Category Archives: Knowledge Management

The Procurement Knowledge Devolution

The internet was supposed to kick off the procurement knowledge revolution, allowing Procurement pros to quickly:

  • find out about best practices
  • get commodity and market pricing for products and services
  • build reasonable (should) cost models
  • find out about new suppliers, carriers, and consulting partners
  • research new products and services
  • hold truly global sourcing and procurement events in real time
  • effectively communicate with, manage, and develop suppliers
  • etc.

For twenty years, that’s what it was. Procurement departments who learned how to use the internet properly for research, deployed the right SaaS to support their processes, and identified the right data for their processes were successful in their endeavours.

But then came Gen-AI LLMs, chatbots were replaced with chat, j’ai pété‘s and clod‘s, and knowledge was replaced with whatever content the LLM generated. Maybe it was correct, maybe it was mostly correct, and maybe it was a 100% fabrication — a hallucination if you please. The problem with LLMs is that they are NOT intelligent. They are essentially super sophisticated multi-level cross-connected deep neural nets that go beyond classification to generation of responses built up from sub-responses built up from deep training on incredibly large data sets.

Therein lies all of the problems. It generates built on random probabilities. Those are dependent on what’s in the training data set, what questions were asked, what results are reinforced, and how it’s used. If the training data is bad and full of bad data and falsehoods, the chances of incorrect, and even dangerous, responses being generated are quite high. If the training was biased, the output is likely to be very biased. And if it’s not “trained to please”, the models are fundamentally designed to “learn to please”, so if computations that are a complete lie will increase utilization of, and faith in the model, that’s what will happen.

Moreover, every vendor is now believing the hype from the big LLM players, treating the technology as real Artificial Intelligence (when it should be called Artificial Idiocy), and trying to plug it in everywhere … promising that it will provide their clients with true natural language interfaces, agentic tech, and even BS AI Employees. Those who are adopting it are literally getting dumber by the day. Not only has the cognitive impairment, atrophy, and potential long-term decline from regular use been well documented, but the failure rate has been well documented as well with MIT and McKinsey studies demonstrating success rates of 5% and 6% successfully. Most pilots are being abandoned, sometimes before they even begin, because the tech isn’t even good enough to put into employee’s hands for the tasks the overpriced Big X consultancies claimed the LLMs would be perfect for.

Furthermore, even when organizations are smart enough to ignore Gen-AI, over-automating using the most advanced last-gen (A)RPA and AI technologies will still give Procurement teams a false sense of security and, due to their very low error rate, as time goes on, the team’s skills will go rusty and their ability to deal with true exceptions quickly disappear, especially as the old Pros (get forced to early) retire and the younglings have never dealt with exceptional situations.

The age of AI hype has ushered in a knowledge devolution faster than any age that has come before.

I hope the profession can survive it!

Success is in the Diary — and the Details … especially in Procurement!

Garry Mansell recently wrote an interesting post on how to understand how a scaling business is really run that had some really good insight on how you build for success versus how you pretend to.

According to Garry — the diary tells you whether the business is scaling, or not. A business that is truly scaling has:

  • a diary that is light — it’s not filled with back-to-back-to-back meetings … it has time for people to work (and think) and allows people to make the day-to-day decisions necessary to function
  • a diary that doesn’t have repeating meetings that just discuss the same thing in an infinity loop that continually eats up revenue
  • a diary that sees the CEO focused external is focused on building and scaling

And for the most part, he’s right. Except, as both an IT and a Procurement professional, I can tell you it’s critical:

  • to have regular stand-up/check-in meetings in Dev, especially if you’re using an Agile framework — but these all-team recurring meetings are scheduled to be as short as necessary, and they don’t waste time on detailed status reports, but where things are, who’s waiting on what, what issues have arisen, and who can deal with them … and as soon as all issues are discussed, you get back to work
  • in Procurement, you need the same series of meetings for every strategic sourcing event, you need regular check in with Risk Management to track ongoing risks, and you need regular team check-ins to ensure all projects are progressing and resources are allocated properly … but in the first case, they are predefined by the process, only include the necessary reps from each stakeholder group, and held when needed — not weekly meetings; in the second, only issues that have arised or change status are discussed; and in the third, when the situation is understood, the meeting is ended, cut short as much as possible

In other words, there are a number of meetings you can’t get rid of, but you can minimize them and adopt practices to minimize their length, schedule them short, and end them when the necessary information has been exchanged and/or decisions reached. So it’s both the diary … and the details!

Turst is Real Procurement Currency — And That’s Why AI CANNOT Do Procurement!

A couple of months ago Garry addressed a point made by the Peter Smith, the Bad Buying Bard, which boiled down to an issue more important than anything technical where AI is concerned … and that point is Trust.

In his original post, Gary asked if AI would change Procurement. However, after reading Peter’s comment, he realized the real question is whether Procurement is trusted enough that the organization will accept Procurement setting the rules around how AI is used. As Garry notes, that’s the crux.

When it comes to trust, it’s not whether or not the suppliers trust Procurement that’s the real issue, it’s whether Procurement is trusted internally. If Procurement is not trusted, it will be bypassed, ignored, and even sabotaged. This includes the (mis)use of AI. If Procurement is not trusted, it will not have any authority, and the organization will not heed their warnings (based on logic and the research they are used to doing), charge ahead with AI, and become yet another failure contributing to the 94%+ failure rate (while costing the organization millions upon millions of dollars and wiping out any savings Procurement may generate, especially if the C-Suite dictates an AI-first solution for Procurement).

Furthermore, you can’t use tools that you cannot trust. And you can’t trust any Gen-AI Procurement platforms built on hallucinatory LLMs. Since hallucinations are a core feature, results can’t be guaranteed, and LLMs can’t even be counted on to follow explicit instructions (and will corrupt your documents and data even when explicitly told not to), you can’t use Gen-AI/LLM-based AI.

And, unless your data is clean, categorized, up-to-date, and easily accessible through modern APIs, “classic” AI won’t work either. Good Procurement Pros will remind you that you can’t jump straight to AI. Just like you couldn’t expect a tribesmen from a culture with no written word who never set foot in modern civilization to begin reading lessons on the works of Shakespeare accessible only on a modern tablet, you can’t jump decades of technology. Or process.

Successful Procurement requires:

  1. getting your processes in order
  2. getting the supporting data in order
  3. implementing classic technology with high-degrees of deterministic, dependable, determination

And then, and only then, do you sit down, identify where there are still inefficiencies and/or a lot of tactical bit-pushing work, and try to figure out where AI will actually help. This means that most organizations are still years behind where they need to be to successfully implement any AI. In the classic Hackett journey to best-in-class, which will take an average large multi-national 8 years, it will be at least 4 years before the organization is far enough along on any process to consider advanced AI. (For a mid-size, this journey can be reduced to 6 years, and then it’s 3 years before Procurement is ready for advanced AI. It’s always People, Process, and Data before AI!)

AI is NOT Failing Because of a Lack of Forward Positioned Data

Lack of forward positioned data is NOT the problem.

(It is a problem, but not the biggest one!)

An AI agent making 1000X the decisions IS!

Right now, while the big AI players have achieved 80% to 90% “accuracy” on their carefully designed synthetic benchmarks, when applied to real world problems, accuracy in many domains drops to 25% (or worse, as at most 20% of code generated by an AI survives into a production application once it gets reviewed by a senior developer who finds a plethora of security issues, boundary condition errors, and code that, frankly, just doesn’t solve the problem at all).

THIS MEANS THAT THE AI IS MAKING 750X MORE WRONG DECISIONS THAN THE HUMAN!

That’s a LOT of mistakes.

Meanwhile, give an expert human

a) always available forward positioned data and Augmented Intelligence applications to process it (so all the data the expert human needs to make the decision is at her fingertips)

b) A-RPA (Automation) software that is best-of-breed and capable of immediately executing any decision the human makes (possibly using the forward positioned data and appropriate augmented intelligence outputs)

And that human will make 100X the decisions she’s making now, and get 95% of them correct. So if you hire 10 humans, you will have 25X less errors (5% vs 75%).

When you consider ten humans will cost considerably less than AI when you consider the rapidly rising token costs and the costs of dealing with the 25X increase in errors the AI will bring, Augmented Intelligence powered by Forward Deployed Data and a small team of humans will be a LOT more productive than you ever thought possible.

The state of global procurement is dire!

Supply Chains are Broken.

  • Terrorists in the Red Sea.
  • The Strait of Hormuz is effectively closed.
  • Piracy is back off the Ivory coast.
  • Climate change is leading to Panamanian droughts and reduced Canal capacity.
  • Natural Disaster / Storms are on the rise and traversing the Capes is riskier than ever.
  • China’s Zero Tolerance policy means complete port shutdown on the detection of a single virus.
  • Sanctions cut off entire countries.

Old Guard Insight is gone.

  • AMR was swallowed by Gartner, who lost the last of their great analysts.
  • Harte Hanks gutted Aberdeen.
  • Forrester saw (well-deserved retirements).
  • Even the IDC Outsourcing greats moved on!
  • Spend Matters is gone. (Rest in Peace)
  • A space that once had almost 200 independent blogs/analyst (firms) now has barely 20.
    (SI once hosted a resource site that tracked each and every one.)(New) Tech is only causing chaos!

    We’ve went through 5 generations of tech-du-jour in the last 25 years.

        1. World Wide Web
        2. SaaS
        3. Fluffy Magic Cloud
        4. Predictive Analytics
        5. AI

    Not one solved the problems they promised — and the current tech, AI, is failing faster than ever before (with a tech failure rate already at an all time high of 88%). (6% of companies are seeing a return on their AI investments. That’s all!)

    It’s our darkest moment in Procurement and Supply Chain to date.

    We need guidance more than ever. We need the masters!

    We need to call for the return of the Enterprise Irregulars.

    Most of you won’t remember — but the greats in our space came back together back in the 2006 to 2008 time-frame and launched the portal that would collectively change our space before each of them went off to form their own ventures and change a part of the space on their own. Some of those parts survive, some don’t. But we need them back together. If you agree, echo the call!

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