
Baptist Hill Church, Mystic, CT
On a personal note, I have to say I’m loving my new 5D Mark II. As I said before, the color depth seems to me to be outstanding (which helps in B and W conversions). More importantly, the dynamic range of this camera is clearly better than that of my old 5D. I haven’t yet done any side by side comparisons, but I can say that scenes that used to cause me problems – especially with highlight blowouts – are now much more manageable. For whatever reason, the “Recovery” slider in Lightroom’s RAW converter seems to ”work” in more instances than it did with 5D images. And the 5D was good in terms of dynamic range potential. The Mark II is just better.
Maybe it’s because I just bought a new camera that I’ve noticed all the hoopla over the new Leica M9. As photographic gear frenzies go, this one appears to be right up there in terms of intensity. Even though the darned thing is going to cost around $7000 (U. S.), everybody seems to want one. As all the positive reviews continue to come in, I’m guessing the demand will go up exponentially.
Now, I have to say that I personally have no interest in the M9 or any other Leica camera. I also have to admit that I don’t know much about rangefinders in general. I know a little about how they work, but I’ve never used one. I’ve always been an “SLR” person. But this isn’t about rangefinders versus SLR’s.
What really got my attention yesterday was a post by Michael Reichmann on The Luminous Landscape. In this 18 minute video, Michael Reichmann describes a visit to the Leica factory, including partial descriptions of the manufacturing and testing processes. As someone who has spent the better part of 35 years working in manufacturing and product testing, this video raised a number of red flags in my mind. If I were a wealthy person and thinking I might want one of these new toys, what I saw might well have changed my mind.
Why? Well, the potential problem (and I strongly emphasize the word “potential”) is actually summarized in one of Mr. Reichmann’s statements that introduced the video:
“It’s also clear that demand for the M9 is turning out to be very high, and so it may be some time until the initial feeding frenzy can be satisfied. When you’ve watched my video of what’s involved in final assembly and testing you’ll understand why. No robots, no mass production – just careful and therefore slow hand work and meticulous testing. No wonder Leicas cost what they do.”
It was, in fact, this statement that induced me to watch the video. I watched it not because I had an interest in the camera, but because I was professionally interested in any insight into how Leica produces one of their top – of – the – line products. In particular, I was interested in the implication that both the manufacturing and testing processes were manually intensive. Most people would probably say that that was a good thing, that relying on highly skilled craftsman is better than relying on automated, computer driven processes. When someone advertises that a product is “handmade”, the implication is that it’s going to cost more because the quality will automatically be superior.
Well, the part about costing more is certainly true. But the notion of “superior quality” is a bit of a myth. More often than not, manually intensive processes yield lower quality products.
How do I know this? For any given product or process, I don’t know that product quality will be inferior if it’s a manually intensive operation. It may very well be that the M9 is, in terms of quality and reliability, the best camera in the world. The only way I (or anyone else) could make that judgement would be to study the process close-up. And that, of course, isn’t likely to happen.
But I can say that I’ve studied many such “manually intensive” processes over the years. I can also say that if the process includes manual (or visual) inspection at the end, outgoing product quality is almost always marginal. In some cases, it’s actually flat out unacceptable. As a general rule, people are very bad at visual inspection. To put it more succinctly, we suck at it.
Here’s some “hard” evidence: When people who do visual inspection are given product of known quality (that is, they are fed “pieces” that are either not defective at all or have known defects on them), the average for culling out the defective pieces is about 60%. If the test, for example, involves 100 pieces, and 20 of them have “major” defects, the average inspector will find 12 of them. The remaining 8 defective pieces will pass through the sytem (and potentially to the consumer). In case you haven’t thought of it, there’s also the other side of the coin – some inspectors will “reject” pieces that are not defective. A perfectly good piece, in other words, will be thrown away or sent back for “rework”. And that means more production costs.
In my career, I’ve done dozens of these kinds of tests and they always come out the same. The average is always about 60%. Some people are a little better and many are worse. It’s also true that people tend to be inconsistent. Inspectors are not as effective at the end of their shift as they are at the beginning. They get tired, or start thinking about what they’re going to do when they get out of work, or maybe they don’t feel very well on a particular day. And, by the way, inspectors are usually at the lowest end of the company’s pay scale. I’ve never figured that one out.
The lesson in all of this is simple. Automation trumps “manually intensive” operations every time. When maintained properly, an automated system works faster, never gets tired, and most importantly, never makes mistakes.
Again, I have no idea if any of this affects Leica. I only know what I saw in Michael Reichmann’s video. But what I saw looked an awful lot like processes I have seen up close and personal. So if it were me looking to buy one of these cameras, I’d be nervous. Think about it: What if some of what I’ve alluded to does affect this process? And what if demand does increase significantly? Leica will either have to spend less time on each camera or hire more operators. Either way, the chance of an error (on your camera) goes up.
Any potential M9 buyers out there?