Back in late 2018 and early 2019, before the GENizah Artificial Idiocy craze began, the doctor did a sequence of AI Series (totalling 22 articles) on Spend Matters on AI in X Today, Tomorrow, and The Day After Tomorrow for Procurement, Sourcing, Sourcing Optimization, Supplier Discovery, and Supplier Management. All of which was implemented, about to be implemented, capable of being implemented, and most definitely not doable with, Gen-AI.
To make it abundantly clear that you don’t need Gen-AI for any advanced enterprise back-office (fin)tech, and that, in fact, you should never even consider it for advanced tech in these categories (because it cannot reason, cannot guarantee consistency, and confidence on the quality of its outputs can’t even be measured), we’re going to talk about all the advanced features enabled by Assisted and Augmented Intelligence (as we don’t really have true appercipient [cognitive] intelligence or autonomous intelligence, and we’d need at least autonomous intelligence to really call a system artificially intelligent — the doctor described the levels in a 2020 Spend Matters article on how Artificial intelligence levels show AI is not created equal. Do you know what the vendor is selling?) that have been available for years (if you looked for, and found, the right best-of-breed systems [many of which are the hidden gems in the Mega Map]). And we’re going to start with Procurement.
Unlike prior series, we’re going to mention some of the traditional, sound, ML/AI technologies that are, or can, be used to implement the advanced capabilities that are currently found, or will soon be found, in Source-to-Pay technologies that are truly AI-enhanced. (Which, FYI, might not match one-to-one with what the doctor chronicled five years ago because, like time, tech marches on.)
Today we start with AI-Enhanced Procurement that was available yesterday (and, in fact, for at least the past 5 years if you go back and read the doctor‘s original series, which will provide a lot more detail on each capability we’re discussing. (This article sort of corresponds with AI in Procurement Today Part I and AI in Procurement Today Part II published in November, 2018 on Spend Matters.)
YESTERDAY
TRUE AUTOMATION
Not sorry to burst the Gen-AI believers’ bubble, but true automation has existed in leading Procurement technology for almost two decades, using tried-and-true rules-based RPA that supports advanced rule construction using the full breadth of boolean logic, mathematical formulae construction, and flexible (regex, clustering, etc.) pattern matching.
SMART AUTO RE-ORDER
Threshold re-order points, adaptive trend analysis (based on sales data for quantity, expected delivery time and economic order quantity for interval and volume determination), and contract/preferred suppliers can handle this better than most stock clerks for MRO / commodity stock items.
GUIDED BUYING
All you need to do this amazingly well is RPA, rules based on contract/preferred/budget, and semantically aware keyword/phrase matching, and, if you want a NLI (Natural Language Interface), traditional semantic processing to extract the key-words/phrases that are the appropriate nouns (and items of interest).
SMART (ADAPTIVE) AUTOMATIC APPROVALS
This is just RPA using a rules based workflow, thresholds, and exception-based decision pattern analysis to allow the thresholds to be adjusted within a range based on an approval and/or the platform to infer the thresholds/rules actually being applied by the approver using pattern identification (based on significant factor analysis or fingerprinting) across exceptions to suggest the necessary rule modifications.
ERROR PREVENTION
This just requires valid pattern definition, context-based range analysis, and outlier detection (using clustering, curve fitting, or trend analysis). Anything that can’t be done with the right mix of these methods can’t be done reliably.
M-WAY MATCH
Anything you can’t do with RPA using rules-based workflow, identifier matching, and confidence-based pattern matching and suggestion SHOULD NOT BE DONE. Moreover, anything that can’t be matched with certainty should be flipped back to the supplier for correction/completion (if key identifiers were missing), possibly with a suggestion/question (for e.g. does this invoice correspond to PO 123XYZ?).
SUMMARY
Now, we realize this was very brief, but again, that’s because this is not new tech, that was available long before Gen-AI, which should be native in the majority (if not the entirety) to any true best-of-breed Procurement platform, that is easy to understand — and that was described in detail in the doctor‘s 2019 articles for those who wish to dive deeper. The whole point was to explain how traditional ML methods enable all of this, with ease, it just takes human intelligence (HI!) to define and code it.