Category Archives: Technology

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?

Proper Solution Selection is Harder Than You Think!

In Jon The Revelator‘s recent post on what can 2005 tell us about Procurement AI in 2024 he listed a dozen vendors from 2004 that no longer exist and asked if we recognized these names. To this, the doctor replied every single one and noted that the market is even more fragmented today than it was in 2004 and pointed you to the Source-to-Pay+ Mega-Map. Jon then asked if history will repeat itself, and as per the doctor‘s recent post on Market Madness, it will … with a vengeance!

This response prompted The Revelator to ask which companies would join their brethren from 2004, to which the doctor provided some indications, which were many (and even more numerous in the Market Madness post). So The Revelator then asked what do practitioners need to do during these pending turbulent times? The real answer is quite a bit and, in fact too much to address in a single article, or even a book, so the doctor decided to focus in on stable solution selection.

And while the doctor made it look as easy as 1, 2, 3 in his comment, when he said:

  1. first identify what kind of solution you need
  2. then identify which providers actually offer those solutions for their geography – market size – vertical
  3. then restrict down to those that are *stable*

It’s a lot more complicated than that, and for some companies, some of these steps will consist of many steps within themselves.

What kind of solution is complicated! At a minimum, one needs to consider:

  • what processes are you doing
  • … and which of these are properly, or not, supported by your current tech
  • what processes should you be doing
  • … and what tech will support those
  • and which subsets of tech are the most relevant (and make sense to focus on)

Which providers is harder.

  • many providers will claim to be everything to everyone, but that’s not true
  • the big analyst firms over-focus on the big vendors, because that’s who they have to (contractually) spend most of their time on
  • smaller firms will focus on the smaller vendors, because some of the big ones believe their big cheque to the big firm(s) covers all their marketing/market needs, and may not have the time to dive deep into geography – market size – vertical appropriateness
  • and logo maps don’t give you near enough detail to even get a short list

In other words, it’s a heck of a lot more than just choosing the first 5 names that come back in a Google or a “chat, j’ai pété” search!

You want a vendor that is going to be around, or if acquired, a solution that is going to be maintained because it’s growing year-over-year, wasn’t built on an oversized investment (pressuring the firm to increase prices or cut costs or grow too fast), 10+ to 50+ customers (depending on solution type and implementation / replacement time and cost and risk tolerance), etc. Where do you get that data? How do you ask in a way that won’t result in the sale person clamming up?

It’s more than most Procurement organization’s can handle as they just don’t have the TQ (Technical Quotient) or the market knowledge. They need to get help from an expert who does who is not biased towards any particular vendor and will follow a proper process, not just throw an RFP over the wall to three providers they have worked with before (as that’s no better than a refined “chat, j’ai pété” search)! And it can be hard to identify the right expert (and the only hint the doctor will give you now is you’re not likely to find one at a Big X — the Big X have them, but they are few and far between, spread thin, and unless you are a Fortune 500 / Global 3000, you won’t get the expert, you’ll get the f6ckw@d). You need a niche consultancy with experts who specialize in this. There are a few, but not as many as the space needs.

Have We Been In The Dank Basement So Long That We Don’t Care If the Fish Stinks?

the doctor has to ask because when Jon The Revelator asked if you would eat a piece of fish that has been in your freezer for 10 years? 5 years? 1 year? not many of you spoke up and it seems you are quite okay with old, smelly fish, which, in this case was a metaphor for provider case studies, as this was a follow up to The Revelator‘s post that asked Should Solution Provider Case Studies Have a Best Before Date.

A question, which was in turn sparked from a comment by Duncan Jones to his preceding inquiry on what can 2005 tell us on why most AI initiatives fail in 2024, which is a question that was partially sparked off of a post the doctor himself made on how we need to hasten onshoring and nearshoring — the drivers will pound those who don’t into the ground! (Part 2).

While this sounds like a long, meandering, pointless introduction, it’s exactly the opposite. The purpose is to demonstrate that not only are many parts of Procurement and Supply Chain connected, but they are connected in complex ways that require sufficiently broad, as well as sufficiently deep, solutions that address the complexities being experienced by the organizations a vendor is trying to sell to.

Furthermore, this means that for an organization, or a consulting partner, to select the right solution, they need deep information on what the solution does, where it’s been used, and what it has been proven to do. Traditionally, this would mean that they would require product sheets and demos, customer references, and case studies to make a good decision.

However, centering in on this last requirement, not all case studies are created equal, and not all are even “case studies” at all. What once was the domain of third party analysts, consultants, and professors (who would do proper due diligence, data collection, and impartial write-ups for educational and investment purposes) has now become the domain of marketers who get happy customers, often still wearing the rose-coloured glasses that came free with the install, to tell a story that they write-up and promote using very little, and often unverified, data. Those are not useful at all. Furthermore, if you don’t know what version of the software, what stack the customer ran on, and/or, and sometimes most importantly, when the study was done (and the time period it was done over), is it even still relevant at all?

This prompted the critical question from The Revelator about whether or not studies should have a best before date. the doctor leans towards no on best before date, because just like different types of fish have a different shelf life, different case studies will have a different shelf life, but votes a most definite yes on a packaging date.

To elaborate on the comment he made when asked, the following is absolutely critical to be included in the case study:

  • when the case study was written (packaging date)
  • the time period it was over (processing dates)
  • the precise metrics that were tracked and how they were computed (labelling compliance)
  • the extent of organizational data that was used (ingredients)
    [as well as the full extent of data available (may contain)]
  • the products, and versions, that were used (processing)

In other words, a feel-good story with a few random numbers is not case study! (the doctor would say any marketer trying to pass such off as one should be ashamed, but any marketer who did would obviously be without shame, so there’s really no point in saying it.) A case study has rigour in definition, methodology, data collection, and exposition and contains all the information that would be needed if a third party wanted to repeat it. (The same way a scientific study provides enough detail for an independent team to verify it.) Anything less should be considered unacceptable.

And, most importantly, since business processes, products, systems, and stacks continually change, a study (processing) date and a publication (packaging) date MUST be included so that a buyer can make an informed decision as to whether that study is still relevant to them (as they decide just how much stink they are willing to tolerate).

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!

Marketplace Madness is Coming Because History WILL Repeat Itself

Over on LinkedIn, Jon The Revelator asked what 2005 could tell us about Procurement AI in 2024, reminding us that major ERP companies have tried multiple times to move “down market”, there’s (still) no dominant player in the pure “Procurement” sector (with a number of big firms showing up in a slice-of-the-pie analysis (and most analyst market maps), and many names that were around in 2004 are names most of today’s practitioners have never heard of.

And, as part of the conversation (check the comments), Jon asked if history will repeat itself. (i.e. Will many of today’s players disappear? Jon listed a dozen names that are no longer in existence.)

the doctor‘ answer, MOST DEFINITELY!

To be more precise, the doctor is predicting twice the percentage of (fire-sale) acquisitions and out-of-business/shut-downs over the next eighteen (18) months compared to usual. What does this mean numbers wise? He usually removes a few dozen vendors from his database every year (which is about 5% of the number of vendors in the Source-to-Pay+ [S2P+] space, as captured in the Sourcing Innovation Mega-Map), and expects that within eighteen (18) months, he will need to remove a few few dozen vendors from his database, which translates into 10% or more, or a number of vendors that is closer to 100 than 50! That’s significant.

Why? A number of reasons, which include, but are not limited to:

1) A lot of the smaller 1 or 2 module pure-play VC funded companies that took (too much) money before the Silicon Valley Bank failure and are not yet profitable are now in a bad situation given that VC funding is still recessed, PE is now looking for close to 300K/FTE for a “good” investment, and these smaller companies are not there as enterprise Procurement software acquisition for the last two years has been recessed (due to overall market fears of recession), and, in addition to sales being down, buyers have been risk averse and newer / smaller players have, in general, being doing worse than they were doing during COVID (when companies were desperate for solutions that were pure SaaS) and just pre-COVID (when companies were more willing to try smaller plays in what they thought was a globally stable economic environment).

2a) A number of smaller plays were started by consultants with no funding, no real sales team, and no marketing support and they just can’t get traction through the noise (or funding).

2b) A lot of smaller plays were started by Procurement practitioners with little or no funding, the same sales and marketing problems, and a bigger disadvantage because they only know their problems, and maybe the problems of a small peer group they meet with in their local organization’s monthly meet-up, and they don’t know the problems in general, what sells, and what doesn’t. This makes funding for them hard (as smart investors know that Procurement experience alone only goes so far), and sales and marketing harder (they were buyers, not sellers; and they don’t understand that the message they needed to hear is not one that will cut through the noise and reach buyers who aren’t as experienced and enlightened as they are).

And when you start to break down Source-to-Pay+, you find that …

3) There are way too many “tech without a cause AI plays” … with no real, demonstrateable value, and, in reality, no future. (Especially since anyone from the Golden Era remembers that all the rebel without a cause managed to do was get his friend killed.)

4) A lot of the carbon “calculators” offer no new functionality (and thus no new value). Most good DIY (do-it-yourself) spend analytics application providers can help you build one in 15 minutes (no joke! — give Spendata a call, for example). Furthermore, you need good data for them to work, so if you don’t have integrations to good data and systems with better data, what’s the point?

5) Moving on to classic sourcing, every developer and their dog can whip up eRFX functionality in a matter of weeks and there is no differentiation there anymore if you’re just another eRFX. So you have a slightly different take on a UX. Well, guess what, that don’t impress me much … and the doctor ain’t alone in that viewpoint.

6) Moving onto classic CLM, if the platform doesn’t support deep analytics, negotiation support, or something that makes it more than an e-filing cabinet, it’s going, going … gone. Way too many over-glorified document management solutions out there to survive, especially at a price point beyond a few hundred per named user per year (given how many freeware/shareware/end-consumer document platforms exist in the open-source repositories).

7) There’s over one hundred (100) SXM plays. OVER ONE HUNDRED. Given that SXM is a CORNED QUIP mash, and you need different types and depths of solution for organizations of different sizes in different verticals, there’s room for two to three dozen. But one hundred? Forget it! Especially since if all your solution ends up being is a glorified SaaS (relational) database, there’s no value there.

8) While there is a desperate need for analytics, and not enough true analytics players, first generation solutions that are nothing more than pre-generated static (OLAP) reports are about to go the way of the dodo. Real-time, dynamic, customizeable analytics are what’s needed today.

9) Standalone ePro is going to go. Given that there are dozens of P2P solutions, and a growing number of P2P solutions with built-in payment support, why would you want old-school ePro, which doesn’t help the average organizational user or get tail-spend under control.

10) AP without full I2P support, integrated payment support, or integrated P-Card support or value beyond classic AP is also going to go. There are dozens and dozens of these solutions (including dozens that started during COVID because people needed to do business entirely online, and since there appeared to be an opportunity for anyone who didn’t do their research beyond bill.com, which is more people than you’d think, see The Biggest Mistake founders in S2P+ keep making after two decades, too many of these were started). The market just doesn’t need that many!


11) Stand-alone Intake(-to)/Orchestrate solutions. The current poster children of the space will soon have a fall from grace (and only the smart will survive)! Call me Scrooge if you like, but there’s a logic behind why I’m developing a bah-humbug attitude towards most of these. And it goes something like this.

Intake

  • Pay For View if modern procurement solutions are completely SaaS, then they should be accessible by anyone with a web browser, so why should you have to buy a third party solution to see the data in those applications? wouldn’t it make more sense to just switch to modern source to pay solutions that allow you to give variable levels of access to everyone who needs access instead of paying for two solutions AND an integrator?

Orchestrate

  • Solution Sprawl while orchestration is supposed to help with solution sprawl, it’s yet another solution and only adds to it. Wouldn’t it make more sense to invest in and switch to a core sourcing and/or procurement platform with a fully open API where all of the other modules you need can pull the necessary data from and push the necessary data to that platform?

I2O

  • Where’s the Beef? Talk to an old Pro who was doing Procurement back before the first modern tools began to be introduced in the late 90’s and they’ll tell you that they don’t get this modern focus on “orchestration” and managing “expenses” and low-value buys because, when they were doing Procurement, it was about identifying and strategically managing multi million (10, 50, 100+) categories where even 2% made a significant improvement to the bottom line, and way more than 10% on a < 100K category.
  • Where’s the Market? This is only a problem in large enterprises — right now, many of these I2O solutions are going after the mid-market who are eating it up because of ease of use, but as soon as they realize the emperor has no clothes, and there’s no support for real strategic procurement (yet alone strategic sourcing) and you have to go out and buy more platforms, what’s going to happen? The reality is that the mid-market is better served by a federated catalog management / punchout platform, and will likely be better served still by a new breed of e-commerce B2B solutions for end-user Procurement (which is being led by providers like BlueBean. Which will only leave the enterprise space, and, more specifically, the enterprise players who are stuck with older generation solutions (due to sunk costs, etc.) that don’t integrate well or have modern bells and wizards.

And so on. The market is over crowded, most of the providers are struggling, funding has dried up for all but the best (who haven’t been overfunded already) [and already profitable with true long-term growth capability], and there’s no room for the rest.

History will repeat, and those who don’t follow best practices and avoid mistakes will be the first to fall.