Common mistakes when creating financial models - and how to overcome them
Over the years, I built many complex models and reviewed even more. I realized that there are a few issues in particular that - if addressed - can make a big difference in how impactful your financial analysis will be.
#1 Not knowing which inputs matter most
Most financial models make predictions based on assumptions of varying degrees of confidence. Modeling how changes impact the result of your analysis gives business partners more than just a go / no-go decision.
Use a sensitivity model to show which inputs matter the most. Under which conditions would the project stop being viable? Discuss how likely it may come to that to assess the risk.
#2 Not challenging the assumptions
Once you know which assumptions have the most significant impact, determine how your business partners came up with them.
They may be based on previous experience and backed up by historical data. Or they may even be a result of small experiments.
In these cases, you have a data-based foundation and can simply document the assumptions made for future reference and post-launch analysis.
However, if it wasn’t much more than a simple guess, it’s your job to challenge it. Show your business partner how even small changes impact the result. But don’t challenge the person. Question the process of how the assumption was made and work together to find a more robust projection.
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