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> The environment they were working in was pretty remarkable. Yes. The heyday of big corporate research labs was roughly from WWII until the mid-1980s. There

> The environment they were working in was pretty remarkable. Yes. The heyday of big corporate research labs was roughly from WWII until the mid-1980s. There was a big open space for pushing things that seemed possible all the way through to commercial products. From synthetic rubber to transistors, the basics had been done but there was plenty of development ahead. There were lots of things which were possible but hadn't been done yet. Sometimes it was too early, and only a non cost effective demo resulted. Sometimes there was a big payoff. Overall, corporate R&D had a positive payoff in that era. I was lucky enough to visit or deal with many of the big corporate labs of that era. They were quite varied in outlook. The Bell Labs people were telco guys; their approach to networking fit the Bell System centralized model. The PARC people got personal computing and local area networking working, but somehow were obsessed with discrete-event simulation as an application. They didn't foresee how it would all be used. The SRI International people were too into abstraction, and kind of hand-wavey. I once tried using string substitution to remove "virtual" and "abstract" from one of their documents, and it got better. The IBM guys had the coolest location, a glass box on a hill overlooking a park. IBM happened to exit the disk drive business the day I visited. That place had invented the disk drive. Their day was over. The Ford Scientific Research Lab people were theoreticians who were also car guys. The back side of the building had a long, long row of garage spaces with tools and lifts, and everybody had a car to which they were doing something. Their in-car fiber-optic network was forty years too early. Common factors? - Steady funding. Not many ups and downs. - A profitable parent company with a stable business model. - Good support. Unlike academia, where grad students tried to do machining, badly, the corporate labs had competent people to build stuff. - Not too rigorous cost accounting. I was once told by a manager of a major lab that "your accounting system is too good", because it kept people on defined tasks. - A focus on good demos. Production was the responsibility of others. R&D did not ship products.

WillAdams 2y ago
An interesting knock-on affect of the importance of rubber was the Chemical Rubber Corporation being the publisher of a de facto handbook, the _CRC Handbook of Chemistry and Physics_: https://www.goodreads.com/work/editions/937703-crc-handbook-of-chemistry-and-physics-88th-edition-crc-handbook-of-che https://www.goodreads.com/work/editions/937703-crc-handbook-... which I have found quite useful for its overview of trigonometry and so forth when machining.
throwoutway 2y ago
Could you expand on the "Not too rigorous cost accounting"
- dartos 2y ago
  Not OP, but my take: Goodheart’s law states: “ When a measure becomes a target, it ceases to be a good measure” If your accounting is too fine grained, there becomes an inescapable draw to point at a metric and declare that a goal. Once that happens, engineering tasks can be come extremely well defined to the point of acting like tunnel vision. Instead of finding improvements or innovations generally, the focus is entirely on moving a specific metric. You see this issue in highly metric driven orgs as well.

WillAdams 2y ago

An interesting knock-on affect of the importance of rubber was the Chemical Rubber Corporation being the publisher of a de facto handbook, the _CRC Handbook of Chemistry and Physics_: https://www.goodreads.com/work/editions/937703-crc-handbook-of-chemistry-and-physics-88th-edition-crc-handbook-of-che https://www.goodreads.com/work/editions/937703-crc-handbook-... which I have found quite useful for its overview of trigonometry and so forth when machining.

throwoutway 2y ago

Could you expand on the "Not too rigorous cost accounting"

dartos 2y ago
Not OP, but my take: Goodheart’s law states: “ When a measure becomes a target, it ceases to be a good measure” If your accounting is too fine grained, there becomes an inescapable draw to point at a metric and declare that a goal. Once that happens, engineering tasks can be come extremely well defined to the point of acting like tunnel vision. Instead of finding improvements or innovations generally, the focus is entirely on moving a specific metric. You see this issue in highly metric driven orgs as well.