Dear Graduate, Don’t Skip the Internship … You Need a Gateway to an Apprenticeship!

A number of AI enthusiasts are advising soon-to-be and recent graduates to skip the internship and instead become proficient with AI because that’s how they are going to get a job. And, as you should know by now, it’s bullcr@p. Being able to write a prompt for a Gen-AI LLM that will return a convincing (but not necessarily sound) result is not going to get you a job. The only skill that’s going to get you a job is competence!

As with every over-hyped tech-du-jour that came before ([predictive] analytics, the fluffy magic cloud, SaaS, the WWW, etc), AI is not a silver bullet that’s going to solve all of an organization’s problems and grant magical status to those who have mastered it.

The only thing you’ll master with Gen-AI is the art of the con since whatever it spits out is so well written (compared to the average literary skill of an average high school, and even University, graduate these days) and so convincing that, without expert guidance, an average person is convinced that it must be right when they don’t know better. But that’s not a skill most organizations are going to hire you for (outside of sales and marketing), even if the organization is known for questionable ethics.

Organizations don’t need clueless idiots. They need experts who can assess situations, determine options, decide on the best option, and implement the decision. Someone who knows the analysis to run, the data to collect, the tools to use, the reports to create, the logs to keep, and the contracts to write.

And while you can’t graduate an expert, you can graduate with the skills to start you on the path to becoming one — the traditional skills of math, logic, critical reasoning, project planning, project management, and relevant domain knowledge — not creative crafting of perilous prompts for a flakey LLM that will eventually fail you no matter how much time and effort you put into that prompt.

And if you get get an internship and prove yourself, maybe that will lead to full time job where you can apprentice under a master in the real world and gain the experience you need to go from an adept (with the core knowledge and skills but not the wisdom needed to succeed in the real world) to practitioner (who has gained enough wisdom and experience to manage standard tasks and functions on their own, and who only needs guidance for new or complex situations not yet encountered) and, eventually, to expert where you become the new organizational mentor and the one that new hires turn to for help.

And organizations need (future) experts because only an expert knows when

  • it only has wrong/incomplete data (which will prevent an AI from ever working)
  • an analysis/outcome is wrong based on math fundamentals
    (and when an LLM-based AI multiplied by -1 because you told it to deliver savings vs. find the best opportunities based on price variability, lowest price, market trends, and differential analysis)
  • reasoning is correlative, not causative (which is a failure of not just LLMs, but many people as well)
  • an analysis is incomplete (because only they have specific insight that was not available to the machine or another analyst)
  • etc.

That’s why, if you want to become a true master of your craft, you need to forget the AI mastery and instead land an internship where you can apply the mastery of the real skills you learned in your degree program to stand out, get an apprenticeship, and learn how things work in the real world and acquire the real world mastery you need to get the job you want. Only then will you be able to work your way up to becoming the leader, and expert, you want to be.

There is no Artificial Intelligence (just Artificial Idiocy) and organizations will always need top talent. Automation, and well designed applications that solve real problems efficiently and effectively, will reduce the number of back-office employees that an organization needs and any employee who’s only skill is pushing bits will be eliminated. However, the need for talented employees will only increase to not only oversee the tools and handle the exceptions, but correctly analyze increasingly complex real-world situations and make the right decisions.

At the end of the day, AI tool mastery is meaningless if you can’t logically and holistically analyze the outputs with respect to math fundamentals and a real-world scenario!

The King is Dead. Long Live the King!

Learn the phrase, because you will soon be living it in every aspect of your life — it’s not only the new fashion in western politics, but the new fashion in enterprise tech tripling down on the AI hype when the big AI vendors are losing money faster than ever before (as compute costs skyrocket, competition heats up, and a lot of people are getting fed up with a total lack of return on their investments)!

However, in the meantime, as the hype wave makes it way though the mass market, a slew of startups emerge building on LLMs and fake AGI offerings, and the marketing mania takes over, expect the e-Procurement is Dead, Sourcing is Dead, and Contract Management is Dead rhetoric to hit all time highs as these new players cr@p their new apps as fast as they can, with new — natural language centric — interfaces, more automation, and instant gratification. (At least when these apps work as desired.)

As these offerings get adopted at a rapid pace in organizations who are just adopting modern solutions (which make up half of the space, or more), replace first generation apps from the noughts in organizations who decided that anti-complex is the way to go, and start to get noticed, the rhetoric picks up the pace and echos.

But that’s all it is — rhetoric amplified through a microphone. Sourcing, Procurement, and Contract Management are not dead, the fundamental requirements are not changing, and these systems are not being adopted en-masse. Not just because they don’t always work very well, but because they don’t fit. (And even when they do, they are just replacing one interface with another.)

First of all, in the public sector, you have to follow rules and frameworks even for tail spend. These systems have no guardrails, and by their very nature can’t guarantee the rules will always be followed. So these systems can’t be adopted.

Secondly, in many large private organizations, very large investments have been made in big suite models (which still have long term subscriptions in place), so unless the new AI solution enables functionality (regardless of interface) that does not exist in the current platform, or allows for a considerable number of seat-based licenses to be dropped on renewal (for a similar or less number in the new, cheaper and more functional, app), it’s not even going to be considered. Even if buyers get blinded by the hype because the CFO is going to say no.

But yes, some organizations will be in a position to adopt these systems, echo that SaaS is dead, hail the new Agents / AI as king, and go back to doing the same old thing through a shiny new interface.

So while THE PROPHET might find it fun to pontificate who killed the e-Procurement king, the reality is that no one killed the king, because the king will die a death by a thousand paper cuts, and then his clone will be put on the throne.

Why? Well, using THE PROPHET‘s examples:

  • most intake/orchestration platforms just put lipstick on the pig you are already using (and the pig isn’t very happy about it), and the king you will get is Merkimer’s clone
  • ERP will do what they always do, acquire what their customers are already using (and this time do it in fire sales as investors who paid 10X for suites get desperate for anything back as the growth in these suite companies stalls), and the king you will get is the next CEO, who will be picked to clone the current CEO in form and function
  • people will see through the BS of “concierge AI employees” when they falter on more complex purchases, over spend on basic items, and allow Sony PlayStations to be charged to the snack budget (because the only AI employees that perform are those based in India), and they’ll keep the king they have until he nominates his successor (whom he expects to be just like him)
  • the viper strikes from fed up merchants being overloaded with RFIs and RFQs to quote items in their public catalogs at non-discount volumes will be laced with poison, and the only way the king will survive is to back down …
  • data aggregators and intermediaries will thrive, and they help to select the next king, but they won’t be king

The King is Dead. Long Live the King!

This Should Be Obvious But Expert in the Loop …

… is Human in the Loop. Not another (AI) system in the loop, no matter how specialized that system is or how well it is trained!

The future is Augmented Intelligence, NOT Artificial Intelligence (which doesn’t exist and won’t exist any time soon until brilliant researchers come up with a few more insights that get us closer to understanding

  1. what intelligence actually is and
  2. modelling it.)

The algorithms might be getting more accurate in average use cases, but the illusion of intelligence, no matter how grand, is still NOT intelligence. (And, even worse, The Wizard of Oz has been replaced by a very poor digital facsimile.)

Done right, Augmented Intelligence will still let your organization reduce its non-value-add tactical workforce by 80% to 90% because the right tools will enable the strategic experts to be 3, 5, 7, and even 10 times as productive and oversee all the tactical work that needs to be done using an exception based approach where every instruction that is given forms a rule that allows the system to automatically deal with the same, and similar, exceptions should they arise again in the future in a predictable and repeatable fashion.

Instead of having to oversee a team of tactical grunts that just take up space (because they don’t have the education, experience, or raw capability required to make good strategic decisions, manage projects, and identify value), a strategic expert can instead focus her time on value-centric activities and training a protege or two who will be one that posses the right mix of EQ and TQ to grow into, and take over, her expert role (when she moves on and up).

In the near future, there will be no more bodies in seats just to push bits around, because that’s what software does best. Number crunching and thunking. NOT analyzing strategically and thinking. (I admit most humans don’t do that well either, especially these days, because they are too attracted to the principle of least action and/or enjoying the cognitive decline from ChatGPT, but those willing to practice strategic thinking daily still do it way better than a machine ever will based on our current approaches to AI). [And while there might be fewer of us each year that are willing to think, there are still enough of us to get the job done if you let us select tools that work. Not necessarily AI. Tools that work.]

We Need Exact Purchasing … But It’s NOT a New Matrix!

We all know the Kraljic matrix is broken, and that it has been broken for a while. As Jason Busch starts off in his article on how Supply Management Must Become Exact Purchasing, Kraljic was right at the time, but it’s time to come back to where we started. And, more importantly, recognize that the Kraljic Matrix was designed as a starting point for supply management to think critically — and Supply Management was supposed to evolve from there. But it never really did.

Sure we got the Purchasing Chessboard by Kearney to supplement a host of seven step methodologies, procurement game plans, new techniques for managing indirect spend, lean supply management, and a slew of techniques from every niche consultancy to enhance your supply, and category management, strategies, but almost all of these are based on the classic 2 * 2 Kraljic matrix with refinement.

In his post, Jason, who rightfully says that procurement at scale is not one-size-fits-all tells us that answer is Exact Purchasing, or more specifically, The Exact Purchasing Quadrant, where he tries to map cost influence vs contract-and-supply complexity because Kraljic told you what a category is when he mapped profit impact vs. risk / complexity, but he didn’t tell you what to do with it. According to Jason, if you have:

  • low cost influence and low complexity, you transaction capture
  • low cost influence and high complexity, you govern the relationship
  • high cost influence and low complexity, you manage market risk
  • high cost influence and high complexity, you architect the cost

And Jason’s mostly right. Depending on the category in question, you’re generally going to apply one of those approaches.

Jason doesn’t stop there. He tells you that the thread that ties all four of these together is data at the core. And he’s right. Without a data-based (not necessarily database) approach, you’ll never effectively manage, and thus never effectively purchase, a category. Moreover, Jason does a great job at telling you what the core data is, where it resides, and where it could sit in your next generation enterprise Supply Management Solution (SMS). But he falls short when dictates the velocity, because that depends on the criticality. And even worse, the depth of data required depends on the criticality — which can also change the quadrant a category falls in!

For example, while packaging, print & marketing, and NPD are definitely strategic (Kraljic) cost architecture (Busch) categories for some companies (i.e. CPG, Advertising Agencies, and Manufacturers), they are tail-spend for other companies (i.e. Retail Store, Luxury Brands, and a Services Consultancy).

Jason’s improved approach still fails because it suffers from the same fallacy as the original Kraljic matrix — that complexity and risk are a single dimension. They’re not. Complexity is a factor of the product or service that you design and is an internal dimension that you have complete control over. Risk is a factor of the external environment that impacts your ability to create and deliver the product or service and depends on the financial stability of your supplier, the geopolitical situation in which it operates, the trade routes that exist between your supplier and your location, your supplier’s supply chain, and everything else in between — these are all factors you can’t control. Furthermore, it’s not profit impact (Kraljic) [which is short term] or cost influence (Busch) [which depends on spend], but criticality, which is measured in value impact [and what happens if the buy is unprofitable, of poor quality, or unavailable]. A category with zero savings potential can risk a 100M product line if your products can’t be completed without it (and we’ve seen this many times over the last two decades as critical sensors or single-sourced components shut down automotive lines or lack of RAM [from the decennial plant fires] or custom control chips [from trade slow-downs or insufficient production] greatly impacted personal computer / laptop or game system production — costing major brands hundreds of millions of dollars).

The reality is that Supply Management / Exact Purchasing / Get My Stuff (and Git-r-Done) is NOT a 2 * 2 matrix. It’s a(t least a) 2 * 2 * 2 pocket cube (and a 3 * 3 * 3 cube in large Enterprises) that is different for every organization where you take into account:

  1. complexity – low (med) or high
  2. market risk – low (med) or high
  3. criticality – low (med) or high

And as you progress from the lower left of the cube (where all dimensions are low) to the upper right of the cube (where all dimensions are high), you’re simultaneously following a three-dimensional path down a bi-furcating decision tree that takes you from non-critical items where you are simply managing as transactions to highly strategic items that you are cost architecting to the best of your ability, monitoring at least weekly, and alerting the category manager to on every major market event. In the middle, you will deal with your leverage and bottleneck items using well-timed market events to mitigate risk and managed relationships to ensure smooth supply, with the depth, and velocity, of the data correlated to the criticality of the item to your operation.

You do that, and you’ll finally be on the road to Exact Purchasing.

And I’ll leave it to Jason to work out the details of the starting cubic, as he’s so intent on fixing Purchasing (now that he’s semi-retired and can pontificate on the philosophical of purchasing).

(And once Jason does that, I’ll tell you how execution differs between small, medium, and large enterprises because “strategic” doesn’t mean the same thing at different levels, there is no one-size-fits-all platform, and, after a lack of operational readiness [which THE REVELATOR will happily fill you in on], this is likely the second biggest reason new technology acquisition projects fail in our space.)

The Future of Business is … Customer Centric Supply Chains!

Phil Fersht of HFS Research recently did a great LinkedIn post summarizing a fascinating conversation with Malcolm Frank that summarized a few key takeaways, including the following:

For 25 years, IT services optimized SG&A instead of transforming cost of goods sold. AI changes that. The real value now sits in agentic, vertical, customer-facing transformation, not back-office efficiency.

Customer-facing transformation is definitely where the value is in a global economy that is (borderline) recessionary, with joblessness and insecurity increasing by the day, and most people having less (and less) to spend on non-essentials and essentials alike. If you want their business, especially if your product or service is discretionary, it needs to be what they want. With constantly crushing weights on their shoulders, they need products that make them feel good, that make them feel like they are being listened to and catered too, that were created for consumer use (and not for the use by the atypical person in the lab who created something just for them), etc. The companies that deliver those will be the big winners, not the ones that still follow the old Ford Mantra (where you can have any colour you want as long as it’s black).

However, it’s not just creating the product that the customers want because IF you can’t deliver the goods at a price point the majority of your customers can afford and will pay in tight/recessionary economies, then you won’t sell any product at all!

We all need to remember that COGS was always a proxy, as it was easy for the accountants to measure, the same way we use revenue as a proxy for determining if a company is an appropriate target for our software and services. In Procurement, it’s not revenue — it’s how much spend is external, how much we can actually manage (retailers can have large leases that make up a significant portion of external spend which Procurement can’t do a thing about), and how many categories are big enough to give us leverage or real options when sourcing that can lead to savings, quality improvements, more resilience, etc.

This means that the future of business is about two things:

  1. tailoring to customers (because we’re long beyond you can have any colour you want as long as its black) to maximize the amount they will pay (to the point they can pay), which Phil astutely noted in his post and
  2. (dynamically) re-configuring the supply chains (as needed) to offer the products at profitable price points based on what the majority of the market will pay

So this would mean it’s simultaneously optimizing the product mix for customer adoption while ensuring the supply chains are ready to serve and re-optimizing them as needed.

As was noted, at the end of the day, back-office costs are pretty insignificant compared to supply chain costs and increased profits from increased price points that create a product that maximizes what a customer will pay (because the product is precisely what the customer wants, and not a product that is simply close enough that it might work for them).