Daily Archives: October 20, 2023

Gartner Inadvertently Makes the Case for NO AI in Supply Chains (which includes Source to Pay)

Gartner, which promotes the use of Generative AI in customer service, even though it did place Generative AI on the Peak of Inflated Expectations on the Hype Cycle for Emerging Technologies, just inadvertently made the best case for never, ever, ever using AI anywhere in the supply chain, including Source-to-Pay, and we love it!

In a press release on their newsroom in late September, where Gartner Says 80% of Supply Chain Not Accounted for in Current Digital Decision Models, the subheading clearly stated that Digital-to-Reality Gap Shows Current Technology Use Fails to Improve Outcomes for Supply Chain Decision Makers.

As a result of this “digital-to-reality” gap, Gartner’s research, based on an analysis of 600 survey responses of supply chain decision makers, not only found that current use of digital models to analyze trade-offs made no meaningful impact on the rate of good decision outcomes but actually found that slightly more bad decisions were made with the use of digital tradeoff analysis than without and marginally increased the percentage of bad decision outcomes. Moreover, More than half of supply chain leaders reliant on digital technology to make a recent strategic decision told us that they felt they would have landed on better decision outcomes without the use of their models, and our analysis suggests that they are correct.

In other words, if source-to-pay and supply-chain decision makers cannot even make decisions when relying on traditional, focussed, machine learning and modelling technology, there’s no chance an unpredictable probabilistic incarnation of Artificial Idiocy that randomly changes its output by the millisecond is going to make good decisions. And the reason is the same — just like traditional (guided) (machine learning) models require good data and a digital representation that covers the majority (if not the entirety) of the process and relevant variables, so do Generative AI models and, in just about every organization on the planet, this necessary digital representation DOES NOT EXIST!

As a result, applying AI without the data it needs to have even a snowball’s chance in h3ll to make a decision is pretty much guaranteed to lead you to worse decisions than you, or any other intelligent human with a decent understanding of the situation, will make without the use of any technology whatsoever.

You don’t need AI, you need end to end process modelling, data collection, data enrichment, data validation, and the ability to use those end-to-end digital tools, interpret the data and recommendations, and make good decisions off of that. And since, with the current rate of digitization, it’s unlikely the majority of organizations will go from 20% supply chain digitization to 80% supply chain digitization (which is the minimum level of digitization you should have before even considering any AI, even for inconsequential decisions) by the end of the next decade, you should not even have AI for decision making on your future roadmap before the next decade rolls around.

the doctor doesn’t say this often, but thank you, Gartner. (Because it really is the case that stupid is as stupid does.)