Don’t build weapons of math destruction

This is an excerpt of the original article. It was written for the March-April 2019 edition of Supply Chain Management Review. The full article is available to current subscribers.

March-April 2019

A few days ago, a colleague sent me “The Death of Supply Chain Management,” an article in the Harvard Business Review. If the title wasn’t enough to grab my attention, the last sentence in the first paragraph had me checking out job openings on LinkedIn: “Within five years to 10 years, the supply chain function may be obsolete, replaced by a smoothly running, selfregulating utility that ….. requires very little human attention.” Read more carefully, what the authors are really arguing is that as NextGen technologies find their place in our organizations, the role of the supply chain manager, including procurement managers, is going to…

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Upon reviewing a model with my first manager at Arthur D. Little, I learned an important lesson. He taught me that while it is important to demonstrate that a model has scientific validity, it is equally important to have “face validity.” Translation: To be useful, a model needs to be statistically sound in representing the real world. But, it must also make sense to managers by incorporating factors that make sense to them.

I am astounded to find that many of the Internet-based Big Data models today only have face validity; apparently developers don’t care about scientific validity. They believe that if a model’s factors seem to relate to dependent factors, those are sufficient. For business models, face validity is necessary, but not sufficient. Indeed, face validity alone might be potentially dangerous. I gained this insight by reading “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy,” a book by Dr. Cathy O’Neil.

What is a weapon of math destruction?

Dr. O’Neil, a former quantitative analyst at a financial hedge fund, experienced first-hand the damage financial models did leading up to and following the mortgage market meltdown of the past decade. They helped the collapse of financial institutions. She became disillusioned with mathematical models that affect society. Or, as one description of the book puts it: “A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life—and threaten to rip apart our social fabric.”

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