Recent Posts by Patrick Smith

Crossing the Great Forecasting Divide Part 2 – Consumption Sensing is New Forecasting Frontier

In my last post, I focused on how retailers and consumer products companies can triage through the worst of the COVID pandemic as consumers were adjusting to a stay-at-home lifestyle. I discussed using a hybrid model of humans and AI/ML-based approaches, delivering science-as-a-service, to bridge the gap and react quickly to the dramatic swings in demand.

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Crossing the great forecasting divide – make the transition with manual processes and AI/Machine Learning

It is true – forecasts from existing demand planning systems, built largely on historical data, will be significantly off, both during and after the pandemic. To quote Yogi Berra, “It’s tough to make predictions, especially about the future.” And right now, we are experiencing an event that hasn’t happened since 1918 providing very little historical experience to draw upon.

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