Category Archives: rants

Even Forbes is Falling for the the Gen-AI Garbage!

This recent article in Forbes on the Supply Chain Shift to Intelligent Technology is what inspired last week’s and this week’s rant because, while supply chains should be shifting to intelligent technology, the situations in which that is Gen-AI are still extremely rare (to the point that a blue moon is much more common). But what really got the doctor‘s goat is the ridiculous claims as to what Gen-AI can do. Claims with are simultaneously maddening and saddening because, if they just left out Gen-AI, then everything they claimed is not only doable, but doable with fantastic results.

Of the first three claims, Gen-AI can only be used to solve one — and only partially.

Procurement and Regulatory Compliance
This is one example where a Closed Private Gen-AI LLM is half the battle — it can process, summarize, and highlight key areas of hundred page texts faster and better than prior NLP tech. But it can’t tell you if your current contracts, processes, efforts, or plans will meet the requirements. Not even close. In fact, no AI can — the best AI can just indicate the presence or absence of data, processes, or tech that are most likely to be relevant and then an intelligent human needs to make the decision, possibly only after obtaining appropriate expert Legal advice.
Manufacturing Efficiency
streamline production workflows? optimize processes? reduce errors? No, Hell No, and even the Joker wouldn’t make that joke! You want streamlining? You first have to do a deep process cycle time analysis, compare it to whatever benchmarks you can get, identify the inefficiencies, identify potential processes and tech for improvement, and implement them. Optimize processes? Detailed step by step analysis, identification of opportunities, expert process redesign, training, implementation, and monitoring. Reduce errors? No! People and tech do the processes, not Gen-AI — implement better monitoring, rules, and safeguards.
Virtual Supply Collaboration
A super-charged chatbot on steroids is NOT a virtual assistant. Now, properly sandwiched between classical AI and rules-based intelligence it can deal with 80% of routine inquiries, but not on its own, and it’s arguable if it’s even worth it when a well designed app can get the user to the info they need 10 times faster with just a couple of clicks. Supply chain communicating? People HATE getting a “robot” on a support line as much as you do, to the point some of us start screaming profanities at it if we don’t get a real operator within 10 seconds. Based on this, do you really think your supplier wants to talk to a dumb bot that has NO authority to make a decision (or, at least, should NEVER have the authority — though the doctor is sure someone’s going to be dumb enough to give the bot the authority … let’s just hope they can live with the inevitable consequences)?

And maybe if the article had stopped there the doctor would let it pass, but
first of all, it went on to state the following for “AI”, without clarifying that Gen-AI doesn’t fit in the process, leading us to conclude that, since the first part of the article is about Gen-AI, this part is too, and thus is totally wrong when it claims that:

“AI” understands dirty data
with about 70% accuracy where it counts IF you’re lucky; that’s about how accurate it is at identifying a supplier from your ERP/AP transaction records; an admin assistant will get about 98% accuracy by comparison
it can “confirm” inventories
all it can do is regurgitate what’s in the inventory system — that’s not confirmation!
it can identify duplicate materials
first it has to identify two records that are actually duplicates;
and how likely do you think this is with a supplier mapping accuracy of 70%?
it can identify materials to be shared among facilities
well, okay, it can identify materials that are used across facilities and could be located in a central location — but how useful is that? it’s not because, first of all, YOU ALREADY KNOW THIS, and, second, IT CAN’T DO SUPPLY CHAIN OPTIMIZATION — THAT’S WHAT A SUPPLY CHAIN OPTIMIZATION SOLUTION IS FOR! OPTIMIZATION!!! We’ll break it down syllabically for you so you know what to ask for. OP – TUH – MY – ZAY – SHUN!
it can recommend ideal storage locations
again, NO! This requires solving a very sophisticated optimization model it doesn’t have the data for, doesn’t know how to build, and definitely doesn’t know how to solve.
it can revamp outdated stocking policies
well, only the solution of a proper Inventory OPTIMIZATION Model that identifies the appropriate locations and safety stock levels can identify how these should be revamped
it can recommend order patterns by consumption and lead time
that’s classical curve fitting and tend projection

And, secondly, as the doctor just explained, most of what they were saying AI could do CAN’T be done with AI, and instead can only be done with analytics, optimization, and advanced mathematical models! (You know, the advanced tech (that works) that you’ve been ignoring for over two decades!)

The Gen-AI garbage is getting out of control. It’s time to stop putting up with it and start pushing back against any provider who’s trying to sell you this miracle cure silicon snake oil and show them the door. There are real solutions that work, and have worked, for two decades that will revolutionize your supply chain. You don’t need false promises and tech that isn’t ready for prime time.

Somedays the doctor just wishes he was the Scarecrow. Only someone without a brain can deal with this constant level of Gen-AI bullsh!t and not be stressed about the deluge of misinformation being spread on a daily basis! But then again, without a brain, he might be fooled by the slick salespeople that Gen-AI could give him one, instead of remembering the wise words of the True Scarecrow.

You Don’t Need Gen-AI to Revolutionize Procurement and Supply Chain Management — Classic Analytics, Optimization, and Machine Learning that You Have Been Ignoring for Two Decades Will Do Just Fine!

Open Gen-AI technology may be about as reliable as a career politician managing your Nigerian bank account, but somehow it’s won the PR war (since there is longer any requirement to speak the truth or state actual facts in sales and marketing in most “first” world countries [where they believe Alternative Math is a real thing … and that’s why they can’t balance their budgets, FYI]) as every Big X is pushing Open Gen-AI as the greatest revolution in technology since the abacus. the doctor shouldn’t be surprised, given that most of the turkeys on their rafters can’t even do basic math* (but yet profess to deeply understand this technology) and thus believe the hype (and downplay the serious risks, which we summarized in this article, where we didn’t even mention the quality of the results when you unexpectedly get a result that doesn’t exhibit any of the six major issues).

The Power of Real Spend Analysis

If you have a real Spend Analysis tool, like Spendata (The Spend Analysis Power Tool), simple data exploration will find you a 10% or more savings opportunity in just a few days (well, maybe a few weeks, but that’s still just a matter of days). It’s one of only two technologies that has been demonstrated, when properly deployed and used, to identify returns of 10% or more, year after year after year, since the mid 2000s (when the technology wasn’t nearly as good as it is today), and it can be used by any Procurement or Finance Analyst that has a basic understanding of their data.

When you have a tool that will let you analyze data around any dimension of interest — supplier, category, product — restrict it to any subset of interest — timeframe, geographic location, off-contract spend — and roll-up, compare against, and drill down by variance — the opportunities you will find will be considerable. Even in the best sourced top spend categories, you’ll usually find 2% to 3%, in the mid-spend likely 5% or more, in the tail, likely 15% or more … and that’s before you identify unexpected opportunities by division (who aren’t adhering to the new contracts), geography (where a new local supplier can slash transportation costs), product line (where subtle shifts in pricing — and yes, real spend analysis can also handle sales and pricing data — lead to unexpected sales increases and greater savings when you bump your orders to the next discount level), and even in warranty costs (when you identify that a certain supplier location is continually delivering low quality goods compared to its peers).

And that’s just the Procurement spend … it can also handle the supply chain spend, logistics spend, warranty spend, utility and HR spend — and while you can’t control the HR spend, you can get a handle on your average cost by position by location and possibly restructure your hubs during expansion time to where resources are lower cost! Savings, savings, savings … you’ll find them ’round the clock … savings, savings, savings … analytics rocks!

The Power of Strategic Sourcing Decision Optimization

Decision optimization has been around in the Procurement space for almost 25 years, but it still has less than 10% penetration! This is utterly abysmal. It’s not only the only other technology that has been generating returns of 10% or more, in good times and bad, for any leading organization that consistently uses it, but the only technology that the doctor has seen that has consistently generated 20% to 30% savings opportunities on large multi-national complex categories that just can’t be solved with RFQ and a spreadsheet, no matter how hard you try. (But if you want to pay them, a Big X will still claim they can with the old college try if you pay their top analyst’s salary for a few months … and at 5K a day, there goes three times any savings they identify.)

Examples where the doctor has repeatedly seen stellar results include:

  • national service provider contract optimization across national, regional, and local providers where rates, expected utilization, and all-in costs for remote resources are considered; With just an RFX solution, the usual solution is to go to all the relevant Big X Bodyshops and get their rate cards by role by location by base rate (with expenses picked up by the org) and all-in rate; calc. the expected local overhead rate by location; then, for each Big X – role – location, determine if the Big X all-in rate or the Big X base rate plus their overhead is cheaper and select that as the final bid for analysis; then mark the lowest bid for each role-location and determine the three top providers; then distribute the award between the three “top” providers in the lowest cost fashion; and, in big companies using a lot of contract labour, leave millions on the table because 1) sometimes the cheapest 3 will actually be the providers with the middle of the road bids across the board and 2) for some areas/roles, regional, and definitely local, providers will often be cheaper — but since the complexity is beyond manageable, this isn’t done, even though the doctor has seen multiple real-world events generate 30% to 40% savings since optimization can handle hundreds of suppliers and tens of thousands of bids and find the perfect mix (even while limiting the number of global providers and the number of providers who can service a location)
  • global mailer / catalog production —
    paper won’t go away, and when you have to balance inks, papers, printing, distribution, and mailing — it’s not always local or one country in a region that minimizes costs, it’s a very complex sourcing AND logistics distribution that optimizes costs … and the real-world model gets dizzying fast unless you use optimization, which will find 10% or more savings beyond your current best efforts
  • build-to-order assembly — don’t just leave that to the contract manufacturer, when you can simultaneously analyze the entire BoM and supply chain, which can easily dwarf the above two models if you have 50 or more items, as savings will just appear when you do so

… but yet, because it’s “math”, it doesn’t get used, even though you don’t have to do the math — the platform does!

Curve Fitting Trend Analysis

Dozens (and dozens) of “AI” models have been developed over the past few years to provide you with “predictive” forecasts, insights, and analytics, but guess what? Not a SINGLE model has outdone classical curve-fitting trend analysis — and NOT a single model ever will. (This is because all these fancy-smancy black box solutions do is attempt to identify the record/transaction “fingerprint” that contains the most relevant data and then attempt to identify the “curve” or “line” to fit it too all at once, which means the upper bound is a classical model that uses the right data and fits to the right curve from the beginning, without wasting an entire plant’s worth of energy powering entire data centers as the algorithm repeatedly guesses random fingerprints and models until one seems to work well.)

And the reality is that these standard techniques (which have been refined since the 60s and 70s), which now run blindingly fast on large data sets thanks to today’s computing, can achieve 95% to 98% accuracy in some domains, with no misfires. A 95% accurate forecast on inventory, sales, etc. is pretty damn good and minimizes the buffer stock, and lead time, you need. Detailed, fine tuned, correlation analysis can accurately predict the impact of sales and industry events. And so on.

Going one step further, there exists a host of clustering techniques that can identify emergent trends in outlier behaviour as well as pockets of customers or demand. And so on. But chances are you aren’t using any of these techniques.

So given that most of you haven’t adopted any of this technology that has proven to be reliable, effective, and extremely valuable, why on earth would you want to adopt an unproven technology that hallucinates daily, might tell of your sensitive employees with hate speech, and even leak your data? It makes ZERO sense!

While we admit that someday semi-private LLMs will be an appropriate solution for certain areas of your business where large amount of textual analysis is required on a regular basis, even these are still iffy today and can’t always be trusted. And the doctor doesn’t care how slick that chatbot is because if you have to spend days learning how to expertly craft a prompt just to get a single result, you might as well just learn to code and use a classic open source Neural Net library — you’ll get better, more reliable, results faster.

Keep an eye on the tech if you like, but nothing stops you from using the tech that works. Let your peers be the test pilots. You really don’t want to be in the cockpit when it crashes.

* And if you don’t understand why a deep understand of university level mathematics, preferably at the graduate level, is important, then you shouldn’t be touching the turkey who touches the Gen-AI solution with a 10-foot pole!

Last Friday Was International Women’s Day. You Made a Big Fuss. Well, What Did You Do This Week?

This is taken from a LinkedIn post the doctor posted on Monday, March 11. It’s being reposted here for those who don’t follow LinkedIn and because, as expected, he hasn’t heard a single peep from any organization that was spewing platitudes last Friday as if praise one day a year was doing enough.

If you truly celebrate women, then please tell me:

What are you doing TODAY to

  1. increase the number of women in Management, STEM, Executive Suites, and Investment Firms,
  2. close the pay gap that is still 15% to 30% across these areas,
  3. encourage women to join your company to pursue their career, and
  4. enable the work life balance they need to be AS or MORE successful than their male counterparts?

As most of you are probably well aware from the deluge of “we support and honour our female leaders who … ” posts on LinkedIn last Friday, International Women’s Day was last Friday (2024-Mar-08). I stayed silent, as usual, because I found the majority of them very upsetting.

While some of the posts were very sincere, and some came from individuals I know had the best of intentions:

  1. Lip service does nothing to address the four major issues above.
  2. The lip service I saw in some of these posts was about as meaningful as a token thank you card at the annual Christmas party.
  3. Few addressed the real issues women still face in “traditional” workspaces run, and dominated, by men.
  4. Those few that honoured teams with equal representation or greater, or at least statistically average representation (in companies in fields where women are currently only 25% of the workforce, like STEM) have done nothing to educate their peers on how important this is and how successful they are because of it.

If you are a leader in a company (with actual employees) that truly cares, then I challenge you to celebrate their achievements and capability every day, and once a month make a post on efforts your company is taking to increase the number of women, close the pay and rank gaps, and support their work life balance, either through hiring, training, support for community programs that do such or at least make a post on the stellar accomplishments they have accomplished that would put an average salesman to shame.

And to keep doing this until they have the equality, and the respect they deserve.

The simple facts are

  1. women are half the population,
  2. are just as capable of men (as there is NO difference between average IQ scores), and
  3. should be half the workforce.

If women are not half the workforce at your company (or at least not represented statistically in line with the average representation in the field your company is in), it’s not their lack of achievement, dear men, it’s yours!

The Public Sector is Giving Procurement Integrity A Bad Name … Can the Private Sector Fix It?

A recent article over on Global Government Forum on Procurement Integrity: A Big Problem That’s Worse Than Most Organizations Think, pointed out that errors, fraud and abuse in procurement cost governments and organizations millions of dollars every year, and even though recent headlines in the US (TriMark, Booz Allen Hamilton), UK (NHS, Royal Mail), and Canada (ArriveCan) are starting to shine the light on the extent of (public sector) procurement fraud, the problem is still bigger than you think. Much bigger.

Current estimates are that organizations, across the public and private sectors, lose 5% per year due to procurement errors, abuse, and fraud. Given that Global GDP is about 85 Trillion dollars, at 5%, that’s 4 TRILLION dollars estimated to be lost annually to errors, abuse, and fraud. And that’s probably a low-ball estimate due to the fact that we just calculated that Over One TRILLION dollars will be wasted on IT software and services due, primarily, to lack of knowledge and/or outright stupidity (and not malicious intent, but if it’s easy for consultancies and third parties to considerably over bill for legitimate goods and services that you need, imagine how much they are fleecing you for goods and services that you don’t need and may not even receive).

It’s highly likely that the true cost of errors, abuse, and fraud (internal, collusion, and external) is closer to 10% of total GDP, or close to EIGHT TRILLION. That’s at least twice the GDP of every country on the planet except China and the United States. That’s a BIG PROBLEM, which is definitely not being helped by the 100M to Multi Billion Procurement Frauds being reported almost monthly across major western economies — and multi-million dollar fines don’t repair the damage. (They don’t even come close.)

This is damage which Procurement needs to repair — because Procurement is the only department that has any hope of putting proper procedures, processes, and platforms in place to minimize the errors; training the organizational employees on proper procedures and monitoring the implementations to prevent abuse; and putting in place proper detection systems to detect, and prevent, potential fraud and quickly identify and track it when it happens.

Unless all the bucks go through, and stop at, a modern Procurement department run by a CPO who puts in place proper people, processes, and platforms, loss is going to continue to run rampant. Which means that while the public sector is failing us daily, the Private sector has to step up and restore the integrity of Procurement. It can start by utilizing some of the the techniques in the linked article, and continue by continually learning and implementing the best technology and processes it finds to not only uncover significant savings in inflationary times, but return integrity and trust into big business, and give governments who have lost their way a model to follow.

And for more details on Bad Buying to avoid, and how to achieve Procurement with Purpose, the doctor suggests you start by following the great public procurement defender, Peter Smith.

One of these things is not like the other — it’s the right choice!

Three bids for that spend analytics project from the three leading Big X firms come in at 1 Million. One bid for that spend analytics project from a specialized niche consultancy you pulled out of the hat for bid diversity comes in at 250 Thousand. Which one is right? Those of you who only partially paid attention to the education Sesame Street was trying to impart upon you when you were growing up will simply remember the “one of these things is not like the other” song and think that any of the bids from the Big X firm is right and the niche consultancy is wrong because it’s different, and therefore must be thrown out because it’s too low when, in fact, it’s the three bids from the Big X firms that are wrong and the bid from the niche consultancy that was right.

Those of us who paid attention knew that Sesame Street was trying to show us how to detect underlying similarities so we could properly cluster objects for further analysis. What we should have learned is that the Big X bids were all the same, built on the same assumption, and can be compared equally. And that the outlier bid needed further investigation — a further investigation that can only be undertaken against an appropriately sized set of sample set of bids from other specialized niche consultancies to compare against. And without that sample set of bids, you can’t properly evaluate the lower bid, which, the doctor can tell you, is likely closer to correct than the wildly overpriced Big X bids.

As per our recent post on don’t hire a F6ckw@d from a Big X if you want to get analytics and AI right, most of these guys don’t have the breadth of expertise they claim to have. In the group that sells you, there will be a leader who is a true expert (and worth his or her weight in platinum), a few handpicked lieutenants who are above average and run the projects, and a rafter of turkeys straight out of private college with more training in how to dress, talk, and follow orders than training in actual analytics … and no guarantee they even have any real university level mathematics (and thus a knowledge of what analytics is and isn’t and can and can’t do).

While there was a time big analytics projects were million dollar projects, that was twenty years ago when Spend Analysis 1.0 was still hitting the market; when there were limited tools for data integration, mapping, cleansing, and enrichment; and when there weren’t a lot of statistics on average savings opportunities across internal and external spend categories. Now we have mature Spend Analysis 3.0 technologies (some taking steps towards spend analysis 4.0 technologies); advanced technologies for automatic data integration, mapping, cleansing, and even enrichment; deep databases on projects and results by vertical and industry size; extensive libraries for out-of-the-box analytics across categories and potential opportunities; and a whole toolkit for spend analysis that didn’t exist two decades ago. This new toolkit, built by best of breed vendors used, and sometimes [co-]owned by these best of breed niche consultancies (that don’t try to do everything, and definitely don’t pretend they can), allows modern spend analysis projects to be done ten times as efficiently and effectively, in the hands of a master — a master that isn’t on your project if you hire a Big X. A niche consultancy will have all these tools, and only have masters on the project who do these projects day in and day out. Compared to the Big X, which will have a team of juniors using the manual playbook from the early 2000s, and one lieutenant to guide them. That’s why their project bids are five times as much — and why you should be inviting multiple niche best-of-breed consultancies to bid on your project and be focussing in on their six figure bids for the one that provides the best value, not the seven figure Big X bids.

(This is also the case for implementations. The Big X always have a rafter on the bench to assign to any project you give them, but there’s no guarantee any of them have ever implemented the system you chose before, or if they did, no guarantee they’ve ever connected it to the systems you need to connect to. You need specialists if you want that big new system implmented as cost effectively as possible. Even if you’re paying those specialists 500 or more an hour because getting a system up in 2 months at 40K is considerably better than a small team of turkeys taking 4 months at 250 an hour and a total cost of 100K.)

Remember, where Big X are concerned, All of us is as dumb as One of us! Don’t fall for the Big X Collectivism MindF6ck! the doctor does NOT want to do say it again, but since a month still is not going by where he’s hearing about niche consultancies being thrown out for “being too cheap” (which means the enterprise throwing them out is too uninformed and not recognizing that the Big X bids are the outliers because they aren’t inviting enough expert consultancies to the table), apparently he has to keep writing (and screaming) this truth. (the doctor isn’t saying that you can’t get a million dollars of value from some of these consultancies, just that you won’t by giving them these types of projects which they are not suited for and don’t have the expertise in. Remember, most of these firms got big in management, or accounting and tax, or marketing and sales consulting, not technology consulting. The only reason these big consultancies are offering these services is because of the amount of money flowing into technology, money which they want, but while the best of the best of the best in more traditional accounting, management, and marketing fields flocked to them, the best of the best in technology flocked to startups and c00l big tech firms. So they just don’t have the talent in tech.)


Did you ever try eating a mitten? the doctor bets they did! (He feels you’re not all there if you think glorified reporting projects still cost One Million Dollars and might actually try to eat your mittens!)