Beyond the obvious, of course. But let’s backtrack.

A recent article over on Fortune noted that consumer dynamics are shifting like never before while purporting to give us some insights from Executives from Instacart, Atlassian, Nordstrom, and Black & Decker [who] share their strategies. However, the insights it shared related to the challenging technology environment the companies, and teams, face daily and not the consumer market in general, which is a very important topic not covered much by most of the publications and analysts that focus on how great the technology (especially AI-backed technology that may or may not work at all) is, but not how it helps you address the consumers that your organization is in business to serve.

Now, it’s easy to track change in demand if you have a good POS system, a good inventory system, at least weekly (if not daily) synchs, and a good DiY (Do-it-Yourself) Analytics system with baseline trend analysis capabilities that can signal changes in demand, the need for rapid reorders to prevent stock-outs, and increasing changes in demand as a result.

It’s not always as easy to track why. Sometimes there’s a strong correlation between the sales and a particular campaign, between the sales and a sustainability initiative, between the sales and recent price decreases in the product line or price increases in a competitor’s product line, or between the uptick in sales and competitor stock-outs, and in this case it can seem obvious, even if it’s not. For example, the campaign may have had nothing to do with it, it could have been the result of a single influencer promoting the product. The sustainability initiative may have had nothing to do with it, as customers may have known it would only impact the next generation of the product. The price decreases may have had little to do with it because it may have already been one of the lowest priced products available at the time as well as the one with the best brand reputation. The competitor stock outs may not have had anything to do with it because those might have been the higher priced products that were only stocked in low quantities anyway.

Moreover, even if you can determine the why with some statistical confidence, that still does not identify the underlying root cause as to why customers reacted to the campaign, the sustainability initiative, the price decreases, or the stock-outs. Are customers shifting towards your brand, adopting a preference for certain products, responding to certain messaging, or just veering away from certain competitors (or at least certain competitor products).

More importantly, how can you predict these trends early, when they are just starting, so that you can make the appropriate Procurement decisions in time to meet the shift in demand better than your competition. Certainly predictive trend analysis (using traditional machine learning fine-tuned to your problem domain) will help, but only if you can identify the right data sets and indicators, which will also mean being able to detect shifts in early sentiment early. So sentiment analysis (not overblown generalized error-prone Gen-AI) will also help.

But that’s just the beginning. Technology indicates possibilities, maybe even probabilities, but not guarantees. For that, you will need a human based assessment of the situation. And possibly an anthropological one. If you want to get ahead, you will need to think ahead of the crowd.