Kate Zabriskie’s picture

By: Kate Zabriskie

Despite our best efforts, it’s not as easy as it looks to get the job training equation right.

“I learned so much during orientation. It’s too bad I won’t use most of it for six months. I took some notes, but I’m sure I won’t remember half of what they told me to do.”

“I’m overwhelmed. I learned a new piece of equipment today. The person showing me what to do knew everything. The problem I had was the deep dives. He spent so much time on troubleshooting techniques. It was just too much for my first day.”

“I can follow the steps, but I have no idea why I’m doing what I’m doing. I sort of feel like a trained monkey. I hope nothing goes wrong because I will have no clue how to fix it if something does.”

These are just a few comments you might hear after someone's first week on the job.

We train too early, we train too much, or we make a host of other errors. Although some of us learn from our mistakes, many of us practice a cycle of rinse and repeat as we make the same blunders year after year. It doesn’t have to be this way. With some careful planning and follow-through, you can avoid problems many people will encounter again and again.

Strategy 1: Keep training relevant and immediately applicable

Jeff Dewar’s picture

By: Jeff Dewar

This is the second installment of a five-part series. 

Some weeks ago,  I attended ASQ’s 2022 World Conference on Quality and Improvement (WCQI) with Quality Digest’s editor in chief, Dirk Dusharme, in Anaheim, California. It was the first in-person conference since Covid hit the world, and attendance was just over 1,000, about a third of what had been the norm. 

ASQ made its leadership available for wide-ranging video interviews covering everything from the future of the quality profession to the society’s new legal structure. Quality Digest appreciates their efforts to help us provide valuable reporting to our readers. 

In all, we conducted five interviews with:
• ASQ’s CEO Ann Jordan
• ASQ’s board of directors
• ASQE’s (ASQ Excellence) CEO Jim Templin
• ASQE’s board of directors
• Both CEOs together, talking about their “connected journey”

Sara Harrison’s picture

By: Sara Harrison

Have you ever had a really bad boss? Think Alec Baldwin as Blake in Glengarry Glen Ross, who announces that “coffee’s for closers only” and then threatens the salesmen he supervises with a number of choice terms not suitable to repeat here. Few leaders use quite so much verbal abuse, profanity, and fear to motivate employees. But plenty of leaders use similar, if less extreme, tactics. Deborah Gruenfeld would like to know why so many people put up with them.

Gruenfeld, a professor of organizational behavior at Stanford Graduate School of Business and an expert on the psychology of power, is interested in “dominant actors” like Blake: leaders who assert power by being the most competitive, most aggressive, and most controlling person in the room.

“There is this tendency for people to allow others to assert dominance without resisting,” she says. “People who behave this way tend to be very successful even though people really don’t like or respect them very much.”

Donald J. Wheeler’s picture

By: Donald J. Wheeler

Many people have been taught that capability indexes only apply to “normally distributed data.” This article will consider the various components of this idea to shed some light on what has, all too often, been based on superstition.

Capability indexes are statistics

Capability and performance indexes are arithmetic functions of the data. They are no different from an average or a range, just slightly more complex. The four basic indexes are the following:

The capability ratio, Cp, is an index number that compares the [space available within the specifications] with the [generic space required for any predictable process].

The performance ratio, Pp, is another index number that compares the [space available within specifications] with the [estimated space used by process in the past].

Del Williams’s picture

By: Del Williams

In industry, gas-fired boilers have been the standard for decades to produce steam and heat process water. However, not all boilers are created equal in terms of safety. By definition, combustion-fueled boilers can emit harmful vapors, leak gas, and even cause explosions and fires.

In a recent example, a natural gas boiler was cited as the cause of a massive explosion and fire at a food processing plant in eastern Oregon that injured six and caused severe damage to the facility’s main building. Given the risks, many processors are turning to a new generation of electric boilers to dramatically reduce these hazards.

“With gas-burning boilers, any gas leak can increase the risk of an explosion wherever there are fuel lines, fumes, flames, or storage tanks,” says Robert Presser, vice president of Acme Engineering Products. “So, gas units must be continually monitored or periodically inspected.” Presser notes that state and municipal safety guidelines vary depending on boiler type and the expected frequency of inspection.

Acme Engineering is a North American manufacturer of boilers for large industrial and commercial applications. The company is an ISO 9001:2015-certified manufacturer of environmental controls and systems with integrated mechanical, electrical, and electronic capabilities.

Multiple Authors
By: Phanish Puranam, Ruchika Mehra

How should humans collaborate with artificial intelligence? This is a question of increasing urgency as AI becomes pervasive in the workplace. From screening job applications and chatting with customers to assessing investment portfolios, algorithms are working alongside us in myriad roles and organizational setups. But whether this collaboration is designed in ways that lead to trust and satisfaction—for us humans at least—is another story.

Respecting, rather than ignoring, human concerns about working with AI is not only consistent with humanistic values, as we noted in an earlier article, but also good for business. That’s why we ran the “Bionic Readiness Survey” to investigate what configurations of collaboration with AI algorithms humans are more or less likely to trust.

Katie Rapp’s picture

By: Katie Rapp

The Covid-19 pandemic brought to light a stark reality about current supply chains. As Nissan Motor’s chief operating officer Ashwani Gupta points out, “The just-in-time model is designed for supply-chain efficiencies and economies of scale. The repercussions of an unprecedented crisis like Covid highlight the fragility of our supply chain model.” The U.S. supply chain has so far struggled to adapt and restock pandemic-depleted inventories. There are industrywide shortages and a lag in how many manufacturers are responding.

Alexander Gelfand’s picture

By: Alexander Gelfand

For years, researchers have known that our physical and mental well-being improves when we freely give our time to help others. And when we do so through company-sponsored programs, performance-related outcomes like job satisfaction and commitment to work also get a boost.

But there has been little agreement among experts on why this should be the case.

Recently, however, professors Jeffrey Pfeffer and Sara Singer of the Stanford Graduate School of Business analyzed survey data from hundreds of businesses in the United Kingdom to tease out the mechanisms through which volunteering improves both employee health and organizational outcomes. (The data were collected through Britain’s Healthiest Workplace and includes more than 53,000 employee responses.)

David L. Chandler’s picture

By: David L. Chandler

Virtually all wind turbines, which produce more than 5 percent of the world’s electricity, are controlled as if they were individual, freestanding units. In fact, the vast majority are part of larger wind farm installations involving dozens or even hundreds of turbines whose wakes can affect each other.

Now, engineers at MIT and elsewhere have found that, with no need for any new investment in equipment, the energy output of such wind farm installations can be increased by modeling the wind flow of the entire collection of turbines and optimizing the control of individual units accordingly.

Illustration shows the concept of collective wind-farm flow control. Existing utility-scale wind turbines are operated to maximize only their own individual power production, generating turbulent wakes (shown in purple), which reduce the power production of downwind turbines. The new, collective wind-farm control system deflects wind turbine wakes to reduce this effect (shown in orange). This system increases power production in a three-turbine array in India by 32 percent. (Image: Victor Leshyk)

Lauren Dunford’s picture

By: Lauren Dunford

Industry 4.0 has been a hot topic for years now, for good reason: 86 percent of manufacturing C-suites say digital transformation is a priority, and about 91 percent of industrial companies are investing in digital factories. Yet Industry 4.0 has also become a buzzword in many ways, as so many companies’ attempts to execute have fallen short.

Syndicate content