Simulation : The impact of assumptions

In designing solutions, it is important to closely evaluate the assumptions you have used to define what will work and what will not work. Often, we make decisions without the necessary information required to design a solution that will work. To improve the outcome of your actions, first you should clearly define your objective/purpose, then evaluate your current state, your desired state and all of the pieces and parts that influence the outcome of that goal.

What are the factors required for successful outcome?  What information influenced your decisions and actions? Evaluate the information that you’ve used to take action and ensure that it is both accurate and relevant to the objective.  Then, reduce the number of assumptions and interferences. As an example, let’s consider launching a startup. As a part of the business planning process, many entrepreneurs will create sales forecasts which indicate metrics such as their target market size, pricing model, operating expenses, sales conversion rates and expected sales.

Simulation Project : The Impact of Using Assumptions in Sales Forecasting for Startups

I am using a simulation tool called Insight Maker to demonstrate the impact of assumptions on forecasting profits. As with any simulation project, I first need to indicate the problem statement and the goal for the simulation. This is essentially in controlling the scope of variables (factors) needed in the simulation.


The Problem
A common mistake in creating sales forecasts is to define your number of expected sales leads based on your total market size and your assumption regarding the percentage (%) of that market that you can reach.

The Goal
The purpose of this simulation is to demonstrate the implications of a startup using assumptions regarding market reach to forecast sales.

In this example, the objective is to demonstrate that a startup business model works. The pieces and parts that influence the success of a business include metrics such as pricing, sales, expenses, and market size.

Simulation Run #1

A common mistake in sales forecasting is to forecast using the following formula:

Your Expected Revenue – Your Projected Expenses = Your Profit

Evaluate each variable in the equation to uncover the assumptions used to reach the final number.  Let’s take a look at the number used for expected revenue. Often the revenues are projected based on the number of expected sales leads, which are based on your total available market size and your best guess regarding the percentage (%) of that market you can reach. The problem with that approach is that the percentage of the market YOU can reach is often an arbitrary number. How do you know that YOU can reach this audience? What does it take to reach that size of an audience? Running the simulation using this method, will forecast a profit after several months because the model itself assumes that the business will be able to reach 20% of this total market size; there is no consideration for the factors required to do so. The only way you could realize a loss here is to not reach the 20% of the total market size. We know that startups must spend money to reach their target audience.  If it requires money to reach your desired target audience and that cost exceeds your budget, it would not be wise to forecast YOUR sales based on your ability to convert a percentage of a market place that you cannot afford to reach.


Simulation Run #2 : Reducing an assumption

The second simulation run includes an alternative run model ([LAC]) that will demonstrate the implications of factoring YOUR ability to reach a market into your calculation of your target market size. Instead of simply assuming that your target market size is equal to your (desired conversion rate * total market size), this model using information regarding how much it cost you to convert one lead. How many Google Ads must you run before someone clicks on it? How much did that cost? Now, how much money do you available have to spend to reach your target audience? The model uses those numbers to determine YOUR target (reachable) audience. What is your capacity to reach this audience?


Comparing The Results

In running simulation #1, a consistent, fixed profit is projected after a few months in business. The profits are a result of an assumption that the startup has the ability to convert 20% of the total market size to leads (by any means necessary, hook or crook).  Using the same business metrics, simulation #2 is projecting a loss, every single month. Both simulations were generated using the same business metrics for pricing and expenses, the only thing that changed was the value regarding the target (reachable) audience.  The first simulation assumes that the business can reach 20% of the marketplace with no consideration for the cost incurred to reach them. The second simulation integrates the budget for sales & marketing and a cost-per-lead metric to determine the reachable marketplace.

The Takeaway

In this exercise, the objective was to demonstrate that a startup business model works and will turn a profit. Eliminating one assumption revealed a simple fact:  You will make better decisions if you reduce the number of assumptions used in making your decisions.

The Simulation Project
To play with the live simulation and view it in full screen, visit Feel free to play around with the input variables and provide feedback. Over time, I will be updating and expanding the model to consider other factors that are important to consider as well.


Show More

Kishau Rogers is the editor and founder of The bigThinking Project. The bigThinking Project is a resource center and collaborative innovation project which promotes the principles of systems thinking. Our mission is to empower the next generation of innovators to think bigger, to think better and to create solutions which make significant impact in the areas that matter. Kishau Rogers is an award-winning entrepreneur with over twenty years of experience in the computer science industry. She is a serial entrepreneur having founded and co-founded companies such as Websmith Group, TimeStudy, PeerLoc Inc., and Websmith Studio.

Related Articles

1 thought on “Simulation : The impact of assumptions”

Leave a Reply

Your email address will not be published. Required fields are marked *