The most natural wellbeing and performance booster – nature itself. Global supply chains being re-shuffled for resilience. Why Russia’s war in Ukraine risks being a long one. China’s new social credit law explained. 52 things Tom Whittel learned in 2022.
QUOTE OF THE WEEK
ARTICLE OF THE WEEK
Fiona Campbell, (Extremely) out of office: Let nature boost your team’s creativity and performance
(McKinsey, 18 November 2022)
A bit longish and of course self-serving, but when McKinsey embraces a fundamental component of our business model, we must rejoice! Multiple scientific studies prove that time spent in nature has a positive effect on attention span, cognition, creativity, physical and mental wellbeing. This is exactly why we do it at the Monthly Barometer and Summit of Minds! As McKinsey observes: “companies that harness its power can create a resilient and productive workforce for the long term.” Having just returned from our Families Summit of Minds in Banff, where we had walkshops and nightcaps in the magnificent Canadian Rockies in temperatures as low as -20C, we can confirm this is most definitely true (free access – reads in 10 min).
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Lucas Kitzmüller, Helena Schweiger and Beata Javorcik, The reshuffling of global supply chains is already happening
(CEPR, 24 November 2022)
A timely article to understand what’s going on with supply chains and the implications for businesses and investors. Contrary to the disruptions of early 2020 when most firms failed to take steps to improve the resilience of their supply chains, they are now starting to do so in response to Russia’s war in Ukraine. Rather than sourcing more components domestically (re-shoring) or from friendly countries (friend-shoring), firms have begun to source more inputs from suppliers in different countries, as well as stockpiling inputs (free access – reads in 6-8 min).
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Christopher Blattman, The Hard Truth About Long Wars
(Foreign Affairs, 29 November 2022)
A scholarly argument for explaining why the conflict in Ukraine won’t end anytime soon. The author of “Why We Fight: The Roots of War and the Paths to Peace” observes that most conflicts are brief, but that Russia’s fighting in Ukraine could carry on for months, if not years. Why? (1) This war is rooted in ideology – each side rejects realpolitik and fights on principle; (2) Wars persist in conditions of uncertainties, which abound in the case of this war); (3) Every long war has at its heart a “commitment problem” – the inability on the part of one side or both to credibly commit to a peace deal because of anticipated shifts in the balance of power (again: something apparent in the current conflict) (metered paywall that may require prior registration – reads in 7-9 min).
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Zeyi Yang, China just announced a new social credit law. Here’s what it means
(MIT Technology Review, 22 November 2022)
A detailed account of China’s social credit system, which the West, says the author, with its image of AI-powered social control, has misunderstood. The draft legislation just introduced in November offers a more accurate picture of the reality. It shows that the central government has been slowly working on a mix of attempts to regulate the financial credit industry, enable government agencies to share data with each other, and promote state-sanctioned moral values—however vague that last goal in particular sounds. There’s no evidence yet that this system has been abused for widespread social control (though it remains possible) (metered paywall – reads in about 10 min).
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Tom Whitwell, 52 things I learned in 2022
(Medium, 1 December 2022)
A yearly ritual – always fun and with plenty of surprising insights, with the appropriate link and reference. Some examples: 37 per cent of the world’s population (2.9 billion people) have never used the Internet; Data centres will consume 29% of Ireland’s electricity by 2028; Teenage smoking seems to be a solved problem; 40% of global shipping involves moving fossil and other fuels (oil, gas, wood pellets) around. Therefore, more renewables (solar, wind, nuclear, geo), means fewer ships. A deep learning model trained on 85,000 eyes can tell male from female eyeballs with 87% accuracy, but no one knows why. And so on (free access – reads in 6-8 min).
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