Finance Expert Shares How Building a Forecasting Model Can Separate Startups Seeking Investment

Tony Kontzer, Contributing Editor

March 1, 2021

Building a financial model that yields accurate forecasts is an art form. Done right, it makes it possible for a company to predict what's coming, spend wisely and dodge financial bullets. But it's also a process rife with trial and error, numerous hiccups and potential frustration.

When a startup engages in financial modeling(opens in new tab) for the first time, it can be an unsettling experience. But an expert in the world of startup finances recommends that they embrace the uncertainty and charge ahead.

"The model you create for your company will always be wrong," said Miran Ahmad, an angel investor, seasoned CFO of startups and former vice president of finance at healthcare infrastructure provider Truepill, during a recent NetSuite-sponsored webinar(opens in new tab). "The act of modeling is what's good."

Ahmad and his webinar host, Eric Bahn, co-founder and general partner at early-stage venture firm Hustle Fund Management, made it clear that startup investors want to see that founders are thinking ahead, and that they're able to project three years out. Engaging in financial modeling(opens in new tab) is a powerful way to demonstrate the desire to achieve this, especially if the founders are adhering to the golden accounting equation: assets equal liabilities plus equity.

"It's super impressive when the founder knows the nitty-gritty of everything," Ahmad said. "As an angel investor, I want to see this."


Push the Limits

Bahn said he has a lot more confidence in startup founders who are trying to "up-level" their companies through financial modeling, meaning they're aspiring to behave as if they're in a later stage of maturity. Often this means trying to create a forecasting model without any of the actual historical data on which assumptions are based, and doing their best to stay on top of the balance sheet, income statement and cashflow.

"Even if I know it's going to be completely wrong, it still tells me you're thinking about your business," said Bahn.

Even so, being able to make assumptions based on historical data is a fundamental aspect of financial forecasting. And that's why Ahmad recommended that startups pay particular attention to creating accurate historical data. If they don't, he said, they're subject to the dreaded "garbage in, garbage out" reality of working with flawed data.

In other words, the more thorough and accurate a company's historical data is, the more accurate and valuable its financial model — and the forecasts it generates — becomes.

"The model gets better with engagement," said Ahmad. "Modeling forces you to actually think through the inputs."


Adopt a Big Picture View

That's important given that Ahmad said he considers the tendency to want to capture everything to be one of the primary potential pitfalls startups must avoid. Instead, he suggested that they adopt a big-picture view and focus their time and effort on the three to five levers that are likely to drive 80% of the model's output.

"Don't be seduced by the dark side and think that modeling is going to answer all of my questions," Ahmad said. "It will distract you in the weeks when you need to be at 30,000 feet."

When built effectively, financial models yield projections that, at minimum, can inform companies how much they can afford to spend, and where that money would be optimally spent. But as they mature, they can deliver much more predictive if/then scenarios, serving as a sort of crystal ball.

"The whole point of a model is to get you to think about the future world," said Ahmad. "Planning is the end-stage you want to get to."

Learn about NetSuite’s financial software for startups(opens in new tab).

NetSuite has packaged the experience gained from tens of thousands of worldwide deployments over two decades into a set of leading practices that pave a clear path to success and are proven to deliver rapid business value. With NetSuite, you go live in a predictable timeframe — smart, stepped implementations begin with sales and span the entire customer lifecycle, so there's continuity from sales to services to support.