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Global Advisors is a leader in defining quantified strategies, decreasing uncertainty, improving decisions and achieving measureable results.
We specialise in providing highly-analytical data-driven recommendations in the face of significant uncertainty.
We utilise advanced predictive analytics to build robust strategies and enable our clients to make calculated decisions.
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Thoughts
Global Advisors’ Thoughts: Empathy and understanding – why they are the qualities that help us achieve our own happiness and success
By Marc Wilson
Our team had just finished a book review presentation on Dale Carnegie’s “Making Friends and Influencing People”. Jane (*name changed) looked troubled: “Isn’t this stuff about manipulating people?”
Therein lies a paradox in showing empathy: without empathy for others, you face less influence, friendship, love and success. But if those are your goal rather than the sincere care for others, then your empathy is not really empathy at all.
Many people might react to empathy as “soft.” But empathy is a mark of incredible strength. It dares us to care. It requires us to put ourselves to one side. It requires us to be vulnerable – otherwise all we are doing is showing sympathy. Empathy requires self-awareness and skill.
Sympathy is easy. Sympathy does not go as far as empathy – it keeps us distant from the situation someone else is experiencing. It places us in danger of being condescending. Empathy requires us to put our self into their situation as them – not us.
Empathy gets the best out of those around us – and opens us up to be a better version of ourselves.
I find it incredibly difficult to manage a balance. A balance of being sufficiently confident and willing to share my own experience in an unbiased and helpful way – while removing enough of myself to allow someone else to find their own path and live their own experience. To be an empathetic leader, I believe I need to care about my team being at their best at work and in life.
Skills such as active listening are important to remove ourselves from the coaching we give others. But I think empathy requires us to be authentically present and involved in a way that facilitating someone else’s own solution does not.
Empathetic leadership challenges me to use my own experience and position in a way that is open to the challenges and experiences of others. And most critically demonstrates that I act out of care and acknowledgement of them.
Empathy requires that we know our self well enough that we are able to remove our projections of our own biases and feelings from the situation, appreciate the other person’s view of the world and how that impacts the situation for them.
Think about how you respond to others. How often do you respond to their experience, feelings and fears based on your own fears? Do your responses contain the word “I?” Do you fear genuinely experiencing the world as them? Do you seek to affirm your own view and experience through your response? Are you scared as being seen as similar to the other person in their own “deficiencies” and “imperfections”? How many of these imperfections are merely your own biases and fears?
Read more by clicking here: http://www.globaladvisors.biz/thoughts/20170627/empathy-and-understanding-why-they-are-the-qualities-that-help-us-achieve-our-own-happiness-and-success
Strategy Tools
Strategy Tools: Repeatable Business Models in Times of Uncertainty
By Innocent Dutiro
Innocent is an associate partner at Global Advisors and based in Johannesburg, South Africa
Research (Allen and Zook) tells us that sustained profitable growth and the methods for capturing it are much less about the choice of hot market than about the how and why of strategy and the business model translating it into action. The ongoing Coronavirus crisis is likely to put these beliefs to severe test. It is likely that the survivors and winners that emerge on the other side of the crisis will be businesses that have pursued repeatable business models.
These businesses’ approach to strategy focus less on a rigid plan to pursue growth markets and more on developing a general direction built around deep and uniquely strong capabilities that constantly learn, continuously improve, test, and adjust in manageable increments to the changing market. Repeatable business models enable organizations to distinguish between transient crises and game-changing developments while enabling them to take action that ensures their sustained prosperity. All without compromising on the beliefs that underpin the culture of the organization.
This might sound counterintuitive; how does a repeatable business model help you deal with a “black swan” event such as the COVID-19 pandemic? To answer this question, it is important to understand the three principles that underpin repeatability.
Principle 1: A strong, well-differentiated core
Differentiation drives competitive advantage and relative profitability among businesses. The basis for differentiation must deliver enhanced profitability by either delivering superior service to your core customers or offering cost economics that help you to out-invest your competitors. The unique assets, deep competencies and capabilities that make this differentiation possible and that are translated into behaviours and product features, define the “core of the core” of the business.
Principle 2: Clear non-negotiables
Non-negotiables are the company’s core values and key criteria used to make trade-offs in decision making. These improve the focus and simplicity of strategy by translating it into practical behavioural rules and prohibitions. This reduces the distance from management to the frontline (and back). Employee loyalty and commitment is driven primarily by a strong belief in the values of the management team and the organisation’s strategy. A clearly understood strategy is evidenced through:
- Widespread understanding of the strategy at all levels within the organization.
- Seeing the world the same way throughout the organization.
- A shared vocabulary and priorities.
Principle 3: Systems for closed-loop learning
Self-conscious methods to perceive and adapt to change alongside well-developed systems to learn and drive continuous improvement are hallmarks of successful repeatable business models.
A second form of closed-loop learning is more relevant to a crisis such as the coronavirus as it relates to those less frequent situations when fundamental change in the marketplace (like technology, competition, customer need and behaviour) threatens a key element of the repeatable business model itself. A company’s ability to adapt or have a sufficient sense of urgency in response to a potentially mortal threat is key to survival and continued prosperity.
The various steps that governments are taking to contain and eradicate the virus have the potential of building habits that consumers might choose to adopt on a more permanent basis even after the pandemic. These include working from home, remote meetings, reduced commuting, greater use of online services and more cashless transactions. Businesses thus need to be prepared to adjust and adapt their strategies and business models to meet the demand created by the new behaviours. Firms with a clearly defined set of non-negotiables will find it easier to mobilize their employees towards the necessary change.
While business is currently focused on taking measures to safeguard their staff, serve their customers and preserve cash to ensure liquidity during the period of low demand and/or production, attention should also be turning to steps necessary to adapt strategies to enable competitiveness in the new normal after the pandemic.
Fast Facts
Modern portfolio theory (MPT) can be applied to business portfolio decision-making
- Shareholders seek to maximise company profits while minimising risk
- However, lower risk businesses are usually accompanied with lower returns and high risk businesses with higher returns
- Comparisons between various risk and return profiles can be measured using the Sharpe ratio – return per unit of risk
- Combinations (degree of balance sheet investment) in individual portfolios could realise higher returns per unit of risk than what is achievable in an individual business unit – some combinations are not always obvious
- By exiting a higher risk-return portfolio BU J, ABC would be able to increase its return per unit of risk from 4,3 to 4,5
- It is often psychologically difficult for businesses to exit high return portfolios
- Emotional decision-making can be muted by applying the logic of modern portfolio theory in the board room
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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