In today’s fast moving supply chain environment, the most valuable insights are often hidden in data that appears to be random. Yet every demand series contains underlying structures—seasonality, trends, cyclicity, and subtle autocorrelations—that can be uncovered, quantified, and leveraged for better planning decisions.
In this quick 30-minute session, Dr. Barry Keating (University of Notre Dame) and Thomas Baxter (John Galt Solutions) will discuss why patterns matter even when they seem absent. They’ll demonstrate how ForecastX can automatically uncover those patterns to deliver a high-quality forecast in seconds. Additionally, they’ll look at Distribution Replenishment Planning (DRP) to illustrate how pattern-rich forecasts feed directly into smarter replenishment decisions.
Key Takeaways:
- A clear conceptual framework for spotting hidden demand patterns and understanding their impact on forecast bias and error.
- Why a best fit algorithm matters - an overview of how an automated model selection engine (Procast) evaluates multiple statistical techniques and chooses the one that best captures the underlying pattern.
- How technology surfaces hidden signals - a discussion of the tool’s ability to detect subtle seasonality, trend, and irregular components within seconds, all while staying inside the familiar Excel environment.
- Linking pattern rich forecasts to DRP - practical insights on how accurate, signal driven forecasts improve distribution replenishment logic, inventory positioning, and service level performance.
- Immediate actions you can take - to embed pattern-based forecasting into your own planning process right away.