In this video, Justin Siefert from John Galt Solutions shares a fascinating story from World War II that serves as a meaningful reminder of how decisions can go wrong when we focus only on the data we can see. The real risk (and opportunity) is often hidden in the missing data, which is why AI in supply chain planning is so powerful, helping teams minimize decision bias.
Leaders often analyze suppliers that are still operating, lanes that usually perform, or scenarios that haven’t yet failed, while overlooking the signals that point to future disruption. Confirmation bias, intuition, and organizational echo chambers all compound the problem, especially when decisions must be made quickly.
AI changes the game by evaluating data holistically, challenging assumptions, identifying anomalies, and highlighting what isn’t happening but should be considered. By continuously learning from disruptions, delays, and demand shifts, AI helps supply chain teams reduce bias and make better decisions under uncertainty.
The Atlas Planning Platform brings these capabilities directly into supply chain planning. With explainable AI at its core, Atlas enables faster scenario analysis, smarter recommendations, and human-in-the-loop governance.
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- Full Transcript
Many decisions continue to be made based on intuition and gut feel. Now, more often, we talk about the need to shift towards data driven decisions – using the vast amount of structured and unstructured data available to us to help us determine what we should do. However, sometimes that data can lead you down the wrong path... Recently, I was reminded of a fascinating example of how using data can sometimes lead to a less than optimal conclusion.
During WWII as bomber planes returned from missions, the Allies studied them and marked where damage was located. Their first instinct based on these findings was to add armor and strengthen the planes where they were hit most... But that was wrong. The conclusion based on the data available overlooked a significant issue.
The planes that came back weren’t the problem. Quite the opposite in fact. The real issue was the planes that never returned. They were hit in critical areas, engines, cockpits, fuel tanks and the like. This view is known as survivorship bias.
In supply chain planning, many companies make similar mistakes. They focus only on the data they can see, often missing hidden relationships. The AI in the Atlas Planning Platform reduces that bias by analyzing what’s missing, challenging assumptions, and uncovering risks that humans often overlook.
And that’s just one of the ways AI from John Galt Solutions helps supply chain teams make smarter, faster decisions amidst uncertainty.
Learn more by visiting johngalt.com.