In May 2019, James Beagle and I published an article that contained tables for the analysis of mean moving ranges or ANOMmR (pronounced a-nom-m-r). By request of those using this technique, I have expanded these tables. This article contains these expanded tables and

Shigeo Shingo is one of my heroes in industrial engineering. He had a great mind that thrived on curiosity. Today I am looking at Shingo’s Whys. This is in contrast to Taiichi Ohno’s 5 Whys method.

One of my favorite movies is Stripes.

Stop asking, “Which tool should I use?” and start asking, “How can I work smarter?”

‘We shouldn’t be calling some jobs essential.”

The Covid-19 pandemic is disrupting business across the globe, and supply chains are being stressed to their limits by sudden and drastic increases in online commerce.

I hear this lament from new practitioners to seasoned veterans: Why isn’t our (insert school of workflow management here) transformation working?

Many industrial businesses have heard of the dangers of relying on tribal knowledge. But what exactly does tribal knowledge mean? How does tribal knowledge impact an organization? How do you capture tribal knowledge?

During the last several decades, many forward-thinking manufacturers have adopted factory automation for all that it promises—greater efficiency, consistency, productivity, and cost savings.

There’s a little bit of irony in the title of this article. Why do we have to make sure the customer—and employee—experience is crisis-ready? Well, as John Kennedy said, “The time to repair the roof is when the sun is shining.”