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Forecasting for Uncertainty with Causal
FP&A is becoming increasingly important strategically for both startups and scaled companies alike. As the volume of available data increases and the market pushes companies towards efficiency, it is critical to be able to analyze and plan accordingly. This is the strategic role of finance inside any company - allowing every department to understand the quantitative implications of their decisions and performance.
I had a great discussion this week with Taimur Abdaal (CEO of Causal) and Brady Ellis (VP Finance at Branch Insurance).
Some of the key takeaways:
It’s never too early to build a model
Great models start in PowerPoint - build yourself a dependency map
Simplicity is the key to any good model
Build sub-models that feed into a main model if you feel like there’s no way to keep it simple and maintain accuracy
Make sure variables tie to measurable, operational triggers in the business
Focus on your mathematical reality rather than quick and dirty diagnostics as your guide
Get technical buy-in with your team
Using variable input ranges can be very helpful to gain intuition around scenarios (Causal.app makes this easy)
…And many more great insights in the video!
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