Category Archives: Best Practices

Bring Back the Interns!

Even the offshore interns!

And since, like Meat Loaf,

I know that I will never be politically correct
And I don’t give a damn about my lack of etiquette

I’m going to come out and say I long for the days when AI meant “Another Indian”. (In the 2000s, the politically incorrect joke when a vendor said they had AI, especially in spend classification, was that the AI stood for “Another Indian” in the backroom manually doing all of the classifications the “AI” didn’t do and redoing all the classifications the “AI” got wrong over the weekend when the vendor, who took your spend database on Friday, promised to have it by Monday).

The solution providers of that time may have been selling you a healthy dose of silicon snake oil, but at least the spend cube they provided was mostly right and reasonably consistent (compared to one produced with Gen-AI). (The interns may not have known the first thing about your business and classified brake shoes under apparel, but they did it consistently, and it was a relatively easy fix to remap everything on the next nightly refresh.)

At the end of the day the doctor would rather one competent real intern than an army of bots where you don’t know which will produce a right answer, which will produce a wrong answer, and which will produce an answer so dangerous that, if executed and acted on, could financially bankrupt or effectively destroy the company with the brand damage it would cause.

After all, nothing could stop me from giving that competent, intelligent, intern tested playbooks, similar case studies, and real software tools that use proper methodologies and time-tested algorithms guaranteed to give a good answer (even if not necessarily the absolute best answer) and access to internal experts who can help if the intern gets stuck. Maybe I only get a 60% or 70% solution at best, but that’s significantly better than a 20% solution and infinitely better than a 0% solution, and unmeasurably better than a solution that bankrupts the business. Especially if I limit the tasks the intern is given to those that don’t have more than a moderate impact on the business (and then I use that intern to free up the more senior resources for the tasks that deserve their attention).

As for all the claims that the “insane development pace” of (Gen)-AI will soon give us an army of bots where each bot is better than an intern, given that the most recent instantiation of Gen-AI released to the market, where 200 MILLION was spent on its development and training, is telling us to eat one ROCK a day (digest that! I sure can’t!), I’d say the wall has been hit, been hit hard, and until we have a real advancement in understanding intelligence and in modelling intelligence, you can forget any further GENeric improvements. (Improvements in specific applications, especially based on more traditional machine learning, sure, but this GEN-AI cr@p, nope.)

When it comes to AI, it’s not just a matter of more compute power. That was clear to those of us who really understood AI a couple of decades ago. AI isn’t new. Researchers were discussing it in the (19)50’s, ’56 saw the creation of Logic Theorist, which was arguably the birth of Automated Reasoning, ’59 saw the founding of the MIT AI lab by McCarthy and Minsky, and ’63, in addition to seeing the publication of “Computers and Thoughts“, saw the announcement of “A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators“, which was arguably the first AI program (as AI needs to adjust its parameters to “learn”).

That was over SIXTY (60) years ago, and we still haven’t made any significant advances towards “AI”.

Remember that we were told in the ’70s that AI would reshape computing. Then we were told in the 80s that the new fifth generation computer systems they were building would give us massively parallel computing, advances in logic, and lay the foundation for true AI systems. It never happened. Then, when the cloud materialized in the 00’s, we saw a resurgence in distributed neural nets and were told AI would save the day. Guess what? It didn’t. Now we’re being told the same bullshit all over again, but the reality is that we’re no closer now then we were in the 60s. First of all, while computing is 10,000 times more powerful than it was six decades ago (as these large models have 10,000 cores), at the end of the day, a pond snail has more active neurons (than these models have cores), and neuronal connections, in its brain. Secondly, we still don’t really understand how the brain works, so these models still don’t have any intelligence (and the pond snail is infinitely more intelligent). (So even when we reach the point when these systems are one million times bigger than they are today, which could happen this century, we still won’t have intelligence.)

So bring back the interns, especially the ones in India. With five times the population of the US, statistically speaking, India has five times the number of smart people, and your chances of success are looking pretty good compared to using an application that tells you to eat rocks.

Procurement 2024 or Procurement’s Greatest Hits? McKinsey’s on the money, but … Part 2

… in some cases this is money you should have been on a decade ago!

Let’s backtrack. As we noted in Part 1, McKinsey ended Q1 by publishing a piece on Procurement 2024: The next ten CPO actions to meet today’s toughest challenges which had some great advice, but in some cases these were actions that your Procurement organization should have been taking five, if not ten years ago. And, if your organization was doing so in these cases, should be moving on to true next actions the article didn’t even address.

So, as you probably guessed, we’re in the midst of discussing each one, giving credit where credit is due (they are pretty good at strategy after all), and indicating where they missed a bit and tell you what to do next if you are already doing the actions you should have been doing years ago. And, just like we did to THE PROPHET‘s predictions, grade them. In this second instalment, we’ll tackle the next three actions, which they group under the heading of:

NEW SOURCES OF VALUE

4. Manage Volatility. B+

If Procurement doesn’t manage volatility, those savings they project never materialize. Hence, this is something Procurement should be doing every single year, so this is not really a next step — it’s an ongoing action. However, macroeconomic drivers are in flux and need to be monitored, and planned for, more regularly this decade than in the 2000s and 2010s. The organization needs to have multiple sourcing strategies for each of its categories based on potential shifts in the market driven by these macro-economic drivers, and be ready to play offence instead of defence.

5. Optimize Operations End-to-End. A-

Procurement should be constantly optimizing its operations, so this is not something that should be new. However, it needs to take another step up the optimization ladder and go beyond Source-to-Pay+ and include supply chain operations in its planning and make sure everything is in synch in its planning. In addition, a deeper integration with finance and market monitoring, risk management and risk monitoring, and logistics and delivery monitoring is also required for better optimization of procurement operations.

6. Integrate ESG and optimize upstream Scope 3. A

While sustainability should have been a front-and-center concern since it became clear near the end of last decade if you didn’t get ahead of it, you’d be behind (and in trouble when the legislations rolled into effect). However, while sustainability was clear, and targets were clear, it wasn’t necessarily clear (without thinking about the issue) that you would have to focus on not only tacking upstream Scope 3, but on how you will need to help those suppliers, possibly a few tiers down in the supply chain, optimize Scope 3 as there is nothing significant you can do to control your carbon debt if you don’t minimize it before it gets to you.

Procurement 2024 or Procurement’s Greatest Hits? McKinsey’s on the money, but … Part 1

… in some cases this is money you should have been on a decade ago!

Let’s backtrack. McKinsey ended Q1 by publishing a piece on Procurement 2024: The next ten CPO actions to meet today’s toughest challenges which had some great advice, but in some cases these were actions that your Procurement organization should have been taking five, if not ten years ago. And, if your organization was doing so in these cases, should be moving on to true next actions the article didn’t even address.

So, as you probably guessed, we’re going to discuss each one, give credit where credit is due (they are pretty good at strategy after all), and indicate where they missed a bit and tell you what to do next if you are already doing the actions you should have been doing years ago. And, just like we did to THE PROPHET‘s predictions, grade them. In this first installment, we’ll tackle the first three actions, which they group under the heading of:

End-to-End Value Capture

1. Utilize New Frontier Analytics and AI. B

Even though you should have been doing this since the introduction of spend analysis over 20 years ago, the recommendation to employ advanced analytics to extract valuable insights from procurement data is definitely A+ because analytics gets better every year, knowledge of which analytics to apply to a vertical and category gets better every year, and the constant increases in computing power makes it an increasingly powerful tool at your disposal.

However, the “AI” part is a B- at best. Using predictive analytics for commodity and market forecasting, risk prediction, and performance optimization is good, but AI can’t predict talent and you definitely should NOT use a Gen-AI bot to develop strategic decisions! Remember Gen stands for Generative which is defined as “make sh!t up” and there is a strong likelihood that it will hallucinate and the hallucination will sound more reliable than the non-hallucinatory recommendation it gives in very similar situations. Properly used, traditional, predictable, and, most importantly, deterministic (or at least verifiable) techniques can provide great value … but new, generative, unproven AI technology (which could have embedded sleeper behaviour) is NOT the answer.

2. Create a Request for Proposal (RFP) Engine. B

The article notes that you should develop … an approach for prioritizing categories and suppliers based on market development, spend analysis, and supplier leverage. This is something you should have been doing since the day you first implemented a strategic sourcing program. And you definitely should have been prioritizing spending with the highest potential to drive value for the organization, while deprioritizing categories or suppliers where value will be more challenging to obtain. In 2024 what you should be doing as part of this RFP engine is prioritizing categories and suppliers based on potential return from the strategic effort at this time (not potential for future value, potential for immediate value to meet the organization’s #1 priority of cost control) and then shifting all of the other categories to semi-automated sourcing events most likely to generate the best return. (i.e. well designed events, not an event for every request, you don’t want the squirrels thinking you are nuts)

The organization should have a platform that supports multi-round RFX-based events and multiple templates, reverse auctions (of various types), and the intermixing thereof. It should also support supplier onboarding, API-based verification with third parties, business/insurance/certification verification where possible, and so on. A buyer should be able to select a template for a single or multi-round event, define a timeframe, define a volume, click go, and the platform should automate an entire sourcing event until it’s time to verify an award (as the the platform should also recommend the award based on the bids and RFP responses). That’s the key to cost control — everything is sourced, but the effort made is relative to the potential return on that effort. Small return potential, semi-automate everything using the right technologies and processes. Large return, put in full manual effort in to maximize the value.

3. Redesign Value Creation with Key Suppliers. A

While this is something that needs to be done on a regular basis, given that rapid inflation is back, logistics is still unstable (we went from COVID to disruptions in the red sea at the same time as Panamanian droughts, forcing a return to long, dangerous, ocean routes around the capes), consumer demand is down, relations with China are deteriorating, and so on. Furthermore, not only is cost control paramount, so is value creation to increase not only value capture, but to also maintain, and maybe even slightly increase, consumer share in a down economy.

Come back for Part 2!

Procurement Leaders Listen to Roxette!


How do you do (do you do) the things that you do?
No one I know could ever keep up with you
How do you do?
Did it ever make sense to you …

A recent article over on Procurement Leaders asks CPOs why do you do and notes that a recent exercise they’ve been carrying out has been to ask CPOs to share the value propositions they have in place for their function.

Procurement Leaders’ goal was to force extremely busy people to take a step back and think deeply about why they do what they do. What are the ultimate goals of those negotiations with suppliers? Why are they spending time building relationships with certain suppliers and not others? Where should scarce resources and investment dollars be spent? This is because while a value proposition for a Procurement department is not an easy thing to produce and even more challenging to agree and implement, the provocation can allow a Procurement Department to get back to strategy, think about how our decisions affect our stakeholders, suppliers and the communities we do business in.

And while a Procurement department should understand its value proposition, because it helps it focus and relay its value, getting everyone in the organization to agree can be a very extensive effort and extremely time consuming. Furthermore, when you consider the possibility that the “value proposition” ultimately agreed on could be such a mish-mash of different viewpoints and demands to the point that it adds absolutely no value whatsoever, just like a corporate “mission statement” when everyone gets to add their bit to it (and the end result is no different than what the Dilbert Mission Statement Generator used to generate).

However, if you look at the example questions Procurement Leaders’ quoted, you realize that while a vision might be a good goal, a better effort, or at least a better way to start, is to ask the C-Suite to outline it’s top goals for the year, and then for the Procurement organization to identify the best ways they can meet those goals. From there they can identify: which categories should be strategically sourced, which products or services are critical for them, which suppliers are likely critical, and then, for each project, define the value and the goal and not spend effort building relationships with suppliers who are supplying tactical products or services that can be just as easily obtained from the next three lowest bid suppliers and instead spend time developing relationships with suppliers who are critical, even if the overall spend is low. For example, control chips in cars and power regulation systems are extremely critical and often only (capable of) being produced by a few suppliers due to highly specific requirements or proprietary natures. Compared to the costs of the steel, the transmission, the engine and/or the batteries, and even the tires, the total spend might not even register when the chips are only a couple of dollars each — but if a supplier failure, logistics delay, or raw material shortage shuts down your entire production line because you didn’t see a shortfall coming and either work with your supplier to build up an inventory or work with the backup supplier to allow production to be ramped up quickly, hundreds of millions of dollars in revenue could be at stake.

Furthermore, no effort should be spent “strategically” sourcing a product or category where the payback isn’t at least 3X the cost of the manpower required to do so. If an automated multi-round RFX with automated feedback or a reverse auction will get you 99% of the savings and the last 1% won’t even pay for 3X the salary and overhead of the buyer, it’s just not worth it if this prevents the organization from sourcing a lower cost category with a 5% savings potential through better analysis and negotiation. Know the value, define the value, and only put effort in where there is real value to be gained. Otherwise, use appropriate automation or redefine categories and projects. (Definitely don’t go nuts and RFQ everything, because even the squirrels will know you’re nuts if you do. But maybe do some overarching sourcing or negotiation that you can just cut POs or one-time orders against for a year. Sometimes just negotiating for 20% off of lowest list price in a 30 day window [and carefully tracking and documenting those prices to prevent invoice overcharges] is enough to automate catalog orders.)

And similar logic applies to all Procurement (related) activities. While machines can’t replace procurement professionals, they can take over the tasks where their intervention doesn’t add value. That’s the point. So think before you act, and act appropriately.

You NEVER Have to Go Crazy on 3 Bids and a Buy!

This is a follow-up to last Friday’s article on RFP Everything? Are You Mad? Even The Squirrels Will Think You’re Nuts!,
which was in response to a LinkedIn Post where a consultant noted that a remarkable example of AI was autonomous tail spend RFP’s generating over 15,000 RFP’s annually through a programmed bot. the doctor‘s response to this was that it was absolutely terrifying. Sales professionals who are already over-inundated with ever more demanding RFQs where they know, statistically, they will only get 20% to 33% of the business if they are on par, and less of the business if they are not, are going to be so overwhelmed that they are going to have two options:

  • pick favourites and stop responding, or selling, to clients that over-inundate but under-buy or
  • acquire an auto-responder and counter auto-generated RFQs with auto-generated bids from their catalog, which may be good, bad, or pointless

Neither is good for the buying company. The counter to this was that there is a category of services which is one off and needs the collection of a number of competitive bids. The value of these services in the €10-100k bracket needed a tail spend management program for which we developed the automated ‘3 bids and a buy program’ … and there is no better way to organize it.

Which is totally not true, because the doctor saw a better way successfully implemented 16 years ago. Back in the day, Iasta (acquired by b-pack, renamed Determine, acquired by Corcentric) identified that one of the BEST uses for strategic sourcing decision optimization was services procurement (when most firms were still using it for indirect or fledgeling direct).

What they did was:

  1. identify all of the services their large mid-market clients would contract over the course of a year with typical durations
  2. collect bids from national, regional, & local providers
  3. build a huge optimization model which would identify the lowest cost providers for each service in each area and then make an annual award to a mix of national, regional, and local providers guaranteeing a certain volume / $-value of services across a certain number of service categories / roles across awarded service areas as long as the provider locked in the rates for a year

It was ingenious because, when the service was needed, the company simply sent the requisition to one of the chosen providers (lowest-cost first if available, or second-lowest if not or if they weren’t sending enough business to the second-lowest in other categories to meet the commitment).

ONE single RFQ event. One year of quotes negated. The approach regularly identified up to 40% savings, and realized up to 30% savings. David Bush and team were geniuses!

The morale of the story is this: if you think you need to send 15,000 auto-generated RFQs to get tail spend under control, you haven’t done enough thinking about, or analysis of, the problem!