures and forecasts, but also the quality of the data used to reach the desired outputs. By making sure the accuracy and reliability of the data used are adequate, the confidence in the model's output is increased.

The validation process should begin before the model is even completed. When utilizing a bottom up financial model, data validation should start with each individual input and be tested throughout the entire model. This strategy allows users to identify discrepancies and errors quickly and effectively before they propagate throughout the entire model.

Validation should also include the processes used to develop the model. Testing for accuracy and consistency should be ongoing, starting with the smallest and most basic assumptions and check the and rising to the highest levels of assumptions made. This process should be documented and repeated over the course of the life of the model.

Finally, validation of a bottom up financial model should extend beyond the numbers themselves. Questions on the assumptions used in the model should be asked as well as ensuring the outputs are relevant to the purpose of model.

Summary of Points Made

• Validation of a bottom up financial model should start with individual input and be tested throughout the entire model.
• Testing for accuracy and consistency should be ongoing, starting with the smallest and most basic assumptions.
• Validation should extend beyond the numbers themselves to include questions on the assumptions used in the model.

Reiteration of the Benefits of Validating Your Bottom Up Financial Model

Ensuring that a bottom up financial model is validated is a critical step in realizing desired outputs. By following the processes outlined above, users can maintain accurate and reliable data and assumptions, resulting in increased confidence in the results of the model. Validation is paramount in ensuring the financial model will yield the most accurate and useful outcomes for the user.