Friday, March 27, 2020
Business Intelligence and Analytics 57
1 Supply chain outlook: Why the situation varies by industry
http://news.mit.edu/2020/sheffi-global-supply-chain-covid-19-0325
By now, the media images are familiar: empty shelves in large markets where shoppers have loaded up on food, toiletries, and medicine. Many people, if they can afford it, have bought large quantities of goods to avoid repeated trips into public, in line with their state and local government guidelines. But others may be simply spooked by the unknown: Will we run out of the things we need?
2 Supply chain outlook: The timing of the slowdown
http://news.mit.edu/2020/simchi-levi-supply-chain-covid-19-0325
The rapid spread of the Covid-19 virus is already having a huge impact on the global economy, which is rippling around the world via the long supply chains of major industries.
MIT supply chain expert David Simchi-Levi has been watching those ripples closely in 2020, as they have moved from China outward to the U.S. and Europe. His tracking of supply chain problems provides insight into what is happening in the global economy — and what could happen in a variety of scenarios.
3 Strategy under uncertainty | McKinsey
https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/strategy-under-uncertainty
At the heart of the traditional approach to strategy lies the assumption that executives, by applying a set of powerful analytic tools, can predict the future of any business accurately enough to choose a clear strategic direction for it. The process often involves underestimating uncertainty in order to lay out a vision of future events sufficiently precise to be captured in a discounted-cash-flow (DCF) analysis. When the future is truly uncertain, this approach is at best marginally helpful and at worst downright dangerous: underestimating uncertainty can lead to strategies that neither defend a company against the threats nor take advantage of the opportunities that higher levels of uncertainty provide. Another danger lies at the other extreme: if managers can’t find a strategy that works under traditional analysis, they may abandon the analytical rigor of their planning process altogether and base their decisions on gut instinct.
4 Pandemic Panic: Can Governments Protect Jobs and Markets?
https://knowledge.wharton.upenn.edu/article/layoffs-loom-governments-respond-pandemic-panic/
The COVID-19 virus has infected populations around the world and slammed the global economy. While it is unclear where the coronavirus pandemic is headed, experts believe that it will lead to a worldwide recession.
Mauro Guillen, professor of international management at Wharton and the creator ofan online course on the coronavirus crisis that the school plans to launch on March 25, believes that the challenge on the economic front is whether policy makers can find a way to prevent firms from laying off workers and if they can help calm panicky markets.
5 Taking Care of Our People
https://www.business2community.com/strategy/taking-care-of-our-people-02296299
Like our customers, each of us and our people are facing things we may have never experienced before. We are being asked to work in new ways–some of which we are ill equipped to support. We have no clear answers and are figuring them out on the fly. And things we decide this week, may have to be changed in the coming weeks.
6 How To Painlessly Analyze Your Time Series
https://www.kdnuggets.com/2020/03/painlessly-analyze-time-series.html
We’re surrounded by time series data. From finance to IoT to marketing, many organizations produce thousands of these metrics and mine them to uncover business-critical insights. A Site Reliability Engineer might monitor hundreds of thousands of time series streams from a server farm, in the hopes of detecting anomalous events and preventing catastrophic failure. Alternatively, a brick and mortar retailer might care about identifying patterns of customer foot traffic and leveraging them to guide inventory decisions.
7 Technology Driven Insurance Data Analytics
https://datafloq.com/read/technology-driven-insurance-data-analytics/8081
The nature of the Insurance industry being data-centric, insurers abide by the policy of keeping data as a treasure for their respective growth. This data can only be turned into a gold mine of Insurance Data Analytics by in-depth analysis of other engagement areas of the customer and the insurer depending upon the kind of insurance one prefers.
8 Making sense of ensemble learning techniques
https://www.kdnuggets.com/2020/03/making-sense-ensemble-learning-techniques.html
For many companies/data scientists that specialize or work with machine learning (ML), ensemble learning methods have become the weapons of choice. As ensemble learning methods combine multiple base models, together they have a greater ability to produce a much more accurate ML model. For example, at Bigabid we’ve been ensemble learning to successfully solve a variety of problems ranging from optimizing LTV (Customer Lifetime Value) to fraud detection.
9 How bad will Canada’s COVID-19 recession be?
https://www.cbc.ca/news/business/covid-19-recession-economy-analysis-1.5510596
The black swan has landed.
The novel coronavirus pandemic is well underway worldwide, but it wasn’t until this month that Canadians started coming to grips with the economic pain it can bring, in addition to its heavy human toll.
10 Coronavirus measures could cause global food shortage, UN warns
https://www.theguardian.com/global-development/2020/mar/26/coronavirus-measures-could-cause-global-food-shortage-un-warns
Protectionist measures by national governments during the coronavirus crisis could provoke food shortages around the world, the UN’s food body has warned.
Harvests have been good and the outlook for staple crops is promising, but a shortage of field workers brought on by the virus crisis and a move towards protectionism – tariffs and export bans – mean problems could quickly appear in the coming weeks, Maximo Torero, chief economist of the UN Food and Agriculture Organisation, told the Guardian.
11 MIT-affiliated companies take on Covid-19
http://news.mit.edu/2020/mit-companies-covid-19-0326
As the world grapples with the public health crises and myriad disruptions brought on by the Covid-19 pandemic, many efforts to address its impact are underway.
Several of those initiatives are being led by companies that were founded by MIT alumni, professors, students, and researchers.
12 AI program could check blood for signs of lung cancer
https://www.theguardian.com/society/2020/mar/25/ai-program-could-check-blood-for-signs-of-lung-cancer
Scientists have developed an artificial intelligence program that can screen people for lung cancer by analysing their blood for DNA mutations that drive the disease.
The software is experimental and needs to be verified in a clinical trial, but doctors are hopeful that if it proves its worth at scale, it will boost lung cancer screening rates by making the procedure as simple as a routine blood test.
13 Want to Build an AI Model for Your Business? Read this
https://www.kdnuggets.com/2020/03/build-ai-model-business-read-this.html
Artificial Intelligence, Machine Learning, and Deep Learning models have demonstrated significant power to grow and improve businesses. We have found that the best approach to AI production is what venture capitalists do when they evaluate and invest in startups.
14 Preparing the Supply Chain for the Next Disruption
https://medium.com/bcggamma/preparing-the-supply-chain-for-the-next-disruption-48bbbc63b79f
COVID-19 has put supply chains for all industries under enormous stress. From the sourcing of raw materials to the distribution of finished products, supply chains are at the frontline of this crisis. But this is not likely to be the last pandemic or global crisis. How supply chains are currently coping — or not — provides some valuable lessons for facing similarly widespread disruptions in the future.
15 Managing the Flow of Ideas in a Pandemic
https://sloanreview.mit.edu/article/managing-the-flow-of-ideas-in-a-pandemic/
Most organizations are hierarchical or centralized, so their senior leaders are at the center. All roads lead to them. The leaders are typically older and have more health conditions. During a pandemic, like the one we now face with COVID-19, standard organizational structures are a management disaster in the making — because the senior people are likely to be the hardest hit.
16 Coronavirus pandemic has delivered the fastest, deepest economic shock in history
https://www.theguardian.com/business/2020/mar/25/coronavirus-pandemic-has-delivered-the-fastest-deepest-economic-shock-in-history
The shock to the global economy from Covid-19 has been faster and more severe than the 2008 global financial crisisand even the Great Depression. In those two previous episodes, stock markets collapsed by 50% or more, credit markets froze up, massive bankruptcies followed, unemployment rates soared above 10% and GDP contracted at an annualised rate of 10% or more. But all of this took around three years to play out. In the current crisis, similarly dire macroeconomic and financial outcomes have materialised in three weeks.
17 5 Ways to Do Smart & Responsible Marketing During COVID-19
https://www.business2community.com/marketing/5-ways-to-do-smart-responsible-marketing-during-covid-19-02295026
In everything we do as brands, context matters. Beyond the basic actions taken to protect employees and businesses during a crisis, brands can either help or hinder our collective experience. So when a cultural moment shifts as dramatically as it has in the face of COVID-19, it’s important that brands address the issue with tact, empathy, and mindful marketing.
18 Using artificial intelligence to detect COVID-19
https://medium.com/@haidaramohamed32/using-artificial-intelligence-to-detect-covid-19-6fcd9857b93f
Among the tens of thousands of cases detected, several cases of COVID-19 are asymptomatic. These most common symptoms of the virus are fever and a dry cough. Some people may also experience aches, headache, tightness or shortness of breath. These symptoms suggest an acute respiratory infection or radiologically detectable lung abnormalities. We can use Artificial Intelligence algorithms to detect the disease using automatic X-ray analysis to support radiologists.
19 What is the probability that someone you know will die from COVID-19 this year?
https://statmodeling.stat.columbia.edu/2020/03/24/what-is-the-probability-that-someone-you-know-will-die-from-covid-19/
I teach a Math Methods class that covers basic probability, mathematical modeling, and data science. For one of my upcoming lectures I plan on applying the very simple tools that we’ve covered so far to COVID-19. As I’m sure you’re aware, there are very dire predictions for the total number of Americans that will die from COVID-19, ranging from 0.5–3M. However, I wanted to connect these impersonal numbers to a very basic question:
