Follow the Money to Find Future Opportunity — Which Will NOT Be Fully Found With Autonomous Sourcing!

Spend Matters has thrown caution to the wind and followed Gartner’s lead jumping onto the AI Hype Bus (with no steering and no brakes) that is still heading straight for the cliff and are wheeling out webinars on AI faster than a prairie fire with a tailwind. (Needless to say Sourcing Innovation does not think this is a good thing. There are valid uses for AI and automated processing, but fully handing over financial decisions is like wheeling in the Trojan Horse and leaving it unguarded in the server room with unrestricted access to your bank integration.)

Recently, The Maverick advertised yet another Spend Matters webinar on Autonomous and AI Sourcing where he said we should “follow the money”. Which we should, but there are a few things we need to clarify first.

1. No Money Changes Hands In Sourcing

It changes hands in Procurement … and it’s because most companies don’t follow the money after the contract is signed that 30 to 40 cents of negotiated savings never materialize in many companies, which The Maverick should remember from his AMR and Hackett days, as it was laid clear in Mickey North Rizza‘s famous 2009 “Reaching Sourcing Excellence” series, which we know is in his archives.

2. “Speed” is NOT a strategic edge if you don’t get it right!

If you don’t go out with the right strategy, don’t know the current market price, don’t know the reason for the current market price, and don’t have the knowledge to project if the trend is going to continue, stabilize or reverse, going to market is not a good decision … and it’s an even worse decision to automate the sourcing project and secure an award as fast as possible if you don’t know if it’s the best you could have done or the worst you could have done.

3. “Pecunia non olet”, but yet these vendors are asking you to treat it like it does!

They want you to automate spend analysis, sourcing, contracts, purchases, and everything else that involves money by turning over everything to their Agentric AI because, apparently, money stinks and you don’t want to touch it. (But they are quite happy to not only spend yours for you but takes as much of it as they can for their services.)

But here’s what they don’t tell you.

  • AI is NOT Intelligent.
    The level of intelligence in their “AI” is equivalent to the level of intelligence in a carpenter’s hammer. The level of effectiveness is entirely dependent on how skilled the person “training” the system and how skilled the person “using” the system is, just like the effectiveness of a hammer is dependent on how well the carpenter was trained and how experienced he is in it’s use.
  • AI Does Not Know What it Does Not Know.
    If the data is incomplete, the recommendation is very likely incorrect.
  • AI Cannot Do Better than the Best A Human Has Ever Done in Decision Making.
    So, if none of the situations it was trained on led to great results, neither will what it recommends for you.

You need to remember how Gen-AI does its work (or should we say does not work). It is large document search and summarization and chain of compute. Now, the more advanced players are trying to embed knowledge graphs into this, but these are not perfect either. With good training examples, and a very similar situation, the probability it will work well is very good, but it’s still only a probability. As a result, nothing should ever be fully automated where money is concerned. The tools should be used for their recommendations, and if the recommendations are good, and the risk is low, most of the tactical data processing and event management should be automated, but the decisions should ALWAYS be made by a human, who should be involved at every decision point. Even if that decision is verifying the system recommendation. It only takes one miscalculation due to an incomplete data source to project a wrong trend, rush an auction, lock in a price 3X what you are paying now, only for it to fall in a month later when a factory (which went offline temporarily due to a manmade or natural disaster) comes back online and the supply-demand balance returns to normal. And while you may have stocked out for two weeks, those losses will be orders of magnitude less than paying 3X at a contract you have to honour (unless you want to get dragged into court).

Now, if you really want to make money, forget all this Autonomous and Agentric AI BS, look for Augmented Intelligence solutions that make your staff two, three, five, and even ten times more efficient, purchase those, and, remembering that the US infrastructure is crumbling fast (and not going to get renewed under a Republican administration that is more interest in trickle-on economic tax cuts for its billionaires than ensuring you have running water), it’s time to remember how the smart made money in ancient Rome — public bathhouses and latrines. Time to invest in your own desalination facilities and be ready when the public wells run dry. After all, “Pecunia Non Olet“.

How Do You Turbo-Charge Negotiations?

Not that long ago, THE REVELATOR asked some questions around negotiations and how you could turbo-charge them for a better outcome. Of course, the doctor answered because this is becoming an even more important topic given the state of world, and technology, affairs, but its also one that needs a repeat discussion because this topic comes up a lot and the doctor fears that everyone is missing at least one key point.

What does it mean to “turbocharge” negotiations?

How about “what should it mean”. Everyone has their own answer for “what does it mean”, and most aren’t that useful.

Turbocharge should mean to back up with facts (based on organizational data) and market data relevant to every aspect of the negotiation, to go in knowing both what value there is in it for you as well as your BATNA, and the value that it is in for your counterpart, and a best guess at their BATNA.

Without all this insight, you don’t know if you even have a leg to stand on, or how to reach common ground to carry the negotiation forward. Data insight goes much, much, further than a carrot or a stick ever will.

What do you define as being a successful negotiation outcome?

A successful negotiation outcome is a win-win. It’s not a zero-sum win-lose game like a certain world famous infamous author thinks it is … unless, or course, both parties have the exact same collection of goals which they would rank and weight the exact same way, which is astronomically rare. Thus, since the vast majority of the time both parties have their own unique definition of winning, which can have some overlap, both parties can win.

What are your thoughts about AI and the negotiation process?

When it comes to AI and Negotiation, the answer is no, No, NO, ??, ??! Since it’s not true artificial intelligence, you should never, ever, ever let it negotiate as that is letting the system make a decision, vs recommending a decision, which even IBM told all its employees 46 years ago that this is something you should NEVER, EVER do!

To what degree do experience and expertise impact negotiations?

Experience and Expertise both help, but reality is that the results depend more on the differential between the two parties at the table than any scale you might come up with to measure your own. So you want both, but you should always expect to be outmatched, which is why data, facts, and insight are so critical. If you can find that common ground and give up at least some of what the other party truly wants, you have a much better chance of getting something you want and coming out okay.

Bonus Questions

“Are women better at negotiation than men?”

That would, of course, depend on your definition of negotiation and success. I’m inclined to say yes, but if your definition of success is to be a complete a-hole pre, during, and post, well, I’ve seen way more men who excel at that.

“Is AI better at bluffing than humans?”

Regular humans, or sociopaths? Since AI has no feelings, and doesn’t understand truth from lies, depending on how you define bluffing, it can be absolutely great at it … or not.

“Is AI “Genderless”

Not the right question. We know tech is genderless.

The right question is the following: Is AI trained genderless? Usually not as its usually trained on results that were predominantly created and input by men (who make up 75% of STEM). So it’s not genderless and, sometimes, it is very, very biased.

FINAL QUESTION

Is it the technology or how you use it?

It is most definitely how you use the technology, not the technology itself. Heck, you can get good results with a carrot if you are in negotiations with a bunny. 😉

And that technology must be used to get you the data and insights you need to have a good human to human negotiation. No more, no less. Because, at the end of the day, that’s the only way you can turbocharge a negotiation for success!

The Best Way to Survive the AI-Powered Apocalypse? Go Old School!

If you’ve been following along, you know that a great purge is coming on two fronts. All the pundits agree on that! On the first front, a large number of vendors are going bye bye, as we’ve been telling you since our first post on the Marketplace Madness. On the second front, they took ‘er jobs. Except it’s not they, it’s AI.

So doesn’t this mean that if you want to survive the days ahead that you should find the most advanced AI provider that isn’t going to get purged in the near future, adopt the tech, replace as much staff as you can with AI, find a way to survive the hardship, and come out ahead when everyone decides that what they have to do?

Well, for the vast majority of the analysts and pundits, it is exactly what you should do — and do it right now. It’s AI overload all the time. And just when most hype cycles start to die down, this one gets a second wind of hurricane proportions.

But, in fact, it’s the last thing you should do. In fact, you should implement a Gen-AI ban and Agentric AI ban immediately, and identify classic ML-powered AI augmented intelligence tech that can supercharge your team, acquire it, and train your team on that immediately. Because you can get the same results as any Agentric AI can get if you employ the right classic ML-powered human-driven AI technology with the right algorithms, analytics, optimization, etc. Sure, a human might be a little bit slower than an algorithm that can work 24/7/365 without a break, but human who is appropriately skilled and trained will make up for this with something the AI doesn’t have, true intelligence.

You see, the thing about Gen-AI and Agentric AI is that it works great until it doesn’t. As per our recent post, Gen-AI is full of problems. In a recent post, we noted that, Gen-AI can:

  • get you sued
  • increase the chance you will be hacked
  • result in Million/Billion-Plus processing errors
  • shut down your organization’s systems for days
  • help your employees commit fraud

And those are the good side effects from its hallucinations. There are much worse side effects that can happen. If you refer back to our posts on the valid uses for Gen AI and the valid uses for Gen AI in Procurement

  • the embedded biases, that you might not even be aware of, could result in decisions diametrically opposed to what you are expecting
  • when it computes two options that are equally likely to generate the same end result for the company relative to the KPI it is using, there’s no guarantee it will select the right option — and there’s always a right option, especially if one option for cost savings is a longer term contract so the supplier can upgrade equipment and the other option is forcing the supplier to cut an already razor thin margin 50%
  • the hallucinations eventually become real, as the systems get so advanced that they not only create super realistic evidence to back up their recommendations, but take over your entire systems in the background so that you don’t know that a web request to verify a claim is actually still being processed by the AI that is now running in the background
  • it starts negotiations and cutting contracts you haven’t even authorized yet
  • it becomes you … and you get blamed for all its mistakes

In other words, ignore the Gen-AI and Agentric-AI technologies that are not the miracle cures they are promised to be. The miracle cures are the last generation ML-based AI technology that was just about to transform your operations under the expert fingers of your leading practitioners, not some probabilistic monstrosity that requires an entire data center to run to generate an output no one verify using a system no one understands. Hone your chops on those and you’ll get the results you need, without having to deal with unexpected, possibly catastrophic, failures along the way.

After all, when we told you about all of the great advancements that were coming in Source To Pay in our classic series (indexed here), none of it required Gen-AI to achieve!

Your Upteenth Reminder That Every Dollar Saved By Procurement Goes Straight to the Bottom Line!

… while 10 cents from every additional sale might make it, if you’re lucky!

A week or so ago, Joël Collin-Demers said COVID was the instigating event that pushed Procurement front and center in a comment to yet another post about the tariff crisis (to which, as I keep saying, the only solution is BTCHaaS), when it was really the (fist) elevating event in over a decade.

The first event that really put ProcureTech on the map was the 2008 financial crisis. This is because companies had to stop the bleeding, fast, and charged Procurement to get ‘er done. But once the markets settled, and the provider base stabilized, and companies willing to spend the money they needed to implement proper tech and get more efficient did so, Procurement kind of faded into the background again. That’s because, when markets rise, and sales rise, the C-Suite focusses entirely on revenue, almost to the point of irrationality, because the faster that revenue rises, the higher the valuation, and the more money they can make on the markets and trades.

However, the 2008 financial crisis is why the M&A and PE activity started to ramp up in ProcureTech in the early teens, because of the importance placed on cost cutting as a result of the 2008 financial crisis. And why, if something else had happened sooner, Procurement would have risen up the organizational chart faster, instead of falling back into obscurity at many organizations who returned undue focus to Sales and Marketing.

This, of course, belies the sad, sorry, state of affairs of North American business that still sees marketing and sales as the key to growth in a shrinking economy (and yes, with birth rates declining in almost all first world countries, it is a shrinking economy) when the real key is cost management. Remember your business 101 equation: Profit = Revenue – Expenses.

This says that every dollar of revenue you add is eaten up by the total cost to acquire that dollar — the total cost of that good or service, which is usually at least 90 cents of that dollar.

However, every dollar of expense you cut is gone in its entirety. Every dollar saved goes straight to the bottom line.

Thus, Procurement is 10 times as valuable as sales! But yet, the marketing madmen will try to hide that from you to protect their multi-million budgets!

So if you want to survive the crisis of the day, whatever that crisis may be, it’s not sales, it’s not marketing, it’s not finance, it’s not executive leadership or vision, it’s Procurement. Plain and simple. Maximize every dollar spent while eliminating those that don’t need to be.

Unless, of course, you are a ProcureTech vendor, in which case, as per a previous post, skip the fairy dust and buzzwords, focuses on your customers pain, and put together some educational materials (marketing and training) that will help them ease the bleeding. If you’ve forgotten how to do that, or never learned, there are those of us who can help you!

With Great Data Comes Great Opportunity!

In fact, it can quadruple your ROI from a major suite.

Not long ago, Stephany Lapierre posted that your team may only be realizing <50% of the ROI from your Ariba or Coupa investment, to which, of course, my response was:

50% of value on average? WOW!

Let’s break some things down.

A suite will typically cost 4X a leaner mid-market offering which is often enough even for an enterprise just starting it’s Best in Class journey (that will take at least 8 years, as per Hackett group research in the 2000s).

Moreover, even if the enterprise can make full use of the suite it buys for 4X, at least 80% of the “opportunity” comes from just having a good process, technology, baseline capability and automation behind it. That says you’re paying 4X to squeeze an additional 20% worth of opportunity in the best case.

On average, it takes 2 to 3 years to implement a suite (on a 3 to 5 year deal). So maybe you’re seeing an average of 66% functionality over the contract duration.

As Stephany pointed out, bad data leads to

  • increased supplier discovery and management times
  • invoice processing delays and errors
  • increased risk and decreased performance insight

As well as an

  • inability to take advantage of advanced (spend) analytics
  • inability to build detailed optimization models
  • decreased accuracy in cost modelling and market prediction

This is even more problematic! Why? These are the only technologies found to deliver year-over-year 10%+ savings! (This is where the extra value a suite can offer comes from, but only with good data. Otherwise, at most half of the opportunity will be realized.)

Thus, one can argue an average organization is only getting 66% of 25% of 80% of its investment against peers (based on 2/3rd functionality, the 4X suite cost, and the baseline savings available from a basic mid-market application that instills good process and cost intelligence) and 50% of 20% (as it is able to take advantage of at most half of the advanced functionality offered by the suite due to poor and incomplete data). In other words, at the end of the day, we’d argue an average company is only realizing 23% of the potential value from an opportunity perspective!

However, as one should rightly point out, the true value of a suite is not the value you get on the base, it’s the ROI on that extra spend that allows for 20% more opportunity than a customer can get from lesser peer ProcureTech solutions.

For example, let’s say you are a company with 1B of spend with a 100M opportunity.

If tackling 20M of that opportunity requires advanced analytics, optimization, and extensive end-to-end data, it’s likely that you’ll never see that with an average mid-market solution with limited analytics, no optimization, and only baseline transactional data. If the company paid an extra 1.5M over 3 years for this enhanced functionality, then the ROI on that is 13X, which is definitely worth it.

Moreover, if the suite supports the creation of enhanced automations, you could get more throughput per employee and realize the base 80M with half or one quarter of the workforce, which would lead to a lowering of the HR budget that more than covers the baseline cost.

However, ALL of this requires great data, advanced capability, and the in-house knowledge to use both. This is only the case in the market leaders. As a result, we’d argue that the majority of clients are only realizing about 25% of the suite’s potential — when sometimes the only thing standing in their way of realizing the rest is good data.