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OM in the News: Computer Vision Systems and the Start Up Nation

November 21, 2018

A Mobileye autonomous driving vehicle at the company’s HQ in Jerusalem

Israel (famously known as the Start Up Nation after the best-selling book by that title) has become a leader in one of the most promising frontiers in the technology world: computer vision. An area that has come of age this decade, it covers applications across dozens of industries that have one thing in common: the need for computers to figure out what their cameras are seeing, and the need for those computers to tell them what to do next.

Israel’s biggest success story is Mobileye, which uses a dozen cheap cameras to see the traffic around autonomous cars and then guides them through traffic. In 2017, Intel paid $15.3 billion to acquire the technology.

“Computer vision is the connecting thread between some of Israel’s most valuable and promising tech companies,” writes The Financial Times (Nov. 20, 2018). And unlike Israel’s traditional strengths— cyber security and mapping (Waze is another Israeli invention) — computer vision slides into a broad range of different civilian industries, spawning companies in agriculture, medicine, sports, self-driving cars, the diamond industry and even shopping. This lucrative field has benefited from a large pool of engineers and entrepreneurs trained for that very task in the Israeli military, where they fine-tuned computer algorithms to digest millions of pieces of surveillance.

Having built massive databases — from close-ups of farm insects to medical scans to traffic data — has given Israeli companies a valuable head start over other nations. And in an industry where every new image teaches the algorithm something useful, that has made catching up difficult. It has also created opportunities in unexpected sectors. Physimax uses a bank of cameras to analyze the posture of athletes, then suggests changes to their exercise routines and techniques. It is already being used by the US military and professional basketball and football teams. Zebra Medical uses AI to scan millions of MRIs from around the world, guiding radiologists to the slightest sign of disease. Trigo automates the checkout in grocery stores. Nexar analyses traffic and collision data from driver’s smartphones.

Classroom discussion questions:

  1. Why are computer vision systems important to OM?

2.  Provide an example not discussed in the article of how the systems can be used in business.

 

 

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OM in the News: In Russia, McDonald’s Serves Local Fries and a Side of Realpolitik

November 19, 2018

A new potato-processing plant is working to produce french fries to McDonald’s exacting specifications.

McDonald’s became a leading ambassador of American culture after opening its first restaurant in Moscow in the twilight of the Soviet Union, writes The Wall Street Journal (Nov. 8, 2018). Now, as Russia-U.S. tensions rise and pro-Kremlin politicians call to close the U.S. chain, management is taking a new tack: Go Russian. This year, the company boosted the share of Russian suppliers its restaurants use to 98%. McDonald’s has succeeded world-wide in part by finding local suppliers wherever its restaurants operate, shortening supply chains.

The local focus appears to be paying off. The number of McDonald’s restaurants in Russia grew 6% this year. The firm sees Russia as a high-growth market able to offset the saturated U.S. market. The company opened its first restaurant on Pushkin Square in 1990, where it served 30,000 hungry Soviet Muscovites on its first day.

U.S.-Russian ties have frayed in recent years. The first shots against McDonald’s were fired in 2014 after the U.S. sanctioned Russia following Moscow’s annexation of Crimea. Russian authorities at the time closed 12 restaurants nationwide, including the Moscow flagship, and subjected hundreds of others to snap health inspections. The temporary closures had little effect on sales, but management used them as an opportunity to refurbish restaurant interiors and start digitizing processes.

After that experience, McDonald’s focused on boosting purchases from local producers for almost everything it served. Critically, McDonald’s signed a contract to buy its french fries from a Russian producer—a first in its almost 30-year history. The agreement ends one of McDonald’s most fraught endeavors here: finding the right supplier to reliably deliver fries up to the company’s standards. And McDonald’s advertising strategy is focused on getting the word out. Delivery trucks are painted with a large “98%,” signifying the company’s share of local suppliers.

Classroom discussion questions:

  1. What makes the Russian supply chain so difficult for the firm?
  2. Why are the French fries an issue?

OM in the News: Amazon’s HQ2 Spectacle Ends

November 16, 2018

The Amazon HQ2 saga is finally over. Fourteen months ago, Amazon announced a beauty contest, in which cities could apply to win the honor of landing the 2nd headquarters. The prize: 50,000 employees. The cost? Just several billion dollars in tax incentives. Then last week, Amazon announced it would split the prize between Arlington VA, and NYC. So the question, writes The Atlantic (Nov. 12, 2018) is: “Did the world’s smartest company really need 13 months, and applications from 238 cities, to reach the striking conclusion that it should invest in New York and D.C.?”

When covering Location Analysis (Ch. 8), you could also ask your students: Why are U.S. cities spending tens of billions of dollars to take jobs from one another in the first place? (Recall the “Border War”, in which the Kansas and Missouri sides of Kansas City have spent $1/2 billion dragging companies back and forth across state lines, within the same metro area, creating no new jobs.)

Every year, American cities and states spend about $90 billion in tax breaks and cash grants to urge companies to move among states– more than the federal government spends on housing, education, or infrastructure. These deals take resources from everything local governments would otherwise pay for, such as schools, roads, police, and prisons. In the past decade, Boeing, Nike, Intel, Royal Dutch Shell, Tesla, Nissan, Ford, and G.M. have each received subsidy packages worth more than $1 billion to either move their HQs within the U.S. or, quite often, to keep theme right where they are. New Jersey and Maryland offered $7 billion for HQ2, which would have been the biggest corporate giveaway in history.

And companies don’t always hold up their end of the deal. Consider Wisconsin, which lured Foxconn with a subsidy plan that will end up costing over $4 billion. Foxconn said it would build a large manufacturing plant that would create about 13,000 jobs. Now the company is building a much smaller factory with just 1/4 of its initial promised investment, and much of the assembly work to be done by robots.

Classroom discussion questions:

  1. Money aside, why did Amazon select the D.C. suburb and NYC as co-HQ2 winners?
  2. Make the argument for and against the giant incentives being offered to companies.

OM in the News: The Stressed Global Auto Supply Chain

November 14, 2018

The automotive supply chain is a complex, global network of interdependent businesses ranging from small, family-owned manufacturers based in the U.S. heartland to large publicly traded overseas auto parts companies—all working in unison to keep cars rolling off the assembly line. But fights are emerging across the auto industry over who should bear the costs of tariffs, leading to new stress along the supply chain, reports The Wall Street Journal (Nov. 10, 2018).

Recently, Pierburg US, a manufacturer of parts used in the Ford F-150 pickup truck and Jeep Wrangler SUV, sued one of its suppliers over new tariffs imposed. The two sides have been in business for 20+ years. Pierburg says that the supplier’s refusal to ship electric motors from China to Pierburg’s factory in South Carolina unless it paid the 25% tariff cost in full was “extortion.” A failure to deliver the parts could shut down multiple auto factories and “plunge the automotive industry into complete chaos,” Pierburg added. Sorting out the cost of tariffs is difficult because some parts cross the U.S. border multiple times before being installed in a car, blurring the lines of what is “domestic” content.

A typical vehicle is made up of roughly 30,000 individual parts, and car companies on average work with hundreds of suppliers at once for each model line, either buying components directly or contracting them out further down the chain. Thousands of individual contracts outline in detail parts orders, delivery dates and prices, and many of them are locked in place months and even years in advance.

Toyota has told suppliers they shouldn’t count on the Japanese car maker to help absorb the higher tariff-related costs. The average operating profit margin in the auto parts manufacturing business is already slim–about 7%—so extra costs can hit earnings hard.

Classroom discussion questions:

  1. Describe the auto supply chain.
  2. What is the impact of tariffs proposed?

OM in the News: The Fourth Industrial Revolution–Industry 4.0

November 12, 2018

A recent IndustryWeek survey (Nov. 6, 2018) found that manufacturers are having trouble joining the Fourth Industrial Revolution, called Industry 4.0. And the World Economic Forum (WEF) found that 7 out of 10 manufacturers fail in pushing initiatives in big data analytics, A.I., and additive manufacturing.

But there is hope, the Forum asserts. They scoured the planet and after vetting 1,000 manufacturers, selected 9 “lighthouses” (listed below) with a solid Industry 4.0 strategy. “These pioneers have created factories that have 20-50% higher performance and create a competitive edge,” says a McKinsey exec. “They have agile teams with analytics, IoT and software development expertise that are rapidly innovating.” Industry 4.0 is expected to deliver productivity gains over $3.7 trillion.

Bayer Biopharmaceutical: Italy. Most companies use less than 1% of the data they generate. Bayer makes the most of its data, leading to a 25% drop in maintenance costs and while gaining 30-40% in operational efficiency.

Bosch Automotive: China. Bosch uses data analytics to deeply understand and eliminate output losses, simulate and optimize process settings, and predict machine interruptions before they occur.

Haier: China. Use of AI facilitates a “user-centric mass customization model” with electronic products made on-demand. Maintenance needs are predicted before incurring downtime via AI.

Johnson & Johnson: Ireland. This hip and knee joint factory implements IoT, leading to a 10% reduction in operating costs and 5% drop in machine downtime.

Phoenix Contact: Germany. The electronics manufacturer relies heavily on customer-specific clones to cut production time for repairs or replacements by 30%.

P&G: Czech Republic. Production lines, in a plant built in 1875, seamlessly change the product being manufactured with a push of a button, an innovation that reduced costs by 20% and upped output by 160%!

Schneider Electric: France. Sharing of best practices across its multinational force allows each site to reap the benefits of the others, saving 10% on energy and 30% on maintenance.

Siemens: China. Leveraging augmented reality to create 3D simulations, Siemens has optimized its production lines with reduced cycle time and 300% jump in output.

Fast Radius: U.S. The lone U.S. company uses real-time analytics and globally positioned distribution 3D printing farms to maintain rapid turnaround times to deliver prototypes and custom parts.

Classroom discussion questions:

  1. What is Industry 4.0?
  2. What do these 9 firms seem to have in common?

 

OM in the News: China, High-Tech, and the 996 Schedule

November 9, 2018

“Crazy Work Hours and Lots of Cameras: Silicon Valley Goes to China,” is the title of the New York Times article (Nov. 6, 2018), describing the visit by US high tech execs to China.

A Chinese voice-controlled A.I.-powered family robot

The Silicon Valley natives were introduced to the Chinese concept of 996: Work from 9 a.m. to 9 p.m., 6 days a week. One Chinese technology executive said he worked 14-15 hours a day at least 6 days a week. Another said he worked every waking hour. The reaction from a group of Silicon Valley executives: Wow! “We’re so lazy in the U.S.!” blurted a venture capital investor.

Chinese technology executives, they found, were even more driven and more willing to do whatever it takes to win. But punishing work schedules are only the beginning. They found Chinese tech executives to be less reflective about the social impact and potential misuse of their technologies, a worrisome quality in a country with loosely enforced privacy laws, strict government censorship and a powerful domestic surveillance.

The Americans got upfront lessons on how quickly China embraced mobile phones, electronic payments and video streaming, and how intensely it has pursued artificial intelligence. (For example,  mobile payments are almost ubiquitous in the biggest Chinese cities, but setting up an account requires a local mobile number and a Chinese bank account). In addition, everything seemed to be moving at an extraordinary speed. While Silicon Valley start-ups raise funding every 18 to 24 months on average, the most successful Chinese companies do it every 6 months. They also found that everybody working in the firms visited is Chinese. Even in its early days, Google had employees from 39 nationalities speaking 40-plus languages.

Classroom discussion questions:

  1. Compare the U.S. to Chinese high-tech work styles.
  2. Would the 996 concept work in the U.S or Europe?

 

OM in the News: Making Sense of Supply Chain 4.0

November 7, 2018

McKinsey, Cap Gemini and the Boston Consulting Group all suggest Supply Chain 4.0, digital transformation, is about applying digital technologies– Artificial Intelligence (AI), Machine Learning (ML), the Internet of Things (IoT) and Blockchain– to operational processes and creating improvements.

 If digital transformation is to “transform” SCM, then it must as efficiently as possible match supply to real demand, writes IndustryWeek (Nov. 2, 2018). In SCM, there are 3 key factors that impact the ability to match supply to demand: (1) Demand uncertainty and the inability to accurately forecast demand; (2) Production uncertainties leading to changes in supply; and (3) Lack of synchronization among supply chain partners.

(1) Traditional forecasting methods can be impacted by one-time events (such as economic changes, special promotions, fashion trends, or a spike in social chatter) that affect the stability of historical sales patterns. Digital transformation can improve traditional forecasting methods in 2 ways. The first is to gather new data, such as sentiment information from social channels, weather inputs, economic performance or information from new IoT or Fog Computing sensors that can provide insights into customer demand. The second is to use ML to continuously “learn” from this data to determine the contributions of these factors in predicting demand.

(2) Digital transformation can use IoT to continuously monitor machines on the shop floor, track key performance metrics and then use predictive analytics to understand what these performance metrics mean for yield, quality or the likelihood of machine failure.

(3) At one end of the supply chain, a retailer may determine a particular demand based on what end consumers are buying. This demand signals the next tier in the supply chain, which sends its own demand signal to the next tier and so on. The end result is a view of demand a few tiers into the supply chain that is very different from the original demand requirement from the retailer. The supply chain, in effect, becomes unsynchronized.  Blockchain is a distributed ledger, with information instantly visible to all parties of the blockchain and ensures a single version of the truth – such as a single understanding of true end-customer demand – in the supply chain. This is what synchronizes all supply chain partners.

Classroom discussion questions:

  1. How does digital transformation differ from traditional forecasting?
  2. What is IoT? Give an example.
  3. What is blockchain and how can it help SCM?

 

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