Category Archives: rants

DO NOT CONFUSE THE ILLUSION OF UNDERSTANDING WITH ACTUAL UNDERSTANDING!

Because if you do, you will believe AI is Actually Intelligent when, in fact, as we have pointed out again and again and again, it is Artificial Idiocy, and the best modern technology only uses AI for thunking, not thinking, as thinking needs to remain the domain of us humans (before X robs us of our ability to use actual words).

Not only is there no AI, but when you type a command, there isn’t even any understanding by the algorithm of what you are asking for when you type a query into an AI tool. NONE. It’s all based on a statistical algorithm that uses pre-computed similarity probabilities to infer what you are asking. That’s not understanding. Not even close.

The Guardian recently published a long read article on Weizenbaum’s nightmares: how the inventor of the first chatbot turned against AI that anyone who is even mildly contemplating an AI tool needs to read. Slowly and carefully. Three times.

Weizenbaum, who was a mathematician, computer scientist, and a student of psychoanalysis, was one of the founders of modern artificial intelligence who not only invented the first chatbot (Eliza), but also built early (mainframe) computers (back when they used vacuum tubes and took up entire rooms) for the University he was studying at, General Electric, and the Navy. In the 1960s, he was part of Project MAC at MIT, a Pentagon program for “machine aided cognition” that perfected time-sharing, created in-system messaging (like instant messaging or early email), and created new tools for word processing.

He was also one of the first to think about the implications of Artificial Intelligence years, if not decades, before anyone else and one of the founders of computer ethics. He was a genius, and when he said that Artificial Intelligence is an “index of the insanity of our world“, he was totally right — and he was right five decades before AI became the buzz-acronym-du-jour. Few people effectively saw that far ahead in technology, so maybe we should sit back and listen. Carefully.

So please take the time to read Weizenbaum’s nightmares: how the inventor of the first chatbot turned against AI and realize that AI is not the answer. Deterministic algorithms developed by smart people that have studied the problem, tested their assumptions, and been consistently proven reliable are the answer. They may be based on machine learning, but machine learning that is expertly selected, tuned, and monitored by validation code that detects when the algorithm is not performing to expectation and interjects a human into the process. Not a multi-layered pseudo-random statistical algorithm that randomly predicts the next seven days worth of orders, starting on Monday, are 210, 198, 307, 250, 185, 250, and 3095 and thinks everything is A-OK even though the store is closed on Sunday.

There’s No Nearshoring Revolution on the Horizon!

the doctor recently saw a headline that the nearshoring revolution is just beginning, and while he wishes this were true (as he’s been preaching the need for a nearshoring revolution since Sourcing Innovation started, which, for those keeping track, was 17 years ago), it’s not.

A few progressive thought-leading innovators are doing it, but a few is not a revolution. It’s just a few people and organizations who are both willing to do the right thing and wealthy enough to
a) pay for all the upfront costs (where the return may not be recouped for years) involved in shifting a supply chain, bringing new factories online or upgrading those that have been offline for years (or decades) and
b) not be beholden to investors, shareholders, or Wall Street demanding profits now.

The reality is that reorganizing supply chains has a large upfront cost and when most corporations are beholden to shareholders who want profit now, Private Equity firms who want profit now, and Venture Capitalists who want profit now, the last thing they want is upfront cost. They want margin, and the best margins are finding the lowest cost of supply out there and using that, even if it means continuing to source from halfway around the world with all the risks involved (and the losses that would accompany any of those risks), especially if you can buy supply chain insurance at a reasonable cost.

As long as the backward-thinking financial models and economics continue to focus on profit over value or true wealth creation, nearshoring is going to face the same obstacles that Corporate Social Responsibility and Sustainability has faced for the last two decades where everyone says they want it, but unless legally mandated, no one is willing to pay for it. the doctor is aware of multiple surveys that have been conducted in this area over the last couple of decades and while a majority of respondents will say it’s top priority, the majority will not even pay 3% more for a more sustainable product or service as the success criteria they are eventually measured on in Procurement is total “savings” (regardless of the long term cost to society).

The reality is that most corporations bought into the Big outsourcing push of the 1980s and 1990s because their managers and primary shareholders were greedy and wanted profits sooner rather than later, and while that mentality persists, they’re not going to be willing to absorb the upfront costs of shifting back. To truly fix the supply chains, which is as simple as “F*CK China” in the Americas and “F*Ck the Americas” in China as the doctor pointed out in his recent post on how you reconfigure the global supply chain, you need a no upfront cost solution for organizations to switch back, or a value proposition beyond assurance of supply.

In the United States of America, for this to happen the MAGA crowd, instead of wasting all their efforts trying to take away basic human rights away from their citizens (while they are simultaneously trying to put an angry grandpa back in office and hide the huge “gifts” they are getting from certain parties that benefit greatly from laws they pass or block), needs to focus on solutions to actually bring the jobs they are claiming to fight for back to the Americas, which could include:

  • interest free loans for building supply chain infrastructure such as factories, distribution hubs, ports, etc.
  • free, or heavily subsidized, training for Americans to do these jobs
  • higher tariffs on any
    imported products that are produced at sufficient volumes in America to satisfy the American market
  • higher taxes on any
    exported products that should be sold at home

Unless the value is created, or China Sourcing is banned wherever products could be sourced from the USA, Canada, Mexico, or friendly Central/South American states, the nearshoring revolution will not happen. There’s no incentive for it to happen, and no Tribore Menendez taking up the charge!

X

… Logged into Twitter just the other day
Just saw a Big X, seems the bird had flown away
It had two lines and one was double wide
I knew the letter, but I just could not surmise
… Musk didn’t leave a number, not an picture or a clue
But something in that pictogram reminded me of coup

Baby, Musk put the X on top
Voided years of trust and it makes me wanna stop
Baby, Musk put the X on top
Twitter’s going bye-bye, baby, ’cause the branding’s gonna flop

… I saw a sign in the middle of the night
Big flashing X, I was blinded by the light
She said “Oh yeah, you don’t want to be here”
I asked who was calling, but she just hung up in fear
… Sometimes you gotta suffer for the network that you seek
You’re beggin’ for connection but you only want to shriek

Baby, Musk put the X on top
Voided years of trust and it makes me wanna stop
Baby, Musk put the X on top
He thinks he is a master, but he just can’t compare to Aesop
… Oh yeah

I heard an app a-beepin’ so I clicked into the pane
It showed icons, pics, emojis, it’s like it was built to feign
It said that it was “happening“, but it didn’t give a clue
Then I saw that white on black X and I knew that we were screwed!

Baby, Musk put the X on top
Words have been displaced and our IQ’s* gonna drop
Baby, Musk put the X on top
A digital nightmare, it’s the new-age online horror shop!

… with sincere apologies to KISS.

* It’s Official! Twitter Has Made Us Dumber Than Goldfish!
Who’s Smarter? A Twitterer or a Pothead?
Has Twitter Already Turned Too Many Into Twits
Twitter Will Make a Twit Out Of You!

That’s Right, You Do NOT need AI for Automation!

In our last article, we stated that our space was full of Overpriced “AI” you don’t need in source-to-pay, and one of our three examples was “Sourcing Automation” in Sourcing. To be clear, we’re not saying you don’t need automation — the whole point of software has always been efficiency through automation — we’re saying you don’t need “AI” automation.

The reason we’re doubling down into this topic is that we know there are a number of vendors pushing AI Automation and while automation is very good, AI is just not needed. But we know you’re going to get pushback if you echo the doctor‘s viewpoint here, so we’re going to double down into the details and explain why no AI is needed for great automation.

In our last post, we noted that, at its simplest, it’s the ability to auto-source a (set of) product(s) or service(s) once the need has been identified or the request approved. It’s useful, but you don’t need AI to accomplish this, just good-old rule-based (workflow) automation. After all, it’s just

  1. instantiating a new RFP (which can be done if you have a template tied to the product/service types)
  2. distributing it to known, approved suppliers (which is easily done if you have supplier management that tracks approval status and associated products/services)
  3. collecting the bids (automated submission management through a portal or provided spreadsheet for upload)
  4. selecting the lowest bids and marking it as an approved award (simple analytics)
  5. assembling the contracts (with templates, it’s just sucking in the supplier details, product details, and bids using tag-based search and replace)
  6. push it into the e-Signature portal (via the API)
  7. alert the buyer when the contract is ready for signature (via alerting)

1 You just need templates, and good providers have had those for a long time. And “AI” is not going to invent one you can trust.*1 It’s not too hard to tag your (provider’s) existing templates to all of the products and services you buy, and you only have to do it once.

2 When you onboard a supplier, you should tag it as approved, associate it with the products and services it is approved for, look up its risk and environmental scores, and track its performance over time. If it’s performance drops, it can automatically be suspended from consideration for new projects using old-fashioned business rules that will prevent it from being included in events it shouldn’t be. Thus, approved supplier management isn’t that hard to do and simple saved searches find all the suppliers that should be automatically invited to an event.

3 RFP and e-Auction software has been around for 25 years, so don’t let anyone ever tell you that you need AI.

4 If you’re trying to administer an award subject to constraints or goals, that’s good old fashioned strategic sourcing decision optimization. That’s not AI. MILP using classic tableau and interior point algorithms works just fine in predefined scenarios that suck in the organizational constraints … that leading SSDO (Strategic Sourcing Decision Optimization) providers were building over two decades ago.

5 Contract templates should be prescribed by Legal Counsel, not by software flipping random bits using layered statistical algorithms in combinations no one truly understands. The vendor will provide you with templates, but you should be the one reviewing them to make sure they are too your liking. This includes the standard clauses and variation by geography, industry, or risk you want to address.

6 Software integration happened for decades before AI.

7 Alerts have been standard software capability for decades, no AI needed.

If the right data is captured, and the right rules are written, standard workflow-driven software systems can be fully automated without any AI. The only thing preventing them from going from one step to the next is the human verification checkbox being completed. You can turn that off and they will work just fine. So, again, don’t be fooled that you need AI for Sourcing Automation, because you don’t. And with rules-based systems, you’re guaranteed you won’t get the odd, unpredictable result, every 10th sourcing project (because AI is only statistically effective, which means, eventually, it will always fail).

*1 Sure “Generative AI” can generate one. But there’s no guarantee it won’t be hot garbage.

Overpriced “AI” You Don’t Need in Source-to-Pay (S2P)

Everyone and their dog is trying to sell you an “AI” solution. Most of which, as we continually lament is “Automated Idiocy” at best (and “Applied Indirection” at worst, see our article on the April Fools joke vendors are playing on you year round that relaunched SI full time). Some vendors, for select capabilities, actually have the first stage of AI, Assisted Intelligence and a few, for very select capabilities, actually have the second stage of AI, “Augmented Intelligence”, but, and this is what they won’t tell you, especially if you’re a mid-market (MM), you probably don’t need it.

In fact, if you don’t yet have complete S2P, we’d wager that you absolutely don’t need it and likely won’t get an ROI from it, at least not with respect to the price tag they try to charge. (Just like spending more than 120K a year on S2P as a MM generally decreases your Return On Investment [ROI].)

While what is and is not effective and valuable can be situation dependent (just like certain high-priced capabilities can be highly valuable in 10M+ categories but detrimental in 1M categories), there are some capabilities that are almost never valuable, and in this post we will give you some examples, and the reasons therefore, so that you will be able to both analyze whether or not a solution actually has AI AND whether that AI will provide any value.

While there are dozens of capabilities being marketed as AI (which, if implemented using advanced techniques could fall under Level 1 AI), we’ll pick one from three (3) areas as our goal is exposition and not an all-inclusive treatise (that’s a novella, not an article).

Sourcing: Sourcing Automation

What is this? At its simplest, it’s the ability to auto-source a (set of) product(s) or service(s) once the need has been identified or the request approved. It’s useful, but you don’t need AI to accomplish this, just good-old rule-based (workflow) automation. After all, it’s just

  • instantiating a new RFP (which can be done if you have a template tied to the product/service types)
  • distributing it to known, approved suppliers (which is easily done if you have supplier management that tracks approval status and associated products/services)
  • collecting the bids (automated submission management through a portal or provided spreadsheet for upload)
  • selecting the lowest bids and marking it as an approved award (simple analytics)
  • assembling the contracts (with templates, it’s just sucking in the supplier details, product details, and bids using tag-based search and replace)
  • push it into the e-Signature portal (via the API)
  • alert the buyer when the contract is ready for signature (via alerting)

And while very useful for non-strategic and/or low-value categories, no AI is needed. Now, the vendor will counter with multi-round, but guess what, you just implement ceiling, best X, or mandatory response rules before allowing a supplier to progress to the next round and close round one and open round 2 on pre-set dates.

Low bid prediction? i.e. when should the RFX be ended? Guess what, if the platform has anonymized community intelligence, integrates with market data feeds, or supports should-cost modelling (and knows industry average margins), it’s pretty easy to calculate what the low-bid should be (and any bidder that bids lower has likely made an unsustainable bid that should be ignored), and end bidding when you hit that. No AI needed for any of this.

Contract Management: Contract Generation

The ability to auto-assemble a contract is cool, but leading platforms have had it for almost 15 years. How?

  1. A contract template for the category that specifies the clauses that are required, the data that needs to be included, and the meta-data that is needed to assemble the contract correctly.
  2. Default clause templates for each clause, with variants for each geography or industry of interest

That’s it. Then, the system just uses rules to select the template and the clauses and fill in the required supplier, product, and price data from the RFP.

Invoice-to-Pay: Automated Invoice Parsing

Yes, it’s great if you can reduce the number of invoices you need to review from an average of 15% with issues to 1.5%, but let’s face it, you can reduce it to 5% or less with just a little bit of automation, no AI needed.

Almost all invoices are coming in electronic these days, and suppliers that invoice regularly and want to be paid fast will use EDI, XML, or PO-flip through the portal, which means the invoices will come in electronic in an easily parseble format. Missing data / errors will be easily detectable in address, PO field, line items, amounts, etc. when there is an empty field or a mis-match between expected and received data (based on the PO, etc.), etc. and the invoice can be flipped back with notifications of issues for the supplier to correct. Most of the time it will be an honest mistake or oversight and the supplier will happily make the correction to get paid.

The remaining problems will fall into two categories.
1) Those few suppliers that don’t have a solution and have to send PDFs (or images) through e-mail, but those aren’t the suppliers doing massive business (as we’re talking about one time suppliers or consultants for the most part)
2) Those suppliers who don’t accept the requested corrections and have a dispute that needs manual intervention.

With respect to these two categories.
1) An “AI” parsing solution with 80% accuracy is just going to create more manual work, since you will have to correct all the errors anyway (which will be just as much work as entering the data in the first place). (And if the invoice automatically flows through, then it flows through with errors, and that touchless system leads to overspend. Better to touch an extra 3% of invoices and get it right than trust AI that, instead of saving you money, overpays suppliers or sends money to non-existent fraudulent suppliers.)
2) No AI will resolve a dispute. In fact, it will just annoy the h3ck out of the supplier representative and make the dispute worse.

So don’t fall for “AI” in the sales-pitch, even if it isn’t automated idiocy. The vast majority of it you don’t need as good rules-based workflow, configuration, and human ingenuity in the solution still gets the job done (and as the vendors get smarter, the software gets better, and that manually driven best-of-breed software optimized for the process doesn’t make company ending mistakes).