ARTIFICIAL INTELLIGENCE
An AI-native strategy firmGlobal Advisors: a consulting leader in defining quantified strategy, decreasing uncertainty, improving decisions, achieving measureable results.
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Quantified Strategy
Decreased uncertainty, improved decisions
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.
We support implementation of adaptive capability and capacity.
Our latest
Thoughts
Global Advisors’ Thoughts: Getting the Balance Right
By Kate Barnes
I am a working mother, as are many of my friends and past colleagues. Naturally we often debate the challenges of getting the balance between work and family right.
Personal circumstances vary widely and have a big impact on the choices one has, but my solution has been to work on a part-time basis. I have been lucky enough to do so for the past seven years and to me it seems like an excellent compromise. Yet there are many times when it feels like balance is the last thing I am achieving – in fact, I have the distinct feeling that I am failing on every front – my kids, my husband, and my boss, colleagues or direct reports, all want more of me.
Perhaps the truth is that I want too much. I want to be stimulated, challenged and to feel like I am adding value in the work place, but I also want to see my children more than the average, full-time working mother.
Many working mothers have made decisions involving changes to their working day in order to manage the work-family balance better. Unfortunately, I have found that one of the biggest issues is that one cannot simply decide on an approach, agree it with your employer, and then settle into whatever routine that entails. You might agree an arrangement to work 5, or 6 or 7 hours a day, or 30 hours a week, or to arrive at work early and leave by 3 or 4pm. But in most jobs, you will have to consider the balance equation on a daily basis, sometimes multiple times a day. Is today the day I give more to work because there is a demanding deadline and everyone else is working late, or is it the day I give more to my child, because he is receiving an award at school or swimming in a gala?
And often the call has to be made taking into consideration not only what is happening today, but also looking at where the pendulum fell yesterday, or last week, or over the past couple of weeks.
As with any decision there are consequences, even if at first they are unforeseen. In the early stages of my career, I like many, was an idealistic youngster with dreams of holding a very senior, leadership position. I was ambitious, and some might say that I had much of what it takes to achieve my goal. Some years down the track I was being interviewed for a prospective job and the potential employer noted from my CV that the achievements in my career (or lack thereof) were not in line with my academic record, and he wondered why this was. I can’t remember what my response was, but I know I knew the answer. I even knew at exactly which point in my career the upward trajectory slowed. It was the day I was working at a large corporate, and I asked for flexitime. I negotiated that on two afternoons a week, I would be allowed to leave at 2pm and I would make up the time in the evening, after my young children were asleep.
Shortly thereafter, when a potential internal move to a new position was being discussed I was informed that I could not be considered for the role as I was “part-time”.
This was a wake-up call.
Read more at http://www.globaladvisors.biz/thoughts/20170719/getting-the-balance-right/
Strategy Tools
Strategy Tools: Growth, Profit or Returns?
By Stuart Graham and Marc Wilson
Stuart is a manager and Marc is a partner at Global Advisors.
Both are based in Johannesburg, South Africa.
Growth, profit or returns? It’s all three, however we find that the relationship between these and shareholder value creation is poorly understood – if at all.
All three measures become critical to the way forward as companies navigate the Covid-19 crisis.
After ensuring business survival, navigating through the Covid-19 crisis requires returns on invested capital AND growth to deliver shareholder returns. S&P 500 companies averaged 13% RONA and 5% revenue growth (CAGR) through the financial crisis (2008-2012) .
Monolithic survival approaches may starve compensating growth opportunities – a portfolio approach is required.
Key insights
Returns are not enough – companies must also grow to create value.
Profits and cash flows cannot increase indefinitely through cost-reduction, efficiency, business mix, etc – top-line growth is critical.
Returns must be above costs of capital to be value accretive.
S&P 500 companies averaged 13% ROIC and 5% revenue growth (CAGR) through the financial crisis (2008-2012).
Margins and revenue growth, or even profit growth in themselves don’t answer that question of whether shareholder value was created or destroyed. There are many examples of where growth and high margins actually destroy value.
Company valuations reflect an aggregate of their business portfolio – rebalancing segments based on their growth and return profiles can lift company value.
Growth requires investment – at the very least in the working capital required to support revenue growth.
Measuring RONA or ROIC and Revenue growth shows whether business activity is value accretive or destructive.
You can use the Global Advisors Market Cap (valuation) framework to map your business – and agree action to deliver improved shareholder returns.
Fast Facts
The use of full absorption or average costing in asset-intensive industries with under-utilisation can lead to self-defeating pricing strategies
The use of full absorption or average costing in asset-intensive industries with under-utilisation can lead to self-defeating pricing strategies
- The use of full absorption or average costing in a manufacturing environment with under-utilisation can lead to self-defeating pricing strategies
- The increase in price to cover costs results in volume decreases – lowering factory utilisation and increasing unit production costs. This is the start of the utilisation-pricing “death spiral”
- Costing according to factory utilisation – partial absorption costing – offers the opportunity to be more strategic about costing and utilisation
- “Unabsorbed” costs can be targeted through OEE and volume improvements. At the same time, the “disadvantage” of having a large factory is normalised and pricing can compete with more fully-utilised factories
- A recent manufacturing client saw 60% of unit costs arise from factory under-utilisation – sub-optimal OEE levels (non-conformance), low volumes and work-centre bottlenecks contributed to the utilisation gap
- These principles can apply to any asset-intensive business – for example banking
Selected News
Quote: Dr Eric Schmidt – Ex-Google CEO
“The win will be teaming between a human and their judgment and a supercomputer and what it can think.” – Dr Eric Schmidt – Former Google CEO
Dr Eric Schmidt is recognised globally as a principal architect of the modern digital era. He served as CEO of Google from 2001 to 2011, guiding its evolution from a fast-growing startup into a cornerstone of the tech industry. His leadership was instrumental in scaling Google’s infrastructure, accelerating product innovation, and instilling a model of data-driven culture that underpins contemporary algorithms and search technologies. After stepping down as CEO, Schmidt remained pivotal as Executive Chairman and later as Technical Advisor, shepherding Google’s transition to Alphabet and advocating for long-term strategic initiatives in AI and global connectivity.
Schmidt’s influence extends well beyond corporate leadership. He has played policy-shaping roles at the highest levels, including chairing the US National Security Commission on Artificial Intelligence and advising multiple governments on technology strategy. His career is marked by a commitment to both technical progress and the responsible governance of innovation, positioning him at the centre of debates on AI’s promises, perils, and the necessity of human agency in the face of accelerating machine intelligence.
Context of the Quotation: Human–AI Teaming
Schmidt’s statement emerged during high-level discussions about the trajectory of AI, particularly in the context of autonomous systems, advanced agents, and the potential arrival of superintelligent machines. Rather than portraying AI as a force destined to replace humans, Schmidt advocates a model wherein the greatest advantage arises from joint endeavour: humans bring creativity, ethical discernment, and contextual understanding, while supercomputers offer vast capacity for analysis, pattern recognition, and iterative reasoning.
This principle is visible in contemporary AI deployments. For example:
- In drug discovery, AI systems can screen millions of molecular variants in a day, but strategic insights and hypothesis generation depend on human researchers.
- In clinical decision-making, AI augments the observational scope of physicians—offering rapid, precise diagnoses—but human judgement is essential for nuanced cases and values-driven choices.
- Schmidt points to future scenarios where “AI agents” conduct scientific research, write code by natural-language command, and collaborate across domains, yet require human partnership to set objectives, interpret outcomes, and provide oversight.
- He underscores that autonomous AI agents, while powerful, must remain under human supervision, especially as they begin to develop their own procedures and potentially opaque modes of communication.
Underlying this vision is a recognition: AI is a multiplier, not a replacement, and the best outcomes will couple human judgement with machine cognition.
Relevant Leading Theorists and Critical Backstory
This philosophy of human–AI teaming aligns with and is actively debated by several leading theorists:
- Stuart Russell
Professor at UC Berkeley, Russell is renowned for his work on human-compatible AI. He contends that the long-term viability of artificial intelligence requires that systems are designed to understand and comply with human preferences and values. Russell has championed the view that human oversight and interpretability are non-negotiable as intelligence systems become more capable and autonomous. - Fei-Fei Li
Stanford Professor and co-founder of AI4ALL, Fei-Fei Li is a major advocate for “human-centred AI.” Her research highlights that AI should augment human potential, not supplant it, and she stresses the critical importance of interdisciplinary collaboration. She is a proponent of AI systems that foster creativity, support decision-making, and preserve agency and dignity. - Demis Hassabis
Founder and CEO of DeepMind, Hassabis’s group famously developed AlphaGo and AlphaFold. DeepMind’s work demonstrates the principle of human–machine teaming: AI systems solve previously intractable problems, such as protein folding, that can only be understood and validated with strong human scientific context. - Gary Marcus
A prominent AI critic and academic, Marcus warns against overestimating current AI’s capacity for judgment and abstraction. He pursues hybrid models where symbolic reasoning and statistical learning are paired with human input to overcome the limitations of “black-box” models. - Eric Schmidt’s own contributions reflect active engagement with these paradigms, from his advocacy for AI regulatory frameworks to public warnings about the risks of unsupervised AI, including “unplugging” AI systems that operate beyond human understanding or control.
Structural Forces and Implications
Schmidt’s perspective is informed by several notable trends:
- Expansion of infinite context windows: Models can now process millions of words and reason through intricate problems with humans guiding multi-step solutions, a paradigm shift for fields like climate research, pharmaceuticals, and engineering.
- Proliferation of autonomous agents: AI agents capable of learning, experimenting, and collaborating independently across complex domains are rapidly becoming central; their effectiveness maximised when humans set goals and interpret results.
- Democratisation paired with concentration of power: As AI accelerates innovation, the risk of centralised control emerges; Schmidt calls for international cooperation and proactive governance to keep objectives aligned with human interests.
- Chain-of-thought reasoning and explainability: Advanced models can simulate extended problem-solving, but meaningful solutions depend on human guidance, interpretation, and critical thinking.
Summary
Eric Schmidt’s quote sits at the intersection of optimistic technological vision and pragmatic governance. It reflects decades of strategic engagement with digital transformation, and echoes leading theorists’ consensus: the future of AI is collaborative, and its greatest promise lies in amplifying human judgment with unprecedented computational support. Realising this future will depend on clear policies, interdisciplinary partnership, and an unwavering commitment to ensuring technology remains a tool for human advancement—and not an unfettered automaton beyond our reach.
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