Simulations vs. Financial Planning

For pre-revenue companies, forecasting demand is very challenging because there is no financial history.

To overcome that problem, some startup founders use random number generation as a tool to “logically generate” demand for their product or service. In their minds, this strategy is their best bet because they have no idea how to estimate demand otherwise.

However, this is wrong. In this article and the corresponding  video, we discuss specific situations when using random number generation is appropriate and why it is never correct to use it in financial forecasting.

A random number generation strategy is appropriate when your actions cannot change the outcome, For example, when you project the returns on financial assets, you have no control over how the prices of these assets move. Thus, in this case, you should use random number generation to simulate daily price changes. In this case, it is your best bet to predict the outcome, because from your perspective the result is random.

On the other hand, your asset allocation strategy, or how you allocate your money among different asset classes, is not random, and your actions do affect how much risk you take and how much reward you can expect to get for a given level of risk.

Similarly, your financial goals should not be determined randomly either because your strategy affects what happens with the company, and you decide on what your strategy should be. When you build a financial model for your company, you put together a quantitative plan based on that strategy.

To learn more about The Startup Station’s four-step framework you can use to properly estimate demand for pre-revenue companies, read our blog.

Victoria Yampolsky, CFA, is the President and Founder of The Startup Station, a comprehensive financial resource for early stage startups. She evaluates the financial feasibility of business models and specializes in the financial modeling and valuation of pre-revenue companies. She also created a finance curriculum for early stage founders and launched The Startup Station’s educational program in 2015. Since then, more than 1,000 founders have attended her online and in-person finance classes and learned the basics of financial modeling, valuation, and startup financing.

Previously, Victoria worked for the Deutsche Bank Research Department and performed IT consulting for CapGemini’s Financial Services Division. Victoria holds a Bachelor’s Degree, Cum Laude, in Computer Science, with a minor in Mathematics, from Cornell University and an MBA, with honors, from Columbia Business School. Victoria is also on the Advisory Board of the Computing and Information Science (CIS) Department of Cornell University.