In this blog, we go over the following:
“Your ability to forecast income and costs is the best barometer of how well you know your business.”
What is Financial Modeling?
Financial modeling combines accounting and financial business metrics to create an abstract representation of a company to forecast into the future what might happen to the business. Financial models are most commonly used for making business decisions about how to manage the company. The following are uses of financial models:
Business Decisions This is usually at an operating company where the finance, corporate development, treasury, or other groups at the company have a model that they use to make decisions about managing the business.
Investments Make investment decisions in a private or public company.
Pricing Securities If a company is going to raise money that is issue more shares, then a financial model is needed to value the securities
Corporate Transactions Undergoing a corporate transaction such as merger and acquisition, divestiture, capital raise
Steps for Building Financial Models
Starts with taking historical data and putting it into Excel (at Financial GPS use Summit), usually at least 3 years of information.
From there, you can calculate historical ratios and metrics. This includes (but not limited to) margins, growth rates, asset turnover, inventory changes. By studying the past, you might get a good indication of what the future holds.
Once the historical data has been analyzed, you can build ratios and metrics into the future by making those assumptions about margins, growth rates, capital spending, etc.
After making the ratios and metrics, that drives a forecast. The forecast is the three financial statements all linked together in a spreadsheet. Typically, a forecast is at least 3-5 years long.
A valuation can then be layered on top. Value the company using the discounted cash flow (DCF) analysis method. This calculates the net present value, which is the most common type.
On top of that, there could be additional analyses such as sensitivity, scenarios, charts, graphs, and dashboards. There’s almost an endless amount of analysis that can be layered on top of the model.
Here’s a video tutorial on how we can create a proforma profit and loss statement on Summit.
What Makes a Good Financial Model?
A good financial model is simple enough that anyone can understand it, yet detailed enough to handle complex situations. How Financial GPS determines a good financial forecast includes the following 5 components – easily recallable using an acronym, LUCID.
Logical – a good forecast must be logical and grounded in reason. While assumptions must be made, it is important to have support (preferably data).
Understandable – a good forecast must be understandable to be useful to multiple stakeholders. Just as a balance sheet or income statement can be generally understood by operators, investors, banks and tax authorities, so too should be a forecast.
Comprehensive – a good forecast must be comprehensive which is to say it must be complete. It should start at a logical beginning and conclude at the appropriate ending.
Integrated – a good forecast must be integrated because business is a multidisciplinary activity.
Dynamic – a good forecast must be dynamic. Inputs must be changeable in real-time to be useful for what-if and scenario analysis.
The reality is that any business owner that wants to make financial business decisions, needs to be able to create financial models. As mentioned, financial modeling can help with making business decisions which includes but is not limited to the following:
Investing into other companies, assets, or security
Pursue in projects (such as R&D projects at a firm, building continuing new factories, or continue with building continuing a merger acquisition deal)
Sell your company or purchase another organization
Financial modeling is a critical part of being in business as it will showcase that the possibilities can be endless or maybe expenses need to be cut back. It is a representation of a business’s performance given all relevant factors, networking effects, and risk assumptions. It enables the user to interpret the impact of a confluence of factors and present how they will manifest in future results.