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Comment by neverartful | Hacker News Reader

My first job out of college (undergraduate) was working for a small consulting firm that did a lot of work in this area for the petrochemical industry and their suppliers. The owner had a PhD in decision sciences (statistics) and he did consulting work on statistical process control (SPC). This was my first exposure to this field and was so fascinated by it that after working there for a year, I quit my job so that I could go back to school full time and pursue a Masters degree in this area, but with focus on management information systems (MIS). Ironically, my work after graduate school has never touched on SPC or quality control.

It's unfortunate that Deming (and many others) never really got the attention that their methods deserved.

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GE and other companies tried to implement Demings approach. They called it Six Sigma. Those that used Deming's concepts were successful. Yet too many misunderstood the idea of SPC and used in areas that was not meant for quality control. For instance trying to use SPC in the managerial process itself.

Gawd, Six Sigma was an ever-present factor in all our work when I was at IBM in the late 80's to early 90's. I have complete respect for Deming, but when anything becomes "religion" it gets damaged or mis-used a lot, as you say.

In our software group, we were constantly battling with management that wanted to start to look at software development as a factory-like process, and to apply factory QA processes.

Cargo culting one’s way to attempt obtaining results seems like the default approach of leadership unable to really adapt the proper lessons from other organizations and apply them to their own. If I as a person look up to a world class bodybuilder as a scrawny weakling, the solution to achieve that goal isn’t to just eat like a bodybuilder but to train like one and that usually means dropping other activities like playing a bunch of video games (not that it’s mutually exclusive - see Henry Cavill). But we as humans do the same thing all the time (how many people think of rich people in terms of consumption or some sets of personalities from popular media rather than to look at the data fully). However, there is a lot to learn and enjoy in the process, and companies that do well learn to have clear goals and processes that seem genuine and that employees can connect with. When people stop feeling this connection, they simply stop doing the habits at the individual (not working out, relapsing, etc) or disengage in organizations (burn out, disillusionment, etc)

Six Sigma is to the field of Statistical Process Control what PowerPoint templates are to the field of graphic design. The biggest problem with Six Sigma is many of the people who roll it out understand how to follow the instructions in a Six Sigma book, but don’t understand the underlying statistics well enough to recognize when the templates will fail or need to be changed.

Amen. The principles behind Six Sigma are solid. They're just a repackaging of Deming's SPC principles after all. However, too often it devolves into a box ticking exercise. That being said, in my experience just educating everyone in your organization on the basic principles (e.g. what Six Sigma would call yellow belt) tends to be quite valuable. Even without a lot of statistics, teaching people to first properly define a problem statement and emphasizing finding root causes before taking action tends to lead to better decision making.

Six Sigma is a travesty of statistical process control. For one thing, only rarely does a process attain six sigma reliability. Six Sigma is about cult-like in-group/out-group dynamics for the Six Sigma Black Belts.

I’m reading a book called Working Backwards about Amazon. There is a chapter on metrics and it says to use the DMAIC process, which comes from six sigma, for developing reporting and metrics. The authors provide an example about applying this to e-commerce at Amazon. They don’t seem to use control charts, but they are still trying to examine the metrics for common vs special cause of variation.

If you can relate inputs to the outputs of a process and you can get reliable data on the inputs, then you can use SPC in most areas. The costs to do so many not be worth it, however.

Which managerial processes do you think this doesn’t apply to?

Amazon, the Supply Chain part of it at least, has one of the best metrics systems I have ever seen in my life. Every metric is measuring something meaningful, each one is measuring a crucial process interface, each one is based on a simple calculation. Also most are measured in DPMO, looking at defects instead of things meeting expectations. The funny thing is, during my time metrics where presented, across all levels, in blunt, no chart, tables in a auto created PDF. And yet this is still light years ahead of everything else I saw, including fancy control towers.

Twenty-five or thirty years ago, one hear a great deal about total quality management (TQM).

Yep, it was back in the early 1990s.

I'm hoping that will change. I'm a big fan of Deming and Drucker, they've both got really insightful thoughts on business.

My goal is to work more of Deming into knowledge work (software) to develop meaningful improvement into the process and product while leveraging Drucker for better effectiveness of the individual.

Until recently, there hasn’t been enough data to apply statistical process control in a lot of fields. Chemical process companies (like Kodak used to be) have used SPC. “Web scale” companies commonly talk about running experiments now. Lots of people talk about A/B testing, which is an extremely simplistic example of SPC. I’ve been anticipating more advanced SPC tools to replace A/B testing for years, but am not aware of any. Maybe I should have created one.

Now I wonder if Machine Learning might pass up SPC as the primary method by which people identify and control key process variables.

Actually, it does not take a huge amount of data to make use of statistical process control. In fact, it's so little that someone should be able to do it with paper, pencil, and calculator.

The statistical technique I think that's better able to displace A/B testing is design of experiments (DOE). This approach also does not require that much data to implement. There was an excellent youtube series on it where the presenter used popping popcorn for his experiments. I can't seem to find it now.

I've observed DOE in use. It's a statistical method at its core, and as such potentially suffers from the replication crisis.

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