Category Archives: AI

Why Do Outsourcing and AI Go So Wrong?

In a recent post on how We Need to Hasten Onshoring and Nearshoring, Jon The Revelator was inspired to ask the following question:

even though outsourcing and AI have merit when properly implemented, why do things go so wrong?

This was after noting, in another post, that we have suffered year-by-year, decade-by-decade disappointment when 80% (and even higher) of initiatives fail to achieve the expected outcome.

Because in both cases [and this assumes the case where the organization is implementing real, classic, traditional AI for a tried-and-true use case and not modern Gen(erative) A(rtificial) I(diocy)], things have gone wrong, and sometimes terribly wrong, on a regular basis.

So, the doctor answered.

Fundamentally, there are two reasons that things consistently go wrong.

The first reason is the same reason things go so wrong when you put an accountant in charge of a major aerospace company or a lawyer in charge of a major hobby gaming company (when the first has zero understanding of aerospace engineering and the second of what games are and what fans want from them).

Like the accountant and the lawyer, they don’t understand their organizational and stakeholder/user needs!

The second major reason is that they don’t understand what these “solutions” actually do and how to properly qualify, select, and implement them. And, most importantly, what to realistically expect from them … and when.

A GPO is not a GPO is not a GPO — these Group Purchasing Organizations specialize by industry and region; and in making an impact by category and usage. They are not everything for everyone.

AI is not AI is not AI (unless it’s all Gen-AI, then it’s all bullcr@p). Until Gen-AI, the doctor was promoting ALL Advanced Sourcing Tech, including properly designed, implemented, and tested AI, because the right AI was as close to a miracle as you’ll get. (And the wrong AI will bankrupt you.) Now, any AI post 2020 is suspect to the nth degree.

Simply stated, the failures are because they all think they can press the big red easy button and throw it over the wall. But you can’t manage what you don’t understand! And until the world remembers this, these failures will continue to happen on a consistent basis.

And, as organizations continue to press that Gen-AI powered “easy” button while outsourcing more and more of their critical operations, expect to see a resurgence of the big supply chain disasters, like the ones we saw in the 90s and the 00s (including the ones which wiped out Billion $ companies). Hard to believe that only nine years ago the doctor was worried about companies relying on outdated ERPs ending up in the supply chain disaster record books, given how many of the disasters were the result of a big-bang ERP implementation. However, the risks associated with Gen-AI makes ERP risks look like training wheel risks!

As a result, it’s more critical that you select the right provider and / or the right solution if you want a decent chance of success. (The worst part of all this is that while there have been spectacular failures, most of the failures were not the result of selecting a bad provider or a bad solution, but the result of selecting the wrong provider or the wrong solution for you. (Remember, provider sales people are not incentivized to qualify clients for appropriateness, they are incentivized to sell. It’s your job to qualify them for you. In other words, even though there are bad providers and bad solutions out there, they are considerably fewer than there were in the days when Silicon Snake Oil was all the rage.) In the majority of failures, primarily those that weren’t spectacular failures, the providers were good providers with good people, but when the solution they offer is a square peg for your smaller round hole, what should be expected?

More Valid Uses for Gen-AI … this time IN Procurement!

Some of you were upset that my last post on Valid Uses for Gen-AI weren’t very Procurement centric, arguing that there were valid uses for Gen-AI in Procurement and that the doctor should have focussed on, or at least included, those because why else would almost every vendor and their dog be including “AI” front and center on their web-site (about 85%+)!

Well, you’re right! To be completely fair, the doctor should acknowledge these valid uses, even if they are very few and very far between. So he will. Those of you following him closely will note that he mentioned some of these in his comment on LinkedIn to Sarah Scudder’s post on how “AI is a buzzword“.

AI is a lot more than a buzzword, but let’s give Gen-AI it’s due … in Procurement … first.

With Gen-AI you can:

1. Create a “you” chat-bot capable of responding to a number of free-form requests that can be mapped to standard types.
This is especially useful if the organization employs one or more annoying employees who always waits too long to request goods and then, after you place the order, insist on emailing you every day to ask “are they here yet” in reference to their request, even though you flat out told them the boats are coming by ship, it takes 24 days to sail the goods across the ocean once they are on the ship, typically 3 days to get them to the port, 3 to 14 days to get them on that ship, 3 to 7 days to get the ship into a dock, 3 to 4 days to unload the ship, and 3 to 4 days from the fort, for a minimum delivery time of 35 days, or 5 weeks, and asking week one just shows how stupid this employee is.

2. Similarly, you can create a “you” chatbot for RFP Question Response.
More specifically, you can create a bot that can simply regurgitate the answers to sales people who won’t read the spec and insist on emailing you on a daily basis with questions you already answered, and which they would realize if they weren’t so damn lazy and just read the full RFP.

3. Create meaningless RFPs from random “spec sheets”.
Specifically, take all those random “spec sheets” the organizational stakeholder downloaded from the internet just so you can check a box, send it out, and make him happy. (Even though no good RFP ever resulted from using vendor RFP templates or spec sheets.) Which is especially useless if you have a subscription with a big analyst firm that includes helping you identify the top 5 vendors you are going to invite to the RFP where you will focus on the service, integration, implementation, and relationship aspects as the analyst firm qualified the tech will meet your needs. (After all, sales, marketing, human resources, and other non-technical buyers love to be helpful in this way and don’t realize that just about every “sales automation”, “content management”, and “application system” has all of the same core features and you can usually make do with any one of a dozen or more low-cost “consumerized” freeware/shareware/pay-per-user SaaS subscriptions.)

4. Or, do something slightly more useful and auto-fill your RFPs with vendor-ish data.
You could use the AI to ingest ALL of a vendor’s website, marketing, and sales materials as well as third party summaries and reviews and auto-fill as much of your RFP as you can before sending it to the vendor, and then approximately score each field based on key words, to ensure that the vendor is likely capable of meeting all of your minimum requirements across the board before you ask them to fill out the RFP and, more importantly, spend hours, or days, reviewing their response.

5. Identify unusual or risky requests or clauses in a “ready to go” contract.
Compare the contract draft handed to you by the helpful stakeholder to the default ones in your library that were (co-)drafted by actual Procurement professionals and vetted by Legal and don’t have unusual, risky, or just plain stupid clauses. For example, an unvetted draft could have a clause that says your organization accepts all liability risk, you agree to pay before goods are even shipped, you’ll accept substitute SKUs without verification, etc. (because the helpful stakeholder just took the vendor’s suggested one-sided contract and handed it to you).

6. Automatic out-of-policy request denial.
Program it to just say “denied” for any request that doesn’t fall close to organizational norms.

7. Generate Kindergarten level summaries of standard reports for the C-Suite.
Got a C-suite full of bankers, accountants, and lawyers who don’t have a clue what the business actually does and need simplified reports translated to banker-speak and legalese? No problem!

Of course, the real question is to ask not what Gen-AI can do for you but what can you do without Gen-AI because the doctor would argue that you don’t need Gen-AI for any of this and that the non-Gen-AI solutions are better and more economical!

Let’s take these valid uses one-by-one:

1. You could hire a virtual admin assistant / AP clerk in the Phillippines, Thailand, or some other developing country with okay English skills to do that for 1K a month!
Furthermore, this full time worker could also respond to other, more generic, requests as well, and do some meaningful work, such as properly transcribing hand-written invoices (or correcting OCR errors), etc. And give your employees the comfort of a real, dependable, human for a fraction of the cost of that overpriced AI bullsh!t they are trying to shove down your throat.

2. Classic “AI” that works on key phrases in the hands of the admin assistant will work just as well.
It will find the most appropriate data, and then the admin can verify that the question can be answered by the paragraph(s) included in the RFP, or that the sales person actually read the RFP and is asking for a clarification on the text, or a more detailed specification. The sales person gets the desired response the first time, no time is wasted, and you haven’t p!ssed off the sales person by forcing him to interact with an artificially idiotic bot.

3. When they said the best things in life are free, they weren’t referring to vendor RFPs.
In fact, those free RFPs and spec sheets will be the most expensive documents you ever handle. Every single one was designed to lock you into the vendor’s solution because every single one focussed not on what a customer needed, but the capabilities and, most importantly, features that were most unique to the vendor. So if you use those RFPs and sheets, you will end up selecting that vendor, be that vendor right, or wrong, for you. The best RFPs and spec sheets are the ones created by you, or at least an independent consultant or analyst working in your best interest. No AI can do this — only an intelligent human that can do a proper needs, platform, and gap analysis and translate that into proper requirements.

4. Okay, you need AI for this … but … traditional, now classic, AI could do that quite well.
Modern Gen-AI doesn’t do any better, and the amount of human verified documents and data you need to sufficiently train the new LLMs to be as accurate as traditional, now classic, AI, is more than all but a handful of organizations have. So you’re going to pay more (both for the tech and the compute time) to get less. Why? In what world does that make sense?

5. Okay, you need NLP at a minimum for this, but you don’t need more. And you barely need AI.
All you have to do is is use classical NLP to identify clause types, do weighted comparisons to standard clauses, analyze sentence structures and gauge intent, and identify clauses that are missing, deviating from standard, and not present in standard contracts. And, as per our last use, do it just as well without needing nearly as much data to effectively train. Leading contracts analytics vendors have been doing this for over a decade.

6. Even first generation e-Procurement platforms could encode rules for auto-approval, auto-denial, and conditional workflows.
In other words, you just need the rules-based automation that we’ve had for decades. And every e-Procurement, Catalog Management, and Tail Spend application does this.

7. Any semi-modern reporting or analytics platforms can allow the templates to be customized to any level of detail or summary desired.
And if you have a modern spend analysis platform, this is super easy. Furthermore, if your C-Suite is filled entirely with accountants, bankers, and lawyers who don’t understand what the business does, because they fired all the STEM professionals who understood what the business actually does, then your organization has a much bigger problem than reporting.

In other words, there isn’t a single use case where you actually need Gen-AI, as traditional approaches not only get the job done in each of these situations, but traditional approaches do it better, cheaper, and more reliably with zero chance of hallucination.

At the end of the day you want a real solution that solves a real problem. And the best way to identify such a solution is to remember that Gen-AI is really short for GENerated Artificial Idiocy. So if you want a real solution that solves a real problem, simply avoid any solution that puts AI first. This way you won’t get a “solution” that is:

  • Artificial Idiocy enabled
  • Artificial Idiocy backed
  • Artificial Idiocy enhanced
  • Artificial Idiocy driven

As Sarah Scudder noted on “AI is a buzzword“, AI is a delivery mechanism which, scientifically speaking, is a method by which the virus spreads itself. This is probably the best non-technical description of what AI is ever! And the best explanation of why you should never trust AI!

Valid Uses for Gen-AI!

the doctor has been told he’s too hard on Gen-AI. He doesn’t think he’s hard enough, but there are those who keep insisting that Gen-AI has some valid uses. And they’re right, it has some. Not the uses that you need it for, but actual uses nonetheless.

So today, in a rare moment of weakness, he’s going to acknowledge those uses. Soak it in. He may never do so again.

1. Ensure your insurance / bank only covers and lends to people you like.
One of the great things about Gen-AI is that almost all models are biased, and it’s really easy to train them to be as biased as you want. Only want your health insurance to accept only young people between 25 and 40 with no family history or indicators of any illness whatsoever? No problem. Don’t want your bank to approve a loan to anyone who isn’t an all American Christian white? No problem. Race-Biased Gen-AI to the rescue!

2. Have it make up a new story for your child who constantly wants new stories every night.
Train it on thousands of stories kid suitable and it will make up a new story every night (with a high probability of most those stories being safe and suitable — chances are only a few will scare them into therapy). Your kid will be happy (at least until they get scared into therapy) and your brain will get the rest it needs at night (so it can start worrying about how it’s going to pay for that therapy). Put those constant hallucinations to use. It’s your own personal Scheherazade, with just a little bit of Grimm and occasionally a bit of King (Stephen).

3. Incite the mob.
Need a mob behind you to get your cause front page on the headlines? Incite a mob to cover your theft attempt at a corporate headquarters above a luxury department store? Maybe even help you overthrow a capitol? No sweat! Program that Gen-AI to be as hateful and incitory as possible and have it pump out fake news propaganda 24/7 until you have the mob you need on your side and there you go!

4. Scam the Scammers. (Or at least keep them busy and out of your inbox.)
Most scammers will keep trying as long as someone is responding to them (and eating up their time). Guess what AI has a lot of — GPU time. Most models have 10,000 (or more) GPUs at their disposal. That’s a lot of scammers an AI can tie up for you. (Especially if they can’t differentiate easy pickings Grandpa Joe from a very agreeable but completely broke GrandpAI Joe.)

5. Take down a rival’s network.
Simply train in some sleeper behaviour for a few months into the future, and once the competition is done with their tests and trust it … poof … down goes their network.

And if you want to be truly evil, you can always use Gen-AI to

6. Ensure your terror campaign is as lethal as possible.
We’ve read the stories of how even recent tests of self-driving systems decided to ignore the shadows of what were actually people RIGHT in front of them and drive into those shadows at full speed. A few minor alterations and instead of avoiding people-like figures and shadows, it will be the murderous trolley that tries to kill as many as possible. And who says you have to limit it to trolleys? Use it to program bomb-bearing drones and it will seek out the densest crowd possible. And so on. And yes, we went to a very dark place, but just where do you think AI is taking us? There are currently NO bright outcomes. Ponder that before you go singing its praises.

Of course, if you just want to be a little chaotic around the house, and only take that first step down the dark path, just hook up it’s hallucinatory outputs to a random direction generator and use it to:

7. Power your Roomba.
Your pets will think it’s truly possessed!

So there you go — 7 valid uses of Gen-AI. You decide how many of them you want to use.

It’s a Wild Wild West, and (Gen-) AI won’t tame it!

In this linked post, Jon the Revelator shares his thoughts about “supply chain orchestration”, which is, in his words, the latest incarnation of “agent-based modelling within a dynamic Metaprise” (probably because no one understood what a Metaprise was, no one in their right mind would want to live in a Metaverse, and orchestration just sounds cool). After all, the technical definition of “a synchronized [versus sequential] architecture (private hub) that simultaneously links or incorporates the unique operating attributes of all transactional stakeholders on a real-world, real-time basis” is pretty close to what orchestration does, which today is supposed to link all the systems the organization uses to capture the unique operating attributes of the different transactional stakeholders.

Jon also notes that stakeholder input is required to lay a solid foundation, and that orchestration cannot forget the people aspect, as people are responsible for Procurement. This is where most systems fail today. They don’t focus on usability, stakeholder connectivity, or end user enablement. The process is important, as is automation capability, but it’s not about AI (and definitely not Gen-AI which is just Artificial Idiocy), but Augmented Intelligence where the system automates the tactical and not only allows the user to focus on the strategic, but provides enhanced intelligence to enable strategic analysis. Machines are great at the repeated error-free calculations required for thunking, but they are definitely not great at strategic thinking.

As a result, while software can be a tool to tame the wild west of Procurement, it will only be if it is the right software tool in the hands of an old Pro who knows when to grab the reins and when to grab the Colt 1860. And only an old pro will understand what to look for in a reliable tool, because, unlike the new generations, we don’t fall for “the new hotness”. (Check the comments.)

Will AI Make Us Irrelevant?

Short Answer: No. But Improper Use Will Make Us “Redundant.

James Meads asks “Will AI in Procurement make us all irrelevant?”

So I will answer. No, it won’t! But it will make those companies who dive off the deep-end on Gen-AI irrelevant as their supply chains crumble with no real human intelligence there to save them when the next crisis hits. (See the myriad of rants here on Sourcing Innovation on just how over-hyped Open Gen-AI technology is and what you actually need to solve your problems.) Also, if we’re lucky, they will take a few providers with no actual platform capability (or Procurement value) down with them. (We need them to get out of the way for those platforms that have been offering real, deterministic, math-based, tried-and-true analytics, optimization, and machine learning solutions [for up to two decades] as there are many companies that need those solutions today.)

While custom-trained closed LLMs can seemingly do a lot of the work for us, they are NOT intelligent, they don’t know good from bad, they don’t know right from wrong, and they definitely don’t know critical from irrelevant. Thus, even though they can put together an NDA or RFP in seconds, it doesn’t mean it’s “fully functional”, that it protects you from all the risks, or that it captures all your requirements. Only an expert human can verify that. [And it doesn’t matter how good your “prompting” is. It can still fail, with a reasonably high probability to boot! (Which is what you can give it!) There’s a reason that Tonkean, an intake automation/enterprise orchestration solution provider, ALWAYS does pre-validation on inputs and-post validation on outputs before showing you anything when it incorporates your LLM technology, because they know just how often it fails and if the response doesn’t closely resemble something expected with very high probability, they won’t even show it to you.]

“AI”, or, more accurately, rules-based automation, will replace humans who are just doing tactical data processing, but it cannot replace humans who can do real strategic analysis, interpretation, and problem solving. Unfortunately for Procurement, given that 80%+ of the time is tactical data processing and fire-fighting, this will cause companies to think they can eliminate 80% of the Procurement team, even though the reality is that the Procurement team isn’t even addressing 20% of spend strategically in any given year, meaning that they should be augmenting the Procurement team with every useful technology they can find to try and get that spend coverage above 80%!

And if you want to know what companies are truly offering valuable “AI” (where the best you will get is Augmented Intelligence, level 2 on the 4 tier scale, as there is no such thing as Artificial Intelligence and many companies still don’t even offer Assisted Intelligence, level 1, and instead disguise their Artificial Idiocy in slick marketing), talk to an analyst who CAN do the math AND the programming.

First published on LinkedIn.