Fredrick Winslow Taylor Gets a Bum Rap

frederick_winslow_taylor_cropFredrick Winslow Taylor is recognized as the father of scientific management, sometimes called “Taylorism”, the application of which has been responsible for tremendous increases in productivity and standards of living for millions of people.

“Frederick W. Taylor was the first man in recorded history who deemed work deserving of systematic observation and study. On Taylor’s ‘scientific management’ rests, above all, the tremendous surge of affluence in the last seventy-five years which has lifted the working masses in the developed countries well above any level recorded before, even for the well-to-do.”  -Peter Drucker

As outlined in Wikipedia, the conventional view of Taylor’s approach to management consists of four principles, including a strict division of labor between labor and management:

  1. Replace rule-of-thumb work methods with methods based on a scientific study of the tasks.

  2. Scientifically select, train, and develop each employee rather than passively leaving them to train themselves.

  3. Provide “Detailed instruction and supervision of each worker in the performance of that worker’s discrete task” (Montgomery 1997: 250).

  4. Divide work nearly equally between managers and workers, so that the managers apply scientific management principles to planning the work and the workers actually perform the tasks.

Through the early 1900’s, Taylor was an inspiration to the Progressive movement.  Today, however, he and his approach are often criticized as being dehumanizing, treating workers like robots, setting up a ruling class of manager/planners, and otherwise abusing labor.  In some ways, the general perception is that of a sort of smart robber baron who found a more scientific way to exploit labor.

The other day, I decided to read what Taylor himself had to say in his 1911 book, The Principles of Scientific Management (Excerpts below are from the free Kindle edition). To my surprise, Taylor comes across a lot more collaborative and supportive of labor than you would expect from reading about him today.  I’ve highlighted key phrases in bold.  Here’s Taylor on management’s key objective:

The principal object of management should be to secure the maximum prosperity for the employer, coupled with the maximum prosperity for each employee.

At the opening of the book, Taylor is actually something of a proto-environmentalist, arguing that increasing the efficiency of labor is as important as conserving natural resources:

We can see our forests vanishing, our water-powers going to waste, our soil being carried by floods into the sea; and the end of our coal and our iron is in sight. But our larger wastes of human effort, which go on every day through such of our acts as are blundering, ill-directed, or inefficient, and which Mr. Roosevelt refers to as a, lack of “national efficiency,” are less visible, less tangible, and are but vaguely appreciated. We can see and feel the waste of material things. Awkward, inefficient, or ill-directed movements of men, however, leave nothing visible or tangible behind them. Their appreciation calls for an act of memory, an effort of the imagination. And for this reason, even though our daily loss from this source is greater than from our waste of material things, the one has stirred us deeply, while the other has moved us but little. As yet there has been no public agitation for “greater national efficiency,” no meetings have been called to consider how this is to be brought about. And still there are signs that the need for greater efficiency is widely felt.

He writes about making sure that workers have tools that accurately fit their work, make efficient movements, get adequate breaks, and are paid fairly.  Managers and planners need to scientifically study the work and collaborate with workers, in order to train them to do their best. Taylor draws parallels between a well-trained workman and a surgeon:

Now, when through all of this teaching and this minute instruction the work is apparently made so smooth and easy for the workman, the first impression is that this all tends to make him a mere automaton, a wooden man. As the workmen frequently say when they first come under this system, “Why, I am not allowed to think or move without some one interfering or doing it for me!” The same criticism and objection, however, can be raised against all other modern subdivision of labor. It does not follow, for example, that the modern surgeon is any more narrow or wooden a man than the early settler of this country.

The frontiersman, however, had to be not only a surgeon, but also an architect, house-builder, lumberman, farmer, soldier, and doctor, and he had to settle his law cases with a gun. You would hardly say that the life of the modern surgeon is any more narrowing, or that he is more of a wooden man than the frontiersman. The many problems to be met and solved by the surgeon are just as intricate and difficult and as developing and broadening in their way as were those of the frontiersman. And it should be remembered that the training of the surgeon has been almost identical in type with the teaching and training which is given to the workman under scientific management.

The surgeon, all through his early years, is under the closest supervision of more experienced men, who show him in the minutest way how each element of his work is best done. They provide him with the finest implements, each one of which has been the subject of special study and development, and then insist upon his using each of these implements in the very best way. All of this teaching, however, in no way narrows him. On the contrary he is quickly given the very best knowledge of his predecessors; and, provided (as he is, right from the start) with standard implements and methods which represent the best knowledge of the world up to date, he is able to use his own originality and ingenuity to make real additions to the world’s knowledge, instead of reinventing things which are old.

In a similar way the workman who is cooperating with his many teachers under scientific management has an opportunity to develop which is at least as good as and generally better than that which he had when the whole problem was “up to him” and he did his work entirely unaided.

At one point, Taylor calls for the “the accurate study of the motives of men”, presaging the breakthroughs in behavioral economics to come almost 100 years later.  He also cautions against blindly copying the mechanisms of scientific management without it’s underlying philosophy of cooperation and improvement:

The history of the development of scientific, management up to date, however, calls for a word of warning. The mechanism of management must not be mistaken for its essence, or underlying philosophy. Precisely the same mechanism will in one case produce disastrous results and in another the most beneficent. The same mechanism which will produce the finest results when made to serve the underlying principles of scientific management, will lead to failure and disaster if accompanied by the wrong spirit in those who are using it. Hundreds of people have already mistaken the mechanism of this system for its essence.

[The philosophy is..] First. The development of a true science. Second. The scientific selection of the workman. Third. His scientific education and development. Fourth. Intimate friendly cooperation between the management and the men.

When, however the elements of this mechanism, such as time study, functional foremanship etc., are used without being accompanied by the true philosophy of management, the results are in many cases disastrous. And, unfortunately, even when men who are thoroughly in sympathy with the principles of scientific management undertake to change too rapidly from the old type to the new, without heeding the warnings of those who have had years of experience in making this change, they frequently meet with serious troubles, and sometimes with strikes, followed by failure.

Done right, the system works for management, labor, and the whole people:

After all, however, facts are in many cases more convincing than opinions or theories, and it is a significant fact that those workmen who have come under this system during the past thirty years have invariably been satisfied with the increase in pay, which they have received, while their employers have been equally pleased with their increase in dividends. The writer is one of those who believes that more and more will the third party (the whole people), as it becomes acquainted with the true facts, insist that justice shall be done to all three parties. It will demand the largest efficiency from both employers and employees. It will no longer tolerate the type of employer who has his eye on dividends alone, who refuses to do his full share of the work and who merely cracks his whip over the heads of his workmen and attempts to drive them into harder work for low pay. No more will it tolerate tyranny on the part of labor which demands one increase after another in pay and shorter hours while at the same time it becomes less instead of more efficient.

Taylor, a bit modestly, sums it all up:

Scientific management does not necessarily involve any great invention, nor the discovery of new or startling facts. It does, however, involve a certain combination of elements which have not existed in the past, namely, old knowledge so collected, analyzed, grouped, and classified into laws and rules that it constitutes a science; accompanied by a complete change in the mental attitude of the working men as well as of those on the side of the management, toward each other, and toward their respective duties and responsibilities. Also, a new division of the duties between the two sides and intimate, friendly cooperation to an extent that is impossible under the philosophy of the old management. And even all of this in many cases could not exist without the help of mechanisms which have been gradually developed.

It is no single element, but rather this whole combination, that constitutes scientific management, which may be summarized as:   Science, not rule of thumb.   Harmony, not discord.   Cooperation, not individualism.   Maximum output, in place of restricted output.   The development of each man to his greatest efficiency and prosperity.

The writer wishes to again state that: “The time is fast going by for the great personal or individual achievement of any one man standing alone and without the help of those around him. And the time is coming when all great things will be done by that type of cooperation in which each man performs the function for which he is best suited, each man preserves his own individuality and is supreme in his particular function, and each man at the same time loses none of his originality and proper personal initiative, and yet is controlled by and must work harmoniously with many other men.”

 

Sounds a lot like the empowered knowledge worker of the 21st century, actually!  All in all, Taylor was a lot more modern and more truly progressive than we give him credit for today.  I recommend reading his book for yourself.

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This 100-Year-Old To-Do List Hack Still Works Like A Charm

From fastcompany.com, the story of a simple to do list strategy from 1918, effective enough that it motivated Charles Schwab (at the time president of Bethlehem Steel) to reward an efficiency consultant named Ivy Lee $25,000 ($400k today) for improving the productivity of his executives:

The “Ivy Lee Method” is stupidly simple, and that’s partly why it’s so effective:

  1. At the end of each workday, write down the six most important things you need to accomplish tomorrow. Do not write down more than six tasks.
  2. Prioritize those six items in order of their true importance.
  3. When you arrive tomorrow, concentrate only on the first task. Work until the first task is finished before moving on to the second task.
  4. Approach the rest of your list in the same fashion. At the end of the day, move any unfinished items to a new list of six tasks for the following day.
  5. Repeat this process every working day.

As James Clear points out, the real lessons are (1) use a method simple enough to actually work, (2) force yourself to make tough decisions, and (3) remove the friction of starting.

It’s worth reading the whole article.

Oh, and here’s another take on to-do lists from James Clear that’s worth reading:  Warren Buffet’s 25-5 prioritization method.

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If a Driverless Car Goes Bad, We May Never Know Why

Will Knight comments on how the recent Tesla autopilot crash highlights that  the increasing complexity of modern AI systems potentially outstrips our ability to comprehend them:

Tesla hasn’t disclosed precisely how Autopilot works. But machine learning techniques are increasingly used to train automotive systems, especially to recognize visual information. MobileEye, an Israeli company that supplies technology to Tesla and other automakers, offers software that uses deep learning to recognize vehicles, lane markings, road signs, and other objects in video footage.

Machine learning can provide an easier way to program computers to do things that are incredibly difficult to code by hand. For example, a deep learning neural network can be trained to recognize dogs in photographs or video footage with remarkable accuracy provided it sees enough examples. The flip side is that it can be more complicated to understand how these systems work.

Fortunately, the industry is already starting to respond:

As these algorithms become more common, regulators will need to consider how they should be evaluated. Carmakers are aware that increasingly complex and automated cars may be difficult for regulators to probe. Toyota is funding a research project at MIT that will explore ways for automated vehicles to explain their actions after the fact. The Japanese automaker is funding a number of such research projects related to challenges with self-driving cars.

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New data and commentary on clinical research productivity

From BIO (a biotech trade organization), new data shows that over all trials, the 2006-2015 clinical development success rate was only 9.6% for phase I through approval.  Some disease areas have had better luck than others, but overall the report is a very sobering reminder that clinical research is really, really, hard.

From John Ioannidis, a recent essay:  “Why most clinical research is not useful.”   Ioannidis has long been critical of research reproducibility and has advocated for reform.  From the summary:

  • Many of the features that make clinical research useful can be identified, including those relating to problem base, context placement, information gain, pragmatism, patient centeredness, value for money, feasibility, and transparency.
  • Many studies, even in the major general medical journals, do not satisfy these features, and very few studies satisfy most or all of them. Most clinical research therefore fails to be useful not because of its findings but because of its design.

Perhaps current practices actually make clinical research harder than it needs to be…

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The Economy is not a car, and fiscal stimulus is not a gas pedal

Great observations from Arnold Kling, promoting his new ebook, Specialization and Trade: A Re-introduction to Economics.

I don’t buy into everything Arnold writes, but I do agree that there are problems with the paradigm of macroeconomists treating the economy like a homogenous GDP factory driven by an engine that you rev up with more government spending.  Such an approach ignores specialization and patterns of trade which don’t necessarily respond significantly or rapidly to increases in government spending.  “Specialization is subtle, deep and highly dependent on context.”  There’s a lot more complexity and non-intuitive feedback loops in a modern economy compared to 1930 and it’s not clear how useful Keynesian stimulus is today.

Construction projects take too long to get started, and automated factories can ramp up production too easily (without hiring) to meet the increased demand from policies that stimulate consumer spending, weakening the link between increased spending and increased wages.  Real changes in the economy take years to unfold as new pattens of trade need to be identified and developed.  Another short term factor in the globalized world is how increased spending in one country may simply lead to higher purchases of imports (for the U.S. think consumer electronics, toys, clothes, etc.).  A big chunk of your own government stimulus spending therefore goes toward stimulating another country’s economy (e.g. China).

Arnold’s new book is a different take on macro economics, and it’s much more optimistic than this bit of Keynesianism criticism.  In fact, he argues the complexity and productivity that arise from specialization and patterns of trade are at the heart of why modern economies are so successful.

 

 

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The knowledge economy is a myth. We don’t need more universities to feed it | Andre Spicer

Interesting take on the somewhat overhyped knowledge economy.  It’s a pretty accurate assesment in terms of the types of jobs we have in the economy (even in the 21st century) — but it neglects that fact that knowledge management and data analytics are today embedded in everything.

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A fleet of trucks just drove themselves across Europe

TransEUTrucks

About a dozen trucks from major manufacturers like Volvo and Daimler just completed a week of largely autonomous driving across Europe, the first such major exercise on the continent.

The trucks set off from their bases in three European countries and completed their journeys in Rotterdam in the Netherlands today (Apr. 6). One set of trucks, made by the Volkswagen subsidiary Scania, traveled more than 2,000 km and crossed four borders to get there.

The trucks were taking part in the European Truck Platooning Challenge, organized by the Dutch government as one of the big events for its 2016 presidency of the European Union. While self-driving cars from Google or Ford get most of the credit for capturing the public imagination, commercial uses for autonomous or nearly autonomous vehicles, like tractors from John Deere, have been quietly putting the concept to work in a business setting.

Read the whole article at Quartz.

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SpaceX sticks the landing

Dragon9landing1 Dragon9landing2

SpaceX Dragon 9 booster lands safely on an autonomous floating platform, after launching a payload into space.

Potentially a 10-fold reduction versus current launch costs.  Game.  Changer.

Video at: https://youtu.be/sh8V0COrrzE?t=2129

And Blue Origin isn’t far behind.

Update: The payload was the inflatable Bigalow space capsule, scheduled to be deployed on the International Space Station for two years of testing.  Another potential game changer.

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Florence Nightingale was a data scientist

800px-Florence_Nightingale_three_quarter_length

Everyone knows Florence Nightingale as a dedicated and courageous caregiver, the founder of modern nursing.  But she was also quite a good statistician.    In 1850’s, while she served at the British military hospitals in Turkey, she instituted rigorous data collection and analysis for medical records.  She collected new types of data, filling notebooks with tables and graphs.  In fact, she popularized a kind of infographic, the “coxcomb” chart (essentially polar area plots).  Because of her data analysis, she was able to demonstrate seasonal trends in mortality and illustrate the large fraction of preventable deaths caused by disease — supporting the idea that poor sanitary conditions were the main cause of hospital deaths.  In fact, in 1859, Florence Nightingale was elected the first female member of the Royal Statistical Society.

1280px-Nightingale-mortality

 

 

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Liam – Apple’s Robotic System for Recycling iPhones

One of the more interesting topics this week at Apple’s product event was the introduction of Liam, a robotic system for disassembly of iPhones:

Liam

Click here for a cool YouTube movie.

When an iPhone is finally discarded, Liam detects, disassembles, and separate parts for recycling. Cobalt and lithium are recovered from the battery, gold and copper from the camera, platinum and silver from the main logic board, etc.  Check out apple/recycling for more information.

Makes you wonder how far automated assembly of iPhones has progressed…

Update:  Mashable has a detailed article about Liam.  The full system is about as big as a medium-sized warehouse, has 29 different arms, and can process around 11 million iPhone 6S devices a year.  Apple is continuing to fund significant R&D in automated recycling — apparently controlled disassembly makes it much easier to recycle the materials compared to conventional “shred-and-separate” methods.

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