Friday, March 20, 2020
Business Intelligence and Analytics 56
1 Is the COVID-19 Outbreak a Black Swan or the New Normal?
https://sloanreview.mit.edu/article/is-the-covid-19-outbreak-a-black-swan-or-the-new-normal/
In the time between writing this and reading it, whatever I say about COVID-19 will likely be out of date. That’s the nature of something moving at exponential speed through society. The scale of what’s happening is hard to grasp, and it’s logical to wonder whether COVID-19 is the so-called black swan that society and business have feared. The answer is, of course it is. But it also could be the kind of challenge we now will face all the time — a new normal.
2 Responding to coronavirus: Integrated nerve center
https://www.mckinsey.com/business-functions/risk/our-insights/responding-to-coronavirus-the-minimum-viable-nerve-center
Together with many leading companies, we have developed a better approach—a flexible structure for guiding the work—called the integrated nerve center. In an unfamiliar crisis, such as the COVID-19 outbreak, the nerve center concentrates crucial leadership skills and organizational capabilities and gives leaders the best chance of getting ahead of events rather than reacting to them.
3 Is It Time to Rethink Globalized Supply Chains?
https://sloanreview.mit.edu/article/is-it-time-to-rethink-globalized-supply-chains/
The COVID-19 contagion has had a major impact on Chinese manufacturers, and because of the central role many Chinese companies play in the supply chains of other companies, the impact is being felt around the world. The disruption is particularly acute in the electronics and auto industries, but it is also affecting pharmaceuticals, metals, and a wide range of consumer and industrial products, including surgical gowns and masks.
4 Coronavirus’s impact on supply chain
https://www.mckinsey.com/business-functions/operations/our-insights/supply-chain-recovery-in-coronavirus-times-plan-for-now-and-the-future
Even as the immediate toll on human health from the spread of coronavirus (SARS-CoV-2), which causes the COVID-19 disease, mounts, the economic effects of the crisis—and the livelihoods at stake—are coming into sharp focus. Businesses must respond on multiple fronts at once: at the same time that they work to protect their workers’ safety, they must also safeguard their operational viability, now increasingly under strain from a historic supply-chain shock.
5 The data-driven pandemic: Information sharing with COVID-19 is ‘unprecedented’
https://www.cbc.ca/news/canada/coronavirus-date-information-sharing-1.5500709
In the early days of Canada’s COVID-19 outbreak, Elisa Baniassad was able to trace how new cases were spreading and plan her outings accordingly.
“When I plotted how the virus was being transmitted, I saw that it was from close contact. People weren’t getting it out on the street, they were getting it at home from their family members,” said the computer science instructor at the University of British Columbia.
Baniassad is one of a handful of people making use of the reams of data being collected and published daily around the world to help governments and citizens plan and be informed of the latest situation.
6 Coronavirus: 3D printers save hospital with valves
https://www.bbc.com/news/technology-51911070
A 3D-printer company in Italy has designed and printed 100 life-saving respirator valves in 24 hours for a hospital that had run out of them.
The valve connects patients in intensive care to breathing machines.
The hospital, in Brescia, had 250 coronavirus patients in intensive care and the valves are designed to be used for a maximum of eight hours at a time.
7 Is It Time to Rethink Globalized Supply Chains?
https://sloanreview.mit.edu/article/is-it-time-to-rethink-globalized-supply-chains/
The COVID-19 contagion has had a major impact on Chinese manufacturers, and because of the central role many Chinese companies play in the supply chains of other companies, the impact is being felt around the world. The disruption is particularly acute in the electronics and auto industries, but it is also affecting pharmaceuticals, metals, and a wide range of consumer and industrial products, including surgical gowns and masks.
8 Wall Street weekahead: Coronavirus uncertainty muddies views on buying opportunities for plunging stocks
https://www.reuters.com/article/us-usa-stocks-weekahead-idUSKBN2171HV
U.S. stock valuations are tumbling in the wake of the coronavirus-fueled market rout, but determining when equities are cheap enough to buy is a tricky proposition.
The S&P 500’s .SPX price-to-earnings ratio, based on earnings estimates for the next year, has dropped from over 19 in late February to 14.2 as of Wednesday, according to Refinitiv data.
The decline in forward P/E marks a drop from the highest level since about mid-2002 to a level below the index’s historic average.
9 An Open Letter on Customer Service During a Pandemic
https://www.business2community.com/customer-experience/an-open-letter-on-customer-service-during-a-pandemic-02293771
It’s an understatement to say we are living in interesting times. Now declared a pandemic, the novel coronavirus COVID-19 is impacting everyone’s lives. A visit to any grocery or drug store illustrates the panic buying taking place as worried consumers stock-up. Every check of the inbox brings new COVID-19 emails from companies assuring their customers of the precautions they are taking. “Social distancing,” with its many considerations, is a new concept we should all be practicing. And in an attempt to combat the spread of the virus, countries have restricted travel and imposed quarantines.
10 The 4 Best Jupyter Notebook Environments for Deep Learning
https://www.kdnuggets.com/2020/03/4-best-jupyter-notebook-environments-deep-learning.html
Notebooks are becoming the de-facto standard for prototyping and analysis for Data Scientists. Many cloud providers offer machine learning and deep learning services in the form of Jupyter notebooks. Other players have now begun to offer cloud hosted Jupyter environments, with similar storage, compute and pricing structures. One of the main differences can be multi-language support and version control options that allow Data Scientists to share their work in one place.
11 Eight Emerging Lessons: From Coronavirus to Climate Action
https://medium.com/presencing-institute-blog/eight-emerging-lessons-from-coronavirus-to-climate-action-683c39c10e8b
As 100 million people in Europe are in lockdown, the US seems to be completely unprepared for the tsunami that is about to hit. “We’re about to experience the worst public health disaster since polio,” says Dr Martin Makary, professor at Johns Hopkins University’s Bloomberg School of Public Health. “Don’t believe the numbers when you see, even on our Johns Hopkins website, that 1,600 Americans have the virus. No, that means 1,600 got the test, tested positive. There are probably 25 to 50 people who have the virus for every one person who is confirmed. I think we have between 50,000 and half a million cases right now walking around in the United States.”
12 Airline industry crisis deepens as coronavirus pain spreads
https://www.reuters.com/article/us-health-coronavirus-airlines-idUSKBN21542J
The United Nation’s International Civil Aviation Organization called on governments to ensure cargo operations are not disrupted to maintain the availability of critical medicine and equipment such as ventilators and masks that will help fight the virus.
“The spread of the coronavirus has placed the entire global economy and our company as well in an unprecedented state of emergency,” Lufthansa CEO Carsten Spohr said in a statement. “At present, no one can foresee the consequences.”
13 Two generic drugs being tested in U.S. in race to find coronavirus treatments
https://www.reuters.com/article/us-health-coronavirus-usa-treatments-idUSKBN2161QQ
U.S. researchers, following the lead of scientists in other countries, have launched studies to see whether widely-available, low-cost generic drugs can be used to help treat the illness caused by the new coronavirus.
14 Time Series Classification Synthetic vs Real Financial Time Series
https://www.kdnuggets.com/2020/03/time-series-classification-synthetic-real-financial-time-series.html
I was given a “Data Science” challenge as part of an interview in which I had to distinguish between real financial time series and synthetic time series. I document the results here, the data was anonymous and I have no idea which assets were which or from what time series the assets came from.
To conclude I obtained an in-sample-test-accuracy of 67% and an out-of-sample-test-accuracy of 65% (based on what the interviewers told me)
