Financial modeling is a core element to major business decisions, from early stage startups to large corporations.

The primary goal of financial modeling is to represent the economic performance of a business or project at present and into the future. Financial models predict business success, signal business risks, and enable educated business decisions.

A financial model is based on historical performance and assumptions about future performance. Financial modeling is particularly complicated at the beginning of an innovation project because the company has limited or zero historical data. Here's how Tristan Kromer, innovation coach and founder at Kromatic, suggests how you go about it.

A snippet from Tristan Kromer’s session during the Innov8rs Connect Unconference, June-September 2020. To watch the full session recording, join Innov8rs Community with a Content or Premium Pass.

Early Stage Financial Modeling

At the beginning of a project, there is no data, only guesses. Early stage market research and experimentation rarely provides a straightforward financial model. Generally teams are only able to provide qualitative insights, and some qualitative data with very large margins of error. Even after a small Proof of Concept, sales data will be minimal.

If the limited data is entered into a linear projection, the future projections and ROI calculations are unimpressive because the project is not yet off the ground. What a linear model fails to account for is the growth stage of the business, where its financial numbers may rise exponentially.

Modeling is also complicated if a project is approaching or in its growth stage. Modeling at this stage will be equally inaccurate because the project is unlikely to continue on the same growth trajectory forever. Once the market matures, the growth is likely to slow down and smooth out.

What not to do?

A pitch for an innovation project often provides information that is not helpful for financial modeling, such as:
A customer persona, including information like a description of the target customer, with demographics, facts, behaviors, needs, and goals
A value proposition canvas
A business model canvas
A description of the user experience

This fuzzy information is not useless... in fact, it is critical to product development. But none of these frameworks answer the basic question sought after in financial modeling: how much money will the project actually make? This is the key piece of information required when someone is deciding whether to fund a project.

What Information Does An Investment Board Need?

When thinking about a successful financial model, think about a weather chart where the meteorologist tries to predict the path of a hurricane. A hurricane chart begins with information that is definite, like the hurricane’s current location. As the predicted time period extends further into the future, the hurricane’s predicted path widens because the level of uncertainty increases.

The same thought process should be applied to financial modeling. A successful financial model acknowledges future uncertainty. It takes the available qualitative data (customer persona, user experience, etc.) and translates that information into a projection that realistically represents user uncertainty.

A successful financial model acknowledges the uncertainty, takes quantitative and qualitative data, and translates it into a projection that realistically represents the uncertainty. The financial model can project results from a range of highly unlikely to very likely. This allows the potential investor to understand the general range of possible results and helps narrow expectations on the most likely outcome.

How to Create an Uncertain Financial Model

At its simplest, a financial model needs to represent the business model as inputs and outputs. Customers come in and revenue comes out.
Even in the case of a mission impact model (a nonprofit), there are inputs and outputs. Money comes in and lives get saved. It’s the job of the financial model to predict the future, based on the data of today. To do this, companies can use a few basic principles in their approach:

  • Start Simple, Build Complexity – Your first model doesn’t need to account for interest rates and the global economic environment. Starting with five variables is sufficient for a first version.
  • Customer Centricity – Don’t center the financial model arounds assets and COGS. Structure the financial model around the user journey, using conversion rates from step to step as variables in the financial model.
  • Think Visually – A financial model isn’t just about numbers, and spreadsheets are hard to think through. Draw the model as a conversion funnel and remember to draw loops for how customers return again and again and also invite others.
  • Use Variables as Hypotheses – Don’t enter a guess for how many customers or how much revenue you will have four years from now. Estimate the conversion rate of visitors-to-customers and customers-to-revenue. Then use the variables to calculate what happens during each time period.
  • Embrace Uncertainty – Don’t pretend to know the exact value of any variable. Early stage startups don’t know that their conversion rate is 10% or 20%. Use a range 10–20%.
  • Use a Monte Carlo Simulation – If using ranges, employ a statistical approach with a Monte Carlo simulation. This is an approach that uses ranges to produce a large number of simulations of the results of your model. The output is a likelihood of any given financial result, instead of a static prediction.
  • Get Data – If the range is very large, gather more data to narrow your prediction. When you don’t know much, even a little data can improve your predictions radically.
  • Use Output to Set Success and Fail Conditions – The financial model isn’t just a tool to predict the future. Use it to identify your minimum success criteria for future experiments and research.

Although some of these terms and tools such as a Monte Carlo simulation can be intimidating, there are some basic templates that can be useful. Start with a visualization, move to a basic financial model, then move to a Monte Carlo simulation. Even a basic visualization and quantification will help early stage corporate startups have a meaningful conversation with finance.

A Critical Tool For Success

It is important for early stage projects to put time and effort into financial modeling. It does not need to be a major investment of time. A simple model using simple tools can deliver a lot of information. When the startup has more data, the model can improve. But the financial model must represent uncertainty and not fall into the trap of linear projections.

The financial model is a key tool in raising capital as a startup. Investors and corporate executives will place a critical eye on the financial model, looking to understand the sustainability of the business.

In addition to raising early capital, financial modeling will provide value throughout the life of the project. Financial modeling will help in decisions around user acquisition, making decisions about business growth (such as expanding into new markets), budgeting, and valuing a business for sale.

Putting the time and energy into understanding and preparing an accurate financial model in the early stages of a product not only enables meaningful financial conversations, it also forces critical and thoughtful conversations about the success of the business early on.

This is a piece from The Innovator’s Handbook 2021. If you’re keen to dive into the best and latest on corporate innovation, request your copy here. To discuss anything Strategy, Leadership & Governance, join our upcoming Innov8rs Connect online event, 16-20 November.

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