Category Archives: Technology

Another “think tank” article on digitizing procurement that’s off-the-mark!

A recent article in Supply Chain Brain noted that you should be seizing the opportunity for digitizing procurement and the doctor completely agrees. Nothing should be paper based in Procurement today. There’s no excuse for it.

And yes, multiple developments in supply chain are converging to create an unprecedented digital opportunity for procurement professionals. Furthermore, if you work on mastering and combining emerging and maturing technologies in strategic ways since procurement teams are in a position to reshape how they work, and create value across the supply chain, you can revolutionize Procurement and business performance.

But digitizing, by definition, means moving processes from scrolls to systems, from the dark basement to the illuminated screens. It DOES NOT mean that:

  • you use Gen-AI or even machine learning
    there may be tasks where you apply point-based ML, but that comes after the digitization of an appropriate process
  • you use cognification to illuminate (concealed) processes
    especially when it could illuminate you should never have digitized the process in the first place
  • you accelerate workflow through automation
    you automate what you can, and while that includes the acceleration of tactical paperwork processing and thunking, sometimes humans have to step back and think about the data received, insights produced, and options available before making a decision … you don’t accelerate whatever amount of time it takes a human to make a good decision (and, instead, focus on automating and accelerating any non-strategic tactical “thunking” tasks that prevent them from focussing their brain power where it’s really needed)
  • you go straight to content personalization
    when the users might not even know how to use the baseline systems (and, in the process, create a nightmare for the support personnel)

Digitizing Procurement starts by:

  • understanding what processes you are using now
  • understanding if they are appropriate or they should be optimized
  • identifying off-the-shelf best-of-breed modules, mini-suites, suites, and/or
    intake-to-orchestrate platforms and implementing them
  • identifying key points where RPA, ML, or other advanced techs can make the process even more efficient
  • then identifying the right advanced tech to use

Not starting with it. You should never try to run a race before you can walk. The only “impactful opportunity” identified in the article you should start with is

  • adopting ecosystem thinking to enhance data

At the end of the day, nothing works well without good data. So get the data right, and everyone aligned to get the data right, and that will get you further, and help you do better, than any piece of modern tech you can try to throw at the problem.

Thank you Vladimir Putin!

Thank you Vladimir Putin for saying what needed to be said.

(Open/Gen-) AI is dangerous. Very dangerous! And something needs to be done about it!

“Humanity has to consider what is going to happen due to the newest developments in genetics or in AI. One can make an approximate prediction of what will happen. Once mankind felt an existential threat coming from nuclear weapons, all nuclear nations began to come to terms with one another since they realized that negligent use of nuclear weaponry could drive humanity to extinction.

It is impossible to stop research in genetics or AI today, just as it was impossible to stop the use of gunpowder back in the day. But as soon as we realize that the threat comes from unbridled and uncontrolled development of AI, or genetics, or any other fields, the time will come to reach an international agreement on how to regulate these things.”

Transcript

I don’t know about you, but with respect to what has been advertised, these are the six variants of Open/Gen-AI the doctor sees:

Gender/Race-Biased: especially in HR; it’s trained on “good resumes”, but, guess what, when those “good resumes” were selected from a pool of hired candidates that have predominantly been white men, guess what the AI looks for?

Hallucinatory: too many stories to track now of AI creating fake summaries on fake articles by fake authors for which it created fake profiles; Lawyers have fall for this multiple times!

Harmful/Hateful: train it on open data which contains hate speech, just like a kid exposed to its first profanity, it mimics … non-stop

Murderous: multiple examples of self-help chat systems literally telling people to kill themselves (and then a few examples of people actually doing this) as well as self-driving systems ignoring the “shadows” of what were people RIGHT in front of them

Sleeper: the newest threat, sleeper behaviour that can go undetected for days, months, or years until a specific date or phrase is entered (in combination); the perfect sleeper agent!

Thieving: not only are these open AI plays generally trained on stolen data, but since all your queries and outputs are directly used (or indirectly influence) the network, they steal your data (even when the designers didn’t set about to do so)

Roughly Half a Trillion Dollars Will Be Wasted on SaaS Spend This Year and up to One Trillion Dollars on IT Services. How Much Will You Waste?

Before we continue, yes, that is TRILLION, numerically represented as 1,000,000,000,000, repeated twice in the title and yes we mean US (as in United States of America) dollars!

Gartner projects that IT spend will surpass 5 Trillion this year. When you consider that 30% of IT spend is usually for software, and that one third (or more) of software spend is wasted (for unused licenses, which is why we have a whole category of IT and SaaS specialists that analyze your out-of-control SaaS and software spend and typically find 30% to 40% overspend in a few days), that means that roughly half a trillion dollars will be wasted on software this year.

Even worse, Gartner projects that spending on IT Services will reach 1.5 Trillion. And the waste here could be two thirds! Now, we all know that you need IT services to implement, integrate, and maintain those IT systems you buy. But how much do you need? And how much should you pay? Consider that an intermediate software developer should be making 150K a year (or 75/hour), that says that an intermediate implementation specialist shouldn’t be making any more than that, and not billed at more than 3 times that (or 225/hour). But how much are you being billed for relatively inexperienced implementation consultant, with maybe a few years of overall experience and maybe six months on the system that you are installing? the doctor knows that rates of $300 to $500 are not uncommon for these resources that are oversold and overcharged for.

But this isn’t the worst of it. As per our upcoming article Fraud And Waste Are Not The Same Thing, many implementation “partners” will try to get all they can get and make sure that when you go in for a penny, you go in for a pound and they will push for:

  • frequent change orders during implementation, usually billed at excessively high day rates as they have to “divert resources” or “work overtime”
  • unnecessary customizations or real-time integrations that are an extensive amount of work (and cost) when out-of-the-box or daily flat-file synchs are more than sufficient
  • extensive “process evaluation” or “process transformation” processes that are well beyond what you need to eat up consulting hours
  • extensive “best practice” education when your practices are good enough for now and/or those best practices are already encoded in the system you just bought and paid a pretty penny for and just following the default process gives you the same education

That will often double to triple the cost. But that’s not the worst of it. As per comments the doctor has made on LinkedIn, he regularly hears stories of niche providers losing 200K deals because customers said their quote was too low because all the Big X companies quoted over 1,000K for what should be 100K worth of work in their view (and, right or wrong, if a niche firm comes in less with a detailed proposal, they should be evaluated — maybe the Big X, with a very general request, over estimated your requirements and the effort, or maybe the niche firm completely underestimated it — how will you know if you don’t evaluate all the responses?). Literally. This is because, as the doctor has noted in previous posts and comments on LinkedIn:

  • they don’t have always have the talent in advanced tech (and even The Prophet has noted their lack of talent in areas of advanced tech in multiple LinkedIn posts, though he has been much more diplomatic than the doctor in discussing their lack thereof; but he did note in a 2024 advice post that consultancies are going to have a hard time attracting talent this year) — for every area, an average firm will have a team leader who’s a superstar, two or three handpicked lieutenants who are above average, and then 20 to 40 benchwarmers who are junior and not always worth the rate they are charging);  now, as with every general observation, there are exceptions (with some Big X recently acquiring a number of best-in-class technology, analytics, and AI vendors that give them top-notch world class talent, and others actively recruiting top talent form the best tech firms, but every firm is different, and, most importantly, every need is different — it’s up to you to fully qualify your need, review the proposal carefully, and vet the proposed talent, otherwise, it’s your fault if you overpay, fail miserably, and don’t get value
  • some of these firms have an incredible overhead — they got big in good times and built posh offices to house the partners making more than top lawyers who have a lifestyle to maintain (or, in some cases, they just acquired expensive real estate in premiere locations)
  • they don’t always have the knowledge of, or experience in, modern tools — some of which are ten times more powerful than last generation tools; this, of course, means that, in these situations, Big X benchwarmers are using last generation tools which take ten times the manual labour to extract value from
  • etc.

Unless you want to pay 1K an hour, at some of these firms, you’re not guaranteed getting that one superstar resource trying to be the front end to two dozen projects that his three lieutenants are trying to manage, all of which are staffed by junior to intermediate individuals who can barely follow the three to five year old playbook.   (While if you chose a different Big X firm that just acquired a whole consultancy with dozens of top analysts, it’s a different story.)

There’s a reason that The Prophet predicted in his 9th prediction that SaaS Management Solutions [will] Start to Eat Services Procurement Tech and that many companies will go in house if they have tech expertise. Because he realizes that these consultancies will have a hard time not only hiring, but retaining, tech talent when they have hiring freezes, salary freezes, and reduced engagements as more and more companies can’t afford the ridiculous rates they’ve been charging recently. (Companies may not have had a choice during COVID where it was implement on-line collaboration and B2B tech or perish, but now they do.)

But there are still many companies who will, when they encounter a (perceived) tech need, immediately pick up the phone and call their favorite Big X firm and bring them in to help them understand who to bring in for an engagement, instead of widening the net to niche providers who might be 3 to 5 times cheaper, and who will deliver results at least as good, if not better, or, if their proposals won’t cut it, will validate when that multi-million proposal is a great value and will deliver the expected ROI.

Now, again, the doctor would like to stress that, despite how much he insists they are usually not the right solution for specialist advanced tech implementations that aren’t the enterprise systems and suites they usually implement, that Big X are not all bad, and sometimes worth many times more than the high fees they charge. [See when should you use Big X?] Most of these companies started off as management/operational/finance/strategy consultants and grew big because they were one of the best, and in certain domains, each of these companies still are. As they grew, they added more areas and became experts in those.  But no company can, and should, be expected to be an expert in everything!

And while there will be exceptions to the rule (as every one of these companies has some tech geniuses), the reality is that when you need more bodies than there are talented bodies in an entire industry, you’re not going to get them and, because consultancies are not cool when you want to be a tech superstar (and join a startup that becomes a unicorn), the ratio of superstar to above average to average to below average talent in these organizations is much thinner than in multinational tech companies (like Alphabet, Apple, Meta, Microsoft, etc.)  (Because if they were the best of the best, there’s no way they’d lay off 10,000 employees at a time every time the market jitters.)

In short, manage that IT services spend carefully, or you’ll be double paying, triple paying, or worse and providing a big chunk of the roughly ONE TRILLION DOLLARS in IT services overspend that the doctor predicts will happen (again) this year. (Unless, of course, you agree with Doctor Evil who says, why make trillions when we could make … billions. Because that’s exactly what happens when you overpay for software and services. Don’t expect the Big X or Mid-Market to say anything as they get the majority that overspend, and that’s how they stay so profitable.  Plus, they usually need those revenues to deliver what you’re asking for, as ill-defined projects mean they need to make a lot of assumptions and often over engineer to decrease the chance you will be disappointed in the result!  In other words, if you overpay due to your lack of research and preparation, it’s on you. )

Technology for Supplier Onboarding is the NOW, not the Future!

In fact, for any company that hasn’t been in a cave for the last TWO (2) decades, it’s the past!

Needless to say, the doctor was shocked to see this recent headline in Supply Chain Digital that purported to answer why technology is the future for supplier onboarding because either you’re using technology for supplier onboarding today, or you’re not going to be around much longer as a company.

Without a good solution, the time it takes to collect and evaluate enough data to even determine if the supplier is legit, in your industry, appropriately certified, not on any banned lists, financially stable, with real customers, etc. is days, sometimes weeks. And then the time to evaluate the supplier to supply even a single product can be weeks, especially in direct, when you have to trace the product components down to the raw material source to make sure there are no conflict diamonds, no Congolese cobalt, and no indentured / kafala / slave labour in the mines your metals come from.

Even though the article headline is, well, wrong, there are some good points in the article.

Having a strategic approach to supplier onboarding is a key component of supply chain risk management. Most definitely. You don’t want to hook up with a supplier that’s just going to increase your risk, stop your production lines, bring regulatory and compliance investigations your way, and possibly get your CFO or CEO in hot water because you had them sign off on a supplier as being safe when, in fact, it was the business equivalent of a landmine.

With a properly configured supplier management solution, you can check that a supplier meets all of the basic regulatory requirements, financial requirements, and baseline operational requirements in a minute. Literally. You plug in the name and ONE governmental ID code and it pulls in every single piece of information in government systems, third party finance / ESG / Risk databases, insurance and compliance databases, and community intelligence gathered in its systems and indicates if the supplier:

  • failed any registration checks
  • failed any denied party checks
  • has any owners, directors, investors, or connected parties that failed a check
  • has filed its financial reports and is not rated as a going concern
  • has reasonable ESG ratings
  • has any reports of, or known connections to, forced/child/slave labour
  • has valid insurance
  • has valid regulatory compliance certificates
  • any other requirement that can be looked up from a public database

And you know if there are any alerts or failures within minutes, not hours, days, or weeks.

Which lets you dive into evaluating whether or not they can supply the product you need at the quality and quantity, and in a manner that is not quixotic to your business environment.

You can then define additional requirements for automatic lookup, ask for tier 2 suppliers, do the same automatic checks on those, specific to the component or raw material they are providing, and if all that passes, which you will know in minutes, then you can begin the real research in minutes, not hours, days, or weeks. And the real research can take days, or weeks (and sometimes more) in real time when you need to look deep into the production capabilities, the labour that is used, the materials that are used, and the quality of the finished good (which you may need to see a sample of). But the last thing you want to do is waste weeks trying to get to this point only to find out three weeks in that the supplier is on a banned list for one of your main marketplaces, the tier 3 uses cobalt from the Congo (and if you don’t know why that is bad, do ONE minute of web research [unless, of course, you are a psychopath or sociopath with no regard for human rights or even welfare]), or is facing multiple lawsuits for unsafe products in multiple countries.

It is imperative that C-suiters “act with urgency around risk”. Nothing could be truer. It seems that risk is doubling every day. You need to be ready, and while you can’t be ready for everything, you can minimize the chances of risk by ensuring that your suppliers are not adding risk and, in fact, as dedicated as you in minimizing their risk profile. Moreover, if you have a good supply base, they can work with you to mitigate the impact of disruptions when those disruptions rear their ugly head.

“This year we expect to see increased ESG regulation”. It’s coming, and the best way to be prepared for it is with systems that can run checks, collect the required data, flag potential issues, and make sure you keep on top of whatever you need to in order to comply with those regulations.

“Invest in your processes, to ensure you can do more with the same, or fewer, resources. This usually means automating your supply chain data, so you’re finding new suppliers or managing existing suppliers.” Definitely.

Technology has a vital role to play in supplier onboarding. Most definitely. Except you should have been using it for the past two decades, not looking for a solution today. Why do you think there are 100+ vendors offering supplier management solutions? Because they’ve worked wonders (relative to not having any solution) since they were first introduced two decades ago. And, most importantly, they’ve went from simple information management solutions to advanced data collection, validation, and risk assessment solutions where you can quickly validate, analyze, and decide if you want to even consider engaging with a supplier in minutes. You can also collaborate, develop, and implement supplier programs. And you can even orchestrate supply networks with modern solutions.

So if your solution doesn’t solve your CORNED QUIP mash of supplier management problems, maybe it’s time you found a new one. You can’t wait for the future to solve your supplier management problems, you need to solve them today!

Forget Consequence Free. I wanna be Gen-AI Free!

To the tune of Consequence Free by Great Big Sea.

Na na-na, na na na-na na na!
Na na-na, na na na-na na na!

Wouldn’t it be great,
if no one ever was redundant?
Wouldn’t it be great,
if we made all the decisions?

I’ve always said,
All the rules are made for bending.
And if I did the right thing,
What’s wrong with that vision?

I wanna be Gen-AI free!
I wanna be where humans always matter.
I wanna be Gen-AI free!
And say: Na na-na, na na na-na na na!
Oh! Na na-na, na na na-na na na!

I could really use,
To lose my ethical conscience.
Cause I’m getting sick,
Of feeling angry all the time.

I won’t abuse it,
Yeah I’ve got the best intentions.
For a little bit of anarchy,
But not the hurting kind.

I wanna be Gen-AI free!
I wanna be where humans always matter.
I wanna be Gen-AI free!
And say: Na na-na, na na na-na na na!
Oh! Na na-na, na na na-na na na!

Oh! I couldn’t sleep at all last night,
‘Cause I had AI on my mind.
Why can’t we leave it all behind,
You know it could be that easy.

It just takes one person
Wouldn’t it be great,
If the CEO made that call
We could do the work,
And we would never get the slip.

Wouldn’t need to worry about illogic or bad data.
We could slip off the edge,
And never worry about the fall.

I wanna be Gen-AI free!
I wanna be where humans always matter.
I wanna be Gen-AI free!
And say: Na na-na, na na na-na na na!
Oh! Na na-na, na na na-na na na!
Oh! Na na-na, na na na-na na na!

the doctor, while an early adopter of SSDO, rule-based RPA, Machine Learning, and other “AI” technologies, is serious here. Gen-AI is garbage at best, bull crap the majority of the time, and toxic waste when it fails. What other technology produces hallucinations, hate speech, and hot (as in stolen) data on a regular basis? What other technology has literally convinced people to commit suicide?

It’s not ready for prime-time, and may never be. Go back to carefully constructed NLP solutions on carefully designed data sets that actually work. We don’t need Artificial Idiocy where you need more training in prompting to have a chance at solving a problem than developers need training in coding to write a reliable deterministic algorithm that actually solves the problem. Sure it seems to work “okay” 90% of the time with normal usage, but what about that 9% of the time it doesn’t or the 1% it fails so drastically it could cost you millions of dollars in direct and indirect damages? Is it worth it? (The answer is NO!)

Some light reading. More can be found by Googling Gen-AI Fails and similar search terms.