Smartspeakers and wireless ear buds are sending the audio industry “horizontal”
MUSIC lovers do not typically go to the opera to buy a speaker. But at the Palais Garnier in Paris they now can: Devialet, a local maker of high-end speakers, on November 29th opened a store in the 19th-century music venue to sell its most sophisticated product, called Phantom. Looking like a dinosaur egg, this supercomputer for sound (priced at $3,000) is considered one of the best wireless speakers available. It also comes with a dedicated streaming service for live performances, including some at the Palais Garnier.
This Phantom at the opera is the latest example of how digital technology is transforming speakers, headsets and other audio devices. Once mostly tethered to hi-fi systems, they are now wireless, increasingly intelligent and capable of supporting other services. As a result, the industry’s economics are changing.
Only a few years ago the audio industry was highly fragmented, says Simon Bryant of Futuresource, a market-research firm. Hundreds of brands offered their wares, both premium and basic, often with identical components. As with other device businesses, the industry was a “vertical” one: if speakers used any software at all, it was specific to the product.
All this started to change with the advent of smartphones, which made music more portable by connecting music-streaming services such as Spotify with wireless speakers. Smartphones have also given a boost to headphones, which are becoming ever more versatile, with features now ranging from cancelling out ambient noise to real-time translation.
These new possibilities have proved hugely popular: the global market for audio devices has rocketed in recent years (see chart). According to Futuresource, only about 200,000 wireless speakers were sold in 2009; this year the number is expected to be 70m. Headphones have been on a similar tear.
Smartspeakers, which were pioneered in 2015 by Amazon with the Echo, will be even more disruptive. Nearly 24m of these devices, essentially voice-controlled remote controls for everything from music to lights, will be sold worldwide in 2017, estimates Strategy Analytics, another market researcher—a number it expects to quadruple by 2022. Once households have one, they buy more to spread them throughout their homes (apparently nearly a tenth now live in bathrooms).
Smartspeakers are pushing the audio-device industry to become “horizontal”. The voice that emanates from Amazon’s Echo or Google’s Home is not just a digital assistant, but a “platform” for all kinds of services, of which most are developed by other firms. Alexa, as Amazon’s version is called, already boasts more than 25,000 “skills”, as the firm calls such services. These range from ordering goods and finding a mobile phone to turning up the heating and (early next year) asking The Economistfor the latest on any given topic. Similarly, wireless ear buds, such as Apple’s AirPods and The Dash by Bragi, a startup, may become so clever that more and more people will leave them in all day, for instance to monitor their health or for constant access to a digital assistant.
Conventional speaker firms are trying to catch up. In September at IFA, a trade show in Berlin, booths of various makers were adorned with logos of Amazon or Google, signalling that they already have or will integrate a digital assistant in their products. But if the history of the smartphone is any guide, such platforms will turn the hardware into a commodity, with most of the profits going to the providers of software and services. Having sold 75% of all smartspeakers (at low prices that are thought to be close to the cost of making them), Amazon is now the world’s biggest speaker brand. Incumbents will also have to contend with Apple, despite the delay of its smartspeaker until early next year.
The dominance of a few platforms is not a forgone conclusion, says Mr Bryant of Futuresource. More specialised ones are likely to thrive, too—like Microsoft’s Cortana, which is good at understanding business jargon. But some audio firms feel the need to branch out. Sonos, which pioneered wireless speakers a decade ago, now wants to become an über-platform, integrating all voice assistants and streaming services, so consumers who like Sonos speakers have a choice. Harman, which in March was bought by Samsung Electronics, has similar plans for entertainment systems in cars.
And then there are companies which do not build their own speakers, but offer technology to enhance other products. Dolby and DTS, for instance, are busy creating software for what is called “immersive audio”. Combining several speakers, Dolby’s Atmos technology—first introduced in cinemas, but now available for home use—already “places” sounds in space. The next step is separate personal sound zones for each listener in a room, in effect creating invisible speakers.
So why does Devialet, which last year got €100m ($106m) in fresh capital, think it can succeed by selling expensive high-end speakers? The answer is that it wants to be a platform, too. The speakers are mostly meant to demonstrate its technology, in the hope that other companies will integrate it into their products. The first example, launched last month, is a soundbar (a slim loudspeaker) it has developed together with Sky, a broadcaster. “If you see yourself just as an audio company,” says Quentin Sannié, Devialet’s chief executive, “your days are numbered.”
The Mall of America’s terrazzo floors, glazed white like doughnut frosting, ribbon out in every direction, creating a vast mirror maze of consumerism with 520 glassy storefronts. Shoppers, who have escaped an endlessly gray Bloomington, Minnesota, sky on a Monday morning in October, drift through the largest mall in the United States like tourists at an Atlantic City buffet. A couple holding hands strolls into a Zales while buttery perfumes emanate from an Auntie Anne’s next door. Kids and some willing parents fling around on the SpongeBob SquarePants Rock Bottom Plunge roller coaster, one of 27 rides at the Nickelodeon-branded amusement park on-site. Distant echoes of saxophone Muzak clash with both elevator whirs and bubbly pop songs. Somewhere in this otherworldly commercial expanse are five Lids stores and four Sunglass Huts.
When the mall opened, in 1992, it represented the pinnacle of retail convenience and a mecca for young people to gather and spend. But the $650 million megamall was always “vaguely unreal . . . exuding the ambience of a monstrous hallucination,” as novelist David Guterson described it in a 1993 Harper’s article, calling it “monolithic and imposing.” Two years later, Jeff Bezos launched his online book marketplace, which quickly grew into a new type of Everything Store, one that fundamentally redefined the shopping experience and led some to argue that commercial centers like the Mall of America would become gaudy relics of an antiquated era.
Now, Wall Street analysts say, the retail apocalypse is upon us. Amazon dominates e-commerce and has gobbled up 5% of total U.S. retail sales. Some expect that the company will own half the online market within the next five years, a period during which, Credit Suisse predicts, a quarter of all malls will close. By the end of this year, more than 8,600 stores will have shuttered in 2017, the worst year on record.
But here’s the thing about the Mall of America: It’s fighting back. “I hear all this doom and gloom in the industry,” says the mall’s SVP of business development, Jill Renslow, with an upbeat, Midwestern delivery. “I’m like, ‘Folks! Keep your chin up! There’s so much opportunity!’ ” The mall completed a $325 million expansion in 2015, says Renslow, who started working there as an intern in the mid-1990s and has seen it endure recessions and upheaval before. A new 342-room JW Marriott has opened upstairs, and retailers like Zara and Anthropologie are being lured to the space. The mall is experimenting with new leasing models to attract pop-ups and younger players like Untuckit and Toms Shoes. Renslow, who is eager for people coming to Minneapolis for the 2018 Super Bowl this February to visit the mall and be surprised, doesn’t view Amazon as a competitor but as a partner; she recently worked with Amazon to install a set of pickup lockers at the mall. She believes retailers in general can “bring online shoppers to brick-and-mortar.” I ask her directly: Is physical retail dying? “Not at all!” she says.
Renslow isn’t feigning enthusiasm. Despite Wall Street’s pessimism, industry leaders sound downright bullish on the future of traditional retail. Why else, they argue, would Amazon spend $13.4 billion to buy Whole Foods? Sure, the competition is fiercer than ever, and icons such as Sears and JCPenney are dying. But they believe that the narrative has been oversimplified. “Amazon alone isn’t holding the knife,” says NYU Stern professor of marketing Scott Galloway, who studies the retail industry. Cultural tastes have changed. Malls grew too quickly, at twice the rate of the population, from 1970 to 2015. Many retailers succumbed to quarterly earnings pressures, invested in share buybacks rather than their stores, became saddled with private-equity debt, or failed to keep pace with digital trends. What we’re seeing now, industry executives say, is a rational, albeit painful, course correction. One study from retail-research firm IHL Group found that a mere 16 chains, including RadioShack and Payless, account for nearly half of all store closings, and that there will be a net increase of more than 4,000 stores in 2017 and 5,500-plus in 2018.
“Retail is under huge pressure, but the death of stores is greatly exaggerated,” says Galloway, who believes that while Amazon will continue to disrupt the market, an increasing number of competitors will discover new ways to respond. “In the age of Amazon, retailers must leverage assets that [Bezos] doesn’t have: When Amazon zigs, retailers must zag.”
This fall, Fast Company embarked on a journey to learn from those retailers that are flourishing in the age of Amazon. After all, more than 90% of retail sales still happen in the real world, and as relentless as Bezos is, it’s not likely he’ll swallow up all of brick-and-mortar on his own. The truth is that the bigger Amazon gets, the more opportunity it creates for fresh, local alternatives. The more Amazon pushes robot-powered efficiency, the more space there is for warm and individualized service. The more that people interact with Amazon through its AI-based assistant Alexa, the more they will crave the insight and personal connection of fellow humans.
“The idea that everybody needs to be terrified of Amazon is completely wrong,” says Brian Spaly, who cofounded two e-commerce-centric startups, Bonobos (menswear) and Trunk Club (a wardrobe-in-a-box service), which sold to Walmart and Nordstrom, respectively, for nine-figure sums. “Everybody needs to figure out what makes them special and use those weapons to compete.”
SUCCESSFUL RETAILERS WILL FEATURE PRODUCTS THAT CUSTOMERS CAN’T GET ELSEWHERE
A 15-minute drive north from the Mall of America are the downtown Minneapolis headquarters of Target. The company’s $7 billion bet on its future is coming to life in a series of spacious rooms littered across several floors and filled with mannequins, racks of colorful apparel, and fashion magazines. It’s here that Target is designing its own goods, refocusing on the aesthetic sensibility that fueled its success in the early 2000s. “While others are shrinking their footprints, reducing head count, or trying to save their way to the next quarter, we think there’s opportunity for us to take more market share,” says CEO Brian Cornell, who launched the initiative last February.
On the fourth floor, at the studio for Cat & Jack, Target’s new children’s clothing line—which blew up in its first 12 months to become a $2.1 billion brand—mood boards display photos of smiling tots at a July Fourth block party and a family movie night. Julie Guggemos, Target’s SVP of product development, describes the spirit behind the design as “positivity, happiness, saving the world,” citing the adventurous tweens in Netflix’s Stranger Things as an inspiration for the team. “We listen to Mom and Dad, but we have these kids in mind when we’re designing,” says Guggemos, a 27-year Target veteran.
Guggemos and her team of 400-plus designers will be rolling out more than a dozen high-quality, affordable, Target-exclusive brands by the end of 2018. They have already introduced a boutiquey children’s decor line called Pillowfort, a modern furniture collection called Project 62, an athleisure apparel line for the post-yoga brunch crowd called JoyLab, and a dapper menswear brand called Goodfellow & Co, which even Esquire described as “elevated.” Guggemos has just come from a product review for a new line, slated to launch next year. “We’re designing everything from the bottom up, 100% original,” she says.
When consumers can get seemingly anything and everything online, what can Target offer that Amazon can’t? That question was top of mind for chief merchandising officer Mark Tritton when he joined the company from Nordstrom in 2016. Target had fallen into a trap of licensing outside brands like Cherokee, which makes children’s apparel; even its in-house kids’ label, Circo, felt dated. “I thought, Wow, this stuff isn’t right,” recalls Tritton. “It feels tired and disconnected.”
In other words, Target had strayed from what made it “Tar-zhay.” Two decades ago, the company had distinguished itself from other big-box retailers by teaming up with celebrated architect and designer Michael Graves to craft a collection of mass-market housewares, partnering with high-end fashion designers like Isaac Mizrahi for custom fashion lines, and nurturing emerging brands such as Method through forward-thinking curation. “There would be no retail if it weren’t for merchandising, so why isn’t anyone talking about it anymore?” wonders Rachel Shechtman, founder of Story, the novel Manhattan concept store, which reinvents itself regularly (and collaborated with Target in 2014). “Merch assortments designed by spreadsheets and algorithms” is what’s killing department stores, she says.
When I meet Target COO John Mulligan at Target’s flagship, which sits just a block away from the Cat & Jack studio, he’s eager to compare the store’s $10 million renovation with printed-out photos of the old layout, which hadn’t changed much since the flagship was built in 2001. “It was gondola hell, right?” Mulligan says, referring to the basic shelving units you see in stores. “Just rows and rows of stuff. No sight lines.” Mulligan shakes his head as he points to a depressing image of the in-store Pizza Hut that used to greet customers.
The layout has been reorganized around Target’s new brands, and the presentation is crisp and contemporary. (Inexplicably, the company didn’t have a visual merchandising department until just two years ago; Cornell has since poached talent from J.Crew and the Limited.) As Mulligan ushers me through the store, he beams at the displays, each of which will now be refreshed monthly, which is double the previous rate: There’s an autumn-themed collection from Cat & Jack; sporty JoyLab leggings designed in partnership with Clique, whose Who What Wear line has been a hit at Target since it launched in 2016; and modern dining chairs and walnut tables from Project 62. “Before, it was a dead zone back here,” he says of the home-essentials area. Other parts of the store feature bright new arrangements of exclusive products from e-commerce upstarts such as Harry’s and Casper, and even the fitting room looks more like what you’d find in a Club Monaco. As for the Hut? It’s been replaced by fresh groceries and a liquor and craft beer shop. Target will remodel an additional 1,000 stores in a similar fashion by 2020, while also rolling out more localized stores with smaller footprints.
The redesigned “Tar-zhays”—there are around 110 of them so far—have delivered up to a 4% jump in sales at each location, but the more promising return from this investment has come from the house brands themselves. Cat & Jack customers, for example, spend 50% more in surrounding kids’ retail areas, Mulligan says, adding that their total basket size is 23% higher than other customers’. Most significantly, Target’s consumer research has shown that its brands have become a “trip driver”: People come to the store for Cat & Jack as much as they do for essentials like laundry detergent or bread or milk. “Target has always won with a spirit of design that their competitors didn’t have. I don’t see any other move for them: They’re not going to beat Amazon on e-commerce,” says a high-level retail expert who has advised the company on strategy.
Indeed, Target’s digital efforts continue to lag. When Mulligan takes me to the back to show off the redesigned storeroom, I don’t see any floor-roaming robots or automated conveyer belts, despite the fact that Target has stated that it plans to use its more than 1,800 stores as fulfillment centers (80% of the U.S. population lives within 10 miles of a Target). Instead, I find just one store clerk manually taping cardboard boxes for in-store pickup. Later, when I arrive to retrieve a $14.99 Goodfellow Henley shirt I purchased via Target’s app, the cashier asks for my ID because the flagship store’s smartphone scanner is broken. When I test Target’s new curbside-pickup service to buy paper towels, it fails at three consecutive outlets within the Minneapolis area. Ultimately, I give up.
The company needs to improve e-commerce and store pickup, but its future success does not depend only on these services. “Target is going to have to win on stuff that nobody else has,” the high-level expert says. “And that’s great retail, right?”
SUCCESSFUL RETAILERS WILL DELIVER A SATISFYING EXPERIENCE
A time zone away, in the sixth-floor showroom of Warby Parker’s SoHo offices in New York, cofounders Neil Blumenthal and Dave Gilboa are squinting at a backless shelving unit displaying their designer glasses. Customers mill about just steps from the co-CEOs’ desks, a dynamic that helps them relentlessly monitor and surgically adapt Warby Parker’s high-touch experience. Blumenthal is eyeing a wood shelf, which is missing a centimeter-tall lip, so that if a customer slides a pair of $95 Chamberlains too far back, they’ll slip onto the floor. “This does not make me happy,” he grumbles. Addressing these tiny details has proven crucial to the eyewear brand’s success. If they’re not fixed, “we’ll hear about it, like, ‘Fucking shit is falling off [the shelf]!’ ” Blumenthal says, with an effervescent laugh. “I don’t know if it’s right for policing, but broken-window theory definitely applies to retail.”
The 37-year-olds, who on this sunny Friday morning are both wearing slim-fitting button-downs, black sneakers, and patterned glasses—imagine the Black Keys as merchant princes—visit a Warby Parker store each day, hunting “for anything that needs to be refreshed, anything that’s out of place,” Gilboa says. This could be off-kilter frames or neglected customers. As much as the two consider themselves disrupters of competitors like Luxottica (Warby Parker’s $10.5 billion rival, which owns everything from LensCrafters to Ray-Ban), they’re students of retail history and find inspiration in such leaders as hospitality guru Danny Meyer, Apple Store legend Ron Johnson, and Mickey Drexler, the merchandising titan famous for reviving Gap in the 1990s and J.Crew in the 2000s.
Drexler, an early Warby Parker investor and board member, taught them that good experiential design is about solving customer problems. Gilboa describes how Drexler would walk into stores, zoom by Warby’s managers, and head straight to associates to interrogate them for unvarnished feedback. “He’ll isolate them, ask each of them the same questions, and then triangulate: Is he hearing consistent or conflicting answers? Then he really digs in, surfacing nuggets of wisdom hidden even by stores with great numbers,” Gilboa remembers.
When Warby launched its first store, in SoHo in 2013, the mission was to eliminate everything annoying about buying glasses. Blumenthal hated the “little shit vanity mirrors” at optometry shops, while Gilboa couldn’t stand the merchandise locked away in glass cases and the awkward interactions with often-pretentious store associates. They wanted approachable store greeters, an ask-us-anything reference desk, and a warm aesthetic, which they modeled after Sweden’s Stockholm Public Library, complete with its dark-wood shelving. Anthony Sperduti, cofounder of design studio Partners & Spade, who helped Warby Parker conceive its early stores, says they needed to feel like an authentic extension of the e-commerce brand. The high-quality materials of its eyewear products, he says, are reflected in “the brass details, marble counters—this incredible weight, this classicism.” To transform an intimidating experience into a fun and social activity, Warby Parker added photo booths and full-length mirrors so groups can check themselves out together. “If you’re born online, you better have a really good reason to do brick-and-mortar,” Sperduti says. “You better come out swinging.”
Warby now operates more than 60 stores, and on this particular day, it’s opening three new locations simultaneously—in Milwaukee; Fort Worth, Texas; and Harvard Square. Analysts estimate that the company will generate around $250 million in 2017 revenue. As the operation grows, it only gets harder for Blumenthal and Gilboa to keep this experience fresh. Before committing to risky new territories, the company often tests low-cost pop-up shops, rather than get stuck in the kind of expensive, long-term leases that have suffocated many traditional retailers and led them to try to save costs by building out one-size-fits-all stores. The Warby Parker team has developed modular components so that each store shares an identity but there’s room for local flourishes. Vernors ginger ale, a Michigan favorite, is on tap at the Detroit store, honoring the 151-year-old soda maker that once operated a pharmacy at the same location. The Miami store, which opened in 2015, features floors painted to look like swimming lanes, so that photos taken from the ceiling-affixed cameras make customers in sunglasses look like they’re floating in a pool—images that shoppers can then share on social media.
Big retailers and digital-native consumer brands alike cite Warby Parker as an inspiration and seek to mimic, even reverse engineer, what they believe is the core of its hip but inviting store experience. But refashioning stores with a certain wood finish or outfitting employees in a distinctive smock doesn’t make you Warby Parker any more than painting your store white makes you Apple. Piling on frivolous attractions in an attempt at authenticity, as Brooks Brothers did by opening a Stumptown at one of its Manhattan locations, drives the Warby Parker team bonkers. “The way people are defining experience today is way off,” Blumenthal says. “The idea of adding coffee shops to every store is ridiculous,” because it’s driven not by solving a customer problem or introducing a novel experience tied in some way to a brand, but by a hackneyed attempt to boost foot traffic. Equally jarring to them is Amazon’s new Go store in Seattle, which Gilboa recently explored, in which an array of sensors and computer-vision technology enable the ultimate in grab-and-go shopping. “Play that [concept] forward and you can imagine this dystopian experience where you have no human interaction at all,” he says.
Warby Parker is just as maniacally focused on efficiency as Amazon: Its next big initiative is a $15 million optical lab, in upstate New York, which enables greater quality control and faster product delivery. But the company knows that its true value lies in its elevated and personal experience, and Blumenthal and Gilboa never want to stray too far from what Drexler taught them. “We want to reinvent, but we sure as shit don’t want to reinvent the wheel,” Blumenthal says. “Startups sometimes take it too far, like, ‘Oh, we’re an innovator! We’ll just ignore what [traditional] retailers have done!’ Ignore best practices, get crushed.”
SUCCESSFUL RETAILERS WILL CHALLENGE THE FUNDAMENTAL ASSUMPTIONS OF COMMERCE
What does the store of tomorrow look like? Amazon Go is certainly one experiment, and seemingly every big brand, from Mastercard to Sephora, is dreaming up its own vision of the future inside whiz-bang concept labs. Ask around the retail industry and you’ll hear endless, breathless predictions about the potential of in-store augmented reality, drone delivery, or bitcoin payments.
So far, these technologies have amounted to little more than gimmicky distractions. “Customers don’t want stupid disco balls with lasers and holograms,” says Healey Cypher, founder of Oak Labs, which, yes, makes an interactive “smart mirror,” but is more focused on customizing the dressing-room experience. Target, too, seems to have come to this realization. Earlier this year, the company shuttered its much-ballyhooed “store of the future” project built on glitzy tech. “Ultimately, we didn’t want to build a Jetsons-like store just because we can,” COO John Mulligan says.
Vibhu Norby and Phillip Raub, cofounders of B8ta, a San Francisco–based consumer-electronics retailer that has raised $19.5 million to reimagine brick-and-mortar, are thinking different. Rather than depend on a cut of sales from products, like Best Buy does, their company charges brands for the privilege of being featured in B8ta’s 10 stores. By selling only a limited selection of trendy gadgets, B8ta’s store associates act as ambassadors for the products—the true stars—educating consumers on their features and offering white-glove service.
Norby and Raub believe that all physical retailers—Amazon included—need to rethink the business entirely. Norby, B8ta’s CEO, argues that historic metrics for success are completely irrelevant today. Who cares about sales per square foot when products reach customers via Uber and Prime Now? Why do year-over-year same-store sales comps matter when 56% of customers test products in-store but buy online? “Designing stores for throughput is how we ended up with 10-by-10 walls of Tide at Safeway,” Norby says. Perhaps most radical is the new idea that retail can be unbundled from transaction. Bonobos’s “guideshops,” for example, offer fittings and fashion advice, with the assumption that customers will order their apparel online afterward. Decide to buy in-store? Bonobos will ship it for free. “I’m starting to see it more, where retailers are not expecting you to walk out with a bag of their stuff,” says Partners & Spade’s Sperduti.
Some of these ideas might strike industry veterans as heresy, but B8ta’s cofounders view it merely as a shift in thinking about how physical space can be monetized. On a recent Saturday afternoon at B8ta’s downtown Palo Alto location, store associates demonstrate Boosted electric skateboards out front on the sidewalk. Inside, the store has a relaxed vibe, with homey carpets and armchairs occupied by gadget-shoppers’ patient loved ones, though it takes obvious inspiration from Apple’s minimalist stores. Customers sipping bubble tea toy with unboxed gadgets set up on long tables—Oculus Rift VR headsets, August door locks, Onyx walkie-talkies—while B8ta staff politely chats them up. These associates are not pushy at all, because they’re not pressured to sell units. They’re happy to answer questions and are knowledgeable about everything from the Nebia ionizing shower (“It turns your droplets into even smaller droplets,” an employee explains) to the finer points of four different Bluetooth trackers. B8ta’s market advantage is its well-trained staff. The cofounders, who met at the smart-thermostat company Nest, know firsthand how difficult it is to get customers interested in, let alone grasp, the benefits of new hardware products.
For electronics brands, B8ta stores are an excellent (and relatively inexpensive) marketing portal, and an even better data tool. “The real magic happens behind the scenes,” says Raub, the company’s chief business officer, who previously worked at Gap and Nintendo. Every product featured in the store is wired to track how customers play with it. Store associates, called “B8ta testers,” also gather qualitative feedback on why a shopper did or didn’t buy a product. “Why did they look at it? What didn’t they like?” says Raub, listing off a couple of common data points, which he compares to how e-commerce players monitor checkout cart abandonment. “Now brands can know that customers may have liked a product, but gave up once, say, they found out it wasn’t compatible with Android.” In a world where consumer products often end up languishing on shelves at Best Buy or forgotten amid Amazon’s catalog of an estimated 350 million–plus items, this data is more valuable than the sale itself. Traditional retailers now want what B8ta can offer: In late October, the startup announced that 70 Lowe’s locations will add a smart-home-focused B8ta, and Macy’s will soon feature B8ta outposts in its flagship stores.
SUCCESSFUL RETAILERS WILL RESURRECT THE ART OF SELLING
During my reporting, I quizzed each person I spoke with about which stores get retail right. People picked one place more than any other: MartinPatrick3.
An extravagant, 17,000-square-foot cathedral of high-fashion menswear in Minneapolis, MartinPatrick3 looks like what would have happened if Willy Wonka had gone to Parsons School of Design. At once boundless and intimate, the store’s colorful rooms naturally transition to the next, each its own pristinely wrapped Christmas present. In one, a collection of hand-stitched bow ties lie near $5,500 Brunello Cucinelli suits, a shiny black Vespa, and a modern steel cocktail table by a local designer. Down the hall, a white-accented men’s grooming shop stocked with shaving creams and bottled fragrances practically glows. There’s an in-store tailor, a barber, a full-time jewelry designer, and sharply dressed store associates, all with bouquet-like pocket squares blooming from their blazers.
Eleven years ago, Greg Walsh, an upscale interior designer who also sold home furnishings from his studio in the city’s hip North Loop neighborhood, began showcasing men’s accessories he’d collected during his travels: cuff links, watches, wallets. Customers loved them. Walsh brought on his better half, Dana Swindler (they’re “partner partners,” as Swindler puts it, smiling), to build out a stand-alone store in 2008. “The rule was that nothing could have sizes,” Walsh says. “That totally went out the window,” he laughs, explaining that the scope quickly grew to include apparel and much more.
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1/5 Avenue, Tucson, Arizona “Avenue is led by this incredible woman [Alexis Mosij] whose sense of design and taste is just unreal. You look at her store and you just want to live that life.” Healey Cypher, CEO, Oak Labs, a retail technology startup
Walsh and Swindler approach retail drastically differently from any merchant I encountered. Each display in MartinPatrick3, no matter how exquisite, is designed to be ephemeral. “We’re constantly reinventing. We can completely remodel a room within 24 hours,” Walsh says. They pride themselves on always paying vendors within 30 days—uncommon in the industry—and rushing new products into store collections often within days. (“This would take nine months at Nordstrom,” Walsh remembers one vendor telling him.) Whereas the traditional rules of brick-and-mortar dictate that sales matter above all else, store associates at MartinPatrick3 are encouraged to dole out sincere fashion advice, and if it means counseling a guest away from a higher-priced item or directing him to competitors’ shops, so be it. The payback comes in the lasting relationships such honesty builds. The company hosts events for free—even weddings—which it sees as a natural arm of its service, particularly if it has helped outfit the groomsmen. (There are shelves stocked with prosecco in a cozy VIP lounge.) In April, Walsh and Swindler even took down their e-commerce site. “It’s been funny. People in the industry keep saying, ‘You did what?!’ ” Walsh says. “But we decided we’re all about brick-and-mortar—that’s what we do really well—so let’s focus all our energy there.”
The self-financed retailer is growing fast. Walsh and Swindler guide me through back doors into 4,000 additional square feet of empty, brick-walled warehouse space adjacent to the store. This unfinished part of the 131-year-old building they moved to in 2010 is what Walsh is targeting as the company’s fifth addition. Down the hall, in their design studio, where MartinPatrick3’s “board of directors”—Cole and Ella, finely groomed poodles—lounge about on a green-mohair dining settee, Swindler cracks open a thick three-ring binder full of store statistics. (Swindler, who previously ran an engineering firm, is as meticulous about data as Walsh is about design.) Revenue has jumped an average of 40% annually since the company’s founding, with some years reaching triple-digit growth. “We work our asses off,” Swindler says proudly.
The pair can’t quite articulate their secret, but they know other retailers don’t have it. Others move too slowly, they feel, and simply aren’t creative enough. “We started in the recession. We’re used to hustling,” Swindler says. “The retailers we meet, they don’t do anything all day! Their give-a-shit factor is way down; they’re not on the floor every day like we are. Now that they’re making less [money], what do they do? The same thing as before, over and over and over again.”
MartinPatrick3 (the name comes from the ones Walsh’s father almost bequeathed him) offers sophisticated taste, expert curation, and a concierge-like, almost old-fashioned level of service that’s increasingly hard to find. Yes, it’s a store mostly for the 1%, but there is much here that Amazon can’t copy, time-honored lessons of merchandising and customer attention.
Retailers don’t need to chase a futuristic version of themselves that they might never attain; they first need to remember what made them special in the first place. The answers are all here. The talent, too. If Wall Street is right and the industry continues to decline, then this will be what we lose: the art of selling. MartinPatrick3’s store manager once worked at Nordstrom. The self-described concierge, who welcomed me to the store, made helpful recommendations, and even offered to assist with dinner reservations while I was in town, is an expat of Neiman Marcus, another shrinking department store trying to find its footing in the age of Amazon. You don’t need to sell mid-four-figure Cucinelli suits to offer this level of hospitality—Warby Parker does it with $95 frames—you just have to care enough to treat customers with the consideration and cordiality they deserve.
I roam through MartinPatrick3 by myself for a while, and eventually end up at Marty’s, the in-store barbershop with a classic candy-cane pole out front. Christopher Hernandez, my stylist, is dressed in a black vest and a gray flat cap like a 1920s newsboy. He previously worked at the barbershop inside the downtown Minneapolis Macy’s. Last March, Macy’s shuttered the location. “Most of us have a background in some big department store that’s closed,” he says as he snips away. “We’re all orphans here.”
Retailers are using artificial-intelligence software to set optimal prices, testing textbook theories of competition; antitrust officials worry such systems raise prices for consumers
The Knaap Tankstation gas station in Rotterdam, Netherlands, uses a2i Systems artificial-intelligence pricing software.PHOTO: KNAAP TANKSTATION BV
By Sam Schechner in WSJ
ROTTERDAM, the Netherlands—One recent afternoon at a Shell-branded station on the outskirts of this Dutch city, the price of a gallon of unleaded gas started ticking higher, rising more than 3½ cents by closing time. A little later, a competing station 3 miles down the road raised its price about the same amount.
The two stations are among thousands of companies that use artificial-intelligence software to set prices. In doing so, they are testing a fundamental precept of the market economy.
In economics textbooks, open competition between companies selling a similar product, like gasoline, tends to push prices lower. These kinds of algorithms determine the optimal price sometimes dozens of times a day. As they get better at predicting what competitors are charging and what consumers are willing to pay, there are signs they sometimes end up boosting prices together.
Advances in A.I. are allowing retail and wholesale firms to move beyond “dynamic pricing” software, which has for years helped set prices for fast-moving goods, like airline tickets or flat-screen televisions. Older pricing software often used simple rules, such as always keeping prices lower than a competitor.
On the Same Track
Two competing gas stations in the Rotterdam area both using a2i Systems pricing software roughly mirrored each other’s price moves during a selected week.
These new systems crunch mountains of historical and real-time data to predict how customers and competitors will react to any price change under different scenarios, giving them an almost superhuman insight into market dynamics. Programmed to meet a certain goal—such as boosting sales—the algorithms constantly update tactics after learning from experience.
Ulrik Blichfeldt, chief executive of Denmark-based a2i Systems A/S, whose technology powers the Rotterdam gas stations, said his software is focused primarily on modeling consumer behavior and leads to benefits for consumers as well as gas stations. The software learns when raising prices drives away customers and when it doesn’t, leading to lower prices at times when price-sensitive customers are likely to drive by, he said.
“This is not a matter of stealing more money from your customer. It’s about making margin on people who don’t care, and giving away margin to people who do care,” he said.
Driving the popularity of A.I. pricing is the pain rippling through most retail industries, long a low-margin business that’s now suffering from increased competition from online competitors.
“The problem we’re solving is that retailers are going through a bloodbath,” said Guru Hariharan, chief executive of Mountain View, Calif.-based Boomerang Commerce Inc., whose A.I.-enabled software is used by StaplesInc. and other companies.
Staples uses A.I.-enabled software to change prices on 30,000 products a day on its website.PHOTO: RICHARD B. LEVINE/ZUMA PRESS
The rise of A.I. pricing poses a challenge to antitrust law. Authorities in the EU and U.S. haven’t opened probes or accused retailers of impropriety for using A.I. to set prices. Antitrust experts say it could be difficult to prove illegal intent as is often required in collusion cases; so far, algorithmic-pricing prosecutions have involved allegations of humans explicitly designing machines to manipulate markets.
Officials say they are looking at whether they need new rules. The Organization for Economic Cooperation and Development said it plans to discuss in June at a round table how such software could make collusion easier “without any formal agreement or human interaction.”
“If professional poker players are having difficulty playing against an algorithm, imagine the difficulty a consumer might have,” said Maurice Stucke, a former antitrust attorney for the U.S. Justice Department and now a law professor at the University of Tennessee, who has written about the competition issues posed by A.I. “In all likelihood, consumers are going to end up paying a higher price.”
In one example of what can happen when prices are widely known, Germany required all gas stations to provide live fuel prices that it shared with consumer price-comparison apps. The effort appears to have boosted prices between 1.2 to 3.3 euro cents per liter, or about 5 to 13 U.S. cents per gallon, according to a discussion paper published in 2016 by the Düsseldorf Institute for Competition Economics.
Makers and users of A.I. pricing said humans remain in control and that retailers’ strategic goals vary widely, which should promote competition and lower prices.
“If you completely let the software rule, then I could see [collusion] happening,” said Faisal Masud, chief technology officer for Staples, which uses A.I.-enabled software to change prices on 30,000 products a day on its website. “But let’s be clear, whatever tools we use, the business logic remains human.”
Since then, sectors with fast-moving goods, frequent price changes and thin margins—such as the grocery, electronics and gasoline markets—have been the quickest to adopt the latest algorithmic pricing, because they are the most keen for extra pennies of margin, analysts and executives say.
The pricing-software industry has grown in tandem with the amount of data available to—and generated by—retailers. Stores keep information on transactions, as well as information about store traffic, product location and buyer demographics. They also can buy access to databases that monitor competitors’ product assortments, availability and prices—both on the web and in stores.
A.I. is used to make sense of all that information. International Business Machines Corp. said its price-optimization business uses capabilities from its Watson cognitive-computing engine to advise retailers on pricing. Germany’s Blue Yonder GmbH, a price-optimization outfit that serves clients in the grocery, electronics and fashion industries, said it uses neural networks based on those its physicist founder built to analyze data from a particle collider.
Neural networks are a type of A.I. computer system inspired by the interconnected structure of the human brain. They are good at matching new information to old patterns in vast databases, which allows them to use real-time signals such as purchases to predict from experience how consumers and competitors will behave.
Algorithms can also figure out what products are usually purchased together, allowing them to optimize the price of a whole shopping cart. If customers tend to be sensitive to milk prices, but less so to cereal prices, the software might beat a competitor’s price on milk, and make up margin on cereal.
“They’re getting really smart,” said Nik Subramanian, chief technology officer of Brussels-based Kantify, who said its pricing software has figured out how to raise prices after it sees on a competitor’s website that it has run out of a certain product.
Algorithmic pricing works well in the retail gasoline market, because it is a high-volume commodity that is relatively uniform, leading station owners in competitive markets to squeeze every penny.
For years, price wars in cutthroat markets have followed a typical pattern. A retailer would cut prices to lure customers, then competitors would follow suit, each cutting a little more than the others, eventually pushing prices down close to the wholesale cost. Finally one seller would reach a breaking point and raise prices. Everyone would follow, and the cycle started all over.
Some economists say the price wars helped consumers with overall lower prices, but led to very thin margins for station owners.
Danish oil and energy company OK hired a2i Systems in 2011 because its network of gas stations was suffering from a decade-old price war. It changed what it charged as many as 10 times a day, enlisting a team of people to drive around the country and call in competitors’ prices, said Gert Johansen, the company’s head of concept development.
A2i Systems—the name means applied artificial intelligence—was started by Alireza Derakhshan and Frodi Hammer, both engineering graduates of the University of Southern Denmark, in Odense. Before focusing on fuel, they built other A.I. systems, including a game displayed on interactive playground floor tiles that adapted to the speed and skill level of the children running around on top.
For OK, a2i created thousands of neural networks—one for each fuel at each station—and trained them to compare live sales data to years of historical company data to predict how customers would react to price changes. Then it ran those predictions through algorithms built to pick the optimal prices and learn from their mistakes.
In a pilot study, OK split 30 stations into two sets, a control group and an a2i group. The group using the software averaged 5% higher margins, according to a paper Mr. Derakhshan presented last June at an A.I. conference in Seville, Spain.
Scandinavian supermarket chain REMA 1000 says it will roll out price-optimization software made by Texas-based Revionics Inc. in coming months.PHOTO: JOSEPH DEAN/NEWSCOM/ZUMA PRESS
The new system could make complex decisions that weren’t simply based on a competitor’s prices, Mr. Derakhshan said in an interview.
One client called to complain the software was malfunctioning. A competitor across the street had slashed prices in a promotion, but the algorithm responded by raising prices. There wasn’t a bug. Instead, the software was monitoring the real-time data and saw an influx of customers, presumably because of the long wait across the street.
“It could tell that no matter how it increased prices, people kept coming in,” said Mr. Derakhshan.
On the outskirts of Rotterdam, Koen van der Knaap began running the system on his family-owned Shell station in recent months. Down the road, a station owned by Tamoil, a gasoline retailer owned by Libya’s Oilinvest Group, uses it too.
During a late-March week for which both Tamoil and Mr. van der Knaap provided hourly data, the costs for unleaded gas at the two stations—which vary in opening hours and services—bounced around independently much of the time, and generally declined, reflecting falling oil prices that week.
During some periods, however, the stations’ price changes paralleled each other, going up or down by more than 2 U.S. cents per gallon within a few hours of each other. Often, prices dropped early in the morning and increased toward the end of the day, implying that the A.I. software may have been identifying common market-demand signals through the local noise.
The station owners say their systems frequently lower prices to gain volume when there are customers to be won.
“It can be frustrating,” said Erwin Ralan, an electronics-store manager who was filling up at the Tamoil station that week. “Prices usually go up at the end of the day. But when you’re empty and you’re in a rush, there’s not much you can do.”
IN THE stormy and ever-changing world of global finance, insurance has remained a relatively placid backwater. With the notable exception of AIG, an American insurer bailed out by the taxpayer in 2008, the industry rode out the financial crisis largely unscathed. Now, however, insurers face unprecedented competitive pressure owing to technological change. This pressure is demanding not just adaptation, but transformation.
The essential product of insurance—protection, usually in the form of money, when things go wrong—has few obvious substitutes. Insurers have built huge customer bases as a result. Investment revenue has provided a reliable boost to profits. This easy life led to a complacent refusal to modernise. The industry is still astonishingly reliant on human labour. Underwriters look at data but plenty still rely on human judgment to evaluate risks and set premiums. Claims are often reviewed manually.
The march of automation and technology is an opportunity for new entrants. Although starting a new soup-to-nuts insurer from scratch is rare (see article), many companies are taking aim at parts of the insurance process. Two Sigma, a large American “quant” hedge fund, for example, is betting its number-crunching algorithms can gauge risks and set prices for insurance better and faster than any human could. Other upstarts have developed alternative sales channels. Simplesurance, a German firm, for example, has integrated product-warranty insurance into e-commerce sites.
Insurers are responding to technological disruption in a variety of ways. Two Sigma contributes its analytical prowess to a joint venture with Hamilton, a Bermudian insurer, and AIG, which actually issues the policies (currently only for small-business insurance in America). Allianz, a German insurer, simply bought into Simplesurance; many insurers have internal venture-capital arms for this purpose. A third approach is to try to foster internal innovation, as Aviva, a British insurer, has done by building a “digital garage” in Hoxton, a trendy part of London.
The biggest threat that incumbents face is to their bottom line. Life insurers, reliant on investment returns to meet guaranteed payouts, have been stung by a prolonged period of low interest rates. The tough environment has accelerated a shift in life insurance towards products that pass more of the risk to investors. Standard Life, a British firm, made the transition earlier than most, for example, and has long been primarily an asset manager (see article).
Meanwhile, providers of property-and-casualty (P&C) insurance, such as policies to protect cars or homes, have seen their pricing power come under relentless pressure, notably from price-comparison websites. In combination with the stubbornly high costs of maintaining their old systems, this has meant that profitability has steadily deteriorated. The American P&C industry, for instance, has seen its “combined ratio”, which expresses claims and costs as a percentage of premium revenue, steadily creep up from 96.2% in 2013 to 97.8% in 2015, and to an estimated 100.3% for 2016 (ie, a net underwriting loss). Henrik Naujoks of Bain & Company, a consultancy, says this has left such insurers facing a stark choice: become low-cost providers, or differentiate themselves through the services they provide.
One fairly simple way to offer distinctive services is to use existing data in new ways. Insurers have long drawn up worst-case scenarios to estimate the losses they would incur from, say, a natural catastrophe. But some have started working with clients and local authorities on preparing for such events; they are becoming, in effect, risk-prevention consultants. AXA, a French insurer, has recently started using its models on the flooding of the Seine to prepare contingency plans. Gaëlle Olivier of AXA’s P&C unit says the plans proved helpful in responding to floods in June 2016, reducing the damage.
Tech-savvy insurers are going one step further, exploiting entirely new sources of data. Some are using sensors to track everything from boiler temperatures to health data to driving styles, and then offering policies with pricing and coverage calibrated accordingly. Data from sensors also open the door to offering new kinds of risk-prevention services. As part of Aviva’s partnership with HomeServe, a British home-services company, the insurer pays to have a sensor (“LeakBot”) installed on its customers’ incoming water pipes that can detect even minuscule leaks. HomeServe can then repair these before a pipe floods a home, causing serious damage.
The shift towards providing more services fosters competition on factors beyond price. Porto Seguros, a Brazilian insurer, offers services ranging from roadside assistance to scheduling doctor’s appointments. In France AXA provides coverage for users of BlaBlaCar, a long-distance ride-sharing app. The main aim of the policy is to guarantee that customers can still reach their destination. If, say, the car breaks down, it offers services ranging from roadside car-repair to alternative transport (eg, calling a taxi).
Insurers face many hurdles, however, to becoming service providers and risk consultants. Maurice Tulloch, head of the general-insurance arm of Aviva, admits that such services are yet to catch on with most customers. So far, his firm, like its peers, has focused on enticing them to adopt the new offerings by cutting insurance premiums, rather than on making money directly from them. It reckons it can recoup the cost of, say, the HomeServe sensors and repairs from the reduction in claims.
One example of what the future may hold comes from the car industry. Carmakers have traditionally bought product-liability insurance to cover manufacturing defects. But Volvo and Mercedes are so confident of their self-driving cars that last year they said they will not buy insurance at all. They will “self-insure”—ie, directly bear any losses from crashes.
Some think that such trends threaten the very existence of insurance. Even if they do not, Bain’s Mr Naujoks is not alone in expecting the next five years to bring more change to the insurance industry than he has seen in the past 20.
Google unit posts 10-fold increase in viewership since 2012, boosted by algorithms personalizing user lineups
WSJ By JACK NICAS
YouTube viewers world-wide are now watching more than 1 billion hours of videos a day, threatening to eclipse U.S. television viewership, a milestone fueled by the Google unit’s aggressive embrace of artificial intelligence to recommend videos.
YouTube surpassed the figure, which is far larger than previously reported, late last year. It represents a 10-fold increase since 2012, YouTube said, when it started building algorithms that tap user data to give each user personalized video lineups designed to keep them watching longer.
Feeding those recommendations is an unmatched collection of content: 400 hours of video are uploaded to YouTube each minute, or 65 years of video a day.
“The corpus of content continues to get richer and richer by the minute, and machine-learning algorithms do a better and better job of surfacing the content that an individual user likes,” YouTube Chief Product Officer Neal Mohan said.
YouTube’s billion-hour mark underscores the wide lead of the 12-year-old platform in online video—threatening traditional television, which lacks similarly sophisticated tools.
Facebook Inc. and Netflix Inc. said in January 2016 that users watch 100 million hours and 116 million hours, respectively, of video daily on their platforms. Nielsen data suggest Americans watch on average roughly 1.25 billion hours of live and recorded TV a day, a figure steadily dropping in recent years.
YouTube’s success using tailor-made video lineups illustrates how technology companies can reshape media consumption into narrow categories of interests, a trend some observers find worrying.
“If I only watch heavy-metal videos, of course it’s serving me more of those. But then I’m missing out on the diversity of culture that exists,” said Christo Wilson, a Northeastern University computer-science professor who studies the impact of algorithms. “The blessing and curse of cable and broadcast TV is it was a shared experience.…But that goes away if we each have personalized ecosystems.”
YouTube benefits from the enormous reach of Google, which handles about 93% of internet searches, according to market researcher StatCounter. Google embeds YouTube videos in search results and pre-installs the YouTube app on its Android software, which runs 88% of smartphones, according to Strategy Analytics.
That has helped drive new users to its platform. About 2 billion unique users now watch a YouTube video every 90 days, according to a former manager. In 2013, the last time YouTube disclosed its user base, it said it surpassed 1 billion monthly users. YouTube is now likely larger than the world’s biggest TV network, China Central Television, which has more than 1.2 billion viewers.
YouTube long configured video recommendations to boost total views, but that approach rewarded videos with misleading titles or preview images. To increase user engagement and retention, the company in early 2012 changed its algorithms to boost watch time instead. Immediately, clicks dropped nearly 20% partly because users stuck with videos longer. Some executives and video creators objected.
Months later, YouTube executives unveiled a goal of 1 billion hours of watch time daily by the end of 2016. At the time, optimistic forecasts projected it would reach 400 million hours by then.
YouTube retooled its algorithms using a field of artificial intelligence called machine learning to parse massive databases of user history to improve video recommendations.
‘If I only watch heavy-metal videos, of course it’s serving me more of those. But then I’m missing out on the diversity of culture that exists.’
—Northeastern University computer-science professor Christo Wilson
Previously, the algorithms recommended content largely based on what other users clicked after watching a particular video, the former manager said. Now their “understanding of what is in a video [and] what a person or group of people would like to watch has grown dramatically,” he said.
Engineers tested each change on a control group, and only kept the change if those users spent more time on YouTube.
One strategy was to find new areas of user interest. For instance, YouTube could suggest a soccer video to users watching a lot of football, and then flood the lineup with more soccer if the first clip was a hit. “Once you realize there’s an additional preference, exploit that,” the former manager said.
But the algorithm didn’t always deliver. For instance, when Ms. Wojcicki joined as CEO in 2014, YouTube recommended videos to her about eczema because she had recently watched a clip about skin rashes after suspecting one of her children had one, said Cristos Goodrow, YouTube’s video-recommendation chief.
That made the video-recommendation team realize there were certain “single-use videos” to ignore as signals of user interest. But to mark them, they had to think of each example, such as certain health and how-to videos.
Then last year YouTube partnered with Google Brain, which develops advanced machine-learning software called deep neural networks, which have led to dramatic improvements in other fields, such as language translation. The Google Brain system was able to identify single-use video categories on its own.
Big data’s potential just keeps growing. Taking full advantage means companies must incorporate analytics into their strategic vision and use it to make better, faster decisions.
Is big data all hype? To the contrary: earlier research may have given only a partial view of the ultimate impact. A new report from the McKinsey Global Institute (MGI), The age of analytics: Competing in a data-driven world, suggests that the range of applications and opportunities has grown and will continue to expand. Given rapid technological advances, the question for companies now is how to integrate new capabilities into their operations and strategies—and position themselves in a world where analytics can upend entire industries.
The age of analytics
Big data continues to grow; if anything, earlier estimates understated its potential.
A 2011 MGI report highlighted the transformational potential of big data. Five years later, we remain convinced that this potential has not been oversold. In fact, the convergence of several technology trends is accelerating progress. The volume of data continues to double every three years as information pours in from digital platforms, wireless sensors, virtual-reality applications, and billions of mobile phones. Data-storage capacity has increased, while its cost has plummeted. Data scientists now have unprecedented computing power at their disposal, and they are devising algorithms that are ever more sophisticated.
Earlier, we estimated the potential for big data and analytics to create value in five specific domains. Revisiting them today shows uneven progress and a great deal of that value still on the table (exhibit). The greatest advances have occurred in location-based services and in US retail, both areas with competitors that are digital natives. In contrast, manufacturing, the EU public sector, and healthcare have captured less than 30 percent of the potential value we highlighted five years ago. And new opportunities have arisen since 2011, further widening the gap between the leaders and laggards.
Leading companies are using their capabilities not only to improve their core operations but also to launch entirely new business models. The network effects of digital platforms are creating a winner-take-most situation in some markets. The leading firms have remarkably deep analytical talent taking on various problems—and they are actively looking for ways to enter other industries. These companies can take advantage of their scale and data insights to add new business lines, and those expansions are increasingly blurring traditional sector boundaries.
Where digital natives were built for analytics, legacy companies have to do the hard work of overhauling or changing existing systems. Adapting to an era of data-driven decision making is not always a simple proposition. Some companies have invested heavily in technology but have not yet changed their organizations so they can make the most of these investments. Many are struggling to develop the talent, business processes, and organizational muscle to capture real value from analytics.
The first challenge is incorporating data and analytics into a core strategic vision. The next step is developing the right business processes and building capabilities, including both data infrastructure and talent. It is not enough simply to layer powerful technology systems on top of existing business operations. All these aspects of transformation need to come together to realize the full potential of data and analytics. The challenges incumbents face in pulling this off are precisely why much of the value we highlighted in 2011 is still unclaimed.
The urgency for incumbents is growing, since leaders are staking out large advantages, and hesitating increases the risk of being disrupted. Disruption is already happening, and it takes multiple forms. Introducing new types of data sets (“orthogonal data”) can confer a competitive advantage, for instance, while massive integration capabilities can break through organizational silos, enabling new insights and models. Hyperscale digital platforms can match buyers and sellers in real time, transforming inefficient markets. Granular data can be used to personalize products and services—including, most intriguingly, healthcare. New analytical techniques can fuel discovery and innovation. Above all, businesses no longer have to go on gut instinct; they can use data and analytics to make faster decisions and more accurate forecasts supported by a mountain of evidence.
The next generation of tools could unleash even bigger changes. New machine-learning and deep-learning capabilities have an enormous variety of applications that stretch into many sectors of the economy. Systems enabled by machine learning can provide customer service, manage logistics, analyze medical records, or even write news stories.
These technologies could generate productivity gains and an improved quality of life, but they carry the risk of causing job losses and dislocations. Previous MGI research found that 45 percent of work activities could be automated using current technologies; some 80 percent of that is attributable to existing machine-learning capabilities. Breakthroughs in natural-language processing could expand that impact.
Data and analytics are already shaking up multiple industries, and the effects will only become more pronounced as adoption reaches critical mass—and as machines gain unprecedented capabilities to solve problems and understand language. Organizations that can harness these capabilities effectively will be able to create significant value and differentiate themselves, while others will find themselves increasingly at a disadvantage.
The Starbucks stores need to remain a place where people go to seek out human interaction.
SEATTLE — Web sites, e-commerce and what he described as the Amazon effect could lead both large and small companies to close retail stores in the coming years, said Howard Schultz, chairman and chief executive officer for the Starbucks Coffee Co.
Howard Schultz, chairman and c.e.o. of Starbucks
“There is no doubt that over the next five years or so we are going to see a dramatic level of retailers not be able to sustain their level of core business as a traditional bricks-and-mortar retailer, and their omni-channel approach is not going to be sustainable to maintain their cost of their infrastructure, and as a result of that, there is going to be a tremendous amount of changes with regard to the retail landscape,” he said in a Nov. 3 earnings call.
Mr. Schultz said Starbucks stores have an advantage in that they maintain a special place in terms of a sense of community, an environment where people go to seek out human interaction. Starbucks could be in a unique position 5 to 10 years from now. Other retail stores closing could mean fewer stores competing for Starbucks’ customers, he said.
“I’m not talking about the coffee category,” Mr. Schultz said. “I am talking overall, but we are in the very, very early stages of a tremendous change in the bricks-and-mortar footprint of retailers domestically and internationally as a result of the sea-change in how people are buying things, and that is going to have I think a negative effect on all of retail, but we believe that it is going to have ultimately a positive effect on the position that we occupy and the environment that we create in our stores.”
New Starbucks roastery stores will be designed to enhance the consumer experience.
New Starbucks roastery stores will be designed to enhance the consumer experience. The Seattle roastery, the only one in operation right now, delivered a comp sales increase of 24% in the fiscal year ended Oct. 2, Mr. Schultz said. A roastery in Shanghai, China, should begin operations next year.
“Opening in late 2017 on Nanjing Road among the busiest shopping destinations in the world, the Starbucks Shanghai roastery will be a stunning two-level, 30,000-square-foot experiential destination showcasing the newest coffee brewing methods and offering customers the finest assortment of exclusive micro-lot coffees from around the world in an immersive all-sensory experience emblematic of our Seattle roastery, respectfully curated through a unique lens that will make it highly impactful and relevant to our Chinese customers,” he said.
Starbucks plans to open roasteries in New York and Tokyo in 2018. A roastery should open in Europe in 2019, but Starbucks has yet to select a city.
Mobile orders now represent 6% of Starbucks transactions.
Starbucks has a digital presence as well. Mobile orders now represent 6% of transactions, said Kevin Johnson, president and chief operating officer.
“We are continuously improving the mobile order and pay experience with newly released functionality that presents our personalized offer directly on the front screen of the mobile app and allows the customer to save favorite stores, favorite customers’ beverages, and we have new features in the pipeline to be released shortly, including real-time personalized product suggestions and the ability to save favorite orders, and there is more coming,” he said.
Starbucks executives discussed results of the 2016 fiscal year in the Nov. 3 earnings call. Net earnings attributable to Starbucks in the year ended Oct. 2 were $2,817.7 million, equal to $1.90 per share on the common stock, which was up 2.2% from $2,757.4 million, or $1.82 per share, in the previous fiscal year. Consolidated net revenues grew 11% to $21,315.9 million from $19,162.7 million in the previous fiscal year. The 2016 fiscal year contained 53 weeks compared to 52 weeks for the previous fiscal year.
Go to any business conference and you’ll hear people talking about transformation. For a lot of companies it’s a matter of life and death. Their legacy business is fading, and they need to become something new. The problem is that most companies, like most people, aren’t good at change.
Some, though, are amazing at it. Like those Hasbro toys that start out as a robot but can be bent into the shape of a car, these companies start out doing one thing, then—poof!—flip a few switches and become something else.
Consider Nvidia NVDA-0.05%, a chip company in Santa Clara, Calif., that started out 23 years ago and originally became successful in the somewhat humble business of making graphics boards that videogame fans used to soup up the performance of their PCs. Then, in 2006, Nvidia figured out that its graphics chips could be hooked together to make a supercomputer. Today its graphics processors power many of the brawniest computers in the world, and they will be used in two next-generation supercomputers being designed by U.S. Department of Energy labs. That line of business generates $150 million a year for Nvidia.
But now the chipmaker has spotted a market that could be its biggest opportunity yet: self-driving cars. To make a vehicle autonomous, you need to gather massive streams of data from loads of sensors and cameras and process that data on the fly so that the car can “see” what’s around it. Turns out Nvidia’s graphics chips are great for that. So far, 80 companies, including Volvo, Audi, and Tesla TSLA-0.27%, are using Nvidia technology in their research around autonomous vehicles. “We’re transforming into an artificial-intelligence company,” says Danny Shapiro, a senior director in Nvidia’s automotive group.
Why has Nvidia been such a natural quick-change artist? Well, it turns out that it and other “transformers” have a few traits in common:
▸ Big ears. They listen to customers. Nvidia’s self-driving-car business grew out of a long-standing relationship with auto companies. Car guys used Nvidia chips for computer-aided design, then used Nvidia supercomputer chips to do crash simulations. When the car guys started thinking about autonomous vehicles, Nvidia leaped at the chance to help them solve the problem.
▸ An impatient boss. Transformer CEOs like change and will drive it down throughout the organization. Nvidia’s CEO, Jen-Hsun Huang, is an engineer and a chip designer. He cofounded Nvidia and still runs it like a startup.
▸ Active imaginations. Conventional companies try to find new uses for capabilities they already have. Transformers look at what the market needs and then go build it, hiring new people and/or taking people off other jobs.
▸ A brush with death. That’s not the case at Nvidia, but a close call with the corporate undertaker can sometimes provide a necessary spark. Think of Apple’s AAPL-0.20% multiple rebirths under Steve Jobs.
▸ Finally: Yes, transformation is hard—but not changing can sometimes be fatal.
Audi: In 2015, started test-driving an AI-laden prototype nicknamed “Jack” that lets drivers easily switch to autonomous mode via buttons on the wheel
BMW: Has promised an entirely autonomous car called iNext by 2021; BMW’s ReachNow car-sharing service launched in April in Seattle and expanded to Portland, Oregon, in September
Ford: Announced plans for fully autonomous car with no pedals or steering wheel by 2021; recently invested $75 million in California laser-sensor company Velodyne; bought San Francisco–based private bus service Chariot and plans to expand it
Volvo: Forged partnerships with Microsoft (will incorporate HoloLens augmented-reality technology into its cars) and Uber (which is planning to use Volvos as part of its self-driving test fleet in Pittsburgh); teamed up with safety-system-maker Autoliv to set up a new company focused on autonomous-driving software
Alphabet: Launched self-piloting-car project back in 2009; testing retrofitted Lexus SUVs and its own adorable prototype vehicles in several locations; recently partnered with Fiat Chrysler to build self-driving minivans
Apple: Has invested $1 billion in Chinese ride-share company Didi Chuxing; reportedly rebooting its efforts to develop an Apple car; might also build a system to add autonomous features to preexisting vehicles
Baidu: Chinese search-engine company has teamed up with digital-graphics pioneer Nvidia to create a self-driving-vehicle system that uses 3-D maps in the cloud; is in the testing stage with several different self-driving-car prototypes, including one built with BMW
Tesla: After revolutionizing electric vehicles with the semi-autonomous Model S, will release more-affordable all-electric Model 3, possibly in late 2017; Model S’s involved in a pair of high-profile fatal accidents
Didi Chuxing: Acquired Uber’s Chinese operations in August, ending a fierce rivalry for Chinese market
Lyft: Partnered with GM to start testing autonomous Chevy Bolt taxis within the next year
Uber: In September, began testing autonomous Ford Fusions in Pittsburgh—the first self-driving fleet available to the public in the U.S.
Comma.ai: Andreessen Horowitz–backed company making an inexpensive kit that turns regular cars into semi-autonomous ones
Mobileye: Israeli software maker that had partnered with Tesla to provide chips and software, but the two companies ended their collaboration in the wake of a fatal accident in May (Tesla cars currently still use Mobileye chips); has teamed up with Delphi Automotive to build a self-driving system by 2019
NextEV: Shanghai-based electric-car innovator headed in the U.S. by former Cisco exec Padmasree Warrior; set to show off a high-performance all-electric sports-car prototype this year
Nutonomy: Born at MIT and backed by Ford, makes self-driving cars, software, and autonomous robots; started testing driverless taxis in Singapore this summer
Quanergy: Silicon Valley–based company developing light- and object-sensing technology for self-driving cars; boasts $1.59 billion valuation thanks to investors Samsung and Delphi
Zoox: Palo Alto startup behind the Boz, a fully autonomous concept vehicle (still in the design phase) with inward-facing seats similar to a train car; company valued at around $1 billion
A version of this article appeared in the November 2016 issue of Fast Company magazine.
And how doing so helps them keep up with technological change.
Why isn’t Intuit INTU-0.94% dead? Its peers from the Pleistocene epoch of PC software (VisiCalc, WordStar) are long gone; only Intuit survives as a significant independent business. The reason is easy to state, hard to emulate: The company has continually disrupted itself, most recently scrapping its desktop-driven business model of the previous 30 years and switching to one based on the cloud. Revenues went down before they went up, but Intuit’s stock recently hit an all-time high.
Such stories are extremely rare. Successful incumbent firms are more likely to follow the trajectory of Kodak, SearsSHLD2.39%, Bethlehem Steel, and many newspapers, dead or diminished after technology transformed their industries. Little wonder that for the past two years, when we have asked Fortune 500 CEOs to name their single biggest challenge, their No. 1 answer has been “the rapid pace of technological change.”
Yet a few incumbents have defied the odds and succeeded at self-disruption. How they do it is becoming clear.
They see their business as disrupters would see it. This challenge is psychological and requires escaping the aura of headquarters. At the dawn of the web, American Airlines’ AAL-2.31% Sabre subsidiary assembled a team and sent it to another building with orders to disrupt the industry’s travel-agent-based business model. The result was Travelocity. Charles Schwab responded to the rise of “robo-advisers” like Betterment and Wealthfront by forming a full-time team that ignored the company’s corporate playbook. The team developed Schwab Intelligent Portfolios, a robo-product that now manages more assets than any of its disrupter startup rivals.
They find the courage to leap.NetflixNFLX-0.44% CEO Reed Hastings knew that online streaming would disrupt his successful DVDs-by-mail model. He committed to streaming in 2011—and Netflix’s stock plunged 76%. Wall Street called for his head. But Hastings pushed on, and today DVDs are just 7% of the company’s business, while the stock is up 150% from its pre-plunge peak
They never stop. Self-disruption isn’t something you do just once. Every successful disrupter becomes an incumbent in its transformed industry, and digital business models don’t last long. AmazonAMZN0.82% disrupted bookstores 20 years ago, then disrupted its own books-by-mail model with Kindle e-readers. Digital evolution is merciless: Intelwas a champion self-disrupter until it missed the mobile revolution; in April it announced 12,000 layoffs.
Leaders can glean these lessons from the first industries to be disrupted by digital tech. But the hardest step for incumbents is the first one, best expressed by Peter Drucker: “If leaders are unable to slough off yesterday, to abandon yesterday, they simply will not be able to create tomorrow.”