Harry Hertz’s picture

By: Harry Hertz

‘I have been offered a significant increase in salary by another employer and am giving my two-week notice.”

My guess is that this is the most common reason given when employees quit their current job. But is salary the real reason most employees quit? I have always suspected and believed that, given a fair salary, people do not quit their jobs for money. So why do they leave?

I was recently drawn to explore this topic a little more deeply after reading an article about IBM Watson’s latest feat. A new, proprietary IBM AI algorithm can predict with 95-percent accuracy which workers are about to quit their jobs. The algorithm has been successfully deployed to predict IBM employees who are a flight risk and then to propose actions to managers to engage and retain those employees. Exploring a little further the topic of employees quitting, I discovered a recent Harvard Business Review blog by Jon Christiansen. Through looking at 15 years of data, Christiansen identified eight reasons he believes employees quit.

Miriam Boudreaux’s picture

By: Miriam Boudreaux

If you are wondering whether your organization could benefit from formal root cause analysis (RCA) and corrective action training, read on to see if any of these issues are present in your day-to-day operations. RCA and corrective actions are some of the most useful tools for continual improvement.

Here’s why you should include them among your company’s (and all employees’) tool set.

1. High number of NCRs in your company

It’s true that the number of nonconformance reports (NCRs) will depend on the volume of operations a specific company has. Therefore, the “number” of NCRs is a relative figure. However, if you know you have a high number of NCRs, the issue may be that you are not performing effective RCA and corrective action.

Aaron Fox’s picture

By: Aaron Fox

If industrial manufacturing had a buzzword of the decade, it might be “Industry 4.0.” The concept is inescapable, yet it can be hard to define, especially for small and medium-sized manufacturers (SMMs). After all, SMMs’ capabilities, needs, and budgets look very different from the large companies that often drive the latest innovations and trends. However, Industry 4.0 is so pervasive that many smaller manufacturers know more about the technologies than they might think. Below, we define Industry 4.0, then explore ways that SMMs can and do implement it already.

What is Industry 4.0?

To date, there have been four major technological trends during the past few hundred years that have revolutionized industry and manufacturing. The first was the combination of mechanization with both steam and waterpower. The second joined mass production and electricity. The third was the rise of electronic and information technology (IT) systems, and with them automation.

Penelope B. Prime’s picture

By: Penelope B. Prime

The United States and China have reportedly reached a so-called phase one deal in their ongoing trade war.

While few details have been disclosed, the agreement principally seems to involve the United States calling off a new round of tariffs that were slated to take effect on Dec. 15, 2019, and removing others already in place in exchange for more Chinese purchases of U.S. farm products.

Good news, right? The end of the trade war is nigh? Don’t get your hopes up.

Although business leaders in both countries will be temporarily relieved, the underlying tensions between them will not end easily.

As an economist who closely studies the U.S. relationship with China, I believe there are fundamental issues that won’t be resolved anytime soon.

Doing it in phases

Tariffs and other trade issues have received most of the attention during the trade war, but the more fundamental—and difficult—challenges are with lax intellectual property protection and China’s industrial policy.

Nathan Furr’s picture

By: Nathan Furr

Few companies and CEOs have attracted as much praise, derision, skepticism, and enthusiasm as Telsa Motors and its founder Elon Musk. Having interviewed Musk and the Tesla leadership as part of my research, one of the questions I’m asked most frequently is: How can you make sense of Tesla’s wild strategies? The latest example is the move to create a “gigafactory” for car batteries just outside Berlin.

Tesla’s many critics and observers, whose reactions range from short-selling to star worship, are part of the challenge. Many ask the wrong questions, such as why Tesla isn’t making any money—a question appropriate for a mature business but not a growth one. Although all businesses must be sustainable in the long run, Tesla is like most rapid-growth companies that eat up more cash flow than they produce while in the early growth phase.

Corey Brown’s picture

By: Corey Brown

Many manufacturers see reducing changeover time as a golden opportunity to improve operational efficiency and reduce waste. For good reason, a simple reduction in changeover time can increase output, reduce inventory, reduce work in progress, and improve responsiveness to customer demand.

Yet, the most effective method for standardizing and reducing changeover time is often overlooked—standardized work instructions.

The benefits of reducing changeover time

Say, for example, that your current changeover takes an hour. Assuming you’re running five to seven days per week, that’s nearly one day a week spent running changeovers. At a minimum you could be wasting 32 days on changeover time per year.

Imagine what you could do if you got even half of that time back?

Quality Digest’s default image

By: Quality Digest

As usual with Quality Digest’s diverse audience, this year’s top stories covered a wide range of topics applicable to quality professionals. From hardware to software, from standards to risk management, from China trade to FDA regulations. It’s always fun to see what readers gravitate to, and this year was no different.

Below are five articles that garnered a lot of interest from our readers. As you can see, the topics are quite diverse.

Improve Risk Management and Quality Across the Value Chain by Increasing Visibility
by Kelly Kuchinski

Anat Amit-Eyal’s picture

By: Anat Amit-Eyal

Eric, a 40-something married father of three, runs a successful startup. Given his demanding career, he and his wife decided she would be a stay-at-home mum. Eric believed the attention he devoted to his family was adequate, and that he had fully harmonized his work as CEO and life as a family man.

On a recent family trip, Eric continued working as much as he could, as he always did. While taking a conference call, he dropped his phone and, without hesitation, leapt to catch it at the risk of hurting himself. Seeing this, his 13-year-old son blurted out, “I don’t know if you would have jumped after me like that.” Only then did Eric realize that his son didn't think he prioritized their family. Eric had been oblivious that his family felt neglected; he had been unaware or was in denial.

Christy Lotz’s picture

By: Christy Lotz

After being an ergonomist for almost 15 years, I can honestly say I have never been more excited about the future of this field. When I first began working at Humantech and would do wall-to-wall assessments every week, I didn’t think I would last.

The pen and paper-based methods we used were often a little too simple to uncover all the risks that our professional experience taught us were present. I also had terrible handwriting and would often come back to the office after a data collection and not understand my own notes. Now, 15 years later, cutting-edge technologies make things more efficient. I wish I was still going onsite to do data collections because the process is so much better now. Here are three ways that technology has vastly improved the field of ergonomics.

Learning

Training has evolved over time, along with access to technology, and we have a better understanding of how adults learn best. While traditional training focused on telling, research is showing, and actions are proving, that we need to shift from instructor-led to self-paced and action-oriented workshops.

NIST’s picture

By: NIST

A new research effort at the National Institute of Standards and Technology (NIST) aims to address a pervasive issue in our data-driven society: a lack of fairness that sometimes turns up in the answers we get from information retrieval software.

A measurably “fair search” would not always return the exact same list of answers to a repeated, identical query. Instead, the software would consider the relative relevance of the answers each time the search runs—thereby allowing different, potentially interesting answers to appear higher in the list at times.

Software of this type is everywhere, from popular search engines to less-known algorithms that help specialists comb through databases. This software usually incorporates forms of artificial intelligence that help it learn to make better decisions over time. But it bases these decisions on the data it receives, and if those data are biased in some way, the software will learn to make decisions that reflect that bias, too. These decisions can have real-world consequences—for instance, influencing which music artists a streaming service suggests, and whether you get recommended for a job interview.

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