Article 1 – Planning and Structuring a Financial Model:
How to make your financial model more organized

Our series begins with one of the most foundational topics in modeling – how to properly structure and plan a model. A well-structured and planned model improves clarity, efficiency, and effectiveness throughout the entire modeling process. Organized models are perceived as more trustworthy by stakeholders; are easier to audit; and have less “noise” (features and data not relevant to the core business questions). 

In this article we explore various ways a modeler can improve their model’s organisation as they progress through the traditional modeling process: 

1. 1. Beginning with a Modeling Plan
   2. Establishing Inputs and Outputs
   3. Gathering Data & Establishing Gaps
   4. Creating Schedules
   5. Developing Financial Statements

 

Step 1 – Beginning with a Modeling Plan

The first step of every modeler’s process should be to develop a plan for their model. 

A model plan is a short document that details your client’s primary ask, the most important data and scenarios, and an overview of the structure of the proposed model.

To begin your modeling plan, begin by answering the most essential questions related to your model: 

• • What is the important output that the client wants to know? This should be one of the first questions you ask from your initial conversations with the client. What were the key metrics or outcomes that the client sought to derive from the model?
  • Which assumptions in our model should become scenarios? Which variables are most critical to the client’s decision-making process? Which are most likely going to need to be extended into scenarios? Which were apparent from the kickoff that are worth spending extra effort investigating?
  • How much detail is required across this model? Which scenarios and line items are most likely to draw the most questions from the client? Which are the most uncertain? Which can be broken down many different ways? By determining the level of granularity and how you plan to segment/structure your scenarios up front, you can avoid a lot of unnecessary complexity in your schedules
  • Do I have enough/the right historical detail for my model? A good gut check early on is to ensure that you will be able to find reliable and sufficient historical data to feed your historicals in your model. Ensure that however you plan to drive projections, that you have strong historicals from your client 
  • How long should the forecast period be, and should the model be monthly, quarterly, or annualy? Decide on the appropriate time horizon for the forecast, considering the client’s strategic goals and industry standards. Monthly models provide the ability to create stub periods, such as if you are in October but your year end is December. They also allow for more precision if the business is particularly sensitive to month-to-month cash flows, such as if the business has a substantial amount of debt. However, they are materially more time consuming than an annual model and can create room for human error. 

Once you have an agreement with your client on these topics. Write them down. These questions will become your ground truth – and will help you establish a clear statement of the scope of the model. 

By establishing the scope at the onset of the modeling process, you save yourself future headache around potential scope creep and establish objective criteria to measure the success of your final delivery.

Once you have these first questions answered, begin to translate these requirements into a simple modeling plan. Within a word doc or excel workbook start to block out the skeleton of your model:

• • Inputs/Output Worksheets: Include sections for the model cover, summary output values, inputs/assumptions, and sources and uses of capital.
  • Schedule Worksheets: Detail the necessary schedules such as revenue, cost, CAPEX/depreciation, fixed assets, income tax, working capital, debt and interest, shareholders’ equity, valuation, WACC, and others relevant to the client’s business.
  • Financial Statement Worksheets: Plan for the income statement, cash flow statement, and balance sheet
  • Scenarios and Sensitivity Worksheets: Consider how you will incorporate scenarios and sensitivity analysis to provide flexibility and insight into different potential outcomes.

Investing a few hours in thoughtful planning at the onset of building your model can save you tens, if not hundreds, of hours later in the project. The decisions you make at this first step, as a designer of a financial model, will heavily influence what your model will be capable of in the future, so be mindful of which doors you keep open and which doors you close.

Step 2 – Establishing Key Inputs and Outputs

Now that you’ve established the high level structure for our model, you can move onto the second major step in planning your model – the model’s inputs and outputs.

Model inputs represent the data and assumptions that drive the model, while the outputs are the metrics and results that inform strategic decision-making. 

The nature of these inputs and outputs can vary significantly depending on the industry and use-case of your model – but our core objective always remains the same: You want to identify the list of variables that you’ll need to solve your business problem.

In many cases, your first step as a modeler is to identify if what you are modeling already fits a well established model structure (3 Statement Modeling, LBO Modeling, M&A, Valuation, Real Estate, etc.) or if this is something completely unique to your client’s business scenario. 

For new modelers, a great place to start is by being sure you understand the essentials of these base models. (For those seeking to learn on their own, our $150 Self Study Financial Modeling Course is an excellent place to start).

In the case we are dealing with an established business problem, your base model will already come with its own standard structure, assumptions, and schedules. For example, in an investment banking context, our model might be valuing companies, structuring deals, and assessing the financial impact of mergers, acquisitions, or capital raising activities. In those cases, you know you will likely be starting from a 3 statement or M&A model and will be reporting on metrics like future cash flows, EPS, or dilutions.

In contrast, in industries like private equity and venture capital, inputs often involve detailed assumptions about debt structures, equity returns, and market size forecasts. Their models tend to be more granular and operationally focused, given that PE firms are often directly involved in managing their portfolio companies. In these scenarios, we might be dealing with something more akin to a base LBO model, and our inputs would be more geared towards decision-making, and metrics like IRR, operations improvement, growth, and debt repayment.

In all cases, a modeler’s planning process should start by identifying the key drivers of the model and the historical data available that will likely be used. 

Common Model Inputs

If you have a business scenario that needs to be modeled that goes beyond making an adjustment to a standard model (see above), one useful exercise can be to examine the model from a top-down, and then bottom-up planning approach. 

Starting with a “top-down” plan, begin by considering the various modeling inputs and historical data you have access to, and their level of appropriateness in solving the business decision you are trying to model. Below is a list of common model inputs you may consider as key drivers in your model:

Category	Name	Description
Revenue Assumptions
	Sales Growth Rate	Annual growth rate applied to revenue.
	Average Selling Price (ASP)	Price at which products or services are sold.
	Units Sold/Volume Forecasts	Forecasted number of units to be sold.
Cost Assumptions
	COGS as a Percentage of Sales	Ratio of cost of goods sold to total sales.
	Operating Expenses	Forecasted SG&A, R&D, and other operating costs.
Capital Expenditure (CapEx)
	CapEx Growth Rate	Annual increase in capital expenditures.
	Depreciation Rates	Rates at which assets are depreciated.
Financial Assumptions
	Debt Levels	Total amount of debt and its interest rates.
	Equity Financing Plans	Details on any planned equity issuances or buybacks.
	Tax Rates	Effective tax rate applied to earnings.
	Dividend Policies	Planned dividend payments and policies.
Macro-Economic Assumptions
	Inflation Rate	General increase in prices and fall in the purchasing value of money.
	Interest Rates	Rates at which interest is paid by borrowers for the use of money.
	GDP Growth	The rate at which a country’s economy is growing.
Operational Assumptions
	Production Levels	Expected levels of production activity.
	Inventory Turnover Rates	Frequency at which inventory is sold and replaced.
	Employee Headcount	Number of employees required to meet operational needs.

 

Common Model Outputs

Once you’ve considered inputs, consider the inverse. By defining the outputs of the model (key indicators or ratios  such as discounted cash flow (DCF) values, internal rate of return (IRR), and credit ratios.) You can work backwards to understand where you will likely have gaps, given the modeling inputs identified in the previous section.

Common Model Outputs:

Assumption	Description
Revenue	Total projected revenue for the forecast period, including growth rates.
EBITDA	Earnings before interest, taxes, depreciation, and amortization, which provides a clear view of the company’s operating performance.
Net Income	The bottom line profit after all expenses, taxes, and interest have been deducted.
Cash Flow	Key cash flow figures, such as operating cash flow, free cash flow, and net cash flow.
Key Ratios	Important financial ratios that provide insights into the company’s performance and financial health, such as:
	Gross Margin: Gross profit as a percentage of revenue.
	EBITDA Margin: EBITDA as a percentage of revenue.
	Net Profit Margin: Net income as a percentage of revenue.
	Return on Equity (ROE): Net income as a percentage of shareholders’ equity.
	Debt-to-Equity Ratio: Total debt divided by total equity.

 

The outcome of this exercise creates a simple, “what goes in” and “what comes out” understanding of the model. From there, you can identify gaps, and work backwards (or forwards) to begin to structure your assumptions, schedules, and statements.

Step 3 – Gathering Data & Establishing the Gaps

Data is the lifeblood of financial models, but gathering the right data can be one of the most challenging aspects of the modeling process. Clients and managers often ask you to make a model while providing only a fraction of the details you need, assuming you’ll fill in the blanks. 

Before you start modeling you need to find out what we know and what we don’t know. Once you’ve established core inputs and outputs, start asking the important questions regarding key drivers:

• • How should we model revenue? What are our revenue assumptions?
  • How should we model expenses? What are our cost assumptions?
  • What will our Capex / depreciation Schedules look like? What kind of historicals do we have from the client?
  • What are the other model assumptions? DCF: WACC, terminal value? LBO: Entry multiple, exit multiple, debt assumptions?

At this point it’s also valuable to ask other key questions about how we may want to structure our model, such as:

• • Granularity: Do we need separate schedules for revenue, costs, capex and depreciation?
  • Timeframe: Should our model be monthly, quarterly, or annual? Over what time horizon?
  • Statements: What line items do we need to be wary of? Are all three statements equally important?
  • It is also important to critically assess the quality and accuracy of the data provided by the client. Never assume that the data is at the right level of detail or that it is free from errors. Conduct thorough data validation and cross-checks to ensure that the inputs to the model are reliable.

In cases where data is incomplete or unavailable, modelers may need to make educated assumptions or use proxy data. However, when you make an assumption, always be sure to clearly document it within your model and communicate it to the client. Every assumption is a vector of risk within a model, so always be sure to provide an explanation of the potential impact on the model’s outputs. As you face incomplete data or questions, you should also be creating a list of these data gaps and questions. Ideally, you’ll be able to set up a meeting with the client or manager and address the priority items. 

You may find at this point in the process, you are missing critical information or need to make  large assumptions in order to complete your model. That’s a good thing – knowing your model’s limitations and assumptions early both allows you to manage client relations/ expectations, gather better data, keep the scope relevant, and build a more accurate model. 

Step 4 – Planning and Building Schedules

After we have an understanding of our model’s inputs, outputs, data, and assumptions, we can begin to plan the schedules of our model. 

Schedules are the place in our model where the representation of the underlying business becomes most explicit to the reader. As a general rule of thumb, a good set of schedules will capture the journey of revenue from the first customer interaction down to the generation of free cash flow. 

Best practices for creating schedules are as follows: 

1. Align Schedules with Business Operations: Ensure that each schedule accurately reflects the underlying operations of the business. This involves tailoring the structure of the schedule to align with how the business generates revenue, incurs costs, and manages its assets and liabilities.
2. Prioritize Clarity and Transparency: Design schedules to be easily understandable by stakeholders. Clearly document assumptions, methodologies, and calculations, so that the logic behind each schedule is transparent and can be followed by anyone reviewing the model.
3. Maintain Consistency Across Schedules: Ensure that all schedules are consistent in their structure and presentation. This includes using uniform formats, labels, and timeframes (yearly, Quarterly, monthly, etc.) 
4. Balance Detail with Usability: While it’s important to include sufficient detail in your schedules to accurately reflect the business, avoid over-complicating them. Strive for a balance where the schedules are detailed enough to be useful but not so complex that they become difficult to navigate and interpret.
5. Incorporate Flexibility for Scenario Analysis: Design schedules to be adaptable, allowing for easy adjustments as new data becomes available or as different scenarios are tested. This includes building in the capacity to handle changes in key assumptions without needing to overhaul the entire schedule.

Many modelers fall into the trap of focusing too much on one schedule while neglecting others, which can lead to an unbalanced model that doesn’t fully capture the complexities of the business. In most cases, a model will have a schedule that is most important, but no single schedule should be emphasized at the expense of others. 

There is no magic shorthand for how to organize and design all of your schedules. Each schedule has its own standard format, goal, and output. If you are looking to get better at individual schedules we suggest you consider taking one of our many financial modeling courses.

*Reader’s Note*  We are soon planning to publish an extended series on the most common schedules, their most common structures and outputs, and what we as modelers should consider when building these schedules.

Step 5 – Developing the Financial Statements

While the schedules handle many of the critical calculations in our models, it is within our financial statements that our outputs are often most-prominently displayed to our reader. 

Assuming you’ve done the work to properly build and organize your schedules, building your financial statements should largely be an exercise in linking back to your previous schedules. 

As a result, ensure that your statements are organized in a logical and progressive way (that they are easy to navigate, clear in their logic, flexible enough to accommodate changes and updates) and that line items clearly link back to the schedules that drive them. 

To assist in organization, we suggest building all financial statements and related schedules in a skyscraper format—arranged vertically on the same worksheet. This layout minimizes the need to navigate across multiple sheets, and reduces the risk of errors associated with linking numerous formulas across different tabs.

Conclusion

In our next article, we will shift our focus from the structural components of financial modeling to the aesthetic and formatting decisions that enhance a model’s readability and professional appearance.