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Combining operational and financial forecasting

Jun 10, 2018 · Foresight's templates focus on using operational mechanics to forecast financials. Here's why.

Taylor Davidson

CEO / Founder

What is an "operational" model? A typical financial model consists of an analysis and forecast of the financials of a business, with the financial statements - income statement, balance sheet, and statement of cash flows - as the centerpiece of the model. With a business with a lot of historical information, the forecasting method may be to simply take the past and predict different rates of change for the components of costs and revenues to show how revenue, margins, and net income will change over time. Without historical data, the methods used to forecast can be thinner. In many financial models the forecasts start by having an input of what sales revenues are throughout the forecasting period, but without any thought into how the business creates those revenues. [1]

That's a fundamentally limiting way to analyze and forecast a business. One of the reasons why financial models are always wrong is not because of the models themselves but because of our methods and our expectations. A good model is one that helps us think about a business and make operational decisions by understanding their financial impact. It's important to tie together metrics like advertising spend and customer acquisition cost (CAC) with user acquisition; it's important to tie together business development staffing and client contracts signed; it's important to tie together the forecasts with metrics so we can make sense of the business.

In many financial models the forecasts start by having an input of what sales revenues are throughout the forecasting period, but without any thought into how the business creates those revenues. That's a fundamentally limiting way to analyze and forecast a business.

Financial statements are created in all of my models, but they aren't really the centerpieces. The Revenue Model and Costs sheets - which combines users, customers, expenses, CAC, revenues, staffing, and more - and the key metrics analyses are the core of what I try to build in my models. If we're going to create useful models they have to reflect business thinking, not just financial thinking.


  1. This is one of the major differences between models built for private equity or investment banking transactions, and models built for early-stage venture capital and startup transactions. When your fundamental business premise is for the business to disrupt the market or create a new one, using the company's past financials simply won't work the way it does in forecasting mature businesses. ↩︎

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