AI CANNOT TELL YOU WHAT TO DO!

And I’m so glad I’m not the only one saying it!

The (Strategic Sourcing Decision Optimization [SSDO]) Grand Master himself Paul Martyn recently wrote a great post on LinkedIn that made this exceptionally clear and how the real problem is knowing what to do.

Paul starts off with three critical statements:

  1. AI can tell you what’s happening
  2. AI can’t tell you what to do
  3. In sourcing (procurement) the hard part isn’t visibility, it’s choice.

More specifically, it’s making a decision when every decision has tradeoffs, constraints, and (sometimes dire) consequences.

Unless you have an operating model to make those decisions, powered by technology that can actually help you adhere to the constraints, make the tradeoffs, and understand the consequences, the best case with AI is you get overwhelmed with the complexity of what’s happening.

So if you want to be buried in data and complexity and pretend you know what you are doing, there are dozens of BS AI players ready to help you.

But if you want the ability to make good decision, understand tradeoffs, restrict your inquiries to scenarios that adhere to constraints, and model the potential consequences when things go wrong, you need decision optimization with multi-objective capability. That’s Coupa (Trade Extensions). Or Jaggaer (Bravo Solution). Or Keelvar (just Keelvar). Not some BS AI startup offering nothing more than a clod or chat, j’ai pété LLM wrapper.

And if you want to know how to build the right operating model backed up by the right multi-objective optimization model(s) (and save millions while reducing risk and increasing quality), you contact Paul Martyn. He’s saved Billions. (Whereas in 94% of companies, AI has effectively saved 0.)

Now for those who don’t know, not only am I one of the last original (independent) analysts standing in our space (20 years doing SI next month), but I am likely the last original strategic sourcing decision optimization model builder left standing too. (Mindflow [acquired by Emptoris], 2000. First multi-line item model. Before CombineNet [acquired by SciQuest, renamed Jaggaer]. Before Emptoris [acquired by IBM and sunset]. Before all of them. Twelve years before Keelvar. First model to do more: Trade Extensions, acquired by Coupa.)

So unless Thomas Sandholm or Arne Andersson want to come out of retirement and recommend someone better — it’s Paul Martyn. No one still active in our space goes as far back or has worked with as many platforms as he has. (And I helped a PM/Consultant who worked at 2 different optimization providers get hired at 3 others over the past 20 years, and even that doesn’t match Paul’s resume!)

The Dark Ages Were Bad …

… and, after most of western society was likely still recovering from the long term devastating effects of the volcanic winter of 536, that probably set us back 1,000 years in the grand scheme of societal development and civilization advancement.

… but that’s a minor setback compared to what’s in store for the Age of Retardation that is coming!

But let’s back up. Consider this recent article on LinkedIn by Karl Waldman on this Medieval Lesson: Cutting Skilled Workers Hurts Long-Term Growth where Karl discussed why the age of great cathedrals came to an end.

It had nothing to do with lack of wealth — there’s always been wealth, all that changes is who controls it — or a lack of interest — the Christian religion has consistently held more than its fair share of dominance through Europe from the building of the first great cathedral until the present day (and whenever it loses control in one country it finds a new one to take over). It was lack of skill.

As per the post, the European cathedral builders developed an ornamental tradition so specialized it took decades of guild training to master. When the Black Death killed a third of Europe’s population, the skilled tradesmen disappeared because the training pipeline that produced it had been destroyed.

Now think about what we’re doing today.

We’re pretending AI can do the work of experienced professionals and cutting them left, right, and centre. We’re pretending we don’t need junior workers (because they do the tasks that AI seems to do okay) and not hiring. We’re walking all of our institutional knowledge out the door, as well as our ability to react and fix exceptional situations with creativity (that will break AI when they arise), while ensuring there’s no one around to absorb even a morsel of that knowledge and skill.

We’re not only replicating the end results of the black plague at a rate that’s even faster than the black death spread across Europe (it took about 7 years with the first 4 being the worst) — and not only are we destroying all of our capability to build tomorrow’s businesses, but we are throwing away all of our capability to even maintain today’s businesses if something goes wrong! After all, our current staffing levels are minimal, and most of the people we have left are in cognitive decline thanks to the AI they are being forced to use for “productivity” reasons.

When the next unstoppable pandemic hits, and wipes out all of our silver haired experts with no skilled talent to replace them, we will enter the Age of Retardation and our global society will collapse faster than the Aztec Empire. (And if you don’t know how fast one of the greatest civilizations in Central America fell, maybe you should brush up on your history!)

If Instead of Trying to Replace, You Redeployed People — What Could You Accomplish?

The big push for AI is not to help you, but to achieve every executive’s dream of a perfect utopia where they have 24/7/365 robotic workers they don’t have to pay, feed, or even provide safe working conditions for. Where they have endless slave labour, workers with no rights, and only have to worry about counting the virtual dollars in their endlessly increasing bank accounts.

But anyone with a working brain, who doesn’t live in a fantasy world, who hasn’t given into the cognitive surrender brought on by excessive use of Gen-AI, knows that reality is far, far, away. The algorithms are dumber than doorknobs, hallucinate to various degrees on almost every response, and are only good at sounding right, NOT being right. Intelligent humans are still needed, more than ever (as AI has NOT changed the fundamentals of Procurement. It HAS Only Strengthened Them.)

While there is very little Gen-AI can do, there is a lot traditional AI, and even more that (A)RPA (the real agentic technology) can do if properly defined, constrained, and deployed — and in many back office functions, a lot of the data analysis and processing (still) done by humans can be done by machines (and could be done by machines for at least a decade — if not two). In Procurement, we’ve had invoice technology that could automate invoice processing error free 95% to 98% of the time for over a decade, auto-reorder technology based on stock levels, forecast changes, or production schedules for over two decades, technology for automatic contract creation based on clause templates and clause libraries for almost as long, and sourcing automation since the first major sourcing platforms hit the market.

If this was properly done, and 80% of the tactical bit-pushing time that, with fire-fighting, constitutes about 90% of a Procurement professional’s time, was eliminated — imagine what could happen. All high impact and high risk categories could be strategically sourced. All complex categories could be examined in detail, BoMs and production technologies optimized, and supplier relationships (and thus supply assurance) strengthened. And that’s just the start.

Procurement would have time to examine, shape, and even divert (and eliminate) demand. From the classic example of negating the need for more printers, paper, and printer ink by just ensuring every employee had a second monitor at their desk and a tablet for mobile document receipt and review to a more modern example of elimination of expensive cell phones for non-sales on-demand employees by Whatsapp (and cheap subscription) mandates or elimination of expensive office leases in areas where most employees are/work remote most of the time and only a few hot-swap desks at a work-sharing centers (and the ability to book / rent meeting rooms for occasional meetings) is acceptable (as they all use laptops anyway), demand shaping can result in major organizational cost savings.

Moreover, Procurement could even go beyond demand shaping and reduction to true value identification by helping the departments they serve define, and redefine, what value actually is and how best to achieve that value when going to market.

A great example of this is how IKEA approached its use of AI in customer service. As per this great summary on LinkedIn by Alberto, when IKEA’s AI bot deflected 47% of calls, instead of calling it a win, firing half it’s staff, and moving on, IKEA did two things.

  1. They asked what the AI bot wasn’t helping with and what concerns still had to be handled by the customer support team.
  2. They retrained and redeployed over half of their customer support team to handle the most common inquiry, and built a ONE BILLION DOLLAR business around it. (So Far! It’s IKEA. And they’re just getting started.)

To clarify, many (potential) customers weren’t calling just about missing parts or issues understanding the assembly instructions. They were calling to ask what they should buy to meet their needs. “What works in a small living room.”

They needed basic interior design advice. So IKEA trained a significant portion of their customer service workforce as interior designers, and generated over €1 billion in additional business in the first year simply by spending the time to figure out what customers needed before they could make a purchase decision (interior design advice and the identification of products IKEA offered that would meet the design criteria) and giving them exactly what they needed.

Imagine how much value Procurement could add to the business if, instead of reducing staff with automation, the C-Suite retrained (or, if the existing staff doesn’t have the education/experience, replaced that staff with an equal amount of more senior personnel) and redeployed this suddenly freed up staff to act as an internal value identification consultancy that brings Procurement (cost management, risk mitigation, and supply assurance) best practice to the rest of the business.

Think about that before you try to replace real intelligent talent with unintelligent talentless AI (and find yourself in the bog of eternal stench that results from your lack of foresight).

A Buyer is NOT a Buyer — Exact Purchasing Makes That Clearer than Ever!

A month or so ago, Tanya Wade posted a great article on how “A buyer is just a buyer” is BS because a buyer is NOT a buyer.

Tanya noted that while she buys marketing agency services, software, consultancy services, and logistics — stuff that companies need to operate but that customers never directly see — her friend Simon buys food — a commodity that has to arrive on time, meet quality standards, survive audits, and keep processing lines running (as shutdowns can cost millions). This is entirely different from marketing services and consultancy services as it’s rare that a week late will make a difference (and if it does, you waited way too long to contract them).

Tanya then notes that in addition to buyers who support physical supply chains, like Simon, and buyers who support stakeholder needs, like her, there is a third type of buyer — the retail merchandiser who decide what actually hits shelves. And they need entirely different skill sets.

In actuality, there are more types of buyers than that. Think of the physical supply chain — you’re buying inputs or you’re buying finished goods. For the information chain, you’re buying data subscriptions, or you’re buying the software that processes it. For the organization, you’re buying products from the physical chain, information, or services to support the business — which could be agencies/consultancies that process and present the information in different ways (media advertisements, studies, etc.) than software would process such information.

But even this does not capture the complexity of purchasing. You need to embrace Busch-Lamoureux Exact Purchasing to properly segment your buyers.

Because you don’t just care if it’s a product, service, data, or software offering — you care about how it is used and where it falls in the pocket cube. Because if the product is complex (i.e. you need precise specifications for your manufacturing process) or very high risk, you need to manage it differently than if it is not complex or low risk. In the first case, you need to spend a lot of time doing spec reviews and detailed inspections of physical samples before making any decision, and in the second scenario you need to understand all of the events that could present a significant risk of disruption, monitor for them, and have mitigation plans ready to go should an event happen that is going to impact your supply.

And to make matters worse, what’s complex or high risk at one level in the supply chain is less so at another level. If you’re manufacturing electronics, like cell phones or laptops, RAM is a highly complex category that needs to meet exact specifications, have very low failure rates, arrive on time, and fit in your product where the sizes must be within 1/10 mm or it won’t fit in your product. This requires a high degree of manufacturing expertise, spec review, and sample inspection and testing. This is very different than the needs of an IT department supporting desktops in a large development shop where all you care about is the RAM type (SDRAM, SGRAM), the capacity, and the MHz. Brand doesn’t matter — because you’re just upgrading or repairing a desktop or internal server and shoving them in a slot based on whatever is cheapest, height doesn’t matter, because you have extra centimeters, and the production technology (and how that may impact the failure rate) doesn’t matter, because you expect 1% to fail and you just replace them.

In other words, a buyer is defined not just by the category, but where it fits in the Busch-Lamoureux  Exact Purchasing framework from the viewpoint of the organization — as it defines not just how you buy, but how you mitigate, monitor, and manage.

Can You Truly Have Structured Risk Conversations without Exact Purchasing?

We’ve been talking a lot about the Busch-Lamoureux Exact Purchasing Pocket-Cube model lately because we’re never going to solve the exponentially proliferating Procurement problems unless we fix the fundamentals. And when it comes to risk management, it’s pointless unless the risks being managed are the ones that really matter relative to their criticality which should be defined not by Risk Management, but by Procurement based on the importance of the categories they impact.

If you look at risk in isolation, you’re going to focus on:

Traditional Risks

  • limited commodities, especially foodstuffs, where bad yields or natural disasters wipe them out, or minerals that come from limited mines
  • transportation shortages, where routes are at capacity and any man-made or natural event that impacts the lane in any way causes a shortage
  • factory limitations, as it’s a custom product that can only be produced by a few existing factories without extensive customization

And you’re going to completely ignore:

  • restricted commodities, where a significant percentage of global production comes from a single region, or country (and when that gets cut off, a glut of supply suddenly becomes a dearth of supply)
  • global transportation chokepoints, and what happens when a lack of rainfall limits the amount of traffic that can pass through the Panama Canal, the Red Sea closes, the Strait of Hormuz is cut off, etc.
  • local transportation chokepoints, such as the ILA controlled east-coast ports in US or the ILWU controlled west-coast ports in the US, and a strike cuts off your routes and back-up routes
  • skilled worker limitations because it’s not just the factory, it’s the work force, and if most of the workforce is > 60 and the educational/mentorship programs that trained the next generation workers were shut down … that factory is gone in a few years

And what you address might not be that important.

If you’re a traditional mechanical manufacturer, you’re only dependent upon rare earths for magnets and lighting, as most rare earths are in electronics. If you’re monitoring anything beyond the rare earths used in the magnets and lights you need to make/source, you’re wasting your time.

If everything being sourced through a taxed transportation network could be sourced from somewhere else through a network with a lot of capacity, at only a slightly higher price point, then you don’t really care about that transportation network.

If you’re dependent on two factories, and you aren’t monitoring the turnover, the influx of new workers, and the output of future workers in the local economy, you will someday, without warning, find yourself needing to find a new factory with a new supplier that will need to customize their production lines, processes, and workforce to your needs … which they may not be able to accomplish in time to keep your supply chain flowing and main product line in stock — which could risk your entire business model.

Meanwhile, you don’t notice the risk above where

  • 60% of the rare earth you depend on for your magnets are coming from different suppliers in China, so when a pandemic strikes and China institutes a no tolerance policy against a virus that can’t be eliminated, your supply goes up in smoke (and you had no warning to secure as much supply as you could while you still could)
  • you weren’t watching for events that could close the Strait of Hormuz (thinking the Red Sea was the end of it) and aren’t watching the Strait of Malaca (which carries almost 25% of global trade … so if the pirates leave Africa …)
  • you will get shocked when the ILWU contract expires on July 1, 2028 and the US West Coast ports shut down as the pay increase that was negotiated in the last round is NOT keeping up with the inflation your current administration is creating;
  • and so on.

And if you attempt to solve your supply chain risk identification by acquiring a multi-tier supply chain visibility and monitoring solution, you’ll get sucked down every risk rabbit hole that is identified based upon every raw material used anywhere in your supply chain and detected impact event.

Unless you are properly categorizing your purchases using Busch-Lamoureux Exact Purchasing, identifying those categories both high-risk and high-impact, and identifying what risks would be devastating to you, you aren’t addressing the right risks and any attempt at a structured conversation will be a waste of time.

And only then will you be able to identify:

  • where the impacts will be felt,
  • which functions need to be involved,
  • who should own the risk,
  • why identified monitoring via subscription data feeds is needed,
  • when a risk-related event is significant and needs to be manually assessed/addressed,
  • what needs to be done if significance is determined, and
  • how response success will be determined.

And then you can use the tips offered up by Greg Schlegel in his We Discuss Risk Regularly post to have truly successful risk management conversations.