Sourcing Excellence Is Predictability in Tough Times

Sourcing Mediocrity, or worse, Bad Buying, leads to chaos.

Your costs are up.

Your delivery predictability is gone.

Your energy supply is intermittent and brown outs are becoming normal while those costs go up too.

Your taps are running dry.

Your workforce benefit costs are going up as healthcare costs skyrocket.

Your AI costs are going up as compute and consulting skyrockets and more consultant time is needed to deal with the results of bad, bad, hallucinations, that have gone beyond wrong orders, 3-way mismatches, and fraudulent payments to bad customer advice and legal claims that have put you in legal jeopardy.

This isn’t inflation. This is bad buying.

With good buying and sourcing excellence:

Your costs are stable — because you didn’t select risky suppliers, squeeze their margins to dangerously low levels, or make ridiculous asks that only add cost and not value.

Your deliveries are predictable as you’ve selected carriers that can support multiple routes and have re-routing plans in place if a route gets shut down due to a port strike, border closing, or “Geopolitical conflict” (i.e. war).

Your energy supply is regular as you were sure to build where the grid could support your energy needs, select providers (where you had a choice) that could guarantee the supply, and installed backup generators for key functions (and batteries for minimal lights and on-site computing requirements).

Your water pressure is through the roof as you ensured there was adequate supply and put contracts in place to guarantee it.

You manage your benefit negotiations carefully, put long term contracts in place, and work with the provider to prevent fraud (which makes you a customer of choice).

You don’t buy Gen-AI just because every brain-fried consultant and their favourite cognitively atrophied analyst is telling you to. You buy classic AI that works hallucination and error free at a fraction of the compute and cost.

In other words, you apply sourcing excellence end-to-end.

And you make good use of (strategic sourcing) decision optimization.

And you realize savings twice the savings of your peers.

But don’t take my word for it. Take the word of Paul Martyn, one of the original Sourcing Optimization Grand Masters who has sourced over 20 Billion dollars, and seen consistent results doing so over the past two decades.

And saved oodles of cash. To find out how much, check out this post on how you’re seeing your sourcing decisions repriced from bad buying. Then do the math on how much you could be saving (and, of course, reach out to Paul if you’d like someone to help you put a plan in place to save that money).

P.S. If you haven’t figured it out yet, if you were using Busch-Lamoureux Exact Purchasing you’d not only know that you should already be using optimization, but where, why, and would have already reached out to Paul to help you define the program.

Sourcing Excellence IS Optimization!

Sourcing Excellence requires optimization. Not AI. Optimization. We have finally reached a point where nothing else will get you there.

And Sourcing Excellence requires Paul Martyn. You need someone who has built and led programs, evaluated and employed multiple tools, and has the decades of experience to bring the insights you need instantly to the table. With many of the sourcing optimization greats (who founded CombineNet, VerticalNet Tigris, Trade Extensions, etc.) retired or moved on, the number of people left who have over two decades of practical experience are countable on your fingers (just like the number of analysts who have been consistently covering this space for two decades). Paul Martyn is one of the few, true, optimization masters left. So if you want to save your supply chain, reach out to Paul.

If you want to understand why, as well as why sourcing excellence truly requires optimization (as it’s time has finally come), since I know you won’t listen to me, read Paul’s ongoing Sourcing Excellence series, which just saw Part 11 published.

  1. Part 1: (Optimization is Thinking)
  2. Part 2: (Optimization Frames Reality)
  3. Part 3: (Optimization is More than a Capability)
  4. Part 4: (Optimization Changed the Game)
  5. Part 5: (Optimization Must Always Be On)
  6. Part 6: (AI is NOT Yet Fly in Procurement)
  7. Part 7: (Innovation is Just an Input)
  8. Part 8: (Orchestration is the Key)
  9. Part 9: (Value is a Game)
  10. Part 10: (Constraints Dictate)
  11. Part 11: (Constraints Vary)

Another Reason To Avoid AI: NO ECONOMIC GROWTH COMES FROM AI!

A recent study by Goldman Sachs, summarized in Fortune, found no meaningful relationship between AI and productivity at the economy wide level/.

Think carefully about that. 450 Billion, which is more than the GDP of over 100 countries, was sunk (and I mean sunk) into AI last year — for the net result of ZERO economic growth. For 1/6 of that, every college in the US could be free — and you’d have 20 Million smarter adults with no student debt dragging them down, causing them stress, and zapping from their productivity. For 1/12 of that, you could eliminate all the hunger and food insufficiency in the US. For 1/50 of that, you could re-open Alcatraz and provide a King with his own special castle and his own moat.

In other words, there are so many better things that could have been done with that money — including training your people to be more productive, modernizing processes for efficiency, and building deterministic tech that actually works at 1/100 to 1/10000 of the compute power in a data center that’s already powered up.

The only company “winning” is Nvidia, who provides the chips, which means that most of the money is going to its factories in Taiwan and South Korea, and those are the only countries that are actually winning while Americans, who were laid off in droves last year, get poorer, colder and hotter, hungrier and thirstier (as AI sucks up all the energy, which is now not available for heating or air conditioning, and all the water for cooling, which is now not available for drinking or farming).

Think about that the next time you think an overpriced clod or chat, j’ai pété wrapper, even if hyped up as an AI Employee by the A.S.S.H.O.L.E., is going to solve all your problems. Especially since all the Age of AI has done for us is make us dumber, poorer, and less prepared for what is to come next than any age that has come before.

The One Big Benefit Of NOT Going AI …

You don’t have to worry about your AI vendor going toes-up when power costs go through the roof and your AI vendor can no longer charge pennies for compute when its costs rapidly become dollars and it can’t pass them on due to contractual commitments to existing clients (or to new clients who won’t pay dollars for computations that might return hallucinations).

The new generation of AI tech — Gen-AI LLMs / AGI — requires way more compute power than the last generation, 100 to 10000 times more on average, for most requests. Grids are stretched and beginning to break. We’re at the point where only nuclear can power the data centre needed for a modern Gen-AI/AGI offering. And, as per Koray Köse’s recent article on AI leadership is about who controls the power, U.S. nuclear plants operated at 92.3% capacity last year. OUCH!

THERE IS NO ENERGY LEFT!

You can’t build a new nuclear plant overnight — if you can even build one at all anymore! Last year, DOGE’s Firing Fiasco at the NNSA stretched an already stretched organization even more. Many returned to work, but not all, but budget cuts likely left them without the capacity to even properly monitor existing aging nuclear infrastructure, yet alone approve more plants.

And it’s not even clear how much know-how is left in the US to build new plants. The Vogtle Units 3 and 4 in Georgia were the first units built from scratch in over three decades. The experience and expertise isn’t there to safely build these plants en-masse.

And the last thing the US wants to risk is another meltdown. Three Mile Island wasn’t a Chernobyl, but all it takes is a rushed private sector job with a lack of proper oversight and testing and one small mistake to trigger the next meltdown on US soil.

In other words, the power isn’t there for more AI.

So those organizations that can do without modern AI, that can use classic solutions with fit-for-purpose last generation AI that requires a fraction of the power and can run on already strained, non-nuclear, grids will be the big winners when the power squeeze hits and the Big AI players start dropping like flies.

AI is Exacerbating the Need for Global Data Centres NOT Controlled By US Firms!

A recent post by Joël Collin-Demers on why Your LLM Doesn’t Need a US Passport pointed out two very important facts that you’re probably not aware of but should be:

1. Your company is feeding sensitive data to US-based LLMs every single day.

2. The US CLOUD Act lets American authorities demand data from any US-based provider REGARDLESS of where their servers sit in the world!

In other words, you’re giving the USA full access to all of your proprietary and confidential data anytime they want it — in full breach of your data localization laws if you’re NOT in the US and in a country with such laws (and if you’re not in the US and don’t yet have data localization laws to adhere to you will soon have such laws to deal with as a result of the US global over-reach for your data to feed its AI).

This is not just an AI problem (which, if you think you really need, you have other non-US options if you are not a US company as per Joel’s extensive list), it’s an overall SaaS/SaS problem. If you’re not a US company, you need to make sure that not only your data, but all of your applications (including, but not limited to, AI) are hosted in non-US owned data centres off of US soil without safe harbour agreements.