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Best Practices for Creating Easy-to-Use Excel Models

Excel models are an invaluable tool for businesses and professionals across various industries. However, the true value of an Excel model lies in its usability and ease of navigation. In this article, we will explore the best practices for creating easy-to-use Excel models. By following these guidelines, you can design models that are intuitive, user-friendly, and enhance decision-making processes.

Structuring and Organizing the Model

When building an Excel model, it is crucial to establish a clear structure and organization. I would always start by determining the objective and scope of the model and design a logical layout that makes it easy to navigate. Before I even open Excel, I’d take a piece of paper and sketch out the model structure. What are the main tabs, what data feeds what calculations, etc. Having a clear outline of the model I have to build makes it easier to plan out the relationship between different parts of the model and consider every functionality the model needs to have from the start.

Additionally, when you start building the model itself, consider using color-coding and formatting techniques to visually distinguish different sections and types of data. For example, all my models have the same color-coding for cells. I color all static numeric values in blue, all references to external files or other worksheets in green, and all formulas in black.

We recently launched our Magnimetrics Tools for Excel add-in, and the ability to apply bulk color formatting to cell ranges based on whether they are numeric values, external references, or formulas, was amongst the first features we developed. And it’s one of the features I use on a daily basis!

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This allows any external stakeholder to easily get up to speed with how the logic flows, where do calculations happen, and what data is being pulled from where. Doing so is also helpful for me, should I ever need to revisit the model in a few months. Having a clear idea of what cells do what by just taking a look at the overall worksheet helps me quickly remember what I did back when I was creating the model.

Input and Assumption Design

Inputs and assumptions are the foundation of any Excel model. Identify the key inputs and assumptions required for your model and design user-friendly input sections. Clearly label each input and provide instructions on the required format.

Before I start working in Excel, I always ask myself who would use the model I am building. If it’s meant for external stakeholders to play with the assumptions, I would always implement data validation and error checks to prevent incorrect data entry, ensuring the accuracy of the model. By providing clear instructions for input requirements, external users can easily input the necessary information, making the model much more straightforward and easier to work with.

Streamlining Calculations and Formulas

Calculations and formulas form the heart of an Excel model – it’s logic. To create an easy-to-use model, avoid using too complex or specialized formulas. I would also almost always skip named ranges. They make the formulas easier to read, but are way harder to track.

Sticking to simple functions makes your formulas more transparent and reduces the chances of errors during updates. I would try to structure calculations logically, breaking complex formulas into smaller, easily manageable steps. Consider using helper cells or functions to simplify intricate calculations and enhance your model readability. I would go as far as having the feeling that I am dumbing logic down too much. It seems too much, but every time I leave a more complex calculation in a model file, I always regret it when I have to track down what it does and what my thinking was when I have to revisit the model in a few months.

Enhancing Usability and Navigation

One of the most important aspects of a user-friendly model is for it to be intuitive to navigate. Make sure to create a well-organized structure with clearly labeled worksheets and sections. Whenever I am building a model that requires dynamic data selection, I usually implement features like dropdown menus to simplify this for the user. For example, I might have 3 scenarios for a model, in which case I would have a dropdown to select between the options. This allows users to easily explore various possibilities. Additionally, most of my models include an accompanying document with clear instructions and guidance on how the model works to help users understand how to interact with it effectively.

Visualizing Data and Results

For some reason, whenever we think about visualizing data, we mostly connect this concept with financial analysis and reporting. We rarely think about adding visualizations in financial models. However, this is one of the easiest ways to improve your model’s readability and usability.

When it comes to building a model, I like to think about model pieces in three main categories:

  1. Input worksheets: This is where the source data gets loaded (and potentially slightly modified).
  2. Calculation worksheets: This is where all the logic and modeling happen.
  3. Output worksheets: These are all kinds of summaries (e.g., revenues & margins, valuations, etc.). Here is also where I’d put charts and other visualizations to make the data more digestible and easier to understand.

The visual presentation of data and results significantly impacts a model’s usability. We can visualize trends and patterns by creating charts and graphs to support the decision-making process.

Error Handling and Validation

Another crucial aspect of modeling is having proper error handling. This is much more important when the model is aimed at external stakeholders. Most of the models I work on are for clients, so I would always implement error checks and validations to ensure accurate results.

The most common error handling techniques I use are quite simple – implementing IFERROR and IF statements is by far the easiest way to handle potential errors. Now, I have to be honest, I almost always rush into building out the logic and have to go into the model afterwards to wrap everything in IFERROR statements. That’s why one of the features we built into the Magnimetrics Tools for Excel add-in is the ability to wrap all selected cells into an IFERROR statement, allowing you to customize the value being returned if an error occurs.

Documentation and Version Control

I already touched on this above, but I want to reiterate the importance of proper documentation when it comes to Excel models. It is essential for maintaining and especially for sharing with external stakeholders. I would keep a word doc with the structure of the model as a flow chart (a cleaned-up version of what I scribbled on a piece of paper before getting started), all my assumptions, methodologies, and limitations of what the model can do, to provide transparency and clarity. This word doc should include clear instructions and documentation, making it easier for others to understand and use our models.

Lately, I’ve been also adding a Changelog worksheet within my files, where I would document significant changes (e.g., changes in calculation logic, adjustments to key assumptions, additional model pieces being added, etc.). This tab is where I would also track whenever I save a new version of the model. This allows me to maintain version control to track material changes and updates, ensuring accurate historical records.

Collaboration and User Feedback

This one is extremely important, especially if you are building models for clients. In such cases, I always make sure to schedule interviews with the future users of the model. I look at such projects as a collaboration with the client’s team and always seek feedback from them on each iteration of the model. They are the ones that will use it and hopefully benefit from it, so it makes sense to tailor it as much as possible to their needs and requirements. By engaging with the users to understand their needs and incorporating their suggestions for improvement, I can ensure they get the most value out of the model.

Conclusion

By following these best practices for creating easy-to-use Excel models, you can build powerful tools that facilitate informed decision-making. Structuring and organizing the model, designing user-friendly inputs, streamlining calculations, enhancing usability and navigation, visualizing data effectively, implementing error handling and validation, documenting the model, and collaborating with its users are key steps in creating models that are intuitive and efficient.

Building Excel models that are easy to use and read empowers your company and clients by supporting a better decision-making process.

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Dobromir Dikov

FCCA, FMVA

Hi! I am a finance professional with 10+ years of experience in audit, controlling, reporting, financial analysis and modeling. I am excited to delve deep into specifics of various industries, where I can identify the best solutions for clients I work with.

In my spare time, I am into skiing, hiking and running. I am also active on Instagram and YouTube, where I try different ways to express my creative side.

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