Author Archives: thedoctor

The Squirrels Have Us Right Where They Want Us!

Over the last couple of years we’ve chronicled multiple instances of squirrel sabotage and how squirrel sabotage is spreading north, the rise of the terror squirrels that have organized their own rigorous training camps, and how they are targeting us when we are at our weakest.

We’ve done this while all the major news sources have not only stayed quiet, but published articles about how cutesy the squirrels are and how a significant number of Americans are now maintaining their sanity by watching squirrel videos.

And, even worse, there is a growing number of Instagram and Tik Tok Influencers who are feeding, befriending, and even housing their own packs! This is EXACTLY where the squirrels want us! That way, when they’re ready to take back the continent, we won’t suspect a thing.

They know their time is close. A few well placed copies of Mein Kampf. Some well timed sabotage during protests and law enforcement operations. Increased stress and angst through well timed power outages. Once a revolution starts, and everyone needs to be armed, their time will be close. Then they just have to wait for mini single shot firearms to start being mass produced (as every lady will want to conceal one or two on her person, just in case), at which point, once there are millions to be stolen, they’ll organize their operation to clean out entire warehouses overnight (since they are small enough to get in and out without anyone knowing).

And we won’t suspect a thing because they’ve been the critters helping to keep us sane with their cutesy acts and subliminal messaging. (The whole point of Squirrel with a Gun was to show us how insane the idea of a squirrel with a full size gun was and ensure we never suspected them of being capable of mass violence. However, tiny derringers come in around 4″ in length and 4″ in height, with the tiniest being about 3.7″ and 2.4″ (like the NAA-22S). Small enough for a squirrel, big enough to take out even the most hardened human (when they sneak up and fire a shot at our temples in close range). And since there are at least as many squirrels as there are of us …

There is NO Infinite Compression – The Latest DeepSeek Paper is BullCr@p!

Every decade or so, some idiots who never studied Huffman coding or Information Theory believe they have cracked the problem of infinite compression, and this linked paper is just the latest example of this lunacy. I really hope this was a joke paper authored by AI because it’s all bullcr@p!

On average, a text token in a LLM should require 20 bits or less (as 17 bits support a 129,000 word vocabulary) while a vision token can be 16,384 bits (based on 1024 dimensional continuous vectors) — because it takes a lot of bits to represent pixelation of a square in a 2-D image! This says you can store about 820 text tokens in the same space it takes to store one vision token. Or, you can store the entire text (lossless) in 48K, versus the 4M it would take to store the 250 vision tokens (using very lossy compression) that are required in the paper. Looks like a LOT of people can’t do basic math if this is being praised as revolutionary!

Moreover, the raw text, which maintains the full context if the tokens are kept in order, is not only fully lossless, but can be compressed using a modified Lempel-Ziv algorithm to take up an average of less than 2 bits per character (and achieve up to an 80% compression rate). Given that the average length of a word in average text is 5 characters, and a space is one character, 2500 words would be 15,000 characters, storable in 30,000 bits or a mere 4K! In other words, this paper is trying to pass off a ONE THOUSAND FOLD increase in space requirements as space saving! Pure lunacy!

In other words, if someone is claiming something too good to be true, it is! Don’t fall for it or the sure to follow claims that DeepSeek OCR is revolutionary because of this. (Since every document is different, you can’t imagine the true loss with a 90% vision token reduction!)

Dangerous Procurement Predictions Part II

As per our first post, if you read my predictions post, you know SI hates predictions posts. It fully despises them because the vast majority of these posts are pure optimistic fantasy and help no one. Why are the posts like this? Because no one wants to hear the sobering reality off of the bat in the new year and the influencers care more about clicks than actually helping you.

But the predictions are not only bad, they’re dangerous. And to make sure you don’t fall for them and make bad decision based on them, we’re going to tackle some of the most dangerous predictions, which include predictions that look innocuous at first glance (like the last prediction on how a big legacy suite will go out of business) but hide the dangerous consequences of what will actually happen if a big suite finds itself in big trouble. Today we tackle the next four, and you can be sure this won’t be the last post in our series. Feeds are still being flooded with prediction posts, and I’m done ignoring the insanity.

4. The jobs market will be tough for the first half of the year, but will start to pick up in Q3 and Q4.

The job market is tied to the economy, and everyone predicts the job market will rebound when the economy picks up. But here’s the thing. Even when the economy picks back up, the job market never does quite as well as the last time. And the economy isn’t going to magically improve half-way through the year. This is the exact same thing we’ve been told the last two years, and it hasn’t happened.

First off, most of the first world economies around the world are flat, borderline recession, or in recession. Secondly, the only thing propping the US economy up right now is AI, and the money circles keeping it afloat as all the AI, Hardware, and Software companies keep moving the same money around investing in each other to keep each other afloat. If the bubble bursts, the US is in trouble, and the economy will quickly flush itself down the toilet. And the job market will go with it.

Considering only the big tech giants who have been hoarding cash for the last few years are in good shape, and everyone else is trying to conserve cash to survive not only the current market but a potential recession, the last thing they are going to do is hire unless absolutely necessary to fill a critical role as a result of a departure. Remember, they’ve spent the last two years using AI as an excuse to lay people off and are always looking for the next excuse to lay people off, not hire them!

Jobs will continue to be super scarce, and only the best will have a chance to land one.

5. We’re in the early stages of a broader pushback (against unnecessary upgrades or technology investments).

A few companies smartening up and saying no to forced big provider upgrades, eight (8) figure consultancy projects, and big Gen-AI investments is not pushback. There have always been a few leaders who have broken away from the pack, did the math, and made the right decisions, but the pack is still charging ahead on Gen-AI. Every big software shop except IBM (who hired a CEO who can actually do math) has invested heavily in Gen-AI, which still loses four dollars for every dollar of revenue, despite any hopes of a real return in the near future and a 94% failure rate.

Let’s face reality. I warned this space about The Vendor In Black nineteen years ago and how he always Comes Back sixteen years ago, no one took heed then, and no one is taking heed now. The business model of the enterprise software space, which has not changed for the two decades I’ve been covering it, is to solve the problem created by the old sh!t by selling the customers the new sh!t that comes with new problems so they can sell even newer sh!t in three years to fix those (and so on). Same old story. Only the vendor names change.

6. We Won’t Buy Things; We’ll Orchestrate Ecosystems.

This prediction likely came straight from the A.S.S.H.O.L.E. and anyone who repeats it should be ashamed of themselves. There are no AI Employees. Claims to the contrary are false and anyone making those demeaning and degrading claims is simply dehumanizing you. And, as we have clearly explained, you definitely don’t want agentic buying because it will happily spend your money not only on stuff you don’t need but stuff that doesn’t exist and, if you’re super unlikely, stuff that is highly illegal. You need wood, it will buy up all the Minecraft wood because it’s cheap and call your problem solved. And that’s if you’re lucky. If you’re not, it will fulfill your resin need with an illegal purchase of hash (the drug) on the dark web (which is labelled resin so the poster can claim they never advertised an illegal drug). And so on.

Plus, as we have already noted, most of today’s “orchestration” platforms in Source-to-Pay are really ORCestration platforms and can barely connect a handful of major Source-to-Pay offerings. They’re nothing close to what is needed to orchestrate ecosystems.

7. Boards will Zero in on Supply Chain Security and Supplier Risk shifts from quarterly PowerPoints to continuous “signalops”.

Just like they won’t invest more in cybersecurity, they won’t invest more in supply chain security until they lose a shipment in the tens of millions. After all, they’ve got supply chain insurance, why should they care? Especially since their current security measures have been sufficient up until now.

But here’s the thing. When the economy goes down, jobs go down. And then two things happen. People get desperate and turn to crime. And criminals, when their investments in drugs, alcohol, gambling, prostitution, and other quasi-legal through illegal activities start losing money because unemployed people run out of money to spend on their vices, these criminals get desperate too — and high value theft becomes more attractive. A temporarily unguarded truck here. A container there. An entire warehouse. And so on.

If it’s critical raw materials they can move (like rare earths), in-demand finished electronics they can sell (like iPhones, where a single container will contain at least 20M worth), military equipment or weapon (component)s that are now in demand globally, they’ll take bigger and bigger chances, especially if there are weaknesses in security. It’s not just cyber attacks that are going to increase, it’s physical attacks, supply chains aren’t ready, and companies won’t even stop preparing them until they lose tens of millions, don’t recover it all through insurance, and risk losing their insurance entirely. No one likes the math of risk prevention because, when it works, you don’t see the return. Even though it’s so much cheaper than insurance! And that’s why, in the majority of organizations, nothing will change.

Primary ProcureTech Concern: Managing Digital Fragmentation / Digital Transformation

As per our previous concern on Technology Transformation, it’s time to be digital, but with digitization comes digital fragmentation, especially when you don’t fully understand what you’re doing.

Why?

Digital fragmentation increases the risk of IP/cyberattacks (which is one of your top risks) as each fragment presents its own unique weaknesses and opportunity for attack. Moreover, it explodes the tech execution support required and increases one of the largest barriers to organizational success.

Digital transformation is also a concern because organizations know we have reached the age of digitize or die, but the digitization project failure rate is at an all time high of 88%+ (and 95% if it’s AI-based for the sake of AI) and every digitization effort to date has just resulted in more digital fragmentation. (To the point that the average mid-size organization has over 600 SaaS subscriptions and some have over 1,000.)

Impact Potential

The impact potential depends upon the degree of fragmentation. How many software applications? How many different hosting platforms? How many data pools? The impact of data fragmentation can be low if there are a relatively small number of software applications, they are all AWS hosted, and there’s only one data warehouse/lake/lakehouse. Or it can be extremely high if there are 1,000 SaaS applications, they are hosted on half a dozen cloud stacks (AWS, Azure, Google, IBM, Oracle, and Salesforce), there’s a data warehouse/lake/lakehouse for each of the divisions, and so on.

Major Challenges/Risks

Cybersecurity
Every one of your SaaS applications provides an entry point into your organization if hacked. Every cloud provider provides multiple entry points if hacked. Your data warehouses provide a huge amount of data that can be used against you. These hack points are in addition to all of your internal servers / on-site applications, employee laptops and smart devices. An average organization these days is a cybersecurity nightmare and a hacker’s dream.

Data Integration
Chances are all of your applications have their own data models, own unique entity ids, and own standards for data access. Integrating your data across applications is a nightmare, forcing integration through data warehouses/lakes/lakehouses, which in turns creates a data replication and synching nightmare.

Data Maintenance
Not only is there the synching issue from the replication used to support data integration, but less used apps means there are less checks and updates for the critical data they are the master applications for, and data quickly becomes stale and out of date. And employees depending on that data and accessing it through the lake don’t know that, and can make bad buying and partnership decisions based on that.

Final Words

Managing digital fragmentation is not easy. In fact, it’s a nightmare because most organizations don’t have, and never had, Master Data Management (MDM) or a Master Data Governance (MDG) strategy.

Primary ProcureTech Concern: Economic Downturn & Deflation/Recession

There have been recessionary fears for the last two years. They are not going away, because most countries are teetering on the brink of a major recession if not a depression!

Why?

This is a significant concern because it contributes to the top risk of spend pressure because economic downturns always result in job loss and a drop in consumer spending as many consumers have to tighten the belt. And this, of course, contributes to the #1 joint risk of rising cost/spend pressure.

Impact Potential

The impact potential is dependent on how bad the downturn is, how long it lasts, and how global the downturn is. It can result in anything from a slight drop in sales (if you are in a mostly recession proof business and have one of the most affordable price points) to a massive drop in sales if you’re selling “luxury” goods to average consumers who, being unemployed, have to cut all luxury products from their purchasing.

Major Challenges/Risks

Prediction
When will the next downturn hit? How long will it last? How bad will it be. Right now the markets, and the US in particular, are defying all logic. Trade wars usually depress markets. Considerable over-inflation (which is the case in AI right now) typically leads to rapid depressions when the myth fails to become reality.

Detection
Detecting when it’s starting. When it’s not just a temporary blip, but when a downturn, whether a shorter one (of a few months) or a longer one (of a few years) is starting and when your organization should be adjusting its operations and strategy.

Planning
Just like you should have mitigation plans for significant risks, you should have mitigation plans for the downturn, which might involve shifting or changing product lines, pausing all expansion efforts, putting hiring on hold and planning for attrition (as people retire or contracts end), and even reducing operations with respect to production and/or support. It might also mean, for an international organization, shifting focus to different markets.

Final Words

The nature of today’s markets that allow rampant over investment without sufficient regulation ensures that recessions are inevitable. Your job is to predict them, and this is yet another reason you need a top economist.