Every upward trending line, every falling cost, every additional efficiency that can be squeezed out of a set of inputs is the result of the deliberate efforts of thousands of workers, engineers, factory managers, and line supervisors to redesign products, rearrange factories, and test and explore new methods. —Brian Potter, The Origins of Efficiency (304)
Economists focus on overall productivity gains. Instead of considering where they came from, we simply say the words “technology changes.”
Brian Potter’s recent book, The Origins of Efficiency, takes a bottom-up approach to improving productivity. Mr. Potter discusses the various ways companies can lower production costs. His many historical examples help explain and clarify the analysis.
Potter views production in terms of converting inputs into outputs. Process efficiency depends on five factors: production rate. input cost. Size of buffer (work in progress). Output variability.
For example, in a bakery, a transformation method is a set of instructions for making bread. Production rate is the number of loaves per hour. Input costs are the costs of flour, yeast, sugar, salt, energy, labor, etc. Work-in-progress consists of bread that has been formed but not yet placed in the oven. Leaving bread for different lengths of time will result in inconsistent results.
“Through theoretical research and trial and error, enough problems are solved to produce a dominant design that attracts many modification enthusiasts who continue to refine the technique.”
Potter points out that new change methods tend to follow an S-curve of improvement. New technologies may seem promising, but they initially perform poorly and progress slowly because they have many problems that make them costly or impractical. Through theoretical research and trial and error, enough problems are solved and a dominant design emerges that attracts many modification enthusiasts who continue to improve the technology. After that, progress accelerates rapidly. Ultimately, there are fewer opportunities to derive improvements from technology and productivity levels off.
“The S-curve pattern means that new technologies often initially perform significantly worse than established technologies along the most important performance criteria, even if the theoretical performance ceiling is much higher.” (50)
Mechanization can significantly reduce costs. Mr. Potter gives the example of a glass light bulb for an electric light that is blown out by a machine rather than a human. However, he points out that humans have a better ability to adapt to different conditions and work with softer, more changeable materials.
“Successful mechanization has therefore historically required reducing or limiting the amount of information processing that must be performed and the environmental variations that must be taken into account” (70).
One interesting source of efficiency is the removal of unnecessary steps in the production process. For example, raising a conveyor belt on an assembly line eliminates the need for workers to bend or lift objects.
Modern writers often use fear quotes to describe “scientific management” and “Taylorism,” giving the impression that the study of time and motion is a means of oppression aimed at individual workers. But we learned from Potter that time and motion studies are used to discover ways to improve manufacturing processes. Increasing the height of conveyor belts is an example of scientific control that is a win-win for operators and manufacturers.
As I read The Origins of Efficiency, I realized there were many ways its analysis could be applied to the latest developments in artificial intelligence. For example, the release of ChatGPT attracted capital and inventors to similar models using neural networks and “Transformer” algorithms. We are now in the steep part of the S-curve of improvement.
Ordinary machines lack flexibility and adaptability, but artificial intelligence could help machines overcome this limitation. Self-driving cars are one example.
The field of robotics could be dramatically improved through the use of AI. Currently, a nurse or phlebotomist is required to start an IV in a hospitalized patient. Perhaps using AI, robots will be able to handle this task. Today’s construction workers rely on nuanced knowledge and experience that goes beyond the capabilities of ordinary machines. But perhaps in the future, AI-enabled robots will be able to perform more tasks on construction sites.
We believe that AI has the potential to eliminate unnecessary steps in the delivery of goods and services. For example, businesses don’t need to design complex menus on their websites. Instead, users can rely on an AI interface to find the information they need.
But the key lesson from Potter’s book is that developing promising technology applications takes time.
“Solving one problem with early technology tends to uncover many more problems, which can result in significant time and effort being expended without noticeable performance gains” (40).
For more information on these topics, see:
As of this writing, early adopters of AI may be feeling this pain.
The Origins of Efficiency is a book that defies simple summary. It is enriched with many useful concepts and carefully selected examples, and is best understood when taken as a whole.
footnote
[1]Brian Potter (2025), “The Origins of Efficiency.” striped press.
*Arnold Kling holds a Ph.D. in economics from Massachusetts Institute of Technology. He is the author of several books. Invisible wealth: The hidden story of how markets work. Unchecked and unbalanced: How the contradiction between knowledge and power triggered a financial crisis and threatened democracy. Specialization and trade: A re-introduction to economics. I contributed to EconLog from January 2003 to August 2012.
Read more of what Arnold Kling has read. For more book reviews and articles by Arnold Kling, check out our archives.
As an Amazon Associate, Econlib earns from qualifying purchases.
Source link
