Nate Kaemingk is Chief Forecaster for BetterForecasting.com, where he has built a financial forecasting AI for mid-market finance teams. Previously he has been a Fractional CFO for two Montana based companies. Nate started his career as a mechanical engineer using inferential statistics to model chemical reactions in Diesel engines! Later, during his MBA, he applied an inferential statistics background to forecasting and scenario analysis. Nate has had the opportunity to apply these methods in roles with multiple Fortune 500 companies, including Cummins, and subsequently as CFO and Chief Forecaster at Better Forecasting.
Episode links: www.BetterForecasting.com
Connect with Nate (LinkedIn) https://www.linkedin.com/in/nathankaemingk/
On this episode:
- Probabilistic Forecasting, small (not big data) and inferential statistics
- Rolling Forecasts vs Annual Budgets explained
- Importance of not skipping out on the fact you need to update your plan
- Why are we resistant to changing the budget?
- The advantages of a rolling forecast
- Using Leading Market Indicators
- DSO (Day Sales Outstanding) as a powerful forecasting example
- How long range forecasting reveals structural issues in a business
- Building a driver-based model – and why it’s hard
- Renting an RV and touring the country for 3 years
- Favorite Excel function
