Category Archives: Knowledge Management

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!

    Linked In Post

Ontologies Could Have Saved Us — But in the Age of Gen AI, They Might Just Ruin Us!

What is an Ontology?

Philosophically, an ontology is the study of being, existence, and/or reality that is designed to investigate not only what entities exist but how they can be categorized.

In computer science and, more specifically, the data age, an ontology is a formal, machine readable, specification of entities, their properties, and their relationships within a domain that is used to structure information in a way that systems can share and structure it.

In the early days of semantic technology, an ontology was used to structure data in a meaningful way to allow sophisticated models to process, and make sense of, natural language with relatively high degrees of accuracy. It was usually expressed in a formal ontology language that allowed for detailed entity, relationship, part of speech, and even concept definitions. They were often defined in such a way they could be organized into interconnected libraries which formally organized knowledge into large, connected, corpuses that could be deterministically processed (hallucination free) and completely understood by any application that was capable of processing the language the ontologies in the library were encoded in.

And this was the true beginning of the semantic web, which was also known as Web 3.0, which was still in its infancy in the 2010s, but starting to take off by early (early) adopters (with almost 2% of web domains containing semantic markup circa 2014).

But then five things happened.

1. SaaS exploded, and so did the need for data, and the ability to consume it in standard formats.

2. GPT-1 was released in 2018 and the Gen-AI craze began shortly thereafter, leading us down the hallucinatory hole of incessant inanity that every consultant thought could power everything.

3. This led to the agentic craze, which increased the demand for data (and the desire to consume it in structured formats).

4. Every SaaS provider, and their dog all of a sudden needed multiple, steady, streams of data in standard formats to power their agentic applications.

5. In response, every data provider responded by adopting a simple data standard, calling it an ontology, even if all they were serving up was average scope 3 carbon data by country and factory type.

And now the term has no meaning since it’s the term used by every SaaS vendor and data supplier to essentially describe their data file structure. No formality. No relationships. No underlying structure that allows the machine to actually reason. Just another random data file blended into the data soup that feeds the hallucinatory engine that will tell us to go over the cliff like lemmings (and lead countless to their deaths as they cognitively surrender to what the AI tells them to do).

What could have been our saving grace (if Web 3.0 research had continued and true ontologies of ontologies had been created) might soon be the source of our demise as Gen-AI blends together mismatched data with flawed reasoning and produces the digital equivalent of toxic waste.

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).

Today’s Procurement Leaders Aren’t Enough for Tomorrow

Mr. Matthew Buckingham recently posted on LinkedIn that the strongest Procurement leaders today share three traits:

  • (commercial) curiosity — and an understanding of where value is
  • (constructive) courage — and the willingness to challenge the business
  • (crystal) clarity — and the ability to simplify complexity

These are all great, and necessary, skills, but not enough to survive tomorrow where supply chains break daily, technology is in flux, and your processes can’t adapt (fast enough).

In order to survive the simultaneous supply chain (due to unpredictable, and constantly escalating, geopolitical situations) and technology (due to the Agentic AI [Hype] wave) turmoil that is coming, tomorrow’s procurement leader is also going to need:

  • (colossal) creativity — to build a flexible supply chain that can change on a moment’s notice
  • (constant) crusader — to convince the C-Suite that traditional Procurement is dead

The organization is going to have to

  • dual/tri-source everything from at least two/three locales,
  • have contracts with primary and secondary couriers in each locale,
  • be aware of alternate ports / commercial air cargo carriers out of alternate airports for shipping (and have them on speed dial in case of need),
  • have potential back up suppliers (who came in second) in case of supplier failure,
  • near (real)-time monitoring in place not just for communications, missed communications, missed milestone dates, and other indicate KPIs but events that are likely to impact a supplier’s performance and/or availability,
  • pre-defined response plans for region, supplier, carrier, [air]port, etc. availability, and
  • the ability to reallocate and change plans literally overnight …
  • while treating long-term contracts (or at least long-term expectations of fulfillment) as a thing of the past … there is no guaranteed supply, or even price protection, if the supplier becomes unavailable or goes bankrupt

Proactively building a supply chain and supporting technology infrastructure capable of being reactive in real time is going to take a lot more creativity and crusading than what was ever needed before in Procurement.

Curiosity, Clarity, and Courage is just the baseline.

Find a leader who’s ready!

Forget Best in Class, Hype, or Futurism — If You Want To Improve, Mature!

As you know, and as we’ve written about repeatedly, the hype cycles for orchestration and Gen-AI are in full swing (even though both should be declining, they are both picking up steam, likely due to the ridiculous amount of money spent on marketing — which includes vendors buying analyst studies and reports that focus on areas where they look good).

Consultancies are not only trying to promote and sell you these technologies as a panacea for all your technology ills, but also trying to tell you that it’s what the best-in-class do and, by the way, that if you want to be best-in-class, you have to upgrade all of your processes (with their help) to those that the best-in-class use (whatever that means).

Furthermore, both are trying to tell you what the Future of Procurement is in 2030, 2035, 2040, etc.

And the reality is that NONE of this helps you. Not one bit.

As we have repeatedly pointed out, most of the currently hyped technology is still in experimental/beta stages. This is not technology that will help you mature. In fact, if you are not an industry leader, and mature in your processes, it may actually hold you back because you need to be a mature industry leader with your Procurement organization running smoothly to have the time and experience to properly evaluate these technologies and where they might fit in your organization.

Furthermore, every organization is different. As a result, what is a best practice for one organization may not be a best process for another. In fact, it might not even be relevant. While you will need to improve your processes, and streamline them for digitization, there is no set of fixed processes you can just plug and play and succeed.

And, don’t pardon my French, why the fuck would you care about what Procurement will be like in 5, 10, 15, 25 years. That does NOT solve your problem today. You care about what a better organization would like today and how to get there. That’s it. Just like the journey of a thousand miles begins with a single step (and possibly a single kick in the ass), the path to success is continual improvement, and, simply put, doing better tomorrow than you are doing today.

This means that the key to success is good old maturity levels, current state assessments, and simple step-by-step plans to get from one level to another. Nothing fancy. Nothing tech-centric. And definitely nothing hyped!

While the doctor admits he did get a little tired of the plethora of these maturity maps that appeared in rapid succession in the late 2000s and early 2010s, including the one he did, it was much preferable to today where the dearth of these, and simple advice, is deafening. The help that is desperately needed is not there — replaced by (Gen-AI generated) (Gen-)AI and orchestration hype, not how they can (and cannot) support the solutions you need.

[Plus, let’s not forget that analyst firms and consultancies tend to ignore government regulations and industry compliance (except in country-specific studies), day-to-day pain points (because they aren’t sexy and won’t sell the hype), and, unless they can make a quick-buck (or get a major uptick in eyeballs), changing global conditions that require (temporary) supply chain pivots.]

So, if you truly want to improve, find a maturity model that walks you through the process and knowledge improvements you need to

  1. get to where you should have been when you started Procurement
  2. get to where you should be today
  3. prepare for the next 3 to 5 years (since no one looks beyond that anymore)
  4. slowly build out a foundation that will take you beyond that (without another massive investment)

That’s it. That’s how you make progress. And how you do it without flushing Millions of Dollars down the (Big X) consulting toilet.

Need a starting point? You can still download the classic paper the doctor wrote back in 2012, that was sponsored by BravoSolution (acquired by Jaggaer), on Taking the First Step on Your Next Level Supply Management Journey which describes the levels of maturity from standardization and complexity reduction (which is typically the first step an organization takes on its journey), to operational excellence (which is typically the second step an organization takes on its journey), to strategic business enablement (which is when it typically becomes best in class).

If you do a web search, you will find others from the big consultancies, but this gives you an idea of what to look for in a model that you can build a progress plan on. Where do you start, where will go next, and where do you want to end up. Note that a good model is tech free. Tech should support your growth, not the other way around. (In other words, it’s never Tech-First or AI-First, it’s solution first, and then you identify the right tech.)

And if you need help with a current state assessment, or flushing out a roadmap from one level to the next, or where you are now to standardization and complexity reduction, hire a niche consultancy who will take a no-nonsense approach to get you there at a reasonable cost. (This shouldn’t cost millions of dollars in a transformation project. Depending on your organizational size and complexity, somewhere in the low six figures should typically be enough to get your started, or mid to high five figures if you want to just focus on a few core areas at a time. But definitely NOT seven figures. That comes during the transformation process once you have identified the tech you need, and NOT the tech everyone is trying to shove down the proverbial throat.)