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Global Advisors’ Thoughts: Is insecurity behind that dysfunction?

Global Advisors’ Thoughts: Is insecurity behind that dysfunction?

By Marc Wilson
Marc is a partner at Global Advisors and based in Johannesburg, South Africa

Download this article at http://www.globaladvisors.biz/inc-feed/20170907/thoughts-is-insecurity-behind-that-dysfunction

We tend to characterise insecurity as what we see in overtly fragile, shy and awkward people. We think that their insecurity presents as lack of confidence. And often we associate it with under-achievement.

Sometimes we might be aware that insecurities can lie behind the -ias, -isms and the phobias. Body dysmorphia? Insecurity about attractiveness. Racism? Often the need to find security by claiming superiority, belonging to group with power, a group you understand and whose acceptance you want. Homophobia? Often insecurity about one’s own sexuality or masculinity / feminity.

So it is often counter-intuitive when we discover that often behind incredible success lies – insecurity! In fact, an article I once read described the successful elite of strategy consulting firms as typically “insecure over-achievers.”

Insecurity must be one of the most misunderstood drivers of dysfunction. Instead we see its related symptoms and react to those. “That woman is so overbearing. That guy is so aggressive! That girl is so self-absorbed. That guy is so competitive.” Even, “That guy is so arrogant.”

How is it that someone we might perceive as competitive, arrogant or overconfident might be insecure? Sometimes people overcompensate to hide a weakness or insecurity. Sometimes in an effort to avoid feeling defensive of a perceived shortcoming, they might go on the offensive – telling people they are the opposite or even faking security.

Do we even know what insecurity is? The very need to…

Read the rest of “Power, Control and Space” at http://www.globaladvisors.biz/inc-feed/20170907/thoughts-is-insecurity-behind-that-dysfunction

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Strategy Tools

Strategy tools: Effective transfer pricing

Strategy tools: Effective transfer pricing

So much has been written about transfer pricing. Yet it remains a bone of contention in almost every organisation. Transfer pricing is not merely a rational challenge – it often raises the emotions of internal service users and providers who argue regarding scope, quality, price and value.

We have found that effective transfer pricing relies on some fairly simple best practices and critical success factors.

Many organisations recover costs as a regular ‘below-the-line’ deduction from operating division income statements. In our experience, charge out is almost always preferable. This results in internal value judgements and negotiation regarding delivery happening closer to time of use.

Internal prices / cost recovery plays a crucial role within an organisation: it ‘price signals’ to the buyer and the supplier of the service. Buyers make economic use decisions and suppliers make resource and capacity decisions. This fundamental function and consequence governs the optimal implementation of internal pricing / cost recovery.

We have typically seen that the realisation that internal pricing plays this role and the consequences of poor implementation are not well understood.

Results of poor transfer pricing implementation

Sub-optimal economic use decisions

Where costs / prices are higher than they should be, buyers pass this on as an inflated cost to their customers, experience margin squeeze, or utilise less of the service than they might have.
Strategically this can lead to incorrect decisions regarding the provision of services to the market and loss of market share.
Where costs / prices are lower than they should be, this can lead to overuse of a product or service and poor cost recovery from external customers.
Strategically this can result in the over promotion and sales of products and services that are achieving lower margins than thought, or that might even be making losses.

Sub-optimal investment and resourcing decisions

Incorrect pricing can lead to over- or under-investment in capacity and product or service quality. Further, the resourcing decisions will be incorrect should the price signal to the supplier be incorrect.

Political and emotional argument

Where buyers are unable to obtain assurance that an internal price is correct, there is typically resentment regarding the cost of the internal product and service and the sheltered position employees of the internal service provider occupy – in the buyer’s eyes free from commercial pressures.
Buyers and suppliers typically also argue regarding the quality of the service or product relative to the price paid.
Suppliers may react to criticism claiming their product or service is strategic in nature and refute its availability in the external markets.

Poor product / service quality

Poor price signals will result in lack of comparable product and service quality benchmarks. This can result in ‘gold-plating’ or poor-quality product and service provision.

Read more at https://globaladvisors.biz/2021/01/06/strategy-tools-effective-transfer-pricing/

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Fast Facts

Selected News

Quote: Alex Karp – Palantir CEO

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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