Delivered earlier this week during the Belt and Road Summit, Zheng Bijian’s “China’s ‘One Belt, One Road’ (OBOR) plan marks the next phase of globalization” presents OBOR as a global game changer. Indeed, this is the biggest infrastructure plan ever: 65 countries, 62% of the world population and 30% of global GDP. The total investment need is $5 trillion. China already pledged $113 billion, 9 of which in the form of aid to poor countries. More funding will come from the BRICS’s New Development Bank and the Asia Infrastructure Investment Bank. Unless you are in the Americas, chances are that what you do is somehow connected to this initiative. I guess, even if you are in the Americas, there will be externalities. Looking at power dynamics in the region, much of the talk focused on India’s lack of support. Next summit scheduled for 2019.
Danny Hernandez’ “How our company learned to do better predictions about everything” is what I shared when asked about best practices to improve organizational data literacy. Let me be clear here: I don’t know anything about best practices in that area. But I read this interesting article the day before I was asked the question. The company is Twitch, an Amazon offshoot. It invested in growing the predictive skills of every single staff member irrespective of functions and ranks. An initial phase warmed up employees by asking them to play with past company metrics, like “how much do you think our sales grew last quarter?” Once they got comfortable, they were asked to make predictions that would impact their work, like “how confident are you that you can complete this project in 3 weeks?” At first, Twitch employees were not excited: they did not believe in predictions, were afraid of making bad predictions, and thought that there was not enough evidence to make good predictions. But after the training, 96% of them said they would recommend it to a colleague. This initiative improved Twitch’s collective forecasting capacity. And it boosted efficiency as employees got better at evaluating ideas, defending funding proposals, and setting expectations. Other good ideas I heard this week: have data days in your teams or spend 10 minutes everyday on data issues. I am adding the latter to my daily routine.
CBinsights’ “From virtual nurses to drug discovery: 106 artificial intelligence startups in healthcare” maps the growing AI health market which is revolutionizing the whole industry from direct assistance to patients, to diagnosis, to drug discovery and mental health treatment.
My quote this week is from Elon Musk’s “The future we are building – and boring”: “I am not trying to be anyone’s savior. I just want to think about the future and not be sad.“