Quality Digest

Meet Humphrey. Humphrey is a gray squirrel that a friend of mine rescued as an abandoned baby squirrel. For weeks, my friend and his family nursed the young creature by hand. While Humphrey was growing, he became very friendly with the family members, often perching on their shoulders and snuggling in their arms for naps.

Humphrey was permitted the run of the house and had a basket for his sleeping quarters, which he often used at night. As time passed, he grew strong enough to survive on his own, and the family released him back into the wild to enjoy the life of a healthy gray squirrel. Having grown fond of his human family, Humphrey built a nest in a tree just outside their back door and still hops on laps and shoulders while the family sits together outside.

The ‘tail’ of two cities

So how does a story of a rescued squirrel connect with the timely topic of cybersecurity? There is a rampant and significant vulnerability that exists for homeowners and enterprise businesses alike, and in many ways correlates with Humphrey’s story.

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.

October happens to be (among other things) Breast Cancer Awareness Month, Dental Hygiene Month, National Bullying Prevention Month, and my personal favorite, National Pizza Month. Plus, it’s Halloween! But I digress. We’re here to talk about cybersecurity.

Every manufacturer should hold cybersecurity awareness training for all its staff at least once a year. Many people are spooked by the mere mention of the words “cybersecurity” and “training,” so October could be an appropriate time for it. Your training should, at a minimum, cover relevant company policies such as your IT security, information security, and physical security.

Over the years many of us have taken this type of training and learned to dread it: Training where someone gives the exact same cybersecurity speech they gave last year, and then hands out a paper for you to sign saying you were there. A real snooze fest. This kind of training does its job as far as meeting the bare minimum but has little impact on actually molding employee behavior.

To establish a successful quality control program, you need good instrumentation, robust software, and trained users. But even with everything in place, there are some common pitfalls to watch for when using a spectrophotometer to analyze color quality.

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.