Bill Kalmar’s picture

By: Bill Kalmar

For years, when I was the director of the Michigan Quality Council during Gov. John Engler’s administration, we reviewed businesses across the state and looked for world-class service. What we found was that meeting and exceeding the expectations of customers was of paramount importance. And companies who practiced that stood head and shoulders above other companies.

Having said that, I marvel at the ads that herald “Customers are No. 1,” or “We treat you like family.” In my mind, aren’t these just givens? I would hope that as customers we’re the No. 1 when we come into a store or order something online. That seems rather logical. So why do companies have to advertise it? Just wondering.

Then there’s the comment about us being treated like family. Now let me be a bit critical here. I guess it would be nice to be treated like family if we all had the typical Ozzie and Harriet family. But I suspect that isn’t always the case. Thus, are we sure we want to be treated like our family? Again, just wondering.

Donald J. Wheeler’s picture

By: Donald J. Wheeler

Acceptance sampling uses the observed properties of a sample drawn from a lot or batch to make a decision about whether to accept or reject that lot or batch. Although the textbooks are full of complex descriptions of various acceptance sampling plans, there are some very important aspects of acceptance sampling that are not included in the textbooks.

Extrapolation

In the interest of simplicity, the product that has been measured will be referred to as the “sample,” while the product that hasn’t been measured will be referred to as the “lot.” Every time we attempt to use a sample to characterize the quality of a lot, we will be making an extrapolation from the product that has been measured to the product that hasn’t been measured.

Bruce Hamilton’s picture

By: Bruce Hamilton

The level of excitement was high in our machine shop as we drew closer to our goal of less than 9-minute changeovers on the BNC lathe. (See Part One of this story for how we got there.) Setup improvements had so far reduced changeover time to 20 minutes, cutting the economic order quantity from weeks to days of stock on hand.

Our pull system now more closely resembled a supermarket with several containers on hand for each of the 66 parts in our pilot. After decades of viewing setups as a problem and inventory as a protection from stockouts, this new process was still confounding for many persons. But it was working, which was most apparent to the operators on the BNC and their internal customers in assembly:
• No more expedites and angry demands
• No more breaking down a setup in mid run to run a hot part
• No more juggling jobs between machines
• No more fiddling with tools and programs to get a good part

Jonathan Gilpin’s picture

By: Jonathan Gilpin

The world of procurement is often tricky. It involves choosing one appropriate candidate, ultimately benefiting them while rejecting and disadvantaging others.

That said, it isn’t just the businesses picked that will profit from winning the contracts; it’s also their supply chain, their local economy, fellow businesses, families, and so on.

This is particularly true when we take into consideration just how lucrative and valuable some contracts can be. With this in mind, you can see why the role of the buyer in the procurement process can be so complex.

One aspect of sourcing that received considerable attention during the pandemic was that of locality. The idea of “shop local” was thrust into the limelight as businesses and consumers not only struggled to get deliveries from farther afield but also chose to support businesses closer to home in a community-spirit approach.

With responsible consumerism taking center stage in the modern world, shop local is gaining even more traction. However, that is not to suggest that global sourcing doesn’t provide equal opportunity and benefit. In this article we’re going to consider the differences between local and global sourcing before going on to detail some occasions on which local should be the preferred option.

Gleb Tsipursky’s picture

By: Gleb Tsipursky

The pandemic has forced organizations to recognize that they need to address proximity bias to adapt their work culture to the hybrid and remote future of work. Proximity bias is the unconscious perception that those with close proximity to their team or leader are better employees. These employees tend to get preferential treatment to those who are not.

Remote work has exacerbated the problem. Employees may have different office schedules: Some essential employees might be there full-time, others will be there one to three days a week, and some may be fully remote. The danger of resentment building up between “haves” and “have nots” around schedule flexibility calls for a work culture that addresses such issues. Leaders who want to seize a competitive advantage in the future of work should use research-based best practices to create a culture of “excellence from anywhere” to address these concerns. This cultural best practice is based on guidance I provided for leaders at 17 major organizations to develop and implement effective strategies for a work culture suitable for the future of work.

Bruce Hamilton’s picture

By: Bruce Hamilton

We had been working with the Toyota Production System Support Center (TSSC) for two years to build a model line in our assembly department. As we moved from small batch production to one-by-one, the results had been astounding: Customer lead time reduced from two weeks to one day, crew size cut in half, and overtime reduced from 40 hours per week to 10. Hundreds of small changes made by assemblers to the assembly process had made this possible. Everybody every day, GBMP’s slogan, was born from that experience.

Now it was time to move upstream from assembly to our internal supplier, machining, a resource that despite efforts to improve was still overproducing and delivering late. Setups on our CNC lathes averaged 90 minutes despite an improvement project supported by graduate engineers from a notable Massachusetts engineering school.

Kenny Tsang’s picture

By: Kenny Tsang

The e-commerce industry is forecast to see substantial growth in 2022. Retail e-commerce sales in 2021 totaled $4.9 trillion, and may reach $5.42 trillion this year. Exponential growth in the sector has given rise to an ecosystem of millions of third-party sellers on sites such as Amazon that make up more than 55 percent of all sales, all vying to source and sell as quickly and cost-efficiently as possible.

However, traditional banks have failed to service sellers’ needs. Moreover, the added pressures of shipping bottlenecks and warehouse disruption have contributed to a harsh logistics environment for vendors, so much so that Lake Superior State University chose the term “supply chain” for its Top 10 “Banished Words List” in 2021.

Online vendors must be prepared for an increasingly unpredictable year ahead, in which anticipating the challenges of tomorrow will define success. These are some of the innovations sellers can use in 2022.

Scott A. Hindle’s picture

By: Scott A. Hindle

In 2010, new to the world of statistical process control (SPC), I was intrigued by Don Wheeler’s statement that “No data have meaning apart from their context” (from his book, Understanding Variation—The Key to Managing Chaos, SPC Press, 2000, available on Amazon). For a while, I didn’t really get the importance of this message.

Now, some years later, and working mainly to support manufacturing processes, data analysis for me begins in context and ends in context. Moreover, communicating the results to others is driven by context, and the simpler this is done the better. To see an example, read on.

Time order of production

All, or practically all, manufacturing data have an essential piece of context, which is a time stamp. It’s the time stamp that allows you to put your data in a logical sequence—the time order of production—when you start the analysis.

Donald J. Wheeler’s picture

By: Donald J. Wheeler

Last month we looked at analyzing observational data. Here we will consider experimental data and discover a weakness in the way they are obtained that can contribute to the problem of nonreproducible results.

Background

The discipline of statistics grew up in agricultural and biomedical research. There a major problem for researchers is the fact that their basic experimental units are fields, livestock, and people. Since these units all differ, any researcher has to find a way to keep these differences from masking the effects of any treatments being studied. And the classic solution for this problem is some form of randomization.

Chris Hubble’s picture

By: Chris Hubble

There’s a misconception that the most successful business leaders are born with their leadership credentials imprinted in their DNA. Surely because they’re more successful than their peers, it stands to reason they’re extremely sharp or even smarter than their non-CEO cohorts. But in truth, what sets successful business leaders apart is their innate curiosity and sponge-like ability to draw out insights about their business from all kinds of places.

In November 2021 Bastion Db5 teamed up with Vox Media and surveyed more than 400 U.S. small-business owners (SBOs) and decision makers. Many insights into the workings of SBOs’ innate curiosity were gleaned.

When asked about their management style and what it takes to succeed, the No. 1 characteristic small-business owners cite is a “commitment to lifelong learning.” They almost unanimously share a drive to seek and absorb new information. In general terms, this means someone who is highly curious and somewhat obsessive about gathering data—and always learning from it.

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