Most forecasting goals focus solely on accuracy, but Harrison Katz reveals why understanding the true purpose of forecasts can transform how organizations make decisions. From leading Airbnb’s demand predictions to academic research, he uncovers the nuanced role forecasts play beyond numbers—and why misaligned goals and governance can distort the entire process.

In this episode, Harrison shares his nonlinear journey from dropping out of high school at 15 to leading Airbnb’s forecasting strategies across hundreds of global markets. He discusses how COVID-19 exposed the limitations of traditional models and taught invaluable lessons about system agility, regime shifts, and the importance of separating models for flow versus lead times, and not for supply versus demand. Harrison breaks down the often-overlooked concept of forecast governance, emphasizing that forecasts are not just numbers—they are political, strategic, and even behavioral tools that influence outcomes.

In this episode of Forecasting Impact, hosts Mariana Menchero and Laila Akhlaghi speak with Alex McCullough about his research on prediction markets, probabilistic forecasting, and the crypto ecosystem. He is best known for his work analyzing the accuracy of Polymarket, where he has built widely referenced dashboards to evaluate market calibration and performance. Through his analysis, Alex helps bring rigor and transparency to the discussion around how prediction markets perform as forecasting tools. Alex's work includes the following dashboards:

Initial dashboard: https://dune.com/alexmccullough/how-accurate-is-polymarket

And the widely referenced Brier Score dashboard: https://dune.com/alexmccullough/polymarket-brier-score

In this episode of Forecasting Impact, hosts Mahdi Abolghasemi and Mariana Menchero speak with Marco Peixeiro, applied data scientist at Nixtla, about the growing importance of explainability in time series forecasting. Marco shares how his work bridges research and practice, from developing deep learning models in NeuralForecast to writing educational resources that make complex forecasting concepts accessible to all.

We discuss how explainability builds trust in complex models, the role of SHAP values in understanding forecasts, and what the future holds for interpretability in forecasting. Marco also gives us a preview of his upcoming book, Time Series Forecasting Using Foundation Models, exploring how foundation models are transforming the forecasting landscape.

Marco’s books, including the upcoming Time Series Forecasting Using Foundations Models: https://www.manning.com/authors/marco-peixeiro