This Week in Demand: Analytics News Roundup

     

Check out our roundup of important writing from across the web on technology and analytics in retail, consumer goods and manufacturing.

Voice Commerce

Adriana Lee makes a strong argument for the continuousness of voice assistants, meaning fashion needs to reckon with them.

WWD: Adriana Lee – Talk to Me: The Rise of Voice Commerce 

“Although some reports contend that only 2 percent of people with Alexa gadgets use them to buy products — a figure that Amazon strongly denies — CTA predicts that one in four online adults in the U.S. will likely shop by voice next year. That sets up what could be an important early shift in consumer behavior.” 

Future Proofing Supply Chains

Mark Ellwood reveals what actions some brands are taking to ensure they have enough high-quality raw materials to sate the looming boom in demand.

The New York Times: Mark Ellwood – Luxury Brands Buy Supply Chains to Ensure Meeting Demand

“’Hiccup-free supply isn’t the only reason such brands are keen to acquire their sources, said Franck Delpal, an expert in vertical integration and a professor at IFM, a fashion school in Paris. Owning a farm adds a welcome, artisanlike aura to any brand, and consistency of quality is easier; there are financial upsides, too. “If you control the greater part of your supply chain, you get margins at every step, and at the end of the day, it creates big business.’”

Demystifying AI

Kalev Leetaru claims that although the general public sees today’s AI technologies as nothing short of magic, in actuality, today’s AI algorithms are nothing more than traditional machine learning algorithms.

Forbes: Kalev Leetaru – Today's Deep Learning "AI" Is Machine Learning Not Magic 

“This lack of higher order reasoning is the reason that AI algorithms are so easily fooled. Make a few subtle changes to an image and you can easily make an image of a dog appear as an image of a bus or a stop sign be returned as background noise. It is the reason that algorithms are so easily skewed by biased input data, blindly “learning” all of the human biases and faults that we turned to AI to rid ourselves of. Though, at least in AI form it is possible to quantitatively document and correct those biases if we are creative enough to see them.”

The Manufacturing Skills Gap

Erin Winick warns that unless manufacturers start exploring new strategies, they won’t be able to find enough people qualified to work in their specialized factories. 

MIT Technology Review: Erin Winick – Here’s what a manufacturing skills gap of more than 2 million people will look like

“There will be 4.6 million new manufacturing jobs in the US to fill between 2018 and 2028, according to a new report out yesterday from Deloitte.

Over half of the newly created jobs—2.4 million—are predicted to go empty.

The report attributes this to three main things:

  • An increase in the skill level required for manufacturing jobs as they make more use of automation
  • A loss of many experienced workers as baby boomers leave the workforce
  • A negative perception of the manufacturing industry by both students and their parents.”

 Capturing Loyalty Program Lovers

Tania Anderson writes that brands should design and promote their programs in a way that appeals to loyalty lovers’ personal values and preferences.

Digital Commerce 360: Tania Anderson What it takes to capture today's loyalty program lovers

“In general, loyalty program lovers’ shopping behavior favors an in-store environment, but that doesn’t mean they’re not reachable in digital channels. Loyalty lovers’ top shopping behaviors include using coupons and visiting warehouse and club stores. But they’re also highly likely to check prices via mobile when in store and to shop online and pick up in stores. These digital touchpoints represent an opportunity for even online-only brands to connect with these individuals by appealing to the personal values that drive their loyalty behaviors.”

 

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