By Rachel Burger   September 24, 2024

5 Steps to Effective Financial Modeling in Corporate Finance: A Definitive Guide For 2024

Financial modeling is an invaluable technique used by corporate finance professionals to construct a mathematical representation of their business, assessing the impact of various decisions on future financial outcomes. Different financial models serve distinct purposes within an organization, each with specific applications. While Microsoft Excel® is commonly used for basic financial modeling due to its flexibility and ease of use, more sophisticated requirements often necessitate specialized corporate planning and financial forecasting software solutions. Continue reading to explore the fundamentals and applications of financial modeling in corporate finance.

  • What Is Financial Modeling?
  • Why Is Financial Modeling Important?
  • What Is Corporate Financial Modeling?
  • 6 Financial Modeling Examples and Types
  • 5 Steps to Effective Financial Modeling: The Basics
  • Common Mistakes in Financial Modeling and Tips
  • Financial Modeling in Excel: Why It’s Not Selecting the Right Tool for the Job
  • Financial Modeling in Action: OneStream Success Story
  • Say Goodbye to Excel and Hello to OneStream For Your Financial Modeling
  • FAQs About Financial Modeling

What Is Financial Modeling?

Financial modeling is a common tool used by individuals and corporations to create an abstract model of a real-world financial situation. This normally involves the gathering and analysis of historical data, which is then used to create a forward-looking projection for future time periods. Individuals may create a financial model of their monthly or annual income and expenses to help manage their finances. For the purposes of this discussion, we’ll focus on corporate financial modeling.

Why Is Financial Modeling Important?

Financial modeling is important because it provides a detailed, quantitative analysis of a company's financial performance and future projections, enabling informed decision-making. It allows businesses to forecast the financial impact of various scenarios, such as launching new products, entering new markets, or undergoing mergers and acquisitions. This helps in strategic planning, budgeting, and performance monitoring, ensuring that decisions are backed by solid data.

Moreover, financial modeling is crucial for securing funding from investors and stakeholders. It offers a clear picture of a company's financial health and growth potential, making it easier to attract investment. By evaluating potential risks and returns, financial modeling also aids in minimizing financial uncertainties and enhancing business stability. Overall, it is an essential tool for achieving long-term financial goals and maintaining competitive advantage.

What Is Corporate Financial Modeling?

Corporate financial modeling is performed by financial analysts in a corporate finance group within an enterprise, or by the line of business analysts supporting a specific functional department such as Sales, Marketing, Customer Service, or other functions. Use cases for corporate financial modeling include strategic planning, long-range financial planning, financial budgeting, mergers and acquisitions (M&A) or divestiture analysis, capital planning, project planning, or evaluating the impact of critical business decisions. This can include new product development and launch, geographic expansion, pricing of products and services, hiring and staffing, capital investment, and other business decisions.

Of course, in the financial services industry, investment analysts perform financial modeling as part of their evaluation of portfolio companies or potential investment targets.

6 Financial Modeling Examples and Types

There are a wide variety of financial models used in corporate finance, so here we’ll cover the most commonly used different types of financial models. These include the following examples of financial models:

  1. Three Statement Modeling – This is the most common approach for corporate financial modeling, especially in long-range financial planning. It includes the creation and linking of the 3 primary financial statements: Income Statement, Balance Sheet, and Cash Flows.
  2. Discounted Cash Flow (DCF) – This technique is also very common and builds on the three-statement model to value a company or a potential investment based on the Net Present Value (NPV) of the future cash flows. The DCF model takes the cash flows from the three-statement model, makes some adjustments where necessary, and then uses the NPV function to discount the future cash flows back to the present using the organization’s Weighted Average Cost of Capital (WACC).
  3. Mergers & Acquisitions (M&A) – This is a more advanced modeling technique used to evaluate the pro forma impact of a potential merger, acquisition, or divestiture on the financials of an enterprise. The level of complexity here can vary widely based on the size of the enterprise, and it may require the use of complex accounting logic, especially when it comes to consolidating results from multiple subsidiaries and analyzing the impact on earnings per share (EPS). This technique is most often used in corporate development work, or in investment banking
  4. Annual Budgeting – This technique is widely used by corporate financial planning & analysis (FP&A) professionals to create the budget or annual operating plan (AOP) for the next fiscal year. Budget models are typically based on monthly or quarterly figures and focus heavily on modeling revenue and expenses at a departmental level, then rolling up to the corporate income statement.
  5. Forecasting – This technique is also used by corporate FP&A professionals and line of business analysts (e.g., sales forecasting) to update the annual budget model on a periodic basis. This may include combining first-quarter actuals with the budget for the next three quarters to forecast the annual financial results, or to ask managers to submit new projections for future periods based on actual results. Forecasting can also be automated through the use of predictive analytics tools that use statistical forecasting or machine learning (ML) models to predict future results based on the analysis of historic data.
  6. Operational Modeling – This category of financial models can vary widely based on the type of business decision being considered. As mentioned earlier, corporate or line of business analysts typically create financial models to analyze the impact of new market expansion, new product launch, hiring and staffing, capital investments, pricing options, and other scenarios. This type of modeling usually starts with a set of historic or baseline data, followed by the creation of alternative scenarios that layer in or model the impact of the decision on the financial results.

5 Steps to Effective Financial Modeling: The Basics

Financial modeling in a corporate setting is a critical process whereby the results of the process will be used to support decisions that can have a major impact on future financial results. Therefore, great care should be taken to ensure the inputs and outputs of the financial modeling process are as accurate as possible.

Here are five best practices that organizations should consider when performing corporate financial modeling:

  1. Ensure the Accuracy of Historic Data – Remember the adage “garbage in – garbage out?” Having accurate and up-to-date historical financial data provides a critical foundation for corporate financial modeling.
  2. Identify Key Drivers – Based on an analysis of historic financial and operational data, key business drivers can be identified and used as levers in modeling future revenue and expenses. Examples include orders, shipments, average price, new customers, customer retention rates, headcount, events, and others.
  3. Create Multiple Scenarios – Once a baseline financial model is built, alternative scenarios should be created and analyzed based on the flexing of key drivers. The traditional approach is to create a base case, high case, and low case scenarios – but many organizations generate a wide range of scenarios that are used to guide critical decisions.
  4. Leverage Charts and Graphs – While some Finance executives prefer to review and analyze grids of numbers, many find it easier to spot trends and key financial signals through data visualization. So creating charts and graphs to present and analyze financial models is a great way to help users quickly gain insights that can be used to support critical decisions.
  5. Perform Stress Testing – When the financial model is done, the work is not over. The next step is to start stress-testing extreme scenarios to see if the model behaves as expected and yields realistic results.

Common Mistakes in Financial Modeling and Tips

Experienced finance professionals can fall into common pitfalls that compromise the accuracy and reliability of their models. Understanding and avoiding these mistakes is essential to creating effective and actionable financial models. Below, we highlight some of the most frequent errors in financial modeling and offer tips on how to prevent them.

  • Overcomplicating the Model - Creating overly complex models can lead to confusion and errors. Simplicity and clarity should be prioritized to ensure the model is understandable and usable.
  • Lack of Consistency - Inconsistent formatting, labeling, and structuring can cause misunderstandings and mistakes. Maintaining a standardized approach is crucial for accuracy and ease of use.
  • Ignoring Historical Data - Failing to incorporate or correctly interpret historical data can result in inaccurate forecasts. Historical trends provide valuable insights for future projections.
  • Inaccurate Assumptions - Making unrealistic or unsupported assumptions can significantly skew results. Assumptions should be based on reliable data and sound logic.
  • Poor Documentation - Not documenting the logic, sources, and assumptions behind the model can lead to confusion and difficulties in future updates. Clear documentation is essential for transparency and usability.
  • Inadequate Error Checking - Neglecting to implement robust error-checking mechanisms, such as validation checks and audits, can result in undetected mistakes. Regular reviews and audits help ensure the model's accuracy.
  • Ignoring External Factors - Overlooking external economic, industry, or market factors can lead to inaccurate predictions. It’s important to consider broader influences that may impact financial performance.
  • Overlooking Sensitivity Analysis - Not performing sensitivity analysis to understand how changes in key assumptions impact the model can result in a lack of preparedness for different scenarios. Sensitivity analysis helps identify critical variables and potential risks.

Financial Modeling in Excel: Why It’s Not the Right Tool for the Job

If you Google the term “financial modeling” you’ll get a number of results that highlight how Microsoft Excel® can be used to support financial modeling. And while Excel is the “go-to” tool for financial professionals, it’s more suited to personal productivity tasks and less so to supporting enterprise planning requirements. Why? Because Excel is error-prone, has no concept of workflow, lacks controls and governance, and has very limited audit trails. It also wasn’t designed to manage large volumes of data and is two-dimensional in nature.

In corporate financial modeling, large volumes of historic data may need to be integrated, validated, and structured across multiple dimensions to fully support the requirement at hand. Many Finance professionals have tried to handle this in Excel, but over time they find these models and multi-tabbed workbooks become difficult to maintain, and don’t perform well. The alternative many organizations are turning to are purpose-built corporate planning and financial forecasting software applications, such as those that are found in modern corporate performance management (CPM) software platforms.

Financial Modeling in Action: OneStream Success Story

One example of an organization that outgrew the capabilities of Excel for modeling and planning and migrated to a purpose-built corporate planning application is Fibrogen. FibroGen recently transformed from a drug development company to a global multi-channel commercial business. Their transition success depended on rapidly building out sales, channel development, and marketing as well as aligning the business and operational goals of their scientists, business leaders, and the Finance team.

Realizing these goals required a more sophisticated corporate performance management (CPM) solution than their Excel®-based planning models and a 20-year-old legacy budgeting system that was fully matured and accepted within the organization. Fibrogen found that OneStream’s unified and extensible CPM software platform answered the company’s vision to gracefully accommodate their requirements to enable activity-based planning across two unique entities.

FibroGen’s China entity required a top-down model for planning and financial modeling while the United States model depended on non-finance users who are VPs and Executive Directors of their departments to provide the input that is needed for program-level and consolidated plans.

Said Alex Lee, Senior Director, Corporate FP&A, “With impending growth and transition, we sought a solution that can support a program-driven planning process and complex calculations and modeling with the ability to expand to include consolidation, reporting, accounting close automation, SEC reporting, and tax provisioning. We had a very specific vision in mind. It has been 10 months since go-live, and I’m still profoundly touched by the magic that is OneStream.”

Discover how Fibrogen transformed their financial processes by downloading our case study.

Say Goodbye to Excel and Hello to OneStream For Your Financial Modeling

If your organization is ready to move beyond Excel and embrace an intelligent finance platform, contact OneStream to simplify business complexity and accelerate your leadership. Learn how OneStream can help you prepare your organization for the future and request a demo.

Did you know OneStream also offers a weekly live demo webinar every Friday for 1 hour on a specific topic? View a replay of any of our recent webinars.

FAQs About Financial Modeling

What Is Financial Modeling Used For?

Financial modeling is used for forecasting a company's financial performance, evaluating investment opportunities, making strategic business decisions, and assessing the impact of various scenarios on future financial outcomes. It provides a structured approach to analyzing financial data, enabling businesses to plan, budget, and make informed decisions.

What Types of Businesses Use Financial Modeling?

Financial modeling is utilized by a wide range of businesses across various industries, including but not limited to, financial services, technology, manufacturing, retail, healthcare, and real estate. Companies of all sizes, from startups to large corporations, employ financial modeling to forecast revenues, analyze costs, evaluate investments, plan for growth, secure financing, assess risk, and optimize operational strategies.

The flexibility and applicability of financial modeling make it a valuable tool for decision-making and strategic planning across diverse sectors and organizational scales.

Is Financial Modeling Difficult?

Financial modeling can be challenging due to its complexity and the need for a deep understanding of finance, accounting principles, and business operations. It requires proficiency in financial modeling software, as well as knowledge of statistical analysis, forecasting techniques, and financial statement analysis. This is what makes OneStream intelligent finance platform the perfect option.

What Information Should Be Included in a Financial Model?

A comprehensive financial model encompasses historical financial data like income statements and balance sheets, revenue forecasts, expense assumptions, capital expenditures, debt and equity financing details, cash flow projections, key financial ratios, sensitivity analysis, valuation techniques, scenario planning, and documented assumptions and risk factors.

This holistic approach provides a detailed representation of a company's financial performance and projections, aiding in strategic decision-making, assessing financial health, and communicating effectively with stakeholders.

How to Structure a Financial Model

Structuring a financial model involves organizing it logically to accurately represent the financial aspects of a business or project. Begin by defining its scope and objectives, and then create sections for income statements, balance sheets, and cash flow statements. Link input variables like revenue drivers and costs to these statements with clear formulas.

Include sensitivity analysis to test the model under different scenarios, and document assumptions and data sources for transparency and validation by stakeholders. This structured approach ensures the model is clear, accurate, and useful for decision-making and forecasting.

How to Error-Proof a Financial Model

To error-proof a financial model, validate formulas, cross-check data, maintain consistent formatting, document assumptions clearly, conduct thorough reviews, and use version control to ensure reliability.

How Is a Financial Model Validated?

Validating a financial model involves several critical steps to ensure its accuracy and reliability. Validation usually begins with reviewing the model's formulas, calculations, and assumptions to verify they align with the intended purpose and business context. This process involves checking inputs against reliable sources such as historical data, market research, and industry benchmarks to ensure they are realistic and up-to-date.

Sensitivity analysis and scenario testing are then conducted to assess how changes in key variables impact the model's outputs, providing insights into potential risks and opportunities. Finally, peer review by finance professionals and stakeholders helps validate the model's logic, assumptions, and conclusions, ensuring it provides a trustworthy basis for informed decision-making.