Category Archives: Market Intelligence

The world is not binary, flat, or stable!

It’s multi-state, curved, and chaotic.

You need fuzzy math, fractal geometry, and non-linear differential equations to describe it.

Similarly, the supply chain world we built is not a predictable single source flatland (as the work of Edwin Abott Abott in 1884 should have made clear to you).

You need multi-state logic, multiple (supply) chains and multiple methods for managing them.

And these DO NOT fit into a 2 x 2 grid! It’s this ongoing lie that ultimately leads to failure and organizations bringing in one consultancy* after another, and one platform after another, in an attempt to fix problems which never go away.

Every distinct dimension that needs to be considered in classification and decision making is a distinct dimension that needs to be taken account in any methodology or “map” presented to you (and multiplies the number of “buckets” you need for classification). So if you have three dimensions, you need at least 2 * 2 * 2 = 8 buckets in your classification scheme (as you will have at least 2 values per dimension you differentiate on, and that’s assuming each dimension you are differentiating on is a binary decision — if it were ternary, e.g you were classifying each dimension on high, medium, low or red, yellow, green, then you would have 3 * 3 * 3 = 27 buckets).

That’s why every single analyst quadrant map that attempts to assess a vendor, product, or service on more than 2 dimensions is an ultimate failure. (That’s why SolutionMap works — it’s just tech vs customer sentiment, not innovation, service, tech, market fit, market strategy, product strategy, industry strategy, geographic strategy, product viability, pricing, track record, execution, operations, and customer experience randomly squished into two meaningless composite values using absurd average weightings that are equivalent to taking the average weight of an apple, BMX bike, and a cruise ship.)

Mathematically, this would require a 14-D hypercube with 16,384 sub-cubes. And that’s why you don’t measure everything, only what counts! But try as you might, you usually going to end up with at least 3 independent dimensions that are critical to any problem you work on. But that’s not a bad thing! [Remember, the 3-sided triangle is the most stable shape with area in flatland (where analysts and consultants still love to live in to this day), and the 4-sided tetrahedron (pyramid) you can make from 4 triangles in 3-D is one of the most fundamentally stable shapes there is (and atomic bonding proves this).]

Since, when it comes to Procurement, the 3 most critical dimensions are complexity, risk, and organizational impact of what you’re buying, proper Procurement is dictated by a pocket cube. The Busch-Lamoureux Exact Purchasing pocket cube to be precise.

So if anyone else claims their updated Kraljic matrix will work for you, just shut the door. Don’t bother arguing. If they won’t accept real-world reality, you won’t get a real-world solution. Find someone who understands the complexity and can build you a platform to address it, with as much automation as can be brought to bare. (And quite a bit can be brought to bear, as per our series on operationalizing the pocket cube.) That’s how you will succeed. The old fashioned way — define the problem, use Human Intelligence (HI) to address the problem, and design processes and systems to execute the solution as efficiently as possible. The fundamentals don’t change, and anyone who says otherwise is a scam artist trying to sell you (silicon) snake oil. Don’t buy it.

* Now big consultancies won’t tell you this because if you get it right the first time, they can’t continue to sell you consulting hours, which is their ultimate goal.

IDC Misses the Main Point Completely. Outcomes is a Dirty Word!

Sorry, Paul, but when you say MNR is directionally right here, but I think the market still understates how hard “outcomes” actually are, and reference an IDC article, you’re off. The only part that’s right is that AI price wars miss the point (that you probably shouldn’t be using [Gen-]AI to begin with).

Outcomes only matter more … to the vendors. Because the meaning of outcomes in the vendor vernacular has NOTHING to do with results, but how they can spin their story to grift you as much as possible. As I clearly explained in my series on how Outcomes is a Dirty Word, which I now have to revisit, “outcomes” is always a way to charge you more for less (and sometimes next to nothing).

And it all has to do with (Gen)-AI costing way more than what the vendors want you to believe.

As per my initial post, while once exclusively the verbiage of GPOs, who wanted you to turn over a significant share of your procurement to them (to the point you’d be dependent on them and their ever-increasing cost of service for the entire existence of your business), or recovery audit firms, who wanted you to believe their services were the only way to recover your overspend, it’s now on the tip of every snake-slit tongue of every vendor rep.

While the vendor reps want you to believe that the reason you pay for “outcomes” instead of traditional SaaS pricing is that their AI will deliver immediate, measurable, results (instead of just transaction cost reductions where it will take at least a year to measure savings), and therefore you should pay (dearly) for those outcomes up front (because a success today is a CEO pat on the head today), that’s not the real reason. (Especially when those projected savings from the auto-sourcing and procurement events will never materialize.)

The real reason they are pushing for outcome-based pricing is that (Gen)-AI compute costs are now so high (and won’t compress as the energy and cooling costs keep rising as the majority of existing data centers are on already overstrained grids) that they can’t afford to sell the solution using a traditional SaaS based pricing model — they wouldn’t even cover their compute costs! (Most of which is wasted since most of what is being “automated” by these solutions can be automated by traditional A-RPA SaaS solutions for a fraction of the cost, as long as you don’t need a natural language interface or slick UX — and you don’t!)

The reality is that the software (assisted) solution from any vendor selling on an “outcome” model isn’t worth it, and (Gen-)AI forgets what software is supposed to be about — enabling efficiency so Human Intelligence (HI!) can achieve outcomes using low-cost Augmented Intelligence solutions.

And until a new generation of AI emerges where hallucinations aren’t a core function, measurability and confidence are restored, and compute costs are inline with classic AI tech, AI models won’t become utilities. We are years away from a systems problem!

The only way to get value is, as Paul pointed out, to redesign workflows, align incentives, clean up constraints, and embed decision logic into execution and find fairly priced modern tech with orchestration and “real” AI (in the form of Augmented Intelligence built on best-of-breed analytics, optimization, and machine learning) that will allow you to make decisions 10 times faster AND 10 times better.

The vendors who ultimately win when the AI crash hits will be those that built real tech on tried-and-true analytical, optimization, and machine learning models that will, as Paul states:

  • drastically reduce cycle times,
  • minimize manual intervention (via A-RPA where the response to every exception remembered, encoded, and applied to all future instances),
  • improve overall compliance,
  • increase throughput, and, ultimately
  • allow for better decisions.

And, as Paul points out, that’s not building yet another chatbot. That’s building real systems that work!

And, FYI, Gen-AI is not feature theatre. It’s puppet theatre! And while puppet theatre may provide entertainment, it’s not a viable business model!

Ignorance and Apathy were never the problem. Asininity and Exuberance were!

When those of us from the smartest generation were growing up, we were told that we shouldn’t be ignorant or apathetic, because “I don’t know” and “I don’t care” are not good answers. With hindsight, while ignorance and apathy aren’t great qualities, it turns out that asininity and exuberance, especially when mixed, have proven to be far worse.

After all, generally what happened if you were ignorant and apathetic was that you ended up in a remedial program, got your high school diploma, quit your job at the White Castle, and joined the trades. Spent your evenings at the local dive bar with your buddies and the weekends on the couch. (Unless, of course, you liked Mary Jane a little too much, then you kept your job at the White Castle and spent every evening on the couch watching Beavis and Butt-head, because you were convinced they were your alter egos.) You didn’t make your mark on society, but you didn’t ruin it either.

Hindsight is 20/20 and I don’t think that, when we were growing up, our educators could ever have predicted how powerful private equity and venture capital would become, how it would be dominated by the asinine and exuberant, and how much damage they’d collectively do not just to public markets but global economies.

All of the market crisis of the past 40 years have been caused by asinine and exuberant financiers, primarily in the private markets, which includes the loosely regulated investment arms of major banks and financial institutions where they are allowed to take “measured” risks.

I mean 40 years! Black Monday (on October 19, 1987), which was the largely unexpected stock market crash that wiped out 1.7 Trillion worldwide, or about 10% of Global GDP at the time, might have started as a result of actions of the US House Committee on Ways and Means with the introduction of a bill to reduce the tax benefits from financing mergers and leveraged buyouts, and been exacerbated by the the high trade deficit figures which both announced on the prior Wednesday, but the major losses stemmed from automated computer trading adopted by the portfolio insurers and mutual funds (to reduce their trading costs and quickly capitalize on market changes) that dictated very large sales (in response to significant selling pressures, which partly arose from their customers having the right to redeem their shares at will, and do so at the price of the last market close). With a glut of sell orders hitting the market as soon as it opened, and nowhere near enough buy orders, this resulted first in intense downward price pressure and then huge losses as the automated trading models automatically reduced prices and accepted lower buy orders. Had the market not been overvalued, had funds been properly managed (by investors not overly exuberant about the markets), and had trades still been manual, losses would not have been as severe — but the pursuit of quick gains built up a market that could come down just as fast.

Then we had the dot-com bubble, created by the first wave of exuberant and asinine VCs that overvalued any business with an online business model (even if never truly implemented, like Boo.com that blew through £125 million in just 6 months (and fire-sold for less than $2 Million), and was labeled by CNET as the 6th greatest dot-com flop. The bursting of the bubble wiped out over 5 Trillion, or about 15% of Global GDP! (The biggest dot-com flop, according to CNET, was Webvan, the original online grocer. It raised $375M in an IPO in Novemver 15, 1999 to build a gigantic infrastructure from the ground up, including a 1 Billion order for high-tech warehouses, and closed in July of 2001.) Hold onto this.

Next up, the 2008 Financial Crisis (that caused the Great Recession) as a result of the collapse of the U.S. subprime mortgage market from risky lending practices, complex mortgage-backed security, and mortgage trading that should never have been allowed. This cut the DOW in half in less than a year. Total losses were generally estimated to be between 19 Trillion and 22 Trillion, or about 32% of Global GDP! (With some more extreme estimates placing value losses at almost 50 Trillion, or almost 80% of GDP, including the estimate of the Asia Development Bank.)

Finally, the 202X AI Crash. It’s coming. And it’s going to be big!

20X valuations in any company that can claim “AI”, whether or not it’s actually AI and whether or not it actually works, have become all too common. Every month, a new 100 Million+ investment in yet another company valued at over 1 Billion dollars despite having sales of less than 50 Million. (And VCs valuing companies with 2 Million in sales at 40 Million dollars.) It’s insane. The asininity and exuberance are ridiculous. For every company to make those numbers in 5 years, which is the time-frame in which most Venture Capitalists (VCs) and Private Equiteers (PEs) [not to be confused with Privatus Equiterres, although that’s likely what they’re doing, facing backwards of course] expect a return. This means that, for those numbers to be hit, worldwide IT spend would have to quintuple, from about 6 Trillion today to 30 Trillion next year, or 25% of Global GDP would have to be dedicated to IT. That’s not going to happen. To put that number in perspective, that’s the ENTIRE US economy … the richest economy in the world that can’t afford to pay for universal education, basic health care, veteran benefits, and/or social security. So how would it ever pay for all that IT? But still, AI investment last year alone was about 600 Billion, or 1/10th of global IT spend. For a technology where the backlash is beginning since the compute costs are spiraling out of control (with companies having to significantly scale back, or even halt, their AI budgets as a result of skyrocketing costs — with one company burning through 500 Million in one month alone [Source: Yahoo! Finance]). (And the total investment in AI infrastucture and software spend since 2000 exceeds 2 Trillion, with some estimates going as high as 3 Trillion.) Open AI and Anthropic alone have raised over 310 Billion with a current combined run-rate of about 70 Billion. Investments are insane, budgets are being tightened, and with McKinsey and MIT reporting 94%+ failure rates on pilots, the backlash is coming.

The only question is, how bad is this crash going to be. If we look at the trend line, 10% of Global GDP for Black Monday, 15% for the dot-com bust, and 30% for the sub-prime mortgage crisis, this could be catastrophic and make the Great Depression look like the Little Dipper. With most IT assets overvalued by a multiple of at least 5, simple math says that 80% of total IT stock value (and the NASDAQ) could be wiped out overnight! (And while it’s not likely to be that bad, anyone with a bit of logic and math skills can see it’s going to be bad, even in a best case scenario.) And it’s all because of widespread asinine exuberance in the private finance industry!

So never complain about ignorance and apathy again. Those with it may never have amounted to anything, but they never caused any major problems either!

There’s NO Faster Path to a Markdown than “Growth At All Costs”!

THE PROPHET is bemoaning the start of markdowns in private equity when he should be happy (as a former investor) they took this long to happen, especially when the reality is that these markdowns are going to start coming fast and furious in any firm that wants to still be around by the end of the decade.

This is because most of their portfolios in Software, and FinTech/ProcureTech software in particular, have been pursuing growth at all costs as a result of:

  • the insane valuations during COVID for FinTech/ProcureTech that helped companies buy and pay online
  • the insane valuations during the current AI-HYPE for any company that could convince the investors they had a unique AI capability (even if it was just a clod or chat, j’ai pété wrapper)

… which has resulted in unreasonable, and practically unachievable, sales and growth targets being placed on them which they will not reach, especially in a flat, or down, market for software purchases as a result of the AI price squeeze (since “AI” offerings are currently cheap with the big firms underpricing compute costs to try and hook clients, even though it’s costing those firms Billions).

But as Garry Mansell, one of the Godfathers of Modern Procurement, has so eloquently explained in his can of worms post, growth at all costs is equivalent to self-sabotage. That’s because it comes laden with fallacies, traps, and brand value destruction!

Garry points out the three biggest harms we see every single time.

  1. Quarterly Earnings Trap: with the constant pressure to reach unreasonable, if not unobtainable, sales targets, it becomes all about delivering good news on the quarterly earnings call (whether to the public or the PE firm); it all boils down to revenue and cash in the bank, and sales teams are told to hit targets by any means necessary, including, but not limited to, deal-making, over-promising, and grand assurances the solution will solve that problem without any plan to ensure it will do just that once the deal is signed; this leads to unhappy customers when the implementation will take a year (vs. the three months they expected), the expected enhancement needed to solve that problem is pushed two years down the roadmap, and the customer support is non-existent (because all the support reps were fired to fund increases in the S&M budget to try and hit the insane targets)
  2. Heavy Discounting Fallacy: because it will get “not ready” or “likely to go with a competitor” customers over the line and get the deal in the door; first of all, it doesn’t always happen (as some customers see through it and then spot the “we have the right to reprice on a quarterly basis if your user base goes up, and we get to use LinkedIn growth metrics to do so” clause where, even if you hired a dozen janitors for your new office building or 50 fleet drivers for your new private fleet who never use the system, you will be charged for them anyway); secondly, even if it does, given that the smart ones know the old adage “you get what you pay for” is true, if they didn’t pay much, they will believe it’s not worth much and not put in the hard work that’s required on their end for a successful implementation (especially since they also know you can’t afford to, and thus won’t, support them at that price); third, voices carry, word gets out you’re cutting quotes 80% to 90%, and suddenly everyone knows (or at least assumes) you’re doing massive mark-ups with the sole intent of getting whatever you can (and not what the tech, and the IP contained within, is really worth — as you’ve just devalued the IP to the floor)
  3. Shelfware is the Reputation Killer that Keeps On Killing: Good software that generates value for a valued client that uses it daily is the gift that keeps on giving because a happy client, as long as you keep your prices fair, never goes away; but shelfware is the villain that keeps on striking at your darkest hour as that unhappy client will never tire telling people how you are robbing them blind in a contract they can’t get out of for software they aren’t using …

As Garry has said repeatedly, which SI has echoed repeatedly (while giving you a simple relative corporate debt equation to help you calculate how likely that vendor is pursuing growth at all costs, and, thus, likely to screw you [whether they intend to or not]), the only true growth is controlled growth with ready-clients at a sustainable year-over-year rate that allows all customers to be served to expected levels of service, all new employees to be adequately trained before being thrust into critical customer-facing roles, and all current employees to get the regular time off they need to prevent burn-out.

And, as Garry has also pointed out, where the model incentivizes utilization and renewal over implementation and sale, where every member of the organization is incentivized on those metrics, where the sales person doesn’t get a dime of commission until go-live and where the full commission depends on adoption and renewal, that’s where you will see success. (In other words, the sales person should NOT be happy if the client isn’t. That’s one of the best ways to de-incentivize bad deals — what salesperson is going to bend over backwards and/or pull every dirty trick in the book to get a deal he’ll never see a dime of commission on?)