Archive for the ‘Bidness, and Other Current Economic Realities’ Category

By 2020 the U.S will overtake China to earn the top spot for the most competitive nation in the world.  At least, that’s according to predictions from Industry Week, whose stated mission is “advancing the business of manufacturing.”

According to Deloitte and the U.S. Council on Competitiveness this is due largely to America’s investments “in research, technology and innovation.”  “Manufacturing competitiveness, increasingly propelled by advanced technologies, is converging the digital and physical worlds, within and beyond the factory to both customers and suppliers, creating a highly responsive, innovative, and competitive global manufacturing landscape,” says Craig Giffi, co-author of the report.

Last year, Industry Week ranked their predictions of who would be the top manufacturing nations in their 2016 Global Manufacturing Competitiveness Index, noting that the top 11 will remain consistent through 2020 though some will trade places in the rankings.  Their listing showed the following global leaders in manufacturing by 2020:

  1. United States – Research, technology and innovation. Not to mention, access to capital.
  2. China – But of course, although slipping to number 2.
  3. Germany – Industrial production, research & development… a growing lead in advanced mfg.
  4. Japan – Manufacturing is almost 20% of Japan’s GDP… from autos to aviation
  5. India – Engineering, software, lots of factory workers gave rise to a jump from #11
  6. South Korea – Biopharmaceuticals are a major contributor… and then there’s Samsung
  7. Mexico – Electronics manufacturing is stronger than ever
  8. Taiwan – Optoelectronics (think: flat screens) and hi def color displays
  9. Canada – Montreal is the world’s 4th leading center for aerospace manufacturing
  10. Singapore – Big in biomedical sciences

It’s a bold prediction, and to make it happen will require continued innovation here in the U.S., along with advanced manufacturing, access to broad capital markets, access to world trade markets, and the continued research and developments efforts that have long ensured America’s place in the top tier of global manufacturing.

But others are not standing still, and nothing is ever assured.

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There is much debate today about what constitutes manufacturing and “the good jobs” in this country.  Many naively believe that more factories will cure the trade deficit and create jobs (in an economy already around full employment or, here in the Midwest, with jobs going unfilled).

“Die-hard conviction remains among many Americans that the more an economy manufactures, the stronger it is,” notes Michael Schuman a global business writer for several publications, quoted here recently in Bloomberg BusinessWeek magazine.

So with the help of Bloomberg and some recent studies, let’s set the record straight here.

First, while manufacturing is critically important (we may be biased as purveyors of manufacturing consulting and software, but it’s no less true), it now constitutes just 12% of GDP, versus more than double that 50 years ago.  But the idea that “we don’t make anything anymore” as recently touted by the President himself, is simply a fallacy.  The U.S. is a global manufacturing powerhouse, accounting for just under one-fifth of all production worldwide.  While that lags China’s 25%, it exceeds the shares of Japan and Germany combined.  We’re still highly competitive, particularly in the tech sector, and in hard to make products like jetliners and medical equipment, to name a few.

But in today’s world, the real value in making something, as Schuman and others have noted, is no longer in actually making it.  Companies today know that the real value of a product lies in its research and design elements, in product development, in branding, and in after-the-sale support services.  As an example, a study a few years ago by the Asian Development Bank pointed out that the actual assembly production proportion of an Apple iPhone (mostly performed in Asia) relative to its full retail value was only 3.6%.  The remaining 96.4% went to parts suppliers and to Apple, its creator.

And to that point, Apple’s margins overall are over 21% — from a company that is known for its manufacturing prowess but which, in fact, does virtually no manufacturing of its own.  Meanwhile, a typical offshore manufacturer that Apple contracts with posted just a 3.5% margin on sales.  And by the way, Apple creates lots of jobs without having factories, including 80,000 direct employees in the U.S. alone with plans to add more.

While more factories can, technically, mean more jobs on a local basis, studies show that workers who lose their jobs in plant closings take a long-term hit to their standard of living.  21st century factories won’t create the number of jobs that 20th century plants did.  Automation, advanced manufacturing, robots and the like mean we’re making a lot more with a lot fewer people.  Job displacement is a natural byproduct of technological progress, and has been for centuries.  But as old jobs die, new ones are born.  It’s important to remember that early on in our history, 90% of us were farmers; today it’s 3%.  As long as education and skills are developed with the future in mind, there are always likely to be new jobs to replace the old.  But then, that’s a whole other subject.

Meanwhile, let’s see manufacturing for what it is, and worry less about factory jobs that no longer exist and aren’t coming back, and more about the innovation, design, marketing and 21st century product (and skills) development  — along with a healthy dose of free trade, we might add – that will create the innovative companies (think Apple, Tesla, Facebook) of tomorrow.

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About twenty years ago American manufacturers began changing the face of the supply chain when they began “offshoring” — moving production to cheaper sources in foreign nations, expanding a national supply chain into a global one.  Fast forward 15 years or so, and a fair portion of that production has been seen returning home once again due largely to quality issues, but also to the increasing cost of much of that foreign manufacturing, once things like travel, shipping, duty fees, vendor due diligence, theft and piracy and a host of other issues are factored in.

Today, the opportunities and challenges afforded by 3D printing are beginning to create still another new form of “reshoring” that is poised to challenge everything we know about manufacturing.  Since its first patent was issued over 30 years ago, 3D printing is quickly becoming ubiquitous.  Its capabilities are now way beyond the prototype state, and the variety of materials that can be used has grown exponentially, notes John Collins, an APICS CFPIM, and Erick Jack dean of the Collat School of Business in a recent article for APICS Magazine.

Then there’s the recent article in The Economist (“A Third Industrial Revolution”), noting that the digitization of manufacturing is as significant as the mechanization of the textile industry and the introduction of mass production in the automotive sector.  “The ability to produce smaller batches of items tailored to specific customer needs at significantly lower costs could make the factory of the future look more like the weaver’s cottage than Ford’s assembly line.”  And that’s not to mention what this development implies for the changing skill sets of today factory workers as design and programming grow in emphasis.

Some are predicting that global logistics efforts will be reduced as manufacturers shift more of the capabilities and production back to their home shores to take advantage of customer and market proximity.  According to the PLS Logistics Blog, “part of the supply chain will become superfluous.”

When you think about, it makes sense if manufacturers can deliver small batches of customized products and prototypes.  It makes for leaner inventories, for one.  It increases the ability to respond more quickly to customer requests.  Manufacturers may be able to respond to orders directly from factories, thus eliminating some distribution elements.  Locations of stock might be consolidated, and transportation routes are likely to contract as smaller manufacturing locations provide more local 3D printing.

Collins and Jack ask whether it “might even be possible that 3D printing will supersede the concepts of nearshoring and reshoring.  After all,” they state, “where a manufacturing facility is located won’t matter much if customers can ‘deliver’ the products they purchase at home via a personal 3D printer.”

The supply chain of manufacturing has long been all about “speed, cost, quality and flexibility.”  3D printing provides both challenges and opportunities in all these.  Creating ways to incorporate new technologies like 3D printing into our processes provides plenty of both – including the opportunity to be an innovator while remaining competitive in a changing supply chain landscape.

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In our prior post, we pointed out that China is on the verge of becoming the world leader in the production, sale and implementation of robots, with a stated goal of producing at least half the nation’s own robots for manufacturing by 2025.  The takeaway from that view, outlined recently in Bloomberg BusinessWeek might be that the world has much to fear from the ascendance of this wave of Chinese bots.

But a recent counterpoint to such a robot apocalypse offered by Greg Ip of the Wall Street Journal suggests that in fact, robots aren’t destroying enough jobs, fast enough.

In short, Ip points out that by enabling society to produce more with the same workers, automation like robots becomes a major driver of rising standards of living – in effect, a productivity boost.  While some say that “this time is different” because the technological change is so profound they fear that millions of workers will be out of work or at best consigned to more menial tasks… Ip says the evidence shows we’re moving in exactly the opposite direction.

He notes that while the U.S. “has many problems, job creation isn’t one of them.”  Job creation has averaged 185,000 per month this year and unemployment is down to a ten year low.  Wage gains are even up, slightly.  Ip says that “if automation were rapidly displacing workers the productivity of the remaining workers ought to be growing rapidly.”  Instead, worker output per hour has been dismal in most sectors, including manufacturing.

When slow-growing occupations are compared to fast-growing ones in data going back to 1850 (a proxy for job creation and destruction driven by ‘technology’), they find that churn relative to total employment today is the lowest on record.

Ip’s point is that the past was, in fact, much more ‘convulsive’ than today’s job churn.  American consumption he notes is gravitating toward goods and services whose production is not easily automated.  Societies increasingly are devoting “a growing share of their income to consumption in sectors where productivity [is] stagnant.”  The idea is that robots can replace fewer things that go into GDP than we think.

As examples he cites medical breakthroughs in new, more expensive treatments rather than cheaper existing treatments, and that child-care work has soared because parents won’t leave kids in the care of a robot.  Over the past decade, “low productivity sectors” including education, health care, social assistance, leisure and hospitality have added nearly 7 million jobs, whereas information and finance, where value added per worker is 5 to 10 times higher, have cut or barely added jobs.

His conclusion: We need a change in priorities.  Instead of worrying about robots destroying jobs, we need to use them more, especially in low-productivity sectors.  While robots may one day replace truck drivers, “it’s more urgent to make existing drivers, now in short supply, more efficient,” and to be more concerned about reducing the labor, and thus the cost of energy, rather than worry about jobs added in areas like solar power.  The alternative, notes Ip, “is a tightening labor market that forces companies to pay ever higher wages that must be passed on as inflation.  And that, he notes, “is a more imminent threat than an army of androids.”


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As most of us have noticed by now, the pace of technology – long proceeding at a snail’s pace as generation after generation lived more or less as their parents had – has been accelerating at what to many feels like a breakneck rate.  We’ve gone from linear progress to exponential, moving from the industrial revolution to the current digital one at an ever-quickening pace.

Moore’s Law, now over 50 years old, postulated that the number of transistors per square inch on a circuit board would double every year or two since – and today, that continued pace means that exotic technologies that include AI (artificial intelligence), robots, cloud computing and 3-D printing systems are proliferating, evolving in many cases faster than we humans can keep up.  It seems like things keep getting faster, smaller and smarter.

And therein lies the downside of all this technical innovation, says Gary Smith, a logistics expert with the New York City Transit in a recent issue of APICS Magazine.  Smith believes that “the rate of technological change exceeds the rate at which we can absorb, understand and accept it.”  This is acutely true in the world of supply chain, with its deep reach into manufacturing, distribution and just business in general.

Most importantly he notes that “disruptive technologies require a workforce that adapts to new processes, new ways of learning and training systems.”  In that spirit, he suggests key considerations and qualities that are going to be important within supply chains of the future, ones that the next generation workforce can expect to have to incorporate into their work patterns.  Among them:

  • Data analysis and database development skills. The ability to analyze and produce actionable results from data using logic and fact with insightful opinions and interpretation of available data will be critical.
  • Critical thinking. It’s vital to data analysis and fact-based decision making.  The ability to quickly acquire knowledge and break it down into its logical components, and then analyze and drill for accurate and actionable conclusions matters.  You have to be able to take complex situations and break them down into their component tasks.  Or as Franklin Covey would say, “start with the end in mind.”  Critical thinking means “abstraction, systems thinking, experimentation and collaboration,” notes Gary Smith.  To wit:
  • Abstraction. The ability to discover patterns in data.  Often, lessons from one industry can be applied to another, for example.
  • Systems thinking. That is, viewing issues as a part of the whole – how issues relate to the rest of a system.  Often, the “good of the many outweighs the good of the few.”
  • Experimentation. Complex problems require trial and error, testing and experimentation.  It’s okay to fail, as that’s part of learning.  Fail fast, think differently and learn to adapt as new conditions present themselves.
  • Collaboration. It’s working with others toward the common goal.  Easier said than done.  It requires team-building and facilitation skills, along with everyone keeping their eyes on the prize.  Collaboration is particularly important in supply chain and ERP work, where silos need to be broken down and people need to cooperate and effectively communicate.

These are the critical skills companies will be looking for.  We see the need for it every day in ours, and we’re only one of many.  So in a very real sense, the future really is now.

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A bit off topic today, but we think those who work for a living and hope one day not to have to, may find this of interest in the pursuit of sound retirement investment strategies.

We are gradually learning these past few years that when it comes to making money by investing in the stock market, the lowly “exchange traded fund” (or ETF) that tracks a broad basket of stocks across many companies or sectors (the S&P 500 tracking funds being among the more obvious indexes) generally beat the returns of funds managed by human money managers.  In other words, the overall market, over time, will exceed what most of even the best money managers can do for you.

This of course is disconcerting to those who earn their living picking those stocks, or selling their funds.  Nonetheless, it’s proving true.  According to several sources we’ve reviewed, something like 86% of managed funds do NOT beat the market, or even the so-called “benchmarks” they are measured against.

The core of the problem is that it is very hard to beat the market.  Obviously.  But in this era of rocket scientist, algorithm producing, quant-based, big data stock picking… it doesn’t mean folks aren’t trying. And that may be the problem.

With today’s computing power and increasing wealth of raw data, it is possible to test thousands, even millions of data sets, ideas and trading philosophies.  The standard method of doing this involves something called “backtesting” in which someone comes up with a market hypothesis, and then looks back over, say, twenty years, to see how their strategy would have performed against real markets, with their unpredictable ups and downs, over that time.  To check the validity of their results, the technique is then checked against “out-of-sample” data, consisting of market history that was not used to create the original technique.

But in the wrong hands, things can go, well… wrong.  There is a powerful temptation to get published in finance journals among researchers, analysts and economics.  Too often, this leads to “torturing the data” as a recent Bloomberg BusinessWeek article pointed out (April, 2017).  This in turn has led to some exchange-traded funds using flawed statistical techniques according to a couple of experts at Duke University, implying that “half the financial products promising outperformance that companies are selling to clients are false.”

For example, a batch of research involving United Nations data once found that the best (backtested) predictor of stock performance in the S&P 500 was butter production in Bangladesh.  That is to say, out of millions of data sets, tested backwards in time, the one with that came closest to tracking the S&P 500’s actual market performance over time was the output of butter production in a third world nation half-way around the world.

Researches can “twist  the knobs” on their assumptions in search of a prized “anomaly” that they can write about – or sell.  They can vary, say, the “time period covered, or the set of securities under consideration, or even the statistical method,” according to Bloomberg’s Peter Coy.  Negative findings get round-filed; positive findings get published — or make into an ETF whose performance we may be relying upon for our retirement.  With enough tests, notes Coy, “eventually by chance even your safety check will show the effect you want.”

So next time you read about some great new investment strategy vetted by a Wall Street hedge fund’s top “quants” (the math wizards who come up with stuff)… take a deep breath, turn the page, and leave your long-term funds in a plain old vanilla stock market index fund from Vanguard, Fidelity or American Funds.

It will help to ensure that when it’s time to retire, your money will be ready too.

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Be sure to read our previous post beginning here on some basics of “blockchain” technology.  Today, we’ll tell you about an even newer evolution in the rapidly evolving blockchain saga.

Our title headline today is how a fellow named Joe Lubin, founder of a company called ConsenSys that develops applications for the burgeoning “Blockchain” technology, describes Ethereum.  Chances are if you’ve heard of Ethereum at all, it’s because the new platform was the victim of a $60 million hack a while back.

What you may not know is that companies including IBM, Microsoft, BP, JP Morgan and a lot of others recently attended a forum sponsored by an industry group called the Enterprise Ethereum Alliance.  Ethereum technology, while still young, comes with enormous promise, despite last year’s hack setback.  Advocates believe Ethereum “could be a universally accessible machine for running businesses,” according to a Matthew Leising of Bloomberg Businessweek.

Cornell University professor Emin Gun Sirer says “Ethereum gives you a new way for the computer to interact with the real world and how money moves.”  In effect, it’s a complete business-to-business transaction engine and database.  It’s based on the “Blockchain” concept of digital money.  The idea behind Blockchain is to create a verifiable virtual currency that can be distributed as easily as an email.  It’s an online ledger on computers distributed around the world.

We’ll spare you the details, but the idea is that every “bitcoin” distributed is tracked and verified, in a system that basically runs itself.  Its main purpose is to move currency from point A to point B.

What Ethereum adds to the Blockchain is the ability to store fully functioning programs called “smart contracts.”  So beyond moving money, users can potentially control contracts or projects, thus allowing a person to complete a job for a customer and trigger payment on completion – all without added human intervention, in a secure framework.

That’s the concept, at any rate.  As Leising notes, “Once you can create contracts – which in essence are just operating procedures – you can use them to manage almost any kind of enterprise or organization.”

A variant on the technology would see companies participate in an Ethereum platform on a closed invitation basis, given that a public platform tends to increase security risks, whereas a semi-private network among aligned business partners might provide an effective alternative with the same end result.

A variety of companies are exploring their options today.  John Hancock is experimenting with compliance tracking and anti-money-laundering regulations in its wealth management unit.  Airbus is exploring ways to move its entire supply chain to a Blockchain.

If all this sounds a lot like the future of enterprise business models, one shouldn’t be surprised.  There are security and logistical wrinkles to be worked out, to be sure, but the idea of a self-regulating supply chain of integrated enterprise systems that embrace project management, verifiable currency transfers and contract fulfillment has a lot of companies paying attention to the Blockchain ledger technology.

Right now, Ethereum is helping to lead the way.  It’s a name worth remembering.



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