Management

Relationship to mechanization, automation, and offshoring

Scientific management evolved in an era when mechanization and automation existed but had hardly gotten started, historically speaking, and were still embryonic. Two important corollaries flow from this fact: (1) The ideas and methods of scientific management were exactly what was needed to be added to the American system of manufacturing to extend the transformation from craft work (with humans as the only possible agents) to mechanization and automation; but also, (2) Taylor himself could not have known this, and his goals did not include the extensive removal of humans from the production process. During his lifetime, the very idea would have seemed like science fiction, because not only did the technological bridge to such a world not yet look plausible, but most people had not even considered that it could happen. Before digital computers existed, such ideas were not just outlandish but also mostly unheard of. Nevertheless, Taylor (unbeknownst to himself) was laying the groundwork for automation and offshoring, because he was analyzing processes into discrete, unambiguous pieces, which is exactly what computers and unskilled people need to follow algorithms designed by others and to make valid decisions within their execution. It is often said that computers are "smart" in terms of mathematic computation ability, but "dumb" because they must be told exactly what to calculate, when, and how, and (in the absence of any successful AI) they can never understand why. With historical hindsight it is possible to see that Taylor was essentially inventing something like the highest-level programming for industrial process control and numerical control in the absence of any machines that could carry it out. But Taylor could not see it that way at the time; in his wor d, it was humans that would be the agents to execute the program. However, one of the common threads between his world and ours is that the agents of execution need not be "smart" to execute their tasks. In the case of computers, they are not able (yet) to be "smart" (in that sense of the word); in the case of human workers under scientific management, they were often able but were not allowed. Once the time-and-motion men had completed their studies of a particular task, the workers had very little opportunity for further thinking, experimenting, or suggestion-making. They were expected (and forced) to "play dumb" most of the time (which, unsurprisingly to students of human nature, people tend to revolt against). In between craft production (with skilled workers) and full automation lies a natural middle ground of an engineered system of extensive mechanization and partial automation mixed with semiskilled and unskilled workers in carefully designed algorithmic workflows. Building and improving such systems requires knowledge transfer, which may seem simple on the surface but requires substantial engineering to succeed. Although Taylor's original inspiration for scientific management was simply to replace inferior work methods with smarter ones, the same process engineering that he pioneered also tends to build the skill into the equipment and processes, removing most need for skill in the workers. This engineering was the essence not only of scientific management but also of most industrial engineering since then. It is also the essence of (successful instances of) offshoring. The common theme in all these cases is that businesses engineer their way out of their need for large concentrations of skilled workers, and the high-wage environments that sustain them.