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We specialise in providing highly-analytical data-driven recommendations in the face of significant uncertainty.
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Thoughts
Global Advisors’ Thoughts: Who are you and what did you do with my team member?
By Marc Wilson
(Alternative titles could be: “Who are you and what did you do with the person I hired? “Who are you and what did you do with the boss who hired me?” “Who are you and what did you do with my client?” …)
Some years ago, a friend of many friends died tragically. I had never met Joe (not his real name) but often heard of him. He was exceptionally popular and well known. In fact, he was clearly loved by a huge group of people.
What followed Joe’s death was amazing. Hundreds of people went to a Facebook page and wrote of their sadness and memories of him. Many were personal, some merely referring to chance meetings and the incredible impression he had left on them. Some were even from people who had not met him, but were moved by his impact on people they knew.
One person wrote of meeting Joe at a party and how even though this was their first and only meeting, Joe had showed so much interest in her and interacted with her like an old friend. She had felt special – and left with an impression of how special Joe was.
Another wrote of a childhood cricket experience. He had played a blinding hook shot only to be caught by Joe at square leg in the crease of an arm. Joe had laughed and apologised repeatedly for accidentally catching him out off such good shot. Joe was secure with himself and the world and didn’t seem to need praise or undue accolades.
It was incredible. This was the type of person that most of us hope to be. Super-achiever, immensely popular, loving and loved. Years later, people still go back to that page and comment.
Joe committed suicide. It did not fit with …. Read more here: https://globaladvisors.biz/thoughts/20170601/who-are-you-and-what-did-you-do-with-my-team-member
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Strategy Tools
Strategy Tools: ‘Price-Volume-Profit’ Part 1 – A strategic take on cost-volume-profit analysis
By Eric van Heeswijk and Marc Wilson
Eric is an analyst and Marc is a partner at Global Advisors. Both are based in Johannesburg, South Africa.
Almost every person who has studied financial or management accounting at school or university is probably familiar with cost-volume-profit (CVP) analysis. It should be the basis of financial planning in most companies. However, in our experience, most managers do not apply the analysis and get it wrong in its most basic form (e.g. planning for similar / increased volumes together with price increases). The outcome? At best: results that fail to meet budgets. At worst: firms trigger the “margin-price-volume death spiral”. Whether you are a production manager or a CEO, you should understand how CVP analysis applies to your firm. Your business’s survival may be at stake.
Fast Facts
White meat consumption has grown with increases in per capita income and growth of the middle class
- South Africa has experienced rapid growth of middle-to-upper-class citizens fuelled by the parallel increase in disposable income of this socio-economic group
- The GDP per capita of South Africa has grown by 54% in real terms from R45 580 in 1981 to R70 184 in 2013
- As the poor emerge from poverty and the emerging middle class consumers are able to afford more protein in their diets, chicken, being the most affordable and versatile, has emerged as the meat of choice for this burgeoning population group
- The result has been growth in white meat per capita consumption ahead of red meat coupled with added benefits of being easy to produce and with less cultural constraints than pork
- White meat consumption per capita has grown by 223% from 11,93 kg/capita in 1981 to 38,5 kg/capita in 2014
- Consumption of white meat has also been fuelled by the growth of QSRs like KFC and to an extent, people trading down for a cheaper source of protein
- Red meat, being more expensive, is growing at a slower pace
- Pork and sheep meat i.e. Lamb (the most expensive of all red meat) and mutton consumption have remained fairly flat while beef consumption has grown since 2001
Selected News
Quote: Alex Karp – Palantir CEO
“The idea that chips and ontology is what you want to short is batsh*t crazy.” – Alex Karp -Palantir CEO
Alex Karp, co-founder and CEO of Palantir Technologies, delivered the now widely-circulated statement, “The idea that chips and ontology is what you want to short is batsh*t crazy,” in response to famed investor Michael Burry’s high-profile short positions against both Palantir and Nvidia. This sharp retort came at a time when Palantir, an enterprise software and artificial intelligence (AI) powerhouse, had just reported record earnings and was under intense media scrutiny for its meteoric stock rise and valuation.
Context of the Quote
The remark was made in early November 2025 during a CNBC interview, following public disclosures that Michael Burry—of “The Big Short” fame—had taken massive short positions in Palantir and Nvidia, two companies at the heart of the AI revolution. Burry’s move, reminiscent of his contrarian bets during the 2008 financial crisis, was interpreted by the market as both a challenge to the soaring “AI trade” and a critique of the underlying economics fueling the sector’s explosive growth.
Karp’s frustration was palpable: not only was Palantir producing what he described as “anomalous” financial results—outpacing virtually all competitors in growth, cash flow, and customer retention—but it was also emerging as the backbone of data-driven operations across government and industry. For Karp, Burry’s short bet went beyond traditional market scepticism; it targeted firms, products (“chips” and “ontology”—the foundational hardware for AI and the architecture for structuring knowledge), and business models proven to be both technically indispensable and commercially robust. Karp’s rejection of the “short chips and ontology” thesis underscores his belief in the enduring centrality of the technologies underpinning the modern AI stack.
Backstory and Profile: Alex Karp
Alex Karp stands out as one of Silicon Valley’s true iconoclasts:
- Background and Education: Born in New York City in 1967, Karp holds a philosophy degree from Haverford College, a JD from Stanford, and a PhD in social theory from Goethe University Frankfurt, where he studied under and wrote about the influential philosopher Jürgen Habermas. This rare academic pedigree—blending law, philosophy, and critical theory—deeply informs both his contrarian mindset and his focus on the societal impact of technology.
- Professional Arc: Before founding Palantir in 2004 with Peter Thiel and others, Karp had forged a career in finance, running the London-based Caedmon Group. At Palantir, he crafted a unique culture and business model, combining a wellness-oriented, sometimes spiritual corporate environment with the hard-nosed delivery of mission-critical systems for Western security, defence, and industry.
- Leadership and Philosophy: Karp is known for his outspoken, unconventional leadership. Unafraid to challenge both Silicon Valley’s libertarian ethos and what he views as the groupthink of academic and financial “expert” classes, he publicly identifies as progressive—yet separates himself from establishment politics, remaining both a supporter of the US military and a critic of mainstream left and right ideologies. His style is at once brash and philosophical, combining deep skepticism of market orthodoxy with a strong belief in the capacity of technology to deliver real-world, not just notional, value.
- Palantir’s Rise: Under Karp, Palantir grew from a niche contractor to one of the world’s most important data analytics and AI companies. Palantir’s products are deeply embedded in national security, commercial analytics, and industrial operations, making the company essential infrastructure in the rapidly evolving AI economy.
Theoretical Background: ‘Chips’ and ‘Ontology’
Karp’s phrase pairs two of the foundational concepts in modern AI and data-driven enterprise:
- Chips: Here, “chips” refers specifically to advanced semiconductors (such as Nvidia’s GPUs) that provide the computational horsepower essential for training and deploying cutting-edge machine learning models. The AI revolution is inseparable from advances in chip design, leading to historic demand for high-performance hardware.
- Ontology: In computer and information science, “ontology” describes the formal structuring and categorising of knowledge—making data comprehensible, searchable, and actionable by algorithms. Robust ontologies enable organisations to unify disparate data sources, automate analytical reasoning, and achieve the “second order” efficiencies of AI at scale.
Leading theorists in the domain of ontology and AI include:
- John McCarthy: A founder of artificial intelligence, McCarthy’s foundational work on formal logic and semantics laid groundwork for modern ontological structures in AI.
- Tim Berners-Lee: Creator of the World Wide Web, Berners-Lee developed the Semantic Web, championing knowledge structuring via ontologies—enabling data to be machine-readable and all but indispensable for AI’s next leap.
- Thomas Gruber: Known for his widely cited definition of ontology in AI as “a specification of a conceptualisation,” Gruber’s research shaped the field’s approach to standardising knowledge representations for complex applications.
In the chip space, the pioneering work of:
- Jensen Huang: CEO and co-founder of Nvidia, drove the company’s transformation from graphics to AI acceleration, cementing the centrality of chips as the hardware substrate for everything from generative AI to advanced analytics.
- Gordon Moore and Robert Noyce: Their early explorations in semiconductor fabrication set the stage for the exponential hardware progress that enabled the modern AI era.
Insightful Context for the Modern Market Debate
The “chips and ontology” remark reflects a deep divide in contemporary technology investing:
- On one side, sceptics like Burry see signs of speculative excess, reminiscent of prior bubbles, and bet against companies with high valuations—even when those companies dominate core technologies fundamental to AI.
- On the other, leaders like Karp argue that while the broad “AI trade” risks pockets of overvaluation, the engine—the computational hardware (chips) and data-structuring logic (ontology)—are not just durable, but irreplaceable in the digital economy.
With Palantir and Nvidia at the centre of the current AI-driven transformation, Karp’s comment captures not just a rebuttal to market short-termism, but a broader endorsement of the foundational technologies that define the coming decade. The value of “chips and ontology” is, in Karp’s eyes, anchored not in market narrative but in empirical results and business necessity—a perspective rooted in a unique synthesis of philosophy, technology, and radical pragmatism.

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