Houston, We Have a Problem (Part 1 of 3)

Seven of the major eleven International Classification of Diseases codes tracked by the US National Center for Health Statistics exhibit stark increase trends beginning in the first week of April 2021 – featuring exceptional growth more robust than during even the Covid-19 pandemic time frame. This date of inception is no coincidence, in that it also happens to coincide with a key inflection point regarding a specific body-system intervention in most of the US population. These seven pronounced increases in mortality alarmingly persist even now.

The following work is the result of thousands of hours of dynamic data tracking and research on the part of its author. The reader should anticipate herein, a journey which will take them through the methods and metrics which serve to identify this problem, along with a deductive assessment of the candidate causal mechanisms behind it. Alternatives as to cause which include one mechanism in particular, that is embargoed from being allowed as an explanation, nor even mere mention in some forums.

At the end of this process, we will be left with one inescapable conclusion. One which threatens the very fabric and future of health policy in the US for decades to come.

Storm Warnings

On March 21st 2021, a longtime mentor, friend, and business partner of mine, an otherwise healthy 68 year old male, unexpectedly suffered an organ failure cascade which resulted in a shut-down of his pancreas, liver, kidneys, and finally heart. He had just received his second dose of the Pfizer vaccine on that Thursday prior. Carl quickly descended into a coma, and then died on March 26th.1

On May 29th 2021, a rather odd signal began to develop in my regular Covid-19 tracking models. The change which alerted me resided inside the magnitude of the ‘Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified (R00-R99)’ ICD death code group (see chart in Exhibit D and also by clicking here). About this time and as a result of this observation, I began to track R00-R99 deaths, along with eleven other ICD-10 death codes, non-natural cause deaths (suicide, overdose, assault, etc.), and finally a statistic called ‘Excess Non-Covid Natural Cause Deaths’. As the reader reviews the calculated trends featured inside each of these death categorizations, they should note that this was indeed both a prescient and sound decision.

On December 1st of 2021, attending a business meeting at client’s medical complex, passing through the facility I took notice that their large oncology department waiting room was slammed full with patients. This queue of persons awaiting their oncology appointments spilled out into the hallway and finally on into the building atrium.2 While tempted at first blush to pass this off as a result of patients and their physicians ‘catching up on deferred screenings’ and/or ‘Covid-limited office days/hours effect’, my prior observational lessons suggested that I hold-off on such a knee-jerk inference, at least until the CDC – National Center for Health Statistics data (three bullet point sources below) proved out over the coming months. This as well, proved to be a wise decision.

It is not simply the probative and reliable nature of the data one has sourced, but moreover the relative dynamic in how that data changes over a significant or critical period of time, which allows the astute investigator to draw key inference.

The reader should note that there are few fancy academic heuristic tricks employed inside the models presented in this article. Rather, I’ve elected to employ good old-fashioned persistence, curiosity, hard work, logical deduction, and an experienced nose for strategy, systems, and problem-solving. Within my models, I seek to derive this inference through comparing the dynamic (not static statistics) patterns of change across a large set of differentially-compared data points and critical interval in elapsed time, in order to drive this article’s process of deduction. This is what I do professionally inside markets and for corporations and nations after all. I identify, and develop strategy to address exceptional challenges. My motivation in writing this article however is simple. I do not seek income, subscribers, power, office, notoriety, a political victory, book sales, nor a new career. I am simply compelled to stand in the gap for those who have no voice – they who lay victim to the present political hubris and its long shadow of darkness.

That being said, let us outline briefly the data sources employed in these models. All the data used within the analyses presented within this tripartite article series are derived primarily from the following three resources and links. Herein, they are collectively referred to as the MMWR (CDC Morbidity and Mortality Weekly Report) data, because these databases are updated as a part of that CDC weekly reporting process.

  1. US Center for Disease Control and Prevention: Weekly Counts of Deaths by State and Select Causes, 2014-20193
  2. US Center for Disease Control and Prevention: Weekly Provisional Counts of Deaths by State and Select Causes, 2020-20224 (please note that the term ‘provisional’ with regard to this file only impacts the first four to six weeks of this data for the most part. The taper curve can be seen here for the August 17th 2022 drop. Don’t let anyone tell you that 2021 and 2022 data is unreliable because it is provisional – if we have an emergency we must rely upon this data)
  3. US Center for Disease Control and Prevention: Wonder: Provisional Mortality Statistics, 2018 through Last Month – Query by Constraint Engine5

As a part of the process of tracking this MMWR reporting data, by October 2020 it became clear that Excess Non-Covid Natural Cause Mortality (see Exhibit E) was slightly elevated versus its historical trend, yet still conformed to annual seasonal death arrival patterns. A November 2020 chart depicting this can be observed by clicking here. Remember this rather nominal arrival form of non-Covid natural cause deaths for later on – as it is the Holmesian ‘dog that did not bark’.

Despite the fact that many maladies are not seasonal, the reality is that humans indeed are seasonal beings. We tend to die more commonly in the (northern hemisphere) winter months of December and January of each year. Such mortality trends tend to form familiar patterns across the years. These patterns and trends are therefore useful as a comparative in spotting anomalous conditions, such as pandemics. It was reasonable to assume in October of 2020 however, that this slight elevation in non-Covid mortality was indeed an outcome of the systemic damage which the SARS-CoV-2 infection and virus spike protein can produce in the human body. An erstwhile Covid delayed death if you will.

However, by MMWR Week 3 of 2022, a disruptive-exception pattern began to manifest inside this non-Covid mortality group, one which contrasted highly with the 2020 pandemic period alone (not to mention the 2014 through 2019 timeframe), and finally one which could no longer be denied (see an example chart by clicking here). Within these early charts it became clear to me that the complexion of US mortality, the who, when, and why – had changed substantially from early 2021 to the end of 2021 and on into early 2022. In fact, an inflection-point could even be estimated, establishing when this change had occurred (April 3rd – 10th, MMWR Week 14 of 2021) – a crucial date with regard to this novel mortality arrival pattern. Yes, of course people were dying of Covid-19 and as a nation we needed to continue diligent action addressing its challenge.

Nonetheless, by the end of 2021 it had become abundantly clear that US citizens were not just dying of Covid-19 to the excess, they were also now dying of something else, and at a rate which eventually became higher than that of Covid itself.

Identifying The Problem (Methodology Employed and Results Observed)

In a past article, we outlined for the reader those characteristic elements which render a problem facing a nation or corporation, as exceptional. These are the problems I call ACAN problems, or challenges which feature characteristics of Asymmetry – Complexity – Ambiguity – Novelty. As the reader will note below, the challenge with regard to Excess Non-Covid Natural Cause Mortality bears all the requisite features of an ACAN problem. Asymmetry in terms of which cancers are suddenly rising, which age groups are dying to greater numbers, or disparities between cohort vaccination rates and observed infections. Complexity in terms of the Yule-Simpson vulnerable distribution of excess deaths into their various ICD-10 codes. Ambiguity in terms of the political motivations behind official health data tracking practices and Nelsonian gaps in information. And finally, novelty in that we are facing a challenge for which our epidemiological community did not prepare, and with which mankind has never truly grappled before.

In many ways the challenge before us now, may well be as daunting as Covid-19 and the pandemic response itself. This of course all depends upon how the trends depicted inside this article pan out. In my experience, accelerated growth never continues forever, and there are always mitigating circumstances and unintended consequences which serve to confound the future. The reader should keep this in mind as they view the charts and inferences herein. We should always hold out hope in the face of a storm. This was of course as sound of an advice at the beginning of the pandemic as it is now.

For a detailed data and derivation flow chart, outlining data source, handling, and modification, to the first derivative baseline, its smoothing, series of calculations, and how the entailed risk-points are compensated for – in other words, how the charts in this article are assembled – please click on the flow chart thumbnail icon to the right.

Regardless, data is derived from sources 1 and 2 above, and the basic formula for the derivation of Non-Covid Natural Cause Mortality is straightforward, just as it sounds.

ENCNCM = All Cause Mortality – Non Natural Cause Deaths – COVID-19 (U07.1, UCoD) – Baseline Death Reference (BOY 2014 – EOY 2019)

The Problem

Exhibit A – Ten separate ICD-10 death groupings which sum to overall Excess Non-Covid Natural Cause Deaths (top chart).

The series of charts in Exhibit A to the right constitute a set of quick charts (called ‘Variation Against Trend’ or VAT charts) I maintain in my databases, and monitor each week (along with other factors such as reporting lag, Pull Forward Effect, etc.). I began to notice a potential problem beginning to coalesce with regard to many of these depicted trend lines, in late 2021 and into early in 2022. However, before anything statistically significant could be reported, the data needed sufficient time for the tail of statistical deaths from the deadly Delta variant to clear from the weekly MMWR reporting data (the three sources listed earlier). This process was delayed as well by the CDC’s ‘system upgrade’ which began June 3rd 2022 and still has not been fully completed (see pertinent CDC announcement).

As of the publishing of this article, 9,290 death records posted in the June 2nd MMWR update showed as redacted four weeks later and still remain missing from the data. Another 13,245 deaths were re-categorized by the CDC from primarily cancer and heart death, to other codes such as Alzheimer, kidney, or respiratory deaths, as can be seen in part inside this chart. It is hard to envision a scenario explaining this 52,000-record data tampering across the most at-risk weeks (MMWR Weeks 4 through 20) of 2022, as not constituting malicious obfuscation of US citizen mortality data. As a former intelligence officer and strategist for nations facing some pretty tough corruption challenges, I am a skeptic of power, and no eager subscriber to Hanlon’s Razor.

Keep in mind that the charts in this article do not even reflect addition of the CDC-shorted death records redacted for MMWR Weeks 4 through 20 of 2022.

Despite this death record data shortfall, seven of the ICD-10 VAT charts depicted to the right (click on the image to obtain a separate tab version, and click again to magnify the image) depict trends which should instill enormous concern in the mind of any professional, in terms of US citizen mortality post MMWR Week 14 of 2021. In order to comprehend why this week is of critical importance, please click on Chart 1: Critical Inflection Date in Vaccine Doses and examine Exhibit B: Arrival Comparative Between Doses and Deaths (below) – both of which will be detail outlined in Part 2 of this article series. The alignment of critical dates inside these charts is not only pivotal in our argument, but is prohibitively compelling as well.

The charts of particular concern, I have highlighted with a yellow background and listed below. These include the charts featuring stark post MMWR Week 14 2021 rises in mortality. Specifically, they are

  • Excess non-Covid natural cause, 5+ sigma
  • Cancer and lymphomas, 5+ sigma
  • Other respiratory conditions, 2 sigma
  • Nephritis/Nephrotic syndrome, 4 sigma
  • Septicemia, 2 sigma
  • Heart diseases and ailments, 2 sigma
  • All other ICD-10 tracked natural cause deaths, 4 sigma

With regard to these select ICD-10 codes, I have endeavored to highlight only those which have exhibited a stark difference between their arrival patterns during the 2020 pandemic period, and that period after MMWR Week 14 2021. While there are indeed increases in deaths incumbent inside the other ICD-10 codes, those increases appeared to plausibly conform to their same arrival patterns for 2020 as well. In other words, they appeared to be heavily Covid-related in their dynamics, both before and after the Week 14 2021 inflection.

Of particular concern, are those deaths which relate to body-wide regulatory systems as opposed to specific organs or causes. In other words, cancer and lymphomas, heart, autonomous myocarditis/pericarditis/conductive disorders, injuries to the liver and kidneys, etc. These are not only the canaries in the coal mine in terms of pathology, but may serve to indicate as well that a pervasive systemic disruption is at play inside the average US citizen human physiology, especially over the last 71 weeks. These are the death groups which exhibit the most stark trend of increase post MMWR Week 14 2021. I sincerely wish to be wrong in this, and would be the happiest person on Earth if I found a critical flaw in the underlying data or methodology which served to refute it all. Unfortunately, after months of challenging my own work from every angle I could conceive, and patiently waiting for the CDC/NCHS to fix their MMWR reporting systems and processes, I sadly fear that I am not wrong. Hence the need for this article.

As challenging as the excess mortality and VAT charts are, before we examine three particular sets of excess mortality, let us for a moment also review the compelling rationale behind the MMWR Week 14 2021 inflection date. This date is a critical matter of concern for no small reason. Its derivation is no coincidence. The ‘Doses and Deaths Comparison Chart’, Exhibit B below, outlines why.

Exhibit B – The MMWR Week 14 2021 inflection date also happens to correspond to the fastest velocity in administered vaccine doses inside the US population. The red line is Excess Non-Covid Natural Cause Mortality, extracted from the data behind Exhibit E below.

The Inflection Risk in Three Charts

Three charts in particular compel the greatest concern in terms of their being indicative of population-wide systemic health disruption. They are Excess Malignant neoplasm and lymphoma deaths (C00-C97 – Exhibit C), Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified deaths (R00-R99 – Exhibit D), and finally yet most importantly, Excess Non-Covid Natural Cause Deaths (Exhibit E). Those three charts’ ICD-10 trends against historic baseline, are depicted below. Please note that we are evaluating the trend in the peak level of the R00-R99 data in Exhibit C, and not the fact that this ICD code acts as a disposition-depleting bucket (hence the normal stark rise in later weeks to the right hand side of the chart). I will leave these three charts here, for your examination and consideration, before venturing into Part 2 of of this article series – wherein we conjecture regarding the potential cause(s) of this undeniable problem in terms of US citizen health and mortality.

Exhibit C – Cancers and lymphomas have risen to a 5+ sigma level since MMWR Week 14 2021 (latest update for MMWR Week 43 of 2022 is shown). This condition did not exist during the 2020 Covid pandemic period. Of course we hold the lag period period in abeyance barring some exception in this ICD group’s reporting (which showed in Week 36 to indeed be the case for cancer). See PFE Footnote6

Please note that the pull forward effect (PFE) for malignant neoplasms is conservatively substantiated through a detailed analysis of all 15 cancer ICD-10 sub-sub codes maintained in Source #3 at the beginning of this article. That analysis can be seen by clicking here. An example chart, indicating an alarming cancer signal in one of the 15 ICD-10 sub-sub codes is shown as Exhibit C2 below. As one can plainly see, neither the lag calculation, nor the pull forward effect cause this alarming signal. In fact, the lag calculation actually offsets the rate of trend growth in 10 of the 15 ICD-10 sub-sub codes in the analysis (see the ‘click here‘ chart linked above in this paragraph).

Exhibit C2 – C76-C80 (Ill-defined or Secondary Site) Malignant Neoplasms Mortality indicate signals of both an increase in magnitude as well as entropy (Increase in off-season cancers, as well as a rise in less common and secondary site cancers).

Not utilizing pull forward effect inside this type of analysis is an indicator of incompetence and/or maliciousness.

To wit, an academic who conducts debunking work for the pharmaceutical industry tried to coerce me (via a series of emails) into handing over all my thousands of hours of work to him, under the threat that otherwise he would publish a hit piece on this article. An article which he had at the ready, and which indeed he released the very next day after I refused to be intimidated. He insisted that I publish a flawed version of Exhibit C according to the raw data the CDC released after the June 3rd ‘system upgrade’ regarding malignant neoplasms and lymphomas. An approach which made cancer appear as if it was abating, not rising. I refused to do that as well, incurring the ire of both him and his malicious trolls. The ridiculous chart they insisted that I publish, what I call the ‘Everything is Awesome’ graph, can be seen by clicking here. It is not that I do not possess the skill and knowledge to produce a graph like this, but rather that my ethics prevent me from performing such shoddy and disinformative work. This chart and the related malicious activity constitute what this cabal calls ‘Covid Science’. This type of human rights criminal activity exemplifies why the public is very angry right now. A lot of people died because of incompetence and information obfuscation just like this.

Next, we survey the dilation and abuse of the abnormal clinical and lab findings mortality code, which is being used as a repository to conceal cancer and sudden adult deaths. This beige curve’s increase in height indicates a problem, and as well its fatness indicates that the CDC is not assigning its records to their final disposition. Thus, cancer deaths are likely higher than even my chart shows.

Exhibit D – The temporary holding bucket for this category of hard-to-determine, abnormal clinical findings, and odd deaths exhibits a stark rise in its weekly peak (64% rise from Dec 2020 through 23 April 2022). Notice the date of commencement in this rise. It coincides with a critical start date depicted in our next article. The reader should note that 39,000 deaths in this ICD hold-code have not been allocated to their final ICD-10 disposition (the fatness of the beige curve as compared to the green index reference) – very likely resulting in depressed myocarditis, pericardits, and conductive death counts for 2022. The fattening and rounding of this curve in the latter weeks on this chart indicate that the bucket is not being curated by the CDC/NCHS as it has been in the past. This constitutes obfuscation of critical data during a period of extreme risk, a period which demands clear health and mortality intelligence.

The average age of these deaths? 49 years old for 2022, as opposed to the historical average of 82 for both Covid-19 and R00-R99 deaths, for 2019 and earlier. This clump of younger person deaths concealed by the CDC can be seen by clicking this 2022 to 2019 comparative chart.

This defacto concealment of 39,000 death records (inside the R00-R99 code group), is independent of the 22,535 records which were removed from the June 2nd 2022 death data and have either yet to be placed back into the database or were reassigned to non-threatening ICD codes.

That makes for a total of 61,500 potential myocarditis, cancer, pericarditis, conductive, nephrosis, liver, and/or lymphoma deaths which still have not even yet posted into the data over which this article is sounding the alarm.

That is 8.2% of the total deaths for the period in question, and possibly 15 to 25% of these highly concerning death ICD-10 groups’ trend data – missing. Even absent this data however, the entailed trends are alarming.

Finally, we end with the most important chart of all – the chart which indicates deaths which are not from accidents, suicide, addiction, assault, abuse, despair, disruption, nor Covid-19. The Excess Non-Covid Natural Cause Mortality chart which we began monitoring on May 29th 2021. What I called then, the ‘What the hell is this?’ chart. As one can see, we have lost 372,000 younger Americans to something besides Covid and non-natural death, during the period from 3 April 2021 to 10 September 2022. The current rate of mortality in this ICD categorization, is around 5,000 – 6,700 per week (the database shows a most recent five-week, weekly average of 6,700 deaths – subject to lag of course) – which exceeds most weeks of the Covid pandemic itself (save for the absolute peak periods).

By now, if all these mortality excesses were indeed a holdover from Covid-19 itself, they should have already begun to tail off. Unfortunately they are not only not tailing off, in many cases they are still increasing.

Exhibit E – Excess Non-Covid Natural Cause Deaths are at an all time high as of MMWR Week 43 of 2022. 396,000 US citizens have died of some additional factor since MMWR Week 14 of 2021. The current rate of excess mortality represents a five week average of 5+ sigma in excess (hedging conservatively for lag). The faded green curve is the rate of full vaccination percentage by week, historically in the United States. See PFE Footnote7

Accordingly, and without a shadow of a doubt, we have established that right now there exists a problem in terms of US citizen health and mortality. One which is differentiated from Covid-19 itself, and began in earnest MMWR Week 14 of 2021. Our next task, and what will be outlaid in Parts 2 and 3 of this article series, is to employ these and other observed arrival distributions to winnow out the causal mechanism(s) behind this concerning trend in US mortality.

Having made significant progress on the second and third article already, we very much look forward to publishing for the reader, our next article in the series, ‘Houston, The CDC Has a Problem (Part 2 of 3)‘.

The Ethical Skeptic, “Houston, We Have a Problem (Part 1 of 3)”; The Ethical Skeptic, WordPress, 20 Aug 2022; Web, https://theethicalskeptic.com/?p=67865

The ACAN Problem – When the Shit Hits the Fan

How do we approach a problem which is inelastic to experts and siloed expertise? The problem which requires a multi-disciplinary approach in order to even identify as a problem in the first place.
Moreover, the ACAN problem demands a change in the ways in which we speak and think, what we fear, what we value, and finally the praxis of skepticism we employ.

Years ago, my team was brought in to a consumer goods company to develop its operating strategy. The challenge which lay before this number three ranked player in its business sub-vertical resided in its struggle to grow, and compete with the strong sourcing of that sub-vertical’s top operators. The top two consumer goods businesses in my client’s segment had dominated their class for two decades, through strong Walmart-styled product sourcing clout, x-factory production blocking, consolidation prowess, pervasive and exclusionary agency relationships, and a disciplined and highly efficient freight, processing, and delivery infrastructure. These players had achieved ‘best in practice’ status, and furthermore had leveraged this clout to drive lowest first cost and industry dominance by means of exclusivity with their oveseas suppliers. Such was a familiar business landscape, one which capitalized upon Chinese hegemony and played out inside American business at that time. A set of mistakes and bad crony judgment for which we are paying the piper even now. Most of the cronies who drove this strategy are now retired at their villas or deceased, leaving for us the task of resolving their messy legacy.

Cronies crave cash and revenue does not make right. Instead, flows of margin and value are king. This is why value chain analysis is a critical component of sound national, market, and business strategy.

On September 22, 480 BCE, a naval engagement occurred in the Saronic Gulf, called the Battle of Salamis. This event was part of a broader ongoing conflict between an alliance of Greek city-states under politician and general Themistocles and the Achaemenid Empire (Persia) under King Xerxes. In this naval battle, the Persian fleet greatly outnumbered the Greek fleet, and as well was equipped with superior ships. Their ‘best in class’ armada bore both the numerics and efficacy sufficient to dispatch a blue water ocean-going opponent in short order. What Themistocles elected to do, was decline to engage the Persians inside their arena of strength, fighting on the high seas. Instead, he boldly told Xerxes exactly where his fleet resided and invited him to come fight there.1

In order to compress this tale of antiquity into its moral; in short, Themistocles enticed overconfident Xerxes through a bit of sleight-of-hand disinformation (both, constituting ambiguity) to fight him inside a strait between the Greek mainland and the island of Salamis. The Persians were less skilled at the columnar-and-abreast tactics of naval engagement inside a strait (complexity), and moreover faced the reality that in this circumstance, because of the constrained engagement zone, only an equal number of ships could indeed be in actual combat at any given time. This meant that Xerxes could not take advantage of his greater numbers (novelty). Indeed, Themistocles had forced a matching of island warfare specialty ships and crews versus blue ocean warfare specialty ships and crews (asymmetry).

Xerxes in his overconfidence, had failed to spot the asymmetry, complexity, ambiguity, and novelty – the ACAN – of the battle which was about to ensue.

As a result, the Persian fleet lost several command vessels early in the conflict and became confused. In the disarray, they ended up having to retreat from their first sortie. However, anticipating this first retreat, Themistocles had an Aeginetan task group on standby (asymmetry, complexity, ambiguity and novelty all embodied inside one single strategic element), which subsequently ambushed Xerxes’ fleet and routed the armada during its exit from the straits.2

Much as in the way that the Biblical David, refused to fight with sword and shield against a tougher sword-and-shielded opponent in Goliath, instead exploiting his nearsightedness, overconfidence, and lack of mobility against him, the Greeks attained victory simply through the action of changing the playing field on the erstwhile ‘industry leader’.

In this same way, my client elected to change the playing field of their industry sub-vertical. Instead of going head-to-head against the top two companies inside their arena of strength, one of serving the customer as first priority, they elected instead to position their infrastructure to be able to respond more adeptly to the vendor industry. In this manner, they were able to respond to emergent vendor buys in much quicker fashion; physically taking possession of problem, distressed, and overstocked inventory and shipments within 24 hours.

I believe there is an innate wisdom as well, a potency within the simple ethic of refusing to do what everyone else is doing. If a naked emperor skulks somewhere inside the popular fray, you will be most sure to find it.

Vendors loved to avail themselves of this new capability and lowered inventories with abandon by means of this handy exit strategy opportunity. As the economy flagged during the endless George W Bush wars, and as the great preponderance of vendor inventory/production began to fall into these types of distressed dispositions, my client was able to cherry pick the best of this class of goods and obtain them at a fraction of the price the major competitors were paying – despite their volume buying leverage. Yes, it is true that American consumers are pampered by good service, but they love off-priced (not simply ‘discount’) merchandise even more. In our strategy, I called this method of market engagement a ‘source based value chain infrastructure’. Accordingly, my client rose from number three, to number one in its market segment, in part, because of this evolution.

Years later I would have clients in sales meetings cite this very business case back to me, framing for my team their desire to have their business employ its philosophy as means to becoming ‘best-in-class’. They would pedantically lecture me with my very own industry strategy, even citing the company (my client), fully unaware that my team had led the groundbreaking project. Then ironically question whether or not my team was capable of delivering strategy for such best practice. I would remain silent, smile, and nod accommodatingly.

Most strategists don’t even know what a value chain is, much less how to craft a strategy employing such principles. The only way to learn how to assemble, normalize, and make decisions from a value chain is to develop several species of them in the real world, and have surveyed their outcomes at a later date. Value chain principles can be topically addressed in a textbook, but cannot be fully instructed in an academic or pulp-mill publication context. It took me eight years to organically figure out what a value chain even was (through myriad successes and directly observing many business and market collapses/consolidations), and another ten years to explain its principles to the industry, major enterprise resource planning software developers, and the leading instructors at my alma mater. However, now you will find the phrase bandied about frequently by poseurs – often as a cudgel of intimidation. Much of skepticism and science functions in this same way. We are all humans after all, even if elite segments of professional domains fail to remember this reality.

Such elicits a key insight regarding arrogance among poseurs, and that of suit, lab-coat, and logo wearers in particular. They often imitate, but seldom innovate.

The simple reality is this, value chains are a methodology which affords the astute problem solver, the ability to see more clearly into the logical calculus of critical path, comprised inside the prosecution of what I call, the ACAN, or New World problem. And just as in the Penrose endless staircase depicted in the image at the beginning of this article, unless one introduces nodes and measures of value/risk into the decision calculus, the ACAN as well as most strategic problems, are often actually insolvent. As a result of our inability to see this, we as governing entities resort to levers of cash, revenues, derivatives, good-sounding rhetoric, and control – to our eventual demise and the suffering of those who are left out.

The ACAN Problem

The New World Problem or ACAN problem, is one which is ‘Asymmetric – Complex – Ambiguous – Novel’. These are top-shelf problems which are difficult to distinguish in the first place, much less negotiate and/or resolve. They require a different type of thinking – a mode of thought which is essential in identifying the ACAN problem. It is not simply that the ACAN problem requires a multi-disciplinary approach, and of course it does. But moreover, the ACAN problem demands that we change the ways in which we speak and think, what we fear (risk), how we measure and adjudicate value, and finally in order to break the entailed contrathetic impasse, the praxis of skepticism we employ.

Value and risk flow, just like product, cash, and margin. Always seek to become exposed to value flows and robust to flows of risk.

Your every decision and action as a business should be one which seeks to either capture value into your brand and/or displace risk to the market.

As a nation or market, never allow any entity’s margin to outrun their value nor marinate in excessive risk.

If one can systemically measure, model, and equitably leverage value and risk into a value chain – one can rule the world (but then of course that would not serve value nor risk).

The ability to distinguish which ACAN problems society faces in the first place, will be a top shelf skill in the New World. This has become most poignant in the post-Soviet/Nazi era, wherein the bad guys are not as easy to spot as they once were. Darth Vader does not exist in an embodied single person any longer. This is not your father’s bad guy. Now he comes dressed in the cloak of woke, with flowers and and army of people thinking they are doing good – all of whom have zero perception of what value and risk indeed are.

Accordingly, below (and as depicted in Exhibit 1 as well) are the features of a true ACAN problem. Specifically, an ACAN problem is one where the following supra-challenges imbue and enhance the normal challenges which we face with respect to run-of-the-mill problems, specifically in terms of a circumstance bearing the following features.


  • Might serve to conceal shortages, sabotaged efforts, or flawed or incomplete processes
  • May increase exposure risk inside Force Majeure events
  • Can serve to hide the presence and impact of groupthink or bandwagoneering
  • May serve to delude governance into perceiving a false success
  • Introduces left-hand right-hand or compartmentalization ineffectiveness
  • Allows for one critical failure to sabotage a full set of successes


  • Clouds the ability of professionals to observe measurement, precision, and tolerance abuses
  • Clouds the ability of operators to follow through, design or control process or quality
  • Clouds the perception of managers in identifying and resolving complicated-ness (more dangerous than complexity) in their processes
  • Tempts management to think in terms of single indices, linearity, normal curves, or averages
  • Enables confidence to cover for lack of capability
  • May allow politics to foster
  • Allows the incompetent to survive


  • Lack of discipline in language allows goals/processes to be ill defined, and critical actors to talk past each other
  • Ignorance of sensitivity, feedback, or whipsaw conditions renders operators vulnerable to their own processes
  • The presence of neglect or Nelsonian knowledge becomes difficult to spot and eradicate
  • May introduce right-answer wrong-timing or invalid inference problems
  • Serves to conflate inductive and deductive inference
  • May obscure ability to evaluate soundness, logical calculus, or critical path
  • Allows failures to be concealed


  • Tempts players to pretend like they know what is occurring
  • Neutralizes effectiveness of script or method educated professionals
  • Encourages reliance on buzz-phrases and apothegm
  • Serves to confuse or cause dissonance in the Peters in an organization
  • Allows an appeal to authority elite class to emerge
  • Allows a lack of success to come to be expected – or even be rewarded

Anti-fragility after all, is exhibited by the organization which can best identify, measure, and negotiate complexity, novelty, ambiguity, and asymmetry. By mapping flows of value and risk, one can more readily discern asymmetry, ambiguity, and complexity from the mundanity of mere product, margin, and information flow. One can more readily negotiate a novel circumstance, and run circles around the classic experts who inhabit the domain therein.

Notice how well amateurs and ‘conspiracy theorists’ performed on comprehension of critical issues relative to the best epidemiologists and public health officials during the Covid-19 pandemic. Covid-19 was an ACAN problem, which we as a society failed to recognize. We were erstwhile Xerxes, conflating the numbers of ships we possessed, and the cockiness of our captains, with actual competence in combat.

Develop this skill, and one will be the person to call, when the shit hits the fan.

Exhibit 1 – the essence of anti-fragility resides in a team’s ability to spot the presence of complexity, ambiguity, novelty, and asymmetry (rightmost column) – and how they serve to compound more classic organizational or process struggles (left three columns).

The solution entailed with each New World or ACAN problem of course demands creativity, persistence, and insight. There is no one formula which results in a win. But you will find, that the individual or team who can craft a keen vision of the core ACAN problem in the first place, is the only entity which stands even a remote chance of actually solving it.

Everything else is vanity.

The Ethical Skeptic, “The ACAN Problem – When the Shit Hits the Fan”; The Ethical Skeptic, WordPress, 7 Aug 2022; Web, https://theethicalskeptic.com/2022/08/07/the-acan-problem-when-the-shit-hits-the-fan/

King Solomon’s Lost Mine of Ophir

King Solomon in his wisdom, took Egypt’s legacy trading knowledge regarding Sub-Saharan Africa, passed to him through his Exodus royal ancestry, and leveraged that against the world-class military, trade, and ocean-going skills of the Phoenicians. Both nations became very wealthy as a result.
King Solomon’s Lost Mine, source of the legendary pure gold of Ophir, wore the most clever of disguises – it was hidden in plain sight all along.

At one point in my firm’s project history, I was afforded the chance to do some planning and analysis for various West African nations and several supporting corporations. The work focused on health, energy, resources, and trade – and took us to some of the most remote areas in a number of different nations in the region. During the course of this work, several clues began to arise with regard to a mystery I had once pondered and long since tabled in my mind, the location of King Solomon’s Lost Mine of Ophir.

The construct hit me one afternoon as I sat with the head of the ministry of natural resources for a specific client nation. My team had just completed days of exhaustive surveys regarding the rivers comprised by this West African nation’s primary river basin. But rather than go into the resulting hypothesis now, why don’t we take a moment to review the history behind this region, and the legend surrounding King Solomon’s exceptionally pure gold of Ophir. Most of this quasi-mythology is of course, related in the First Book of Kings in the Hebrew Bible, along with a few other works by Greek and Roman historians.1

King Solomon maintained ocean going trade ships which were accompanied by ships of Phoenician King Hiram I of Tyre. Once every three years this deployment would make its round trip, carrying back gold, silver and ivory, and apes and guinea peafowl (Hebrew: תֻּכִּיtukkiyyim or ‘took-kee’).

And this deployment of trading ships from King Hiram I, brought gold from Ophir, and brought in from Ophir a great quantity of almug trees (ebony or redwood – later described as used for making musical instruments and ornamentation) and precious stones.

~1 Kings 10/2 Chronicles 9 (complete context and in modern English)

I will make mortal man more rare than fine gold, and mankind [scarcer] than the pure gold of Ophir.

~ Isaiah 13:12

A Critical Path of Necessary Questions

Exhibit 1 – Phoenicia in the time of Hiram I and King Solomon. Notice that Phoenicia had no access to the Gulf of Aqaba, nor the port of Ezion-Geber.

As related through these passages in the Hebrew Bible, in a way, what Solomon had accomplished in exploiting the gold of Ophir, was to take Egypt’s legacy trading knowledge regarding Sub-Saharan Africa, passed to him through his Exodus royal ancestry, and leverage that with the world-class military, trade, and ocean-going skills of their brethren, the Phoenicians. Remember, both the Phoenicians and the Hebrews were fellow Arameans (Aramaic-speaking common people of Lebanon, Jordan, and Israel) – both cultures treasuring their shared heritage through modern partnerships between states and city-states.2

In addressing this mystery, seven objective and then eight follow-on subjective questions will frame the deductive critical path and concomitance around the question of the Lost Mine of Solomon. Each of those questions follows, inside two separate lists in this article. We begin with the first seven objective/differentiating questions:

  1. Who ventured originally to find the gold mine and when?
  2. How long did each round trip take?
  3. How did they travel?
  4. Who helped Solomon obtain the gold and why?
  5. How was the journey safeguarded?
  6. What came back along with the gold?
  7. What was the name ‘Ophir’, in reality?

Solly, I Think This is the Beginning of a Beautiful Friendship

The foundational trade routes (Exhibit 2 below) in the Mediterranean and beyond were developed (and settled) by the Phoenician Empire beginning in the 14th Century BCE. The Phoenicians established a chain of trading settlements throughout the Mediterranean, including colonies in Sicily, Sardinia, Malta, Cyprus, Marseilles, and North Africa. Like their own city states, these settlements were mainly self-governing.3

Exhibit 2 – The Phoenician Trading Empire (1350 to 574 BCE). Their established military might and trade routes strength resided solely in the Mediterranean Sea.
Exhibit 3 – Israel under King Solomon (970-931 BCE) At the time Israel had no port of Ezion-Geber on the Gulf of Aqaba.

King Solomon was a contemporary of King Hiram I, Phoenician King of Tyre, during the years 970–931 BCE. As we saw in the opening related passages from the First Book of Kings, the Hebrew Bible cites the unique relationship between King Solomon of the United Kingdom of Israel (Judah and Israel in Exhibit 3 to the right), and King Hiram I of Phoenicia. Phoenicia had long before the time of Solomon, established a preeminent strength in trade across the Mediterranean. Solomon would have valued collectively the Phoenician’s knowledge of seamanship, as well as their trade colonies and navy’s ability to protect a shipment of trade goods in transit.

It is doubtful that this footprint of strength extended from the Gulf of Aqaba and into the Red Sea and Indian Ocean, despite what the Hebrew Bible First Book of Kings says about the port of Ezion-Geber being the departure point for such a putative armada. As we will see later in this article, either the goods gathered, or the port of Ezion-Geber departure point, is incorrect. They cannot both be correct. Given the Mediterranean domain of strength of Hiram I and the Phoenicians, my money is on the Ezion-Geber legend artifact being an incorrect assumption on the part of non-knowledgeable scribes of history. Finally, in 2 Chronicles 2:8, it is noted that Phoenicia had an ample supply of ‘almug logs’ on its own merits over the centuries – thus this cannot have been a wood obtained from the east of Africa nor India, as the Phoenicians did not trade there with any regularity.

A key reason as to why Solomon petitioned Hiram I to join his expedition was to afford its valuable and vulnerable shipments protection by Hiram’s navy on the high seas. He did not hire the Phoenicians simply to obtain mere deck hand labor (as 1 Kings 9:27 implies).

If Solomon had been returning the cache of goods to Egypt, he would have merely used the well established overland Egyptian trading routes. However, since the caravans could not transit Egypt and the Sinai without challenge, the sea leg of the journey was critical to its success.

Such a large amount of gold and eclectic combination of goods were not obtained through a mere stop at a couple Asian or East African trading ports. Solomon did not hold the necessary deep expertise regarding India and China in order to successfully pull off this inland expedition. No, this was ancient Egyptian Pharaoh intellectual property (which had also served to make ancient Egypt rich and powerful).4 Intellectual property which had been passed to him from the time of Joseph in Egypt.

As we saw in addition, inside the First Book of Kings, each deployment of trading ships by the partner Kings was scheduled about every three years, as apparently it required a sizeable amount of that time to assemble the goods sought in the trade venture. This amount of time suggests a significant land-bridge portion of the journey, as it would not take 3 years for a simple over-the-ocean trade mission to India or even China for that matter. An overland journey being an essential component of the sourcing itself – this would require the time to layup and secure vessels at port, gather excursion resources, hire staff and guides, conduct an overland journey to gather the trade goods, and further then make both the return journey and voyage. All of this required an extensive knowledge of the journey, as well as experience in defending such a trade mission. Both the two kingdom partnership, as well as the three year turnaround, all make sense in light of such a burden.

Therefore, it seems reasonable to insist that Solomon’s sourcing partnership with Hiram, utilized both Solomon’s legacy knowledge from an Egyptian-African heritage, as well as Hiram’s trade ports and strength on the high seas. Given that it wasn’t until 500 BCE before Hanno sailed down the coast of West Africa, it is reasonable to assume such a circa 950 BCE journey happened in a Mediterranean Sea and land caravan context.5

Āfer is the Legendary ‘Ophir

It is very possible therefore, that the name ‘Ophir’, rather than meaning ‘snake’ or a son of the Biblical character Joktan,6 actually is a transliteration of the Berber word ‘āfer’ (name for a Berber citizen). Āfer (pronounced AwH-fər), further then became the Latin name for that region of the Sahara, referring to the lands south of the Mediterranean (i.e. Ancient Mauri, Numidia, Carthage, and finally Libya).7 Finally then, Āfri, in Latin referred to ‘inhabitants of Āfer’ based upon this derivation – later becoming the origin of the name of the very continent itself.

Such conjecture is merely inductive however, and must of course be tested by predictive confirmation along its per hoc aditum (line of reason). This is the task we undertake below, by means of our eight subjective/context-constraining questions:

  1. What historic major trade port was established by the Phoenicians just prior this Biblical time frame?
  2. What region bore the capability to supply such massive amounts of gold, in secret?
  3. What Kingdom/King coincidentally then grew rich with gold after King Solomon’s/Europe’s trade dominance fell?
  4. What is the single region on Earth which offers a critical nexus of supply in ebony, ivory, sufficient amounts of gold, silver, apes, guinea fowl, and gemstones?
  5. What causes gold to be purer when mined?
  6. What is the most reliable way to find a heavy and pure gold and gemstone cache?
  7. What is the most gold laden river system in the World?
  8. What is the best way to hide (or ‘lose’) a mine?

The Phoenician trading colony of Utica (see Exhibit 4 below) was reputed by ancient historians to have been established in 1101 BCE. The name Utica derives from the Phoenician term ˁAtiq, or ‘Old’ or ‘Ancient of Days’. In contrast, the name of its later successor port, Carthage, literally means ‘New Town’. Utica is considered to be the first colony to have been founded by the Phoenicians in North Africa.8 We speculate in this article that this key port, became the linchpin in King Hiram and Solomon’s joint trading ventures.

In Exhibit 4 below, one may observe the trade route juxtaposition between Utica, and the largest deposits of gold in the world (West African highlands, goldfields, and river basins). It is no coincidence that the richest person in history, in terms of total mass in gold wealth, Mansa Musa (1330 CE), lived right at the Niger River debarkation point (Timbuktu) feeding these Berber-Tuareg trading routes through the land which the Romans called Āfer.9 The vast majority of such trade routes eventually ended at Phoenician trade colony ports until such time as Carthage was conquered in the Second Punic War.10

The only region on Earth, which offers a sufficient quantity of the Hebrew Bible documented mix of goods taken back to King Solomon, is West Africa. More specifically, the Niger, Senegal, Gambia, Guinean, Sanaga, and Volta river basins.11 As one can observe in Exhibit 4 below, the gold regions of West Africa offer the wealth as well as unique combination of goods and game animals documented in the First Book of Kings.

Exhibit 4 – West Africa, accessible by over-land trade routes from the Phoenician trading colony of Utica, offers the only nexus of origin which could supply the array of specific goods ferried back to Israel by Hiram and Solomon’s fleet of ships through Phoenician supply lanes of influence.

In Exhibit 5 below, one may observe that the West African river basins in question are fed from highlands containing the richest goldfields on Earth, the Bamuk, Bure, and Akan runoffs. In this region, gold (and diamonds as well) is continually extracted from alluvial soils and eroding higher strata, and has been deposited for tens of millions of years into the critical pockets and bends of the thousands of kilometers of river bed in the region. It lays there concealed, that is until one comes along who is clever enough to exploit the circumstance.

Exhibit 5 – The Niger and West Africa River Basins hold the largest cache of gold, silver, and fine gemstones on Earth by a factor of 100 to 600 to 1 over comparable regions globally. In addition, because this gold is extracted by river erosion, the resulting gold is easily found, cleverly concealed, and of the purest quality found in nature. It is no coincidence that the richest ruler in history, in terms of total mass in gold wealth, Mansa Musa, lived right at the Niger River debarkation point (Timbuktu) feeding these Berber-Tuareg trading routes through the land which the Romans called Āfer. The vast majority of such trade routes ended at trade ports which were originally founded as Phoenician colonies.

Hidden in Plain Sight – Finding the Lost Mine of Āfer

Those miners who operate in West Africa have a saying, ‘The Devil protects his gold’. To the last person, all of them fully grasp that every ounce of gold exploited from the region comes at the cost of blood, sweat, illness, trafficking, theft, danger, oppression, and graft. As we have noted in previous articles inside The Ethical Skeptic, the person behind the mythical character called the ‘Devil’ is a master at deception – one skilled in the art of the ignoratio elenchi question, legal stipulation and binding, false dilemma, agency, orthogonal and straw man argument, and hiding his most precious assets or threatening truths in ironic and plain sight. West African gold is dealt with in no different manner.

The Argument for Rivers as Hidden ‘Mines’

As alluded to earlier in this article, a colleague on ground in a West African client nation invited our survey group to tour some of the rivers in question. We had been asked to come and assess the mineral reserves of that nation, and to develop strategies for the future of ethical exploitation partnerships with foreign entities – how the revenues for such ventures could be safely diverted to elementary schools, roads, infrastructure, healthcare, etc. We toured some 50 km of river along with the adjoining tribal lands. Tall tales were told of villager ability to simply wade through shallow tributaries and pick up gold nuggets with their toes. Local stores were paid in raw gold at times by the villagers – or so we were told. Store merchants lamented being in short supply of consumable goods for buying customers, but ironically not gold. “Get us reliable supply, this is what we need Mr. G.”, was a common plea.

Exhibit 6 – 100,000 kilometers of river basin form the West Africa exploitation footprint. This area contains over $15 trillion in recoverable gold of the finest quality (river purified).

When we got into the NI 43-101 and JORC surveys which had been conducted by professional assay teams which specialize in measuring gold content however, the contentions of the villagers did not seem so outlandish after all. The region we surveyed for economic strategy comprised a ‘mere’ 4,600 kilometers of river basin. This equated to 2 billion ounces or $2.8 trillion in recoverable gold in this small river system alone. This river basin region, not even a large one, was more than 600 times larger in terms of gold content, than the largest gold mine in the world (Nevada Gold Mines at 3.3 Moz).12 Conservatively extrapolating this metric to the entire 6 river basin region, comes to a whopping total exploitable value of $15 to 20 trillion in the purest gold – the largest repository of pure gold on Earth, by far. A cache suitable to capture the interest of a wise ancient Pharaoh, and then later, King.

Why the ‘purest gold’? one might ask. Well the principle is very straightforward in reality.

Gold that has been present in a river for a long period of time is generally purer than gold that has just recently broken off a gold-bearing vein. The reason is that the water manages to remove at least some of the reactive metals present in the gold.

~ “Gold Nugget Purity Explained” – Prospecting Planet13

Couple with this, the reality that recovering gold from an active (or even dried-up) river bed is much easier than shaft or placer mining, while of course still offering an incredible resource of purest gold. One suitable to impress the likes of King Solomon the Great. “Hiram my friend, allow me to use your trade routes, ships, and navy, and I will reveal to you, the source of my ancestral gold supply. A supplying ‘mine’ which will again hide and conceal itself should the need arise.” – Now that, is a heck of a deal! “Solomon my fellow King, I think this is the beginning of a beautiful friendship.”

As a result, gold will tend to follow its own path together with the heavier streambed materials, and also deposit at places where the lighter gravels are simply washed away by the current. Gold in rivers or creeks tends to be found in the following locations: along inside bends, behind/in front of bedrock outcroppings, behind large boulders, right after sudden widening sections, on bedrock or below false bedrock, in natural moss, below waterfalls.

~ “Where To Find Gold In Rivers & Creeks” – Prospecting Planet14

These same characteristic locations in dry old river beds will also produce millions of years of accumulated and high purity gold as well – which is relatively easy to exploit. Imagine all of this pure gold, shipping down one river, the Niger, and being warehoused for trade at one city of debarkation, Timbuktu. This supply chain constraint explains why Mansa Musa became the most wealthy person in terms of gold mass in history. Right about the time of the Middle Ages and downturn in demand for gold out of Europe and the Middle East, Mansa Musa began to amass its wealth, rather than trade it.15

So lavishly did he [Mansa Musa] hand out gold in Cairo [while on his Haj journey to Mecca] that his three-month stay caused the price of gold to plummet in the region for 10 years, wrecking the economy.

~ Naima Mohamud, BBC World News

But Mansa Musa was only the second ruler to come along bearing the wisdom of Solomon. The wisdom to keep quiet about the true nature of your ‘lost mine of Ophir’. The wisdom to know that your secret mines will be hidden in plain sight and that the Devil himself has your back. The wisdom to know how to leverage two separate sets of cultural tradition, into one inferential knowledge, and an advantage over all other nations.

The Ethical Skeptic, “King Solomon’s Lost Mine of Ophir”; The Ethical Skeptic, WordPress, 24 Jul 2022; Web, https://theethicalskeptic.com/?p=66967