Human proof design is design that prevents people from successful using the item.
It is similar to mistake proofing except instead of prevent mistakes it prevents people from using it.
When you see human proof design you will often see signs to tell people how to use the device that has been human proofed. Common instances of this are hotels that have shower designs so opaque they need instructions on how to use a device most people have no problem using if they are not human proofed.
Human proof design is often created by a subset of designers that care about how something looks more than how it is used.
Most people prefer designs that are beautiful without being human proofed. The Design of Everyday Things is a great book on designing beautifully with customer focus.
A sign your design is human proofed is that a sign or manual is needed for people to use it.
Most human proof design can be identified very simply by having regular people try to use the item. Watch what they do and when they struggle to use it, many problems will be very obvious. You can’t use people in this effort that are significantly different from the normal users.
In several areas I see these failures quite often. Hotel rooms are a common source of problems. The light switches are often very odd and I have to search all over to find out how to turn on or off different lights.
Robert Frost was poking fun at his friend who would obsess over what fork to take in the path as they walked when in reality the choice made no difference.
And “that has made all the difference” is poking fun at self justifications of our actions; congratulating ourselves for doing something not really worthy of accolades.
Still the top three lines do seem like insightful advice. Of course what is really needed is insight into when choosing the road less traveled is wise (or at least a sensible gamble) and when it is less traveled for very good reasons.
I do believe we far too easily slip into habits encouraged by the well worn path most people take. And therefore think balancing that tendency with at least considering the road less traveled more often is wise. But I actually like that when you read the full poem it really isn’t saying that.
Children try a variety of novel ideas and unusual strategies to get the gadget to go. For example, Gopnik says, “If the child sees that a square block and a round block independently turn the music on, then they’ll take a square and take a circle and put them both on the machine together to make it go, even though they never actually saw the experimenters do that.”
And that flexibility may disappear earlier than we think. Gopnik’s lab has also compared toddlers and kindergartners in doing these tests of abstract thinking, and found that the diaper set are actually better at focusing on the relationship between the objects, rather than on the things.
George Box lecture on Statistical Design in Quality Improvement at the Second International Tampere Conference in Statistics, University of Tampere, Finland (1987).
Early on he shows a graph showing the problems with American cars steady over a 10 years period. Then he overlays the results for Japanese cars which show a steady and significant decline of the same period.
Those who didn’t get to see presentations before power point also get a chance to see old school, hand drawn, overhead slides.
He discusses how to improve the pace of improvement. To start with informative events (events we can learn from) have to be brought to the attention of informed observers. Otherwise only when those events happen to catch the attention of the right observer will we capture knowledge we can use to improve. This results in slow improvement.
A control chart is an example of highlighting that something worth studying happened. The chart will indicate when to pay attention. And we can then improve the pace of improvement.
Next we want to encourage directed experimentation. We intentionally induce informative events and pay close attention while doing so in order to learn.
Every process generates information that can be used to improve it.
He emphasis the point that this isn’t about only manufacturing but it true of any process (drafting, invoicing, computer service, checking into a hospital, booking an airline ticket etc.).
He then discussed an example from a class my father taught and where the students all when to a TV plant outside Chicago to visit. The plant had been run by Motorola. It was sold to a Japanese company that found there was a 146% defect rate (which meant most TVs were taken off the line to be fixed at least once and many twice) – this is just the defect rate before then even get off the line. After 5 years the same plant, with the same American workers but a Japanese management system had reduced the defect rate to 2%. Everyone, including managers, were from the USA they were just using quality improvement methods. We may forget now, but one of the many objections managers gave for why quality improvement wouldn’t work in their company was due to their bad workers (it might work in Japan but not here).
He references how Deming’s 14 points will get management to allow quality improvement to be done by the workforce. Because without management support quality improvement processes can’t be used.
With experimentation we are looking to find clues for what to experiment with next. Experimentation is an iterative process. This is very much the mindset of fast iteration and minimal viable product (say minimal viable experimentation as voiced in 1987).
There is great value in creating iterative processes with fast feedback to those attempting to design and improve. Box and Deming (with rapid turns of the PDSA cycle) and others promoted this 20, 30 and 40 years ago and now we get the same ideas tweaked for startups. The lean startup stuff is as closely related to Box’s ideas of experimentation as an iterative process as it is to anything else.
He also provided a bit of history that I was not aware of saying the first application of orthogonal arrays (fractional factorial designs) in industry was by Tippett in 1933. And he then mentioned work by Finney in 1945, Plackett and Burman in 1946 and Rao in 1947.
George E. P. Box died in March 2013. He was a remarkably creative scientist and his celebrated professional career in statistics was always at the interface of science and statistics. George Box, J. Stuart Hunter and Cuthbert Daniel were instrumental in launching Technometrics in 1959, with Stu Hunter as the initial editor. Many of his articles were published in the journal. Therefore we think it is especially fitting that Technometrics should host this on-line collection with some of his most memorable and influential articles.
They also include articles from Journal of the American Statistical Association and Quality Engineering. Taylor & Francis is offering these articles freely in honor of George Box until December 31st, 2014. It is very sad that closed science and engineering journals block access to the great work created by scientists and engineers and most often paid for by government (while working for state government universities and with grants organizations like the National Science Foundation[NSF]). At least they are making a minor exception to provide the public (that should be unlimited access to these works) a limited access to these articles this year. These scientists and engineers dedicated their careers to using knowledge to improve society not to hide knowledge from society.
Some of the excellent articles make available for a short time:
Amazon continues to be innovative not just in technology but with management thinking. Jeff Bezos has rejected the dictates espoused most vociferously by Wall Street mouthpieces and MBAs that encourage short term thinking and financial gimmicks which harm the long term success of companies.
Most CEOs and executives are too fearful or foolish to ignore what they are told they must do because Wall Street demands it. CEO’s and boards often ratchet up the poor management thinking by tying big bonuses to financial measures which are much more easily achieved by gaming the system than by improving the company (so companies get the games there boards encouraged through their financial extrinsic motivation focus).
Amazon does many good things focused on making Amazon a stronger company year after year. These innovative management practices seem to largely be due to the thinking of the strong willed founder and CEO: Jeff Bezos. Jeff was smart enough to see the great things being done at Zappos by Tony Hsieh and bought Zappos.
Jeff Bezos has added his letter to shareholders to Warren Buffett’s (for Berkshire Hathaway) as letters worth reading each year. In the latest Amazon letter he includes many worthwhile ideas including:
Career Choice is a program where we pre-pay 95% of tuition for our employees to take courses for in- demand fields, such as airplane mechanic or nursing, regardless of whether the skills are relevant to a career at Amazon. The goal is to enable choice. We know that for some of our fulfillment center employees, Amazon will be a career. For others, Amazon might be a stepping stone on the way to a job somewhere else – a job that may require new skills. If the right training can make the difference, we want to help.
The second program is called Pay to Quit. It was invented by the clever people at Zappos, and the Amazon fulfillment centers have been iterating on it. Pay to Quit is pretty simple. Once a year, we offer to pay our associates to quit. The first year the offer is made, it’s for $2,000. Then it goes up one thousand dollars a year until it reaches $5,000. The headline on the offer is “Please Don’t Take This Offer.” We hope they don’t take the offer; we want them to stay. Why do we make this offer? The goal is to encourage folks to take a moment and think about what they really want. In the long-run, an employee staying somewhere they don’t want to be isn’t healthy for the employee or the company.
A third inward innovation is our Virtual Contact Center. It’s an idea we started a few years back and have continued to grow with terrific results. Under this program, employees provide customer service support for Amazon and Kindle customers while working from home. This flexibility is ideal for many employees who, perhaps because they have young children or for another reason, either cannot or prefer not to work outside the home.
The first point reinforces Dr. Deming’s words encouraging companies to do exactly that – pay for education even if it wasn’t related to the work the employee was doing or would do for the company. Still quite rare decades after Deming’s advice.
My opinion has long been that football teams are too scared to take an action that is smart but opens the coach to criticism. So instead of attempting to make it on 4th down (if you don’t understand American football, just skip this post) they punt because that is the decision that is accepted as reasonable.
So instead of doing what is wise they do what avoids criticism. Fear drives them to take the less advantageous action. Now I have never looked hard at the numbers, but my impression is that it is well worth the risk to go for it on 4th down often. In a quick search I don’t see a paper by a Harvard professor (this article refers to it also – Fourth down: To punt or to go?) on going for it on 4th down but I found on by a University of California, Berkeley economist (David Romer wrote called “Do Firms Maximize? Evidence from Professional Football.”).
On the 1,604 fourth downs in the sample for which the analysis implies that teams are on average better off kicking, they went for it only nine times. But on the 1,068 fourth downs for which the analysis implies that teams are on average better off going for it, they kicked 959 times.
My guess is that the advantages to going for it on 4th down are greater for high school than college which is greater than the advantage for the pros (but I may be wrong). My guess is this difference is greater the more yardage is needed. Basically my feeling is the variation in high school is very high in high school and decreases with greater skill, experience and preparation. Also the kicking ability (punting and field goals) impacts the choices of going for it on 4th down and that dramatically increases in college. So if I am correct, I think pro coaches should be more aggressive on 4th down, but likely less aggressive than high school coaches should be.
But in any event the data should be explored and strategies should be tested.
In my experience, the way invention, innovation and change happen is [through] team effort. There’s no lone genius who figures it all out and sends down the magic formula. You study, you debate, you brainstorm and the answers start to emerge. It takes time. Nothing happens quickly in this mode. You develop theories and hypotheses, but you don’t know if readers will respond. You do as many experiments as rapidly as possible. ‘Quickly’ in my mind would be years.”
The newspaper business is certainly a tough one today – one that doesn’t seem to have a business model that is working well (for large, national papers). I figured the answer might be that a few (of the caliber of Washington Post, New York Times…) would be owed by foundations and supported largely by a few wealthy people that believed in the value of a strong free press and journalism. Maybe Bezos will find a business model that works. Or maybe he will just run it essentially as a foundation without needing a market return on his investment.
“You are a fool if you do what I say. You are a greater fool if you don’t do as I say. You should think for yourself and come up with better ideas than mine.”
The best examples of Lean in healthcare are examples where leaders and organizations learned, but did not blindly copy. Sami Bahri DDS (the “lean dentist”) read Deming, Shingo, Ohno, etc. and had to figure this out himself, rather than copying some other dentist.
ThedaCare is the first to say “don’t directly copy what we do.”
We can learn from others, run our own experiments to see what works, and keep improving to make it better than even Ohno or Shingo would have imagined.
Occasionally during my career I have been surprised by new insights. One of the things I found remarkable was how quickly I thought up a new explanation for what could have caused a problem when the previously expressed explanation was proven wrong. After awhile I stopped finding it remarkable and found it remarkable how long it took me to figure out that this happened.
I discovered this as I programmed software applications. You constantly have code fail to run as you expect and so get plenty of instances to learn the behavior I described above. While I probably added to my opportunities to learn by being a less than stellar coder I also learned that even stellar coders constantly have to iterate through the process of creating code and seeing if it works, figuring out why it didn’t and trying again.
The remarkable thing is how easily I could come up with an new explanation. Often nearly immediately upon what I expected to work failing to do so. And one of the wonderful things about software code is often you can then make the change in 10 minutes and a few minutes later see if it worked (I am guessing my brain kept puzzling over the ideas involved and was ready with a new idea when I was surprised by failure).
When I struggled a bit to find an initial explanation I found myself thinking, “this has to be it” often because of two self reinforcing factors.
First, I couldn’t think of anything else that would explain it. Sometimes you will think right away of 4 possible issues that could cause this problem. But, when I struggled to find any and then finally came up with an idea it feels like if there was another possibility I should have thought of it while struggling to figure out what I finally settled on.
Second, the idea often seems to explain exactly what happened, and it often feels like “of course it didn’t work, what was I thinking I need to do x.” This often turns out to be true, doing x solves the problem and you move on. But a remarkable percentage of the time, say even just 10%, it doesn’t. And then I would find myself almost immediately thinking, of course I need to do y. Even when 10 seconds ago I was convinced there was no other possibility.