Management Article

John Young’s picture

By: John Young

During the course of helping organizations and teams develop more effective ways of working, I have found that many of the obstacles to delivering value quickly to customers originate from mental models and assumptions that have been internalized. These mental models and assumptions largely exist and operate outside of our awareness. Listening and asking questions can help drive these concepts to the surface.

Listening and asking questions helps me create the partnerships needed to realize more effective ways of working and ultimately help companies serve their customers better and faster. I have found that open-ended questions, when asked with sincere curiosity, spur deeper thinking. This is true for people on both sides of the question—the questioner and the person to whom the question is posed.

Deborah Blumberg’s picture

By: Deborah Blumberg

In the summer of 2014, Aruna Ranganathan was doing postdoctoral research at a garment factory in Bangalore, India, when she noticed that some worker stations—but not all—were equipped with radio-frequency identification (RFID) technology, a tool used to quantify workers’ output.

Ranganathan, now an associate professor of organizational behavior at Stanford Graduate School of Business, wondered how the technology impacted workers’ productivity, a topic that’s received little attention.

So she spent the next several months embedded in the plant, then analyzed multiple years of the factory’s data to find out. Ultimately, she discovered that when companies quantify simple tasks, productivity goes up. Quantifying complex work, however, has the opposite effect: It drives productivity down.

What’s behind this phenomenon? When workers completing simple tasks have their work quantified, they’re more likely to turn the experience into a personal game, a concept known as “auto-gamification.” They compete against themselves to increase efficiency, even when there’s no reward for doing so and no punishment if they don’t.

Eric Stoop’s picture

By: Eric Stoop

Data can transform manufacturing. It’s also a term that continues to prompt discussions within the industry. People have been saying it for years now, and there is plenty of empirical evidence: Data are the way forward in business generally and manufacturing in particular.

But right now, when people talk about data, they often mean either data analytics or automation using artificial intelligence (AI), a technology that is ‘fed’ with data. Often, these discussions focus on marketing and the customer experience, or on cutting business costs by automating specific processes.

All of these things are important, and many of them can be useful to manufacturing businesses, but they don’t entirely represent the potential of data in manufacturing.

What’s more, amidst talk of crunching numbers and automation, it has become too easy to lose track of the human element. But most plants still rely heavily on human behavior, and on processes undertaken by people. If these aren’t done correctly, the business will become inefficient at best, and catastrophically dysfunctional or dangerous at worst.

Multiple Authors
By: Claire Harbour, Antoine Tirard

In 2005, Fast Company published the now famous article, “Why We Hate HR.” Echoing a popular workplace belief, the authors asked why HR was broken and how it could be fixed. Human resources has evolved since then, with some corporations starting to think differently about the “people function.”

One hallmark of this thinking is that HR should be led by someone with strategy and operations experience. As a result, an increasing number of companies have appointed chief human resources officers (CHROs) from business functions. Yet, the debate remains open whether this novel practice is wise. As experts in career and talent management, we set out to shed light on this question by meeting business leaders who switched to the top HR role.

Engineering wellness and engagement at Flipkart

Where Krishna grew up, in Southern India, the most esteemed careers were engineering, medicine, and chartered accountancy. Six months into a degree in engineering, Krishna dropped out when he realized he hated it, a rare move in his community. Instead, he pursued the loftier discipline of pure mathematics.

NordVPN Teams’s picture

By: NordVPN Teams

The FBI reported earlier this year that complaints of cyber attacks received by its cyber division had risen to almost 4,000 a day—a 400-percent increase over pre-coronavirus numbers. In one four-month period (January to April), 907,000 spam messages, 737 incidents related to malware, and 48,000 malicious URLs—all related to Covid-19—were also detected by one of INTERPOL’s private-sector partners.

Hardware-reliant, legacy, and even hybrid network infrastructures have suffered terribly from a lack of quick-fix solutions. These solutions are necessary to facilitate the exponential increase in remote “offices” that require adequate protection.

“One of the things that’s changed is that corporations no longer have control over the infrastructure their employees use for work,” says Juta Gurinaviciute, chief technology officer at NordVPN Teams.

Although no network is immune to attacks, a stable and efficient network security system is essential for protecting data.

Merilee Kern’s picture

By: Merilee Kern

As Covid-19 rages on, warning sirens have sounded of late amid a flurry of headlines surrounding ultraviolet C (UVC) light device-safety issues. Rightfully so, as the current pandemic has ushered in a veritable wild west of UVC gadget deployments with subpar consumer safeguards, instructions, or guidance.

So important are the concerns amid this rapidly proliferating product sphere, that the FDA recently issued a consumer advisory regarding UVC light technology that’s applicable for industrial, business, travel, and residential use. Although the FDA says that “UVC radiation has been shown to destroy the outer protein coating of the SARS-Coronavirus,” it explains that the current SARS-CoV-2 virus is not exactly the same virus mutation. The FDA does, however, concede that “UVC radiation may also be effective in inactivating the SARS-CoV-2 virus, which is the virus that causes the Coronavirus Disease 2019 (Covid-19).”

Ayman Jawhar’s picture

By: Ayman Jawhar

As a business leader, you probably think similarly to McKinsey about what makes a great product manager (PM): a perfect combination of skills like business acumen, market orientation, and technical skill as well as soft ones... the usual suspects.

Unfortunately (or fortunately, depending on your position), just as our management thinking is becoming outdated and requires reform, we also need to update our view of this ultimate management role.

Dawn Bailey’s picture

By: Dawn Bailey

I recently listened to a Ted Talk by Simon Sinek, author of the book Start With Why: How Great Leaders Inspire Everyone to Take Action (Portfolio, the Penguin Group, 2009), and it caused me to reflect on some key questions in and related to the Baldrige Excellence Framework, as well as leadership in general.

Eric Weisbrod’s picture

By: Eric Weisbrod

The idea of digital transformation can be scary. The growth of technology is outpacing a comfortable pace of adoption for many manufacturers. But remaining content with the status quo often means being left behind. Digital transformation has become an imperative to give manufacturing organizations the flexibility and agility required to overcome business disruptions and adapt to rapidly changing and demanding global markets.

Digital transformation of quality management is a process that depends on something you already have: quality data. Your quality management system is key to optimizing all your quality operations, including supplier and materials management, production processes, quality checks, packaging, and shipping.

InfinityQS calls this holistic approach “manufacturing optimization.” It starts with improving the way you use data to answer the strategic, big-picture questions that truly matter to your business.

Limits of the status quo

The barriers to transformation are often a result of operational and resource challenges that typically boil down to one thing: everyone’s plate is already full. Whether managing and maintaining servers and IT projects, or running day-to-day production, no one has the time to take on new transformation projects.

Steve Wise’s picture

By: Steve Wise

The importance of data analysis in manufacturing operations can’t be overstated. Over the years, manufacturers have used statistical process control (SPC) methods and tools to study historical data and reveal differences between comparable items: shifts, products, machines, processes, plants, lot codes, and more.

The foundational benefit of statistical methods is predicting future behavior from historical data. That’s why control charts, box-and-whisker plots, Pareto charts, and the like are so valuable: They indicate that if processes are not changed, then performance (positive or negative) will continue as it is.

Control charts are brilliant tools for assessing performance over time, and their related “control limits” are predictions of normal future behavior. The problem is that many SPC software products struggle to move beyond just data collection to offer truly insightful data analysis.

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