Category Archives: SaaS

How AI Enhances 10 Common Procurement Challenges Part I

A recent CIO article drew my ire because it claimed that AI Overcomes 10 Common Procurement Challenges as it oversimplified the problems and overstated the benefits of AI. Let’s take them one-by-one.

Procurement Takes Too Long, Slowing Innovation: According to the article, AI-driven platforms can generate RFPs, accelerate sourcing, automate approvals, and reduce cycle times … which is mostly true. Properly applied, AI can accelerate sourcing, reduce cycle times, and automate approvals … but not all approvals. As for RFP generation, that’s very limited — LLMs can generate RFPs with a simple prompt, but not necessarily a good RFP. The best RFPs are designed by humans (and then automation, which may or may not use AI, can pull in data from supporting documents as needed), and as for acceleration, it depends on the project — it can’t speed up supplier qualification where humans need to inspect the products and verify the requirements.

Moreover, a rush to AI can make things worse, and not better. Letting AI generate an RFP that misses a key requirement in terms of required certifications, performance criteria, production capacity, etc. can entirely invalidate an RFP process and lead to months of wasted effort if no human realizes that this key requirement was missed until an award is offered and a request for the certification, capacity, etc. is delivered and a “sorry, we don’t have / can’t do that” is returned.

Legal and Budget Complexities Create Bottlenecks: Budget tracking systems and rules-based automation allows for instantaneous budgetary approvals. Contract negotiation software can automate redlining, compliance checks, etc., but cannot handle a complex negotiation for a complex project where each side has a lot of requirements and multiple parties to satisfy. AI speeds up the technical drudgery, but not the human interaction.

Moreover, if you turn over negotiations to software, you have no idea what the end result will be. If you let it negotiate based on market data, and the cost data is off, you could be committing to a bad deal. If you let it predict timeframes based on how it expects prices to rise/stay high, but it’s off by two years, it could lock you into a three year deal when you only need a one year deal. And so on.

CIOs Need to Upskill Their Teams in AI and Cybersecurity: Just because “AI” can simplify processes with guided intelligence, that doesn’t mean the team is upskilled in the process. The reality is, there is no incentive for users to learn anything if they think the system will guide them in everything they need to do.

Thus, if you over invest in AI, especially the kind that guides users in every task they have to do, and works quite well on the basic tasks they have to do daily, and doesn’t screw up the first half dozen or so moderately complex tasks, the user will believe the system is almost flawless, start to trust it implicitly, stop questioning it as time goes on, start believing there is no need to learn anything else because the system knows it, and, over time, stop thinking. And then, instead of performance improving, it will decline … and that decline might be accompanied by a major financial loss if a bad contract is signed or major risk ignored.

Data Inaccuracy Leads to Poor Procurement Decisions: While it’s true that over three quarters of organizations struggle with unreliable data, AI doesn’t magically fix the problem. It can help with cleansing, validation, and procurement trend analysis, but ask any spend analysis vendor who has tried to apply an LLM to unclassified vendors about the classification accuracy (which tends to top out around 70%) — good data still requires manual cleansing and classification, especially where the system reports good confidence. It can definitely help, but it doesn’t take the onus off of the human.

In other words, if you believe that you can plug in a magic AI black box ad that it will fix your data, you are gravely mistaken. Sure it will tell you that it has cleansed, classified, and validated all of your data, but if it’s only 70% accurate, it’s only made matters worse if you trust the data 100% and don’t know what 30% is inaccurate. When you base your decisions on data, and the data is bad, you are bound to make a bad decision. The question is, how bad. You don’t know. And that’s a big problem!

B2B Software Selection is Increasingly Complex: Moreover, despite the claims, AI-powered vendor analysis doesn’t really help that much — see Pierre Mitchell’s crazy conversations with DeepSeek-Rq. Note how it not only recommends inappropriate vendors, but also recommends vendors that don’t even exist anymore … it can help you discover potential vendors, but you still need human reviews and deep pricing intelligence (from expert SaaS optimizers).

Trusting AI to select your software is worse than trusting an analyst firm map! And we know all of the problems those maps contain. (First of all, they only mention the same 10 to 20 vendors year after year, ignoring the dozens of other vendors that might be more appropriate for you.) AI cannot understand your needs, cannot truly map needs to requirements, cannot truly map requirements to features, and cannot truly assess how relevant a solution is, and definitely can’t assess how well a provider’s culture will match yours.

Come back Thursday for Part II!

Accept It! You ARE Selecting Obsolete Tech.

But that’s not necessarily a bad thing.

In a recent LinkedIn article, Joel said that digital procurement is like a pie eating contest, and while we’re not sure we agree, he made one valid point:

The system you select is already heading toward obsolescence the moment you go live.

But it’s worse than that!

1) It’s heading toward obsolescence from the minute the implementation starts … you have no idea the technical debt in the systems you are being sold today from the build fast, scale faster, fix it later mentality infused by VCs and most PE firms!

2) It was probably obsolete when you selected it, especially if you chose a vendor who has been leading the same Gartner and Forrester maps for 10 years with no significant changes to their product or platform!

3) Even worse, chances are that the process you digitized makes you outdated anyways and keeps you that way — digitization is the best time for identifying not how things work, but the way they should work to maximize efficiency and minimize risk (and that’s not, as we continually point out, jumping on the Gen AI / Agentric AI bandwagon and being blinded by the hype).

4) Moreover, you really shouldn’t need different channels (i.e. completely different apps) to source, just different workflows and interfaces, but since most providers don’t do more than one category (among indirect, direct, services, capex projects, etc.), you likely need MORE apps. Moreover, few suites have more than one or two modules that are truly best of breed (despite their claims), so if you don’t plan for the constant upgrades and bolts ons … well … you won’t be ready when you have to select and implement one quick, and then you’ll have even more obsolescence than you planned for.

That doesn’t mean that you should give up on modern tech because it’s all obsolete, because it’s not, and the good vendors recognize this and continually update their tech to minimize the obsolescence. It does mean that you need to be very careful when selecting your tech to find a solution that has minimal technical debt, is beyond where you are at today with respect to the processes it supports, and is being continually enhanced by the vendor. If the vendor offers a truly best of breed solution, is beyond where you are today, and has a track record of keeping up with best practices, and best tech, it’s likely a good vendor.

Especially if the tech today is considerably enhanced against the tech it had two to three years ago (which you should be able to determine by looking up old demo videos, articles, independent reviews, etc.).

However, if you can’t tell any difference between the (mega) suite tech being pushed at you today vs. what the (mega) suite tech were advertising five years ago, then you should probably stay away. Far, Far Away.

Why Are You Still Buying That Fancy New Piece of Software That

  • Could Get You Sued?
  • Increases The Chance You Will Be Hacked!
  • Could Result in a 100 Million Processing Error?
  • Could Shut Down Your Organization’s Systems for Days!
  • Helps Your Employees Commit Fraud?

If someone told you this when evaluating a piece of software, and asked if you wanted to buy it, I’m sure the vast majority of you would say HELL NO!

In which case I want you to please tell me, why are you all still riding the AI Hype Train, Buying, and Using Gen-AI everywhere?

It has already resulted in lawsuits and losses!
The Air Canada lawsuit over the Gen-AI chatbot is just one notable well publicized example.

AI systems are AI coded, and AI code has a much greater security risk
as it generates code using training repositories that contain large amounts of untested, unverified, and high risk code — generating code so full of security holes it’s a hacker’s dream! (See this great piece on the ACM on The Drunken Plagiarists.)

AI systems negotiate on the data they have
and with a single decimal point error and you could be paying 10X what you need to. Not to mention, they don’t always translate right. Remember, the Experimental AI DOGE used claimed an 8 Billion savings on an 8 Million contract!

Bad data generated by an AI system and fed into a legacy system with poor data validity checks can shut it down.
Plus, Gen-AI can also push out bad updates faster than any human can and you can easily have your own Crosslake situation!

Now it’s being used by employees to generate fake receipts
that look so real that, if the employee does a few seconds of research (to get the restaurant info, current menu prices, tax code, etc.), you can’t distinguish the generated image from the real thing. And, before you say “Ramp solves this”, well, it only does if the employee is lazy (which, let’s face it, is human nature, so you’ll catch about 90% of it). But what happens when a user strips the meta data which, FYI, can be as easy as taking a picture of the picture … oops! (And if you’re a hacker, running it through a meta data stripper/replacement routine is even easier as you’re just hotkeying a background task.)

AI is good. Gen-AI has its [limited] uses. But unrestricted and unhinged mass adoption of untested, unverified AI for inappropriate uses is bad. So why do you keep doing it?

Especially since it’s now proven it’s worse for you than some illegal drugs! (Source)

Features ARE NOT Applications; But Applications Require Features!

THE PROPHET recently asked What Procurement Tech Product Categories Were Really Just Features All Along? Which is a great question, except he cheated.

He cheated with the first 5!

  • Supplier performance management
  • Supplier quality management
  • Supplier information management / supplier master data management
  • Supplier diversity
  • Supplier risk management (not supply chain risk!)

We’ve known for years it should be one Supplier 360 solution! (Even though no one offers that when you consider all of the elements that should be there. Heck, none of them even offer the 10 basic CORNED QUIP requirements … in fact, good luck finding a solution that offers 5 of those requirements among the 100+ supplier management solutions).

He you cheated again with the next 3!

  • Should cost / cost modeling (for procurement, not design engineers)
  • RFX and reverse auctions (when not bundled with broader capabilities or services)
  • Sourcing optimization

We’ve also known for yours it should be cost-model and optimization backed sourcing (auction, RFX, hybrid, single source negotiation, etc.) … otherwise, it’s an incomplete solution. But only a fraction of the 80+ sourcing platforms offer true optimization (less than 10) and fewer still do extensive cost modelling. (Note that we are focussed on modelling, not cost estimation — that requires data, and that can, and probably should, be a third party data feed.)

And he was wrong on the last front.

Real Spend Analytics should be standalone. Wrapping restricts it! The modules you use should provide all the specific views you need, but the reason that spend analysis quickly becomes shelfware in most organizations today is the same reason it became shelfware 20 years ago … once you exhaust the limits of the interface its wrapped in, it becomes useless. Go back to the series Eric and I wrote 18 years ago (which you can since Sourcing Innovation didn’t delete everything more than a decade old when it had to change servers in 2024, unlike Spend Matters when it did its site upgrade in 2023).

But Very, Very right in that features are not applications!

And very, very right in that too many start-ups are launching today as features (which will only survive if acquired and rolled up into existing applications and platforms), and not solutions. While apps dominate the consumer world, in business there is not always an app for that, and, frankly, there shouldn’t be. This focus on point-based apps is ridiculous. It’s not features, it’s functions. It’s not apps, it’s platforms. It’s not orchestration (and definitely not spend orchestration), it’s ecosystems!

Recent stats, such as those published by Spendesk put the average number of apps a business uses at 371, with an average of 253 for SMBs and 473 for enterprise firms. WHAT. THE. F6CK? This is insane. How many departments does an average organization have? Less than 10. How many key functional areas? Less than 12. Often less than 10! How many core tasks in each function? Usually less than 6. That says, in the worst case, an enterprise might have 72 distinct critical tasks which might need their own application (but probably not). This says that SMBs have at least 3 times the app they should have, mid-size organizations at least 5 times, and enterprises at least 7 times. That is insane! No wonder there are so many carbon copy SaaS optimizers (as we covered in our piece on sacred cows), because if you have that many SaaS apps, you have features, not applications. And you need to replace sets of these with functional applications that solve your core problems.

(And if you want to know how to prevent app sprawl, before buying yet-another-app, ask yourself “is this supporting a function that should be done on its own, or just a task that should be part of an existing function” … if the latter, it’s a feature, not an application, and if the application it should be part of does not have an upgrade/module that supports the task, then you have the wrong application and it’s time to replace it, not pointlessly extend the ecosystem!)

Everyone In the Procurement Ecosystem Exists For a Reason — But Do You Know Why …

… and more importantly, when you should use them?

Joël Collin-Demers recently commented on a LinkedIn post that

Everyone in the ecosystem exists for a reason. Big consulting and analyst firms are great tools for organizations in particular contexts (e.g. a big firm is a great way to get a lot of smart people deployed on a problem quickly).

The point I’m trying to make is that we tend to over-rely on big consulting and analysts.

And he was correct. Big X consultancies, niche consultancies, implementors/integrators, analyst firms, suite vendors, best of breed vendors, etc. were all started for a reason and continue to exist for a reason. Understanding both of these helps you determine when you should use them, why, and what you should (and should not) expect. In this post on where we asked If You Really Want Success … or Just Say You Do, we made it abundantly clear that Analyst Firms, Big X, Implementors, and even Vendors (beyond a certain point) ultimately don’t care about your success because

Big Analyst Firms (that produce the pay-to-play maps) make money pushing the solutions of the vendors that pay them the most, not on making sure those solutions solve your problems. While there was a time you could always count on the best unbiased advice from an analyst firm, that was long ago. Ever since the first big vendor realized it was faster (and cheaper) to buy influence by sponsoring reports or cutting big research access POs, the end of unbiased recommendations began. (And it’s more your fault than the vendor’s because you came to expect free reports, but no one can work for free, which means the vendors had to pick up the entire cost, which means those reports say what the vendors sponsoring them want said, not what you need to hear.)

Big X need to keep their benches employed addressing your problems, and if a vendor’s solution took care of everything, what else would they do? This doesn’t mean they are going to screw you, but it does mean they are only going to address what you ask them to, that they are going to try to do it with a diamond/platinum/sycophant partner to keep their top-tier consultancy status, and assign the weakest resources they think they can get away with to keep their top tier resources free to top paying clients. Moreover, as we discussed in our article on When Should You Use Big X, the vast majority of Big X did not start out as IT consultancies or Procurement Tech shops and this is still their weakest area (as the “wild west” tech players and boutique consultancies get the majority of best talent), so even if they are doing their best, it’s only so good. (Compared to their core strengths, which, as we said in the latter post, you’d be foolish NOT to take advantage of.) The reality is, many Big X are now mostly body shops who have to keep those junior consultants employed while keeping their big software partners happy. And that’s a difficult balancing act, especially considering their overheads and the luxurious lifestyle these partners have grown accustomed to.

Implementors make money implementing solutions — if that solution solved everything for the next five to ten years, how would they keep their bench employed as well. Now, they are going to make sure it’s implemented to the best of their ability, but since they weren’t hired as a consultancy, they aren’t going to be the ones to tell you when a solution is not the best for a certain task — they are going to do what they are paid to do (so that, when you realize you need another solution in a year and then use the same Big X again to recommend it, they get that contract too).

Vendors need to keep their investors happy, which means securing sales as fast as possible, not ensuring they are the perfect fit and/or outlining where they will fall short. Now, of everyone in the ecosystem, they definitely want you to succeed, but the reality is, they can only spend so much time on you because they took too much money from investors at too high a multiple, aren’t growing at the expected rate, and the management and sales team risk being fired (and the entire company being shut down) if they don’t continually increase the rate they bring on new customers (whether they can reasonably support them or not). It’s all about “what their solution can do for you” and not about “is their solution right for you”.

And so on.

Niche Consultancies are the best IF they do not have preferred vendor partnerships (which require a certain level of business to maintain) as they know they have to perform to get their next contract, but these are few and far between. And even though it is critically important, almost no one does Project Assurance for their ProcureTech project (and then wonders why we have had Two and a Half Decades of Project Failure).

Short story, everyone in the ecosystem exists to make money off of YOU. While that’s not a bad thing IF they provide value (and heck, I’ll happily give you a dollar if I am guaranteed two dollars in return in a reasonable time frame), not all of them do … and those that do are not equal in the value they provide (primarily due to conflicting pressures, not intent). Until you understand that, your returns will be limited.

The important thing to remember is that if you’re just starting your best-in-class Procurement journey, you typically don’t need an end to end suite, and if you’re Procurement maturity is still elementary school, you don’t need a 7-figure mega suite when a low 6-figure mini suite, which can be implemented in 1/4 to 1/6 the time, can get you 80% of potential savings. Especially when this level of savings will take you 3-6 years to realize. Then, when you’re ready (and know how to get the additional ROI the mega-suite can provide), you can upgrade to the seven figure mega-suite in confidence you’ll achieve the same level of ROI. (Instead of being the next ProcureTech disaster. And while you may believe in a beautiful disaster, there is no such thing where tech is involved.)