The Chief Forecaster will See You Now-Nate Kaemingk
Nov 26, 2024
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Nate Kaemingk, Chief Forecaster at BetterForecasting.com and former fractional CFO, dives into the world of AI-driven financial forecasting. He discusses the transition from annual budgets to rolling forecasts, highlighting the importance of real-time updates and market responsiveness. Nate also explores the significance of probabilistic forecasting and how small errors can cause major cash discrepancies. Plus, hear about his unique journey, including a three-year RV adventure, and his favorite Excel function!
Nate Kaemingk emphasizes the transformative power of probabilistic forecasting that utilizes inferential statistics to enhance financial predictions despite limited data points.
The discussion highlights the advantages of rolling forecasts over static annual budgets, promoting adaptive planning to better respond to market changes and incorporate timely data.
Long-range cash forecasting is critiqued for its sensitivity to small errors, indicating the need for robust methods that leverage machine learning to mitigate financial risks.
Deep dives
Nate Kamink's Journey into FP&A
Nate Kamink began his career as a mechanical engineer, utilizing advanced mathematical and statistical skills that he later applied to financial forecasting. His career took a pivotal turn while working at Cummins Inc., a Fortune 500 company, where he recognized a gap in forecasting tools that didn't meet the complexity of actual financial models. This insight, combined with the demand for better forecasting methods, prompted him to establish Better Forecasting, an innovative platform aimed at streamlining financial modeling. The recent launch of their AI-powered forecasting product positions Better Forecasting to offer FP&A professionals valuable insights while automating the modeling process.
Understanding Probabilistic vs. Deterministic Forecasting
Probabilistic forecasting, which analyzes potential outcomes via inferential statistics, differs significantly from traditional deterministic methods often used in finance. This distinction is crucial since financial forecasting frequently deals with limited data points, making it more suited to probabilistic approaches. Nate emphasized that finance professionals typically lack advanced statistics education, creating a gap that specialized forecasting models can fill. By employing smaller datasets effectively, businesses can leverage probabilistic models for more accurate and nuanced forecasting.
The Importance of Rolling Forecasts
Rolling forecasts serve as a critical tool in FP&A, allowing organizations to adapt their planning dynamically rather than relying on static annual budgets. Nate clarified that rolling forecasts should reflect the most likely outcomes and use existing data trends to predict future performance, offering flexibility in the face of market changes. This method emphasizes that bad news can be beneficial if communicated early, enabling firms to adjust their strategies before issues escalate. By separating forecasts from budgets, organizations can facilitate better decision-making and prepare for various scenarios based on updated data.
Addressing Long-Range Cash Forecasting Challenges
Long-range cash forecasting poses considerable challenges due to the sensitivity of cash flows to small errors in revenue or expense projections. Nate illustrated this with an example showing that a mere 5% error in revenue could completely negate an anticipated cash increase from 10% growth. He highlighted the necessity of understanding market dynamics to fine-tune forecasts and ensure businesses are not caught off guard by cash flow issues. Implementing robust forecasting methods, which account for potential changes and leverage machine learning techniques, becomes essential for early identification of these risks.
The Value of Effective Forecasting
Effective forecasting adds significant strategic value to an organization beyond mere financial accuracy, facilitating better operational and market decisions. Nate articulated how accurate long-range forecasts can reveal underlying structural issues like misaligned pricing or changing labor costs, thus providing actionable insights for management teams. By leveraging AI and machine learning, Better Forecasting aims to simplify the forecasting process and enhance accuracy while minimizing uncertainty. This allows FP&A professionals to proactively address potential issues, ultimately enhancing their role as strategic partners within their organizations.
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.