Monthly Archives: January 2026

Why Do Most Vendor Solutions SUCK (For You) And Why Are Most Overpriced?

In our last post on the final top procurement concern of today (well, to be more exact, much of the last five and possibly the next three to five years), we told you Gen-AI, which is (still) the tech-du-jour, is in many ways no different than every other tech-du-jour we’ve had over the last two decades (Advanced Predictive Analytics, Fluffy Magic Cloud, SaaS, World Wide Web) in that, like all these technologies before, is being presented as a panacea that will solve all your woes while being nothing more than the latest instantiation of silicon snake oil, with the only exception being that its failure rate is higher and its much more dangerous (and even deadly) when wrongly applied.

Unless you’re in the top 10% of technologically proficient Procurement/Supply Chain departments, have, and have mastered, the last generation of tech, you shouldn’t even be looking at it. And even if you are, you should be identifying constrained use cases (where you have nothing else) where you can build, and train, your own custom models and install it with guardrails for the inevitable hallucinations (blackmail, and even murder threats).

So if it’s so bad, why are most (new) vendors building on it? A host of reasons, and none of them good.

GREED: they want to build something quick, sell quicker (on the hype), and exit within 3 to 7 years (through PE acquisition or public offering); they are NOT in it for the long haul and not a company you should be looking at

TQ: more specifically, lack of technical knowledge; they see the hype, they see the ability to rapidly build offerings, they see that the solution works okay in the very small set of hypothetical test cases they train and test it on, and see that if they focus on something specific, they can probably build something without a lot of effort or skill

HYPE: Open-AI, Meta, Microsoft, etc are spending so much hyping the tech, and without a lot of counter-hype (or studies showing the dismal success rates, with the first two significant studies from organizations with clout only appearing late 2025), they want to build on this hype and marketing to sell their solutions (often by integrating with or building on the flawed solutions from the big vendors)

CLUELESSNESS: As I have said before, many founders not only have limited technical competence, but limited market knowledge and even Procurement knowledge. They’ve only worked for two or three companies, which had outdated Source-to-Pay solutions (if any), and are only aware of a handful of solutions. I.E. they looked at the Gartner or Forrester Map (which, as we know, haven’t changed in a decade and only contain decades old suites), did a Google search, looked at the website of the first three results that came back, and decided that there was NOTHING at all that even partially solved the problem they identified at their two or three jobs and only they could build it … even though, as we have shown, there are dozens (to over a hundred) solution for every major function in Procurement and Source to Pay and if none solve the problem fully, quite a few likely come quite close! (Like orchestration.)

That’s why most (AI-first) start-ups today SUCK. There’s a right way to build a solution, and, as you can guess, it’s NONE OF THE ABOVE!

Joel is mostly right. Writing …

Writing is something you try to start and then …

“…you suddenly don’t know how to write”
But at least you’re one step ahead of today’s generation that can’t write at all!

“…that you’re [going to feel like] a fraud”
Whereas the influencers don’t care that they are, and that’s why they are more prolific than you.

“…that you actually maybe don’t know anything”
Which will be a great start if it happens! Great writers actually question what they know.

“…that you can’t possibly be this bad at writing”
But, at least for now, you can, because you haven’t actually written since College/University!

“…that your English teacher was right about you”
I hope not, because if you have this thought, you need to get professional help immediately! (As you
have some serious self esteem problems.)

“…that a caffeinated squirrel could produce better prose”
That will always be the case, but this shouldn’t worry you because they are all too busy with sabotage!

“…that you don’t know how sentences work”
It’s just the English language. The question you need to be asking, does anyone?
Nihongo wa kenmeida.
English is not. No structure! No hard and fast rules. Every time you finally comprehend one more thing about the language, even if it was your first language, you realize two more things just don’t make sense (and wonder what idiot decades, if not hundreds of years, ago decided the word, phrase, spelling, grammar, etc. should be part of it).
This is one of the primary reasons some people confuse Gen-AI output with intelligence as Gen-AI produces near perfect English from a spelling and grammatical viewpoint, even if the meaning is pure nonsense upon deeper inspection.

“…that autocorrect is silently judging you”
And this is why you write offline in an old-school text app (like TextEdit on the Mac if you’re out-of-the-box, or a customized Zed or BBEdit which can be configured to the level of help you want). Then you don’t have to worry about this phobia bothering you.

“…that the blinking cursor is mocking your very existence”
This is also a sign you might need professional help, so if this is what you think, please get it. (Your job is to mock the cursor!)

“…that you should have pursued interpretive dance after all”
Let me be blunt here. If you’re better at communicating without words, this is a good option!
Just remember that it doesn’t pay well unless you get into a top troupe, but still …

“…that cave paintings had better narrative structure”
Joel mixed up his tenses here. Compared to the majority of “content” on social media, cave paintings still HAVE better narrative structure! And are sometimes clearer than the weird constructs “modern” language makes us use.

“…that you’re one backspace away from goat farming”
I wish! That would be a great and noble pursuit! I’d go one step further and also provide a rental service and negate the need for gas guzzling or energy sucking lawn mowers! Plus, goat cheese is easier to digest than cow cheese and goats produce (less than) half (of) the CO2 of cows! It’s a win-win-win all around.

“…that your keyboard is conspiring against you”
Nahhh, it’s just wearing out fast because you are taking your frustrations with yourself out on it. Try not to, it’s not the keyboard.

“…that your draft is sentient and embarrassed by you”
Okay, now you’ve reached full delusional status — check yourself into that psyche ward immediately. Then, when you accept that you’re not, get back to it.

“…that the void is staring back at you while laughing”
Well, we all know this. Lovecraft told us it was so! And it is. But it stares back at us through everything we do, so just accept it. Nothing else you can do!

“…that maybe you were completely mad all this time”
Look, if you haven’t accepted you are completely mad by the point you start writing, why the heck are you trying to write? (We’ll get back to this one.)

“…that you should communicate with hand gestures now”
Well, learning ASL would be a fantastic option! Instead of just another language, it’s a whole new way to communicate. And would allow you to communicate more silently and focus more on your thoughts that will help you with your writing.

“…that maybe society peaked with smoke signals”
Any society that is able to function self-sufficiently and harmoniously with nature is a peak society, even if it uses smoke signals for communication. Many of these societies invented some form of writing, so it shouldn’t stop you.

“Writing is masochism but with better branding.”
No, it’s just pain. There’s no pleasure. And you have to be stark raving mad to want to do it. You do it for the greater good. Not just because it forces you to crystallize, cement, and confirm your thoughts (as some people can learn to do that through mediation), but because it helps you simplify them in a way you can convey to others (willing to read and think) so that they too can consume and conceive of the benefits!

“Realize 3 months later that the writing got a bit easier …”

Nope! Because there’s a 99%+ chance that you won’t make it that long! I chronicled the rise and fall of the blogs for over a decade (and while the resource site is now offline, I still have the database backup that contains hundreds of dead blogs and sites).

The rise (and fall, and rise again) of blogging, newsletters, and podcasting all follow(ed) the same pattern:

  • 90% didn’t survive beyond the 3rd entry/3rd day
  • a significant number essentially died by the 32 entry/3rd week
    (as frequency became sparse)
  • 90% of those that remained after the 3rd entry/day didn’t survive beyond the 33 entry / 3rd month

And since social media posting is just Web 3.0 Blogging … odds are 99 to 1 you’re not going to make it 3 months. Sad, but true.

If You Think You’re Ready for AI, You’re Not Ready for AI!

All of the Big Analyst Firms, Consultancies, and Vendors are telling you that you need AI, that it’s the only technology that’s going to allow you to get with the digital times, and that everyone else is using it, so you should too.

But the reality is that you probably don’t need AI, it’s not the only technology that can bring you up to date in the digital age, and while many people are using it, 94%/95% are FAILING.

The only hope you have to succeed is to be brutally honest, to ADMIT what you don’t know, that you’re only chasing AI because of FOMO and FUD, and that real progress has always been methodical and one step at a time.

More specifically, from where you are starting, not from where the market pretends you are.

The only organizations that have been successful at AI are those that:

  • honestly assess where they are today
  • determines their readiness for change
  • identifies the most time consuming processes they are willing to change
  • identifies the appropriate automation one process at a time, which is often just simple workflows/RPAs/built-in automations in existing platforms and other times ML/ARPA
  • monitors and tweaks them until they run smoothly and reliably
  • uses modern meta-workfows/ARPA/AI to connect the individual automations together where, and only where, it makes sense
  • only slaps guard-railed semantic tech / focussed SLMs on top to provide a natural language interface that processes inputs and outputs fixed action requests where appropriate

Successful companies don’t go all in an unproven tech, don’t try to do big bang projects (as that only results in big failures and sometimes the greatest supply chain disasters of all time), and definitely didn’t take the advice of the BIG X that promoted multi-year modernization mega-projects with no successes that they can point to.

In other words, the only companies that have succeeded with AI (the 5% to 6% depending on if you would rather go with McKinsey or MIT) are those that learned from the mega-ERP disasters of yesteryear and did a sequence of successive mini-projects that each built on the lass and slowly ramped to mega success.

In other words, they understand that you have to crawl before you can walk and walk before you can run. And if you can’t even crawl, you’re not ready to try and run at the Olympics, which is the level of tech maturity you have to be at to HOPE to succeed with AI.

Dangerous Procurement Predictions Part III

As per our first two posts, if you read my predictions post, you know SI hates predictions posts. It fully despises them because the vast majority of these posts are pure optimistic fantasy and help no one. Why are the posts like this? Because no one wants to hear the sobering reality off of the bat in the new year and the influencers care more about clicks than actually helping you.

But the predictions are not only bad, they’re dangerous if you believe them. So we are continuing to lay bare the reality of the situation to make sure you understand that this year isn’t much different than last year, no miracles are coming, and only hard work and the application of your human intelligence are going to get you anywhere. Today we tackle the next three, and while we hope we’re getting close to the end of the series, we’re pretty sure there will be at least one more entry.

8. Global Trade Will Shift, Prioritizing Resilience Over Cost.

In the mid to long term some trade will shift to prioritize resilience, but most trade won’t. While defence procurements, critical mineral and material acquisitions for high-end electronics, and valuable commodities that can be traded like currency (such as gold, silver, platinum, diamonds, etc.) will be shifted for resilience, the reality is that, even with natural disasters, sanctions, trade wars, and actual wars, most companies aren’t going to make any changes to their supply chains (unless given absolutely no choice) because

  • finding new suppliers (in new countries) takes time and effort
  • qualifying new suppliers (in new countries) takes time and effort
  • identifying and contracting reliable carriers takes time and effort
  • building and securing new supply lines takes time and effort
  • etc.

and most companies are in constant fire-fighting mode, overworked, overstressed, and they just don’t have the time as long as the current supply chain, while strained, still works. Until their supply completely dries up, their primary production lines and revenue streams are threatened, and they have no other choice, they won’t change because they’ll keep telling themselves random natural disasters won’t impact them, the tariffs are only temporary, sanctions change with administrations, and wars eventually end.

9. Your employees will orchestrate outcomes.

Woody Woodpecker, take it away!

The level of talent needed to orchestrate outcomes is well beyond the average level of talent in an average (and even most above average) Procurement Department(s). There’s a reason that talent is a concern, a <href=”” target=_blank>top risk, and a top barrier for not just the last five years of studies and surveys, but at least the last ten. Talent has been scarce for a decade, and the situation is much worse since COVID. COVID saw many early retirements of the forced and chosen variety. Then the constant fears of recession saw more layoffs, starting with the highest paid (and most experienced) talent first. And you can be damn sure many of them are not coming back. We told you a year ago that talent is about to become scarce, and we’re sad to say we think we underestimated just how scarce talent is about to become.

And the reality is that only top talent can orchestrate outcomes. All the vast majority of talent can do is execute tasks one by one in a well-defined process. They can’t create new processes, and they certainly can’t define new outcome-centric processes on the fly. Especially when the ORCestration platforms they are given can’t even “orchestrate” a process to lead a mouse to the cheese it desperately wants.

10. New Year, New Me.

Who were you last year?

That’s right, the same person you are this year.

This BS lasts until all the bubbly you drank on New Year’s eve wears off, the rose coloured glasses go dim from the glare of doing the same damn thing as you stare at the same damn screen 12 hours a day, and you get overwhelmed with all the same tasks you were doing last year. Within two weeks at most, the new year, new me bullcr@p disappears with your last new years resolution and you’re just fighting to survive being overworked, understaffed, underfunded, and under-resourced, especially on the tech side (because the C-Suite wasted all the budget on a Big X Consultancy Gen-AI project that never even got to beta testing because the prototype phase never actually worked).

Most people won’t even make an effort to improve, which is the best one can hope for! (So if you have an employee who does, proactively give them a raise, any training they ask for, and keep them. Because, as per our response to the last false, and dangerous, prediction, talent is scarce and you should do whatever you can to keep whatever talent you have [instead of trying to replace it with fake AI that will never work fully autonomously].)

Primary ProcureTech Concern: (Gen-)AI Integration/Impact

The non-stop hype coming straight from the A.S.S.H.O.L.E. is continuing to cause market confusion and utter chaos.

Why?

Gen-AI is on the concerns list because it’s the tech-du-jour. Five years ago it was (advanced) (predictive) analytics. Ten years ago it was the fluffy magic cloud. Fifteen years ago it was SaaS. Twenty years ago it was the World Wide Web. And so on.

But not one of these technologies, all sold as the panacea that would solve all your woes, solved your problems because all of the promised capabilities were just silicon snake oil, and Gen-AI is no different. The hype cycle may be slowly coming to an end, but it will quickly be replaced by Some-BS-World-Model-Adjacent-Agentic-AGI that will be sold as the AI that finally solves all your problems but, in reality, still won’t be anything close (but, if narrowly applied in the right domains where the client has sufficient data might actually work quite well … but won’t do anything reliably in general and the failure rate will still be 80%+, which is the average tech failure rate for the last 25 years … and SI knows, because the doctor has been following tech failure for over 25 years).

Not only is Gen-AI no different than the previously over-hyped tech-du-jour offerings of the last two decades, but with a failure rate of 94%+ (McKinsey, and 95%, MIT), it’s arguably the worst yet! And, as per our predictions, it’s not going to get much better. If the failure rate gets as low as 90% this year, it will be the closest thing to a tech miracle that we can conceivably get. Like every other tech before, Gen-AI will only solve a relatively small set of problems.

Just like

  • The Web only solves remote connectivity
  • SaaS only allows solutions to be built in the cloud
  • Analytics only provides insight where you have the right, sufficient, data and the right algorithms to get useful insights
  • Gen-AI is just a next-gen probabilistic deep neural net that often does
    • better semantic processing
    • better search
    • better summarization
    • better potential pattern identification (but only if you can learn how to prompt it to do so and only if you have it trained on the right data subsets, not the entire web which is now more than half AI slop)

    but does so at the additional expense of

    • hallucinations
    • intentional falsehoods
    • thoughtless reinforcement
    • cognitive atrophy
    • etc. etc. etc.

As a result of this, as far as I’m concerned, the AI bubble can’t burst fast enough! It’s all hype, buzzwords, and hallucinatory bullcr@p. And, frankly, any (claims of) agentic AI built on it are fraudulent. (After all, we’ve already seen what happens when you let AI run your vending machine. The last thing you want is it buying for you!)

Especially when, on top of hallucinations, we have plenty of examples of:

We’ve said many times that LLMs are not helpful and ChatGPT (in particular) is not your friend, that if you have a headache you definitely shouldn’t take an aspirin or query an LLM, and that, frankly, you’d be better off with a drunken plagiarist intern because that’s the best case result from an LLM. Most are worse.

Frankly, it’s time to stop falling for the artificial intimidation, fight back against AI Slop, and remember cutting edge tech is NOT defined by the C-Suite or the incessant marketing from the A.S.S.H.O.L.E. that is targeting the C-Suite on a daily basis!

Impact Potential

Huge! Companies will continue to waste millions individually and collectively hundreds of billions on the next generation tech that, with a probability of 90%+, will generate a (huge) loss.

Major Challenges/Risks

The major challenge is not with the tech, it’s helping companies realize that they’re probably not ready for the tech. The reason that tech failure rate has averaged 80%+ over the last twenty years is that consultancies keep promoting, vendors keep selling, and companies keep buying advanced leading edge tech they are not ready for. The reality is that unless you are in the top 10% of buyers of tech, already on the latest tech, and have sufficiently mastered that tech, you are not ready for Gen-AI (which should not have left the research lab when it did and, in all honesty, should still be in the research lab since it still only works in a small number of well defined scenarios and is so bad that every year a couple of AI founders turn away from AI because of it — with Yann Lecun walking away from Meta and LLMs and reverting to world models, that can be thought of as next generation (Semantic) Web 3.0 models augmented with [deterministic and dependable] automated reasoning and, hopefully, very little dependence on hallucinatory probabilistic models [beyond what’s needed to semantically parse an input].)

The only place you should be using Gen-AI is where a non Gen-AI solution doesn’t exist, the task is well defined, and you can build a custom in-house model that works reasonably well in the majority of situations and that can be implemented with guard-rails. But that’s something you can only do if you have a high TQ (Technical Quotient) and have mastered last generation tech. Right now, you should be tripling down on E-MDMA and Advanced Analytics as this tech has improved to the point where it can allow you to optimize processes, spending, schedules, and anything else you can think of with high accuracy and low cost with basic analytics skills as so much comes pre-packaged and the visualizations and drill-downs are much more intuitive than they were a decade ago. Plus, these firms have figured out how to use multiple forms of AI to classify your data with high accuracy and minimize the work required by you to fix errors and reclassify to your preferred schemas. It’s literally drag and drop as compared to the complex rule-building that used to be required. In addition, you should be looking for the mature A-RPA (Advanced Robotic Process Automation) solutions that are highly customizeable and capable of “self-learning” such that the parameters that trigger exceptions will adjust over time based upon user acceptance or rejection of recommended actions and the platform will automatically encode new processing rules based upon the users’ actions on an exception. Much better than Artificial Iiocy that decides everything based on hallucinations.

THE FINAL WORD

If you haven’t mastered all of the tech that existed before Gen-AI, including classical machine learning AI that has been studied, optimized, and proven to work for over a decade, you’re not ready for Gen-AI, should treat it like the drug it is (as it does more damage to your cognitive abilities than many illegal drugs), and JUST SAY NO!