The core of the article (See full version for the extra commentary):
A toothpaste factory had a problem. They sometimes shipped empty toothpaste boxes without the tube inside. This challenged their perceived quality with the buyers and distributors. Understanding how important the relationship with them was, the CEO of the company assembled his top people. They decided to hire an external engineering company to solve their empty boxes problem. The project followed the usual process: budget and project sponsor allocated, RFP, and third-parties selected. Six months (and $8 million) later they had a fantastic solution – on time, on budget, and high quality. Everyone in the project was pleased.
They solved the problem by using a high-tech precision scale that would sound a bell and flash lights whenever a toothpaste box weighed less than it should. The line would stop, someone would walk over, remove the defective box, and then press another button to re-start the line. As a result of the new package monitoring process, no empty boxes were being shipped out of the factory.
With no more customer complaints, the CEO felt the $8 million was well spent. He then reviewed the line statistics report and discovered the number of empty boxes picked up by the scale in the first week was consistent with projections, however, the next three weeks were zero! The estimated rate should have been at least a dozen boxes a day. He had the engineers check the equipment; they verified the report as accurate.
Puzzled, the CEO traveled down to the factory, viewed the part of the line where the precision scale was installed, and observed just ahead of the new $8 million dollar solution sat a $20 desk fan blowing the empty boxes off the belt and into a bin. He asked the line supervisor what that was about.
“Oh, that,” the supervisor replied, “Bert, the kid from maintenance, put it there because he was tired of walking over to restart the line every time the bell rang.”
It took $8 million to take a problem that was only visible to the sales department -- empty boxes are hurting our image! -- and make it visible to the stakeholders who had the right insight to actually fix it -- the people on the production line.
That is it cost $8 million to move the pain point to the "right" spot.
Even if this story was true, neither solution is good as they still have wasted, empty boxes. The solution would be to figure out how the empty ones are produced and fix that (root cause analysis) The scale would be part of the solution to verify the fix (continuous integration)
> The solution would be to figure out how the empty ones are produced and fix that (root cause analysis)
Maybe.. maybe not. One possible outcome:
Likely problem: speed of production. Solution: slow down production. Analysis: the loss on sometimes empty boxes is much lower than the loss on a slower production line. Conclusion: the fan is the correct solution.
That's because the story is bogus. Weighing products for QA (to make sure there wasn't underfilling) is extremely common. It's called "checkweighing" and you can buy COTS scales to do exactly that.
Yeah, a lot of the lesson seems to (unintentionally) be "don't outsource small things". Even completely ignoring the fan solution, the CEO could have assigned one existing engineering employee to work on it and gotten an $8k system with a non-precision scale.
This bit of apocrypha is older than me, and never improves. At this point it’s almost part of a the almost religious ideology around some Libertarians.
Yeah lots of variants of it too. I've heard it told in terms of nationalities too "In nation X they built a multi-million dollar sensor, in nation Y they just used a fan." In that format it's similar to the NASA space pens.
The real space pen story is so much more interesting too! Of course the last thing you want in a spacecraft is graphite dust literally “pen testing” every system.
With regards to the parking space article reference. In the long run with self driving cars we can reduce the overall number of parked cars through greater vehicle utilization. Instead of them being parked for long periods of their life, they can join fleets (think the Tesla fleet idea) and service many people in one day.
But that is a "next" step, unrelated to cars being driverless, sharing fleets (normally human driven) do exist, and they do actually work for some uses, but still they are either on the road or in a parking.
Let's play it another way, let's assume that no self-driving car exists but that all humans (with the exception of those making a living as a driver) can afford a third party human driven car for all their movements/commuting.
This could be either an enormous fleet of Taxis (or Limousines) or Ubers, or each household having one or more cars and a corresponding number of employed drivers.
Still, if the way the city/economy works there is a need that 100,000 people move from point A to point B in a time range between 7 and 9 in the morning and that the same number of people go back from B to A between 17 and 19, the same amount of roads (and the space occupied by them) will be needed.
Even when there are the same number of cars, we can still improve space efficiency. Cars can be much more tightly packed in a parking lot if you only need to be able to retrieve any car, instead of this specific car.
Only if you can negate the need for a personal vehicle, which self-driving cars aren't close to doing.
Self-driving cars do nothing about the fact I need somewhere to put my gym bag during the work day or my gym and work bags while I go out in the evening. Or that I might need a carseat for a child. Or that I might like to keep an umbrella and change of clothes in my car. Or....
Any benefit to not having the static car is quickly mitigated by the inefficiency of storage shuffling for even a moderate amount of things.
There is another objection. People who use a car to go to work need that car at the same time. Playing lottery on whether I will be allocated a car or not to get to work this morning isn't an option. That's why farmers usually own their hardware. They could rent except that they all need it the same days.
It will free up the streets nevertheless. The reason you park your car nearby is so that you can walk to it. But if the car can go park itself and come back 10-15min from where you live in some big car park, you would probably as happy as if you had to walk 5-10min yourself.
Plus ownership isn't fully rational. Otherwise people wouldn't bury themselves into debt to own their house, pushing property prices up. Instead you would have cheap property you can rent.
As someone who is cautious about the prospect of Amazon and other large retailers completely dominating the e-commerce space, this ruling worries me a bit.
As things stand, the Google Shopping results allow smaller, independent e-commerce stores to reach the top of Google's search results.
Take this functionality away, and we risk the top search results being a combination of Amazon + other large retailers for the majority of e-commerce related searches.
Monica Anderson had an interesting post on this a while back. Essentially relating the Boston Dynamics sale to a clash between the deep learning approach at Google, and BD's lack of. Here's what she said:
Google wants to sell (now sold) Boston Dynamics, a robotics company they acquired in Dec 2013. People are speculating why, and some claim this is because of a "culture clash".
I no longer work for Google so what follows is pure speculation.
Boston Dynamics (BD) are very successful pioneers. But their algorithms are not based on Deep Learning (DL) principles. And Google is leading the world in Deep Learning and can apply it to anything they want, including robotics. DL based algorithms do not provide a complete robotics solution today but there is wide agreement that this is the best path forward for the field. Why is this important? The difference is robots that can walk vs robots that can dance ballet. The goal is "graceful locomotion" which will be an order of magnitude more adaptive, more energy efficient, and faster than the current generation of robots.
I am suspecting this is part of the culture clash. Imagine a meeting where Google comes to BD staff and says "we want you to toss out all the software you have written, retrain your engineering staff to use DL and other Holistic methods, and create a new generation of robots capable of learning rather than being programmed"... then I can see BD staff saying "Ahem. That'll take a few years". And Google might then say "Forget that".
Changing one person's mindset and stance from Reductionist to Holistic methods is a multi-month to multi-year effort; I have tried that and have rarely succeeded. Now imagine a company's worth of engineers that need to do that switch. It might be much better, cheaper, and faster to start a company from scratch and hire a more receptive crowd of engineers. And seed them with Googlers that already drank the Holistic Kool-Aid.
The hardware solutions BD created is know-how and intellectual property that Google currently owns since they own BD. When they sell off BD they could exclude the key patents or sell them as non-exclusive licenses. Which means Google could start a competing robotics company, use the BD patents and hardware know-how, and add a Deep Learning based software stack to run that hardware much faster than they could turn BD around.
