razors and blades business model

Billion Dollar Brand Club: How Dollar Shave Club, Warby Parker, and Other Disruptors Are Remaking What We Buy
by Lawrence Ingrassia
Published 28 Jan 2020

Chapter 14: The Brand Is Dead, Long Live the Brand By 2018, they together had grabbed: Euromonitor International, a market research provider, estimates that Dollar Shave Club had a 10.5 percent share and Harry’s had a 3.2 percent share of the U.S. market for men’s razors and blades as measured in dollars in 2018. Although Euromonitor doesn’t track unit volume, the two companies’ combined market share as measured in the number of razors and blades sold would be higher, probably approaching around 20 percent, because their products are less expensive. It is equally hard to imagine Gillette: Euromonitor International estimates that Gillette had a 52.8 percent share of the U.S. market for men’s razors and blades as measured in dollars in 2018. 90 percent had lost market share in recent years: “Catalina Mid-Year Performance Report Finds Challenging Market for Many of Top 100 CPG Brands,” Catalina Marketing Report, September 30, 2015, https://www.catalina.com/news/press-releases/catalina-mid-year-performance-report-finds-challenging-market-for-many-of-top-100-cpg-brands/.

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Michael Dubin was one of the entrepreneurs at the vanguard of this revolution, though that wasn’t exactly what he was thinking when he first got the idea of selling razors and blades on the internet. * * * Out of work, Dubin was looking for his next opportunity when he attended a friend’s holiday party in Beverly Hills in December 2010. At the party, he started schmoozing with Mark Levine, his friend’s father. Levine, who was fifty-six, had an odd assortment of consumer products he’d purchased in bulk a while back that he was having a hard time unloading, including cake slicers and off-brand razors and blades (some 250,000 twin-blade cartridges in all). All were sitting in a nearby warehouse running up unpaid storage fees, a fact he didn’t bother to mention to Dubin when they met.

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As part of the deal, Dorco signed a long-term agreement to supply razors and blades to Dollar Shave Club until 2019. Dubin had little choice but to acquiesce and give a piece of his company to Dorco. “Let’s just say that I understood the importance of the supply chain and wanted to make that deal,” he says. While Gillette and Schick still weren’t paying much attention to Dollar Shave Club’s early success, others were. Jeffrey Raider, one of the four cofounders of Warby Parker, the online eyeglass company, helped start a copycat competitor, Harry’s; in 2013, it started selling razors and blades made by a German manufacturer, which Harry’s would eventually buy, pursuing a different strategy from Dollar Shave Club’s supplier relationship with Dorco.

Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You
by Sangeet Paul Choudary , Marshall W. van Alstyne and Geoffrey G. Parker
Published 27 Mar 2016

As every business student learns, the model behind the safety razor business that entrepreneur King Gillette founded in 1901 involved distributing the razors for free—or at a very low, subsidized cost—while charging for the blades. As it happens, research by Randal C. Picker of the University of Chicago Law School has called into question the traditional story of Gillette and the razors-and-blades pricing strategy. Picker found that the timing of price changes for Gillette razors and blades, as well as the expiration date on the patent covering Gillette’s unique razor design, seems to undermine the notion that the company was employing the razors-and-blades strategy as commonly understood.1 Nonetheless, the familiar story remains a handy symbol for a strategy that has been used in a number of markets, including, for example, the printer market, where sales of high-priced toner cartridges generate profits that the relatively cheap printers themselves don’t produce.

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Picker found that the timing of price changes for Gillette razors and blades, as well as the expiration date on the patent covering Gillette’s unique razor design, seems to undermine the notion that the company was employing the razors-and-blades strategy as commonly understood.1 Nonetheless, the familiar story remains a handy symbol for a strategy that has been used in a number of markets, including, for example, the printer market, where sales of high-priced toner cartridges generate profits that the relatively cheap printers themselves don’t produce. Another version of this strategy is the freemium model, in which a free layer of service attracts users who eventually pay for an enhanced version. Many online service platforms, including Dropbox and MailChimp, work this way. Both the razors-and-blades model and the freemium model monetize the same user base, or portions thereof. Platforms may also offer free or subsidized pricing to one user base while charging full price to an entirely different user base. This makes the design of monetization models more complex, since the platform must ensure that the value it gives away to one side can be used to capture value on the other side.

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“open out” websites, 144 open source, 57, 172–73, 254–55 OpenTable, 17, 90, 95, 101, 103, 194, 262 operating system (OS), 6–7, 52–53, 152–53, 211, 222, 226, 240 Palm Pilots, 80, 83 Parker, Geoffrey G., ix, 23–24, 69, 110, 130, 241, 242 parking, 62, 233, 234 partner-against-partner competition, 211, 212, 227 patents, 109, 157, 174–75, 241 payments systems, 8, 56, 79–83, 85, 137, 142, 145, 155, 222, 274–78, 285 PayPal, 17, 21, 23, 24, 37, 79–83, 85, 91, 93, 94, 111, 275 PDF, 29–30, 92–93 peer-to-peer lending, 170, 275–76 percentage of active users, 190, 192, 193 Percival, Sean, 125–26 peripheral applications, 52–57 peripheral hardware, 178–79 personal computers (PCs), 58, 140, 152–53, 178–79, 200 personal digital assistants (PDAs), 80 pharmaceuticals industry, 225 photo-editing tools, 47, 104 photo-sharing sites, 6, 37, 47, 66, 100–103, 104, 118, 142, 167–69, 172, 173, 193, 198, 217, 226, 299 piggyback strategy, 91–92, 105, 184 Pinterest, 3, 168–69 platform-against-partner competition, 211–12, 227 platform-against-platform competition, 211, 227 Platform Leadership (Gawer and Cusumano), 178–79 platforms: adjacent, 222–23, 295, 296, 298 architecture of, 47–48, 164–65, 170–73, 182, 221 assets of, 9, 68–71, 160, 180, 181, 209, 212, 220–21, 238, 260 authors’ research on, ix–xi, 23–24 as business model, vii, 35, 60–62, 64, 66–67, 73–77, 163, 184–86, 188, 258 capitalization of, 9, 16–18, 82, 109, 145, 278 compatibility of, 53, 213–14, 240, 260 competition in, viii, 17–18, 33, 60–62, 68, 73–77, 83, 86, 87–88, 96–97, 131–34, 152–54, 155, 156, 157–58, 174–75, 181, 185–86, 189, 199–200, 203, 207–27, 234–35, 240–43, 256–60, 264, 287, 299 consumers and customers of, viii, 6–8, 26, 29, 31–49, 60–67, 71–74, 78–82, 86–97, 107, 108–21, 125, 134, 135, 145–47, 157–58, 176–78, 180, 187–92, 197–205, 210–23, 240–43, 251–54, 263, 272–78, 295–99 controversial aspects of, 129–30, 149–50, 192–93, 213–14, 229–30 core interaction of, 38–44, 49–59, 119, 134, 141–42, 180, 187, 189–90, 195, 199–200, 201, 202, 295 costs for, 9–10, 25, 37–38, 63, 82, 152–53, 184, 186, 209–10, 224–25, 228, 234, 265, 286, 296, 299 curation and governance of, 12, 14, 26–28, 32, 33, 34, 42, 47, 49, 51, 67–68, 72, 77, 78, 87–88, 111, 121–22, 123, 157–82, 187, 191, 192–93, 295–96, 297, 298 decision-making in, 73, 127, 139–40, 156, 169, 180, 187–88, 253–56 design of, 35–59, 90, 101, 111, 125–28, 134–35, 144, 154–56, 163, 164–65, 170–73, 179–80, 181, 182, 219, 221, 223–24, 228, 283–84, 285, 295 developers or programmers for, 6–7, 21, 30, 92, 106–7, 124, 131–32, 135, 141–49, 156, 157, 166, 173–74, 199–200 disruption caused by, vii, viii, 3, 4, 14, 60–78, 204, 231, 261–89, 296 economic impact of, vii–xi, 3, 12, 14, 60–62, 66, 72, 78, 159–61, 230, 231, 234–35, 237, 246–48, 261–89, 298–99 ecosystem of, 12, 33, 57, 64, 65, 72, 75, 77, 78, 101, 107, 132, 134–35, 152–53, 154, 158–59, 163, 165, 166, 178, 179, 182, 187, 193, 200, 212, 216, 219, 225, 262, 272, 275, 278 efficiencies of, 7–8, 10, 17, 18–20, 47–48, 60, 63, 69, 71, 72–73, 139–40, 181, 186–87, 191–92, 208, 257, 263–64, 269, 284–85, 286 externalities of, 33, 162, 163, 164, 181, 182, 229–34, 242, 257, 260, 287 fees charged by, 9, 10, 37–38, 73, 82, 106–8, 110, 113–27, 169–70, 194, 225–26, 244, 262–63, 296, 299 financial valuation of, 16–18, 33, 60–61, 79, 126 funding of, ix, 16–18, 23, 40, 51, 52–53, 92, 96, 102, 106, 111, 184–86, 276–77 future trends in, 261–89 global impact of, 104, 111, 205, 246–48, 261, 272–74 glossary for, 295–300 growth of, viii, 3–4, 14, 15, 20, 22–24, 34, 59, 76, 81–86, 97, 99–109, 145, 174, 175, 187–88, 195–99, 203–5, 230, 239–53, 259–60, 297 infrastructure of, 64, 73, 134–35, 141–46, 205, 209–10, 298 intermediation of, 68–69, 71–72, 78, 161–62, 170–71, 298 inversion by, 11–12, 15, 32–33, 211 launching of, vii, viii, 11–14, 58–59, 79–105, 88–99, 112–15, 298 layered interactions of, 49–51, 53, 54, 59, 71–72, 144–45, 169 leadership in, 33, 106–7, 189, 201, 220–21, 235, 259–60, 286–89 leverage by, 103, 206–7, 228, 263–64 management of, 10–18, 24–25, 79–109, 118–19, 121, 126–28, 134–47, 136, 152–59, 164–67, 176–203, 211, 212, 222–23, 296, 298 marketing of, 14, 19, 25, 52–53, 72, 73–74, 84–85, 100, 101, 105, 183–84, 186, 209–10, 267 match function in, 44, 47–49, 59, 187, 189–92, 193, 194–95, 202, 223, 297, 298 as nation-states, 158–61 network effects in, 16–34, 44–51, 65, 68, 78, 90–91, 108–23, 126, 128, 151, 186, 188, 196, 202, 206, 210–18, 224–34, 247–48, 257, 260, 287, 295–300 off-platform interactions and, 87, 116, 117–18, 213–15, 223–28, 250–51, 256, 297, 299, 300 outside contributors to, 10–11, 14, 74, 91–92, 103–4, 111, 119, 127, 130–33, 133, 148–49, 154–56, 173–75, 178, 189, 199–200, 206–10, 216, 219, 221, 227, 228, 240–41, 295, 296 pipelines vs., 6–10, 35, 42, 45, 46, 58, 63–68, 73–77, 89, 101, 105, 110, 123, 183–87, 220–21, 231, 258, 264, 297, 298 producers in, viii, 6, 7, 12, 19, 25–51, 60–66, 71, 87, 90–94, 101, 107–21, 125, 134, 135, 149–52, 187–92, 196–98, 203, 209–10, 212, 218–20, 223, 275, 285, 295–99 profit margins of, ix, 33, 61, 130–31, 138–41, 143, 148, 188, 197, 208–9, 215, 220, 225, 231, 233, 242, 259–60, 284, 285, 287, 296 pull-based process in, 44, 45–49, 59, 84, 86, 89, 99–100, 105, 187, 189, 223, 299 push-based process in, 84, 85, 97, 105 re-architecting of, 57–58 regulation of, 166, 199, 225, 227, 229–60, 239, 263, 274, 281–83, 287, 289 revenues of, 3, 16–18, 81–82, 83, 87, 102, 106–27, 138–41, 143, 144, 157–58, 184–88, 194, 215, 225, 285, 287 revolution in, 5, 6–15, 261–89 risk assessment and management in, 77, 117, 154–56, 162, 165–66, 170, 175–76, 180, 182, 192–93, 232–33, 237–38, 299 sales volume of, 25, 42–44, 82–83, 115–16, 157, 163, 169–70, 183–84, 186, 196, 218 scalability of, 7–8, 18–20, 24–26, 29, 34, 35, 65, 68, 71, 74, 85, 167, 206, 247–48, 262, 298 social impact of, 163, 164–65, 169, 174, 229–60, 239, 280–81, 286–89 strategies for, 204–28 transparency of, 121, 164, 166, 176–79, 182, 243, 253–56, 260 user base of, 58–59, 81–85, 86, 89–99, 118–19, 145–46, 165, 184–86, 190, 203, 215, 218–19, 222–23, 224, 295, 299 PlayStation, 94, 139, 178, 211 PlayStation 3, 139 PlayStation Portable (PSP), 178, 211 PlayStation PSP-2000, 211 “popular in your network,” 197 pornography, 67, 88, 133–34, 152, 164, 167 Porter, Michael, 207–8, 210, 213, 219 positive cross-side effects, 30, 34, 295 positive externalities, 163, 233, 287 positive feedback, 21, 82–83 positive network effects, 17, 20, 26, 28, 29–30, 32–33, 65, 78, 187, 196, 202, 225, 287, 298 positive same-side effects, 29–30, 34, 298 premium listings, 120–21 pre-roll advertisements, 223 prices, pricing: agricultural, 42–44, 60 effects of, 22, 23, 34, 298 fixing of, 169–70, 227, 240–43, 251, 252–53 free (freemium), viii, 22, 108–10, 111, 125–27, 254–55, 258 levels of, 163, 208, 232, 260, 262, 272–73, 286 predatory, 241–43, 258 strategies for, viii, 60, 69–71, 109–10, 115, 208 surge, 252–53 variable, 272–73 printing, 66, 109, 284 privacy and security issues, 79–80, 146, 159, 163, 171–73, 230, 243–48, 260, 285 privacy laws, 247–48 privatization, 232–33, 238 production: costs of, 224–25 efficiencies of, 18–19 evangelism strategy for, 96–97, 105 fraud in, 196–97 openness of, 149–52 products: design and development of, 219–20 distribution of, 19, 64, 186, 209–10 launches of, 52–53 lines of, 178–79 name spelling of, 161–62, 170–71 optimization of, 12, 254 services substitutions for, 207, 208 professional services, 8, 39, 50, 51, 73, 96, 103–4, 111, 117–18, 184–86, 190, 209–10, 218–19, 279–81, 289 Project Homeless Connect, 282 property ownership, 70–71, 124 property rentals, 1–2, 8–9, 10, 12, 64, 67, 101, 111, 142–43, 198, 224, 229–33, 236, 253, 287 proprietary model, 136, 137–39, 140, 146–49, 154–56, 240–43 prostitution, 165, 231 public good, 163, 169, 174, 230, 256–60, 280–81 public relations, 85, 105, 229–30 publishing industry, 7, 10, 63, 64, 67, 68, 71–72, 204, 208, 210, 231, 242–43, 244, 251, 262 QQ social network, 217 Quirky, 47 Quora, 30, 36, 68, 71–72, 93, 103 railroads, 209, 225 random access memory (RAM), 56, 57, 58 Rangaswami, J. P., 245–46 rate of conversion to sale, 197 ratings, 157–58, 265 razors-and-blades strategy, 109–10 Real Audio, 222 real estate market, 9, 12, 62, 124, 237, 277, 282 RealNetworks, 222 real-time processing, 247, 252–53 recipients, 100, 101, 104, 105 recruiters, 50, 51, 119, 218–19 redBus, 73, 95 Reddit, 5, 36, 47, 93, 173 Regulation 2.0, 253–56 regulatory capture, 235–37, 257 RelayRides, 9, 10, 67, 230 research and development (R & D), 14, 33, 275 reservations, 8–9, 90, 95, 101, 137, 142, 194 resources: allocation of, 6, 15, 70–71, 199, 200, 298–99 control of, 208–9, 212, 227 intensive use of, 263–64, 278, 289 model based on, 208–10, 213, 216 restaurants, 36, 37, 76, 90, 91, 95, 101, 113, 120, 142, 170, 194, 259 retail industry, 12, 63, 77, 82–83, 85, 89, 111, 123–24, 141, 145, 157–58, 204–7, 240–49, 251, 264 revenue grabs, 121, 157–58 rewards (incentives), 82, 101, 102, 166, 173–74, 182, 227 R/GA, 76 ride-sharing services, 2, 9, 12, 16–18, 25, 30, 36, 37, 49–50, 60–62, 67, 115, 175, 190, 227, 231, 233, 250–54, 258–59, 264, 278, 287, 297 Ries, Eric, 199, 201–2 Rifkin, Jeremy, 286 Roman military campaigns, 183, 237 Roth, Alvin, 164, 171 royalties, 72, 122 Rudder, Christian, 26–27 Sacks, David, 17, 18 Safaricom, 277–78 safety net, 280–81, 288 Saks Fifth Avenue, 275 sales conversion rate, 191–92 Salesforce, x, 55, 145, 245–46, 267 sales forces, 42–44, 73–74, 91, 125, 145 sales tax, 248–49 same-side effects, 29–32, 34, 298 Samsung, xi, 86, 137, 270–71, 295 San Francisco, 1–2, 18, 61, 233, 278, 281–83 SAP, vii, x, 155, 173–75, 216, 219, 241 scrapers (automated software), 91–92, 107 search engine optimization, 120–21, 145, 191, 297 search engines, 24–25, 40, 120–21, 145, 190, 191, 197–98, 215, 216, 242, 297 Sears, Roebuck, 207 seeding strategy, 18, 92–93, 105 self-driving cars, 62 self-governance, 176–80, 182, 246, 253–56 self-serve advertising, 131, 133–34 semiconductor industry, 225 senders, 100, 101–2, 105 sensor data, 246, 286 service interfaces, 176–78, 221 Shapiro, Carl, 19, 240–41 shared model, 137, 138, 140–41, 154–55 shareholders, 11, 164 sharing economy, 10, 298–99 Shleifer, Andrei, 236–37, 238 shopping malls, 123–24 ShopRunner, 206–7 ShopThis!

Vassal State
by Angus Hanton
Published 25 Mar 2024

On this basis, Gillette has built up high-margin, recurring revenues now worth over $6 billion a year.39 This system of locking people into buying consumables is now widespread, and US firms are always looking to establish this kind of dependency. The cost of recharging a Tesla car on a motorway is much more per kilowatt hour than charging it at home, in another version of the ‘razor and blades’ business model. With more than 1,000 superchargers spread across the UK and installations accelerating, Tesla’s recurring income is speeding along.40 Lock-ins like this also generate streams of monopoly profits in many industrial markets. One businessman in London told me how his suppliers tie him in: ‘If I buy a generator from Cummins, based in Indiana, I can’t get it repaired by anyone else – it needs their software and spare parts.

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Word, Excel and LinkedIn each draw users into the Microsoft world, and an owner of any Apple device will be pulled into an ecosystem of products controlled from Cupertino, California. As tech commentator John Battelle said when Facebook listed shares publicly in 2012: ‘The old internet is shrinking and being replaced by walled gardens.’38 The same psychology that keeps customers in walled gardens also promotes the ‘razor and blades’ model on which many US vendors rely. A desirable piece of hardware – such as a razor or printer – is sold cheaply, sometimes below cost, so that consumers are forced to source the consumables, such as blades or cartridges, from the same supplier. On this basis, Gillette has built up high-margin, recurring revenues now worth over $6 billion a year.39 This system of locking people into buying consumables is now widespread, and US firms are always looking to establish this kind of dependency.

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Their software engineers make games which are highly addictive, and players have to pay extra for ‘in-app purchases’, so although an initial purchase may be for only 60 per cent of a game, extra features will cost more. One outstanding company in the sector is Steam, based in Bellevue, Washington State, which created the best place to find new games. Thousands of creators add more than 14,000 new games each year and generate a handsome royalty for the company.16 It is almost the perfect business model: with no physical delivery needed, no development costs and worldwide reach, the business produces a torrent of cash. So, like many other US companies in the UK, it has become the indispensable marketplace where buyers and sellers meet: the toll bridge over which all must cross. And, in common with hundreds of US companies operating in the UK, they pay minimal tax: historically Steam’s sales have often been routed through Luxembourg.17 Or perhaps we are tired of games and want to go to a real event, for which we get out our laptop, probably made by Dell of Texas or Apple of California, and find we have received an email from Mailchimp of Georgia inviting us to sign up through Eventbrite of San Francisco.

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives
by Peter H. Diamandis and Steven Kotler
Published 28 Jan 2020

See also: “Population, Total,” World Bank, https://data.worldbank.org/indicator/SP.POP.TOTL. Force #6: New Business Models a 2015 article in the McKinsey Quarterly: Marc de Jong, “Disrupting Beliefs: A New Approach to Business-Model Innovation,” McKinsey Quarterly, July 2015. See: https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/disrupting-beliefs-a-new-approach-to-business-model-innovation. “bait and hook”: Randal C. Picker, “The Razors-and-Blades Myth(s),” University of Chicago Law Review, February 6, 2011. See: https://lawreview.uchicago.edu/publication/razors-and-blades-myths. “franchise models”: Kerry Pipes, “History of Franchising: Franchising in the Modern Age,” Franchising.com.

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To unlock the next wave of growth, companies must embed these innovations in a disruptive new business model.” And for those of us on the outside of these disruptive models, our experience will be better, cheaper, faster. Better meaning new business models do what all business models do—solve problems for people in the real world better than anyone else. Cheaper is obvious. With demonetization running rampant, customers—and that means all of us—are expecting more for less. But the real shift is the final shift: faster. New business models are no longer forces for stability and security. To compete in today’s accelerated climate, these models are designed for speed and agility.

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If network size, density, and fluidity have turned cities into the best transformation engines we’ve yet managed to create, then the fact that we are about to link the entire globe into a single network means the whole planet is just a few years away from becoming the largest innovation lab in history. Force #6: New Business Models Traditionally, innovation means the discovery of breakthrough technologies or the creation of new products or services. But this definition doesn’t capture some of the most potent innovation taking place today: the creation of new business models. A business model is the systems and processes a company uses to generate value. For most of history, these models were remarkably stable, dominated by a few key ideas, upgraded by a few major variations on these themes.

The Content Trap: A Strategist's Guide to Digital Change
by Bharat Anand
Published 17 Oct 2016

Some studio executives would acknowledge years later that the industry had lost time fighting piracy rather than creating new business models The single-minded fixation on negative connections had buried the possibility of capitalizing on positive ones. COMPLEMENTS VERSUS SUBSTITUTES—AND THE ROLE OF MANAGERIAL CHOICE Textbook descriptions of complements would lead you to believe that complements are either present in your business, or they’re not. Hardware and software. Printers and cartridges. Game consoles and games. Gasoline and cars. Razors and blades. Lamps and bulbs. Each without the other is useless. Compete on one of these products and you must have the other to provide value.

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These are fine prescriptions for optimizing market share in your own business. But when your entire industry comes under threat, these prescriptions cause you to adopt an overly narrow lens and define too-restrictive boundaries. Some complements are obvious: Hot dogs and ketchup, printers and cartridges, razors and blades, right and left shoes. But many are not. A tire manufacturer offers restaurant guides, eventually becoming so successful in doing so that it creates a worldwide standard for assessing food quality. It’s not that making tires somehow translates into skill at recognizing good food; it’s that making customers aware of high-quality food in faraway places spurs driving.

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Yet in 2013, nearly all of Facebook’s revenues derived from advertising, whereas more than 80 percent of Tencent’s came from user charges. How could two companies with similar products, similar user bases, and similar operating financials have such different business models? It’s natural to ask, Which model is “better”? But if you look at the business models in the context of connections, you’ll realize that’s the wrong question to ask. One difference between the two companies, as I’ve described earlier, involves virtual currency. Tencent makes nearly all its money through virtual currency, Facebook nearly none.

Tech Titans of China: How China's Tech Sector Is Challenging the World by Innovating Faster, Working Harder, and Going Global
by Rebecca Fannin
Published 2 Sep 2019

At first glance, Xiaomi may seem like a hardware company only with smartphones and smart TVs, but it’s actually succeeded as the “first internet-of-things company with an array of smart hardware products,” notes tech and media analyst Ben Thompson, founder of Stratechery.7 Thompson points out that Xiaomi is the rare company that has succeeded in both hardware and software, adding that Alibaba and Amazon (with Kindle) have dabbled in hardware but not as a core business. Xiaomi effectively uses the razor and blade marketing scheme of selling one item at a low cost to increase sales of a complimentary item. Xiaomi keeps the cost of its smartphones and smart household goods at a level that limits profit margins to only 5 percent. This helps to build a customer base. Then it hooks those users on its multiple apps for music, videos and games that are monetized with advertising, subscriptions, and virtual gifts. Take a lesson, Apple! From Rice Cookers to Electric Scooters Another twist in the Xiaomi business model comes from some 100 partner companies that it incubates or invests in.

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Lei claims there’s never been another smartphone maker that successfully rebounded after a sales decline. He and his team put in the hours—“007,” a reference to all hours every day of the week—to make it happen. Xiaomi Advantage: Hardware and Software Xiaomi’s business model is another aspect of its creativity—it’s described by founder Jun as a “triathlon business model” comprised of three synergistic pillars of growth. Handset sales account for the bulk, or about 70 percent, of Xiaomi revenues; IoT gadgets and consumer goods (even spinning wheel suitcases) bring in 22 percent; and internet value-added services, such as games, account for 9 percent.

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See also Mobike; Ofo Bilibili, 83 Blecharczyk, Nathan, 115 Bob Xu, 135 Booking.com, 90 Bo Shao, 138 Breadtrip, 116 Breyer, Jim, 128, 138 Brin, Sergey, 34–35 Buffett, Warren, 208 ByteDance, 31–32, 43, 81–89, 130, 143, 153 C CalPERS (California Public Employees’ Retirement System), 134 CalSTRS (California State Teachers Retirement System), 134 Caltech university, 11 Carlyle Group, 38, 51 Carmen Chang, 142 Carnegie Mellon university, 11 Chan, Connie, 138 Charles River Ventures, 137 Cheetah Mobile, 66, 88 Cheng Wei, 176, 181–183 Chenyu Zheng, 112 Cherubic Ventures, 169 Chesky, Brian, 115 China acquisitions and investments in US tech companies, 53 Belt and Road initiative, 12 car market, 197–210 central business districts, 9 coffee culture, 102 coffee retail market, 103 comparing BAT with US Tech Leaders, 30 consumer economy, 93 Cultural Revolution of the 1960s and 1970s, 28 data privacy issues and monitoring of personal information, 47, 106 data privacy rules, 6 digital economy, 26 digital markets, 8 e-commerce landscape, 185–195 economic development, 14 entrepreneurial culture, 11–12 global tech leadership, 11–12 high-tech giants, 3–4 innovations and business models, 18–20 internet censorship, 15 “Internet Plus” plan, 12 investment in Hollywood, 52–55 investment in US tech companies, 21 “Made in China 2025,” 12 national R&D spending, 13 New Era Technology Fund, 12 number of internet users, 14 patent filings, 13 pointers to win in, 107–108 rise as a tech superpower, 225 robotics and drone market, 212 sharing economy, 175–176 social credit system, 19 startup zeal, 10–11, 16 STEM graduates in, 13–14 supercomputers, 14 tech companies, 50–51 tech economy, 7 tech giants of, 14 tech hubs, 143–144 tech influence and power, 22 tech innovation, 10 tech inventors, 2–3, 5 tech investments, 13 tech IPOs, 20 types of technology phases, 132–133 venture capital market, 12, 130–158 wireless infrastructure and cell sites, 17 world-changing tech sector, 223–224 China Broadband Capital, 112 Chinaccelerator, 214 China Construction Bank, 171 China Creation Ventures, 134, 148 China International Capital Corp., 103 China Investment Corp, 172 China UnionPay, 168 China venture capitalists, 128 Chinese consumers, 3 Chinese culture, 22 Chinese economy, 3 Chinese internet brands, 15 Chinese IPOs, 131 Chinese tourism, 113 ChiNext, 135 Chrysler, 209 Chuhai, 56 City Brain, 163 CloudKitchens, 175 Cloud Valley, 119 Coach handbags, 9 Cohen, Brian, 121 Colin Huang, 185, 192–193 Committee on Foreign Investment (CFIUS), 55 Connie Chan, 86 Consumer Electronics Show (CES), Las Vegas, 32–33 Cook, Tim, 32 Costa Coffee, 102 Costco, 186 Coworking, 111 Creagh, Eleanor, 93 Credit Suisse, 171 CSC Upshot Ventures, 146 D Da-Jiang Innovations, 218 Dalian Wanda, 54 DAMO (discovery, adventure, momentum, and outlook) Academy, 56 Dangdang, 44–45 Daniel Zhang, 49 Danke Apartment, 106 David Chao, 154–155 David Li, 81 David Yuan, 157 DCM Ventures, 84, 106, 154–156 Deng Xiaoping, 16, 28, 128 Derrick Xiong, 217 Dick Clark Productions, 52, 54 Didi, 21, 42, 60, 69, 98, 104, 176–179 international operations, 182–183 safety issues, 184 vs Uber, 179–182 Didi Brain, 178 Didi Chuxing, 20, 44, 69, 173–174 DingTalk, 31, 106 DJI, 5, 211–212, 215–220 Doerr, John, 128, 139–140 Donovan Sung, 73 Douyin, 82, 89 Draper, Tim, 52, 136–137 Draper Associates, 137 Draper University, 137 Dropbox, 218 DST Global, 78 Duoduoyou, 95 Duoshan, 43, 85 E EachNet, 138 EBay, 15, 28, 52, 85, 96, 104, 216 Eclipse Ventures, 220 EHang, 5, 152, 216–217 EHi Car Services, 153 Ele.me, 42, 61, 157, 211 Elephant Robotics, 213 11Main.com, 191 Evans, Michael, 50 Evdemon, Chris, 50 Evernote, 104, 117–119 EyeVerify, 63 F Face++, 29, 165 Facebook, 1, 5, 10, 15, 26, 28, 30–32, 43–45, 48, 52, 82, 84, 87, 104, 115, 128, 132, 162, 218 Facial recognition systems, 2 Fallon, Jimmy, 85 Fandango, 90 Fanfou, 95 FANGs, 26, 50 Fang Xingdong, 138 Faraday Future, 207 FAW Group, 33 Fintech, 19 Fire in the Valley, 68 Fishtrip, 116 Flipagram, 88 Fong, Kevin, 137 Ford, 204, 209 Fortnite, 66 Foster & Partners, 216 Fountown, 110 4Paradigm, 165 Francis Leung, 161–162 Frank Wang, 216–218 Freshippo, 98 Friendster, 43 G Gaopeng, 95 Gates, Bill, 208 General Atlantic, 38, 51 General Catalyst Partners, 117 General Motors, 51, 209 Gen Z youngsters, 6 Gerson Lehrman Group, 107 GGV Capital, 11, 55, 86, 112 Glen Sun, 120, 127 Gobi Partners, 149 Go-Jek, 57 Golden Gate Bridge, 11 Goldman Sachs, 151 Google, 10, 15, 26, 28, 33–34, 45, 52, 57, 75, 79, 95, 104, 115, 127–129, 132, 144, 162, 178, 191, 193 Google China, 34–35 Google Pay, 5, 32 GoPro, 219 Grab, 57 Granite Global Ventures (GGV), 138, 143, 151–154, 169, 198, 217 Graziani, Thomas, 186 The Great Wall, 53 Great Wall Motors, 208 Groupon, 15, 43, 69, 95–96, 104, 186 GrubHub, 90 GSR Ventures, 138, 157 Gu, Amy, 118 Guangzhou Automobile Group, 207 Guinn, Colin, 219 Gullicksen, Ken, 118 H Hainan Airlines, 168 Hans Tung, 11, 55, 78, 120–121, 153, 192 Hao, Robert, 115 Haokan, 85 Hariharan, Anu, 87 Harvard university, 11 HAX accelerator, 213–214 Hearst Ventures, 169 Hemi Ventures, 118 He Xiaopeng, 197, 203–206 Hikvision, 162 Hillhouse Capital, 112, 175, 198 Hilton, 9, 54 Hoffman, Reid, 105 Hollywood, 52–55 Hong Ge, 115 Horizon Robotics, 213 Horizon Ventures, 112 Horowitz, Andreessen, 52, 86, 138 Hortons, Tim, 102 H&Q Asia Pacific, 102 Huahua Media, 54 Huami, 77 Huang, 186 Huawei, 5, 13, 16, 73, 76 Hurst Lin, 120, 155 Hyatt, 9 Hyundai, 28 I IBM, 162 IDG Capital, 138, 193, 198 IFlytek, 163 ING Group, 171 Instagram, 1–2, 15, 51 Intel, 16, 144 International Finance Corporation, 171 IPhone, 70 IQiyi, 19, 60, 84 Israel, 56 J Jack Ma, 3, 26, 28, 45, 47, 49–50, 52, 56, 78, 99–100, 135, 154–155, 191 JAFCO Asia, 154 James Mi, 121, 156, 193 Janow, Merit, 17 Japan, 56 JD.com, 18, 29, 38, 88, 98, 147, 185, 187–189, 191, 211 Jenny Lee, 154 Jerry Yang, 106, 154 Jet Li, 52 Jian Lu, 106 Jing Bing Zhang, 219 Jobs, Steve, 3, 68 Joe Chen, 44 Joe Zhou, 140 Johnson, Kevin, 101 Joy Capital, 103 Joyo.com, 75 JPMorgan, 115 Jurvetson, Draper Fisher, 134 K Kabam, 63 Kai-Fu Lee, 34, 123, 147, 165 Kalanick, Travis, 175, 181 Karma Automotive, 207 Katzenberg, Jeffrey, 85 Kayak, 69, 90 Kellman, Joel, 152 Kentucky Fried Chicken, 9 Keytone Ventures, 140 Khazanah Nasional Berhad, 171 Khosla, Vinod, 138 Khosla Ventures, 134, 138 Kingsoft, 74–75, 79 Kitt.ai, 163 KKR, 83 Kleiner Perkins, 140, 148 Koubei, 61 Kramlich, Dick, 139, 142 Kr Space, 110 Kuaidi, 173, 181 Kuaishou, 66, 84–85, 156 L LAIX, 169 Lam, David, 146 Lashou, 95–96 Lasso, 32, 84 Lau, Marvin, 64 Lazada, 58 Lazada Group, 58 League of Legends, 64 Lee, Jenny, 123 LeEco, 54 Legend Capital, 155, 171 Lei Jun, 44, 68, 71, 74–76, 79, 81, 135, 152 Leju, 66 LendingClub, 171 Leone, Doug, 129 LG, 28 Libin, Phil, 117–118 Lightspeed China Partners, 156, 193 Li Guoqing, 44 Li Haipeng, 175 Li Ka-shing, 171 Lin Haifeng, 193 LinkDoc, 169, 171–172 LinkedIn, 15, 104 LinkedIn China, 104–107 Lip-Bu Tan, 139 Little Elephant market, 98 Little Red Book, 189–190 Liulishuo (LingoChamp), 154 Live.me, 88 Livestreaming, 19, 80–81, 88 Li (David) Xueling, 199 Li Zexiang, 217 Li Zhaohui, 67 Lo, Vincent, 152 Long Hill Capital, 148 Lonsdale, Jeff, 138 Luan, Pan, 67 Luckin Coffee, 99–100 business model, 103 Lu Qi, 33 Lyft, 21, 51, 178, 183 M Macquarie Group, 115 Made-in-China business models, 10 Made in China 2025 initiative, 172, 200, 208, 212, 224 Magic Leap, 21 Ma Huateng (Pony Ma), 28 Mail.Ru, 29 Maimai, 106 MakeBlock, 213 Marriott, 9 Marvell, 15 Massachusetts Institute of Technology, 94, 168 Master-Card, 32 Matrix China Partners, 138 Matrix Partners, 138 Matrix Partners China, 110, 138, 198 Mavic Pro, 218 Mayfield, 51, 137–138 Mayi.com, 116 McDonald’s, 9 Meeker, Mary, 140 Megafunds, 134 Megvii, 165 Meituan, 175, 189 Meituan Bike, 175 Meituan Dianping, 20–21, 38, 42–43, 61, 69–70, 89–98 bike-sharing business, 94 competitors, 93 deliveries, 91–93 merger, 96–97 revenues, 94 travel and hotel segment, 93–94 Meizu Zero, 72 Messenger, 51 Mi.com, 71 Micron Technology, 16 Microsoft, 30, 33, 75, 79, 144, 162, 193 Milner, Yuri, 78, 83, 171 MIT university, 11 Mobike, 21, 61, 94, 151, 174–175 Mobile payments, 5, 19 MoneyGram, 55, 63 Morgenthaler Ventures, 118 Moritz, Mike, 11, 51, 128–129 Morningside Venture Capital, 84, 198 MOX, 214 Musical.ly, 83, 87–88 MySpace, 28 N Naked Hub, 108–111 Naspers, 66 Neil Shen, 97, 119 Netflix, 26, 48, 81 Netscape, 52 Neumann, Adam, 109 New Enterprise Associates, 51 New Enterprise Associates (NEA), 141–143 New Oriental Education & Technology Group, 135 New Space, 110 New York–based RRE Ventures, 133 Ng, Thomas, 152 Nike, 218 Nike shoes, 9 NIO, 2, 19, 200–201, 206–207 Nuomi, 96 Nvidia, 196 O Ofo, 61, 128, 138, 157, 174–175 On-demand ordering and delivery of takeout orders, 5 O2O, 97 OpenTable, 90 OPPO, 76, 168 Optibus, 56 Oracle, 129 O’Sullivan, Sean, 123, 214 P Page, Larry, 29, 34 Palo Alto, 52 Panda Selected, 175 Parrot, 220 PayPal, 31, 46, 128 Peggy YuYu, 44 Penaloza, 107 Penaloza, Dominic, 107 Perkins, Kleiner, 134 Perkins, Tom, 132 Pinduoduo, 2, 29, 66, 134, 185–188, 192–195 Ping An, 137 Pinterest, 15, 104 Pony Ma, 3 PPDAI Group, 171 Primavera Capital Group, 198 Princeton university, 11 Project Dragon, 15 Project Dragonfly, 104 Q Qiming Venture, 95, 175 Qiming Venture Partners, 129, 150–151 Qiye Weixin, 42, 106 QQ instant messaging service, 29 QR code, 109 QR (quick response) code, 1–2 Qualcomm, 15, 144 Qudian, 171 Quixey, 63 Qunar, 60 R Rational Robotics, 214 Reddit, 64, 88 Redpoint China, 157 Redpoint China Ventures, 133 Renren, 44 Retail commerce, 18–19 Revols, 214 Rework, 110 Richard Chang, 142 Richard Ji, 116 Richard Liu, 78, 123 Rieschel, Gary, 8, 16, 120, 122, 129, 150–151 Riot Games, 64 Robin Li, 3, 28, 33–35, 60, 122 Robinson, Jim, 121, 133 Robotics and drone market, 212 Roomba, 214 Rui Ma, 186 S Samsung, 28, 70, 76 Sandell, Scott, 141 Schultz, Howard, 100 SenseTime, 2, 29, 161, 167–169 camera surveillance technology, 162 Sequoia Capital, 11, 110, 129, 171, 175 Sequoia Capital China, 84, 95, 97, 105, 112, 119, 127–129, 194, 213, 218 Sequoia CBC Cross-Border Digital Industry Fund, 119 Serendipity Labs, 111 Sesame Credit system, 6 7Fresh, 189 7Fresh stores, 98 Shanghai Automotive Industry Corp., 208 Shanghai-based Qiming Venture Partners, 8 Shanghai World Financial Towers, 9 Shen, Neil, 128–129, 194 Shenzhen, 2 Short video entertainment apps, 7 Silicon Dragon, 109 Silicon Valley, 20–22, 27, 29, 31, 33, 42, 44, 50–52, 60, 63, 68–69, 79, 95, 105, 117, 129, 132–134, 137–143, 145–146, 150, 153, 158, 178, 192, 196, 199, 204–205, 218–220, 223–225 Silver Lake Partners, 38 Simon Loong, 171 Sina Corp., 95 Sino—US Venture Investors, 135–136 Sinovation Ventures, 110, 146, 165–166 Skype, 1 Snap, 64 Snapchat, 81, 84 Lens Challenges, 69 Social commerce, 20 SoFi, 44 SoftBank, 38, 51, 83, 138, 151, 183 Sonny Wu, 157 Southeast Asia, 56–57, 149 Alibaba and Tencent Investments in, 59 SpaceX, 51, 220 Spielberg, Steven, 52 SQream Technologies, 56 Squawk Box, 86 Stanford university, 10 Starbucks, 15, 99–100, 102–104, 111 initiative with Alibaba, 100–101 Reserve Roastery, 101–102 Startup Asia, 57 “Startup Nation” of Israel, 56 Steven Ji, 128 STX Entertainment, 52 Su Hua, 85 Sun Microsystems, 128 Supercharging stations, 7 T Tai, Bill, 137 Ta-lin Hsu, 102, 139 TangoME, 63 Tang Xiaoou, 167 Taobao, 28, 185, 187 Tao Peng, 113 TechSauce, 148 Temasek, 172 Tencent, 12–13, 20–21, 26, 28–32, 38, 44, 46–48, 51–52, 57, 61, 70, 80–81, 83, 95, 138, 147, 153, 163–164, 171, 190–191, 197, 206, 224 China Literature, 41 corporate culture, 63 diversification strategy, 67 gaming business, 40, 64, 66 growth of, 39–40 social networking service, 41–42 strategic investments, 63–66 in US, 52, 63–65 war with ByteDance, 85 youth culture, 39 Tencent Music Entertainment, 41 Tencent Video, 41, 84 Terminator: Dark Fate, 53 Tesla, 2, 15, 64, 196, 209–210, 220 Thiel, Peter, 138 Thompson, Ben, 77 Tian, Edward, 118–119 Tian Xu, 193 Tiger Computing Solutions, 163 TigerGraph, 163 Tiger Qie, 178 TikTok, 2, 21, 29, 31–32, 39, 43, 66, 69–70, 82, 84, 87 Tina Ju, 140 TMD, 43–44, 69 Tokopedia, 58 The Tonight Show, 85 3D Robotics, 219–220 TopBuzz, 82 Toutiao (Today’s Headlines), 21, 69–70, 80–81, 86–88 Traffic Brain, 178 Trump, Donald, 15, 45, 54–55, 164, 191 Tsai, Joe, 50 Tujia, 116 Twitch, 51 Twitter, 1, 15, 28, 43, 47, 84, 87, 104 U UBazaar mobile, 111 Uber, 21, 44, 51, 57, 60, 64, 83, 103–104, 128, 144, 173, 176–183 Uber Eats, 69, 90 Ubisoft, 64 UBTech, 213 UCAR, 103 UC Berkeley, 11 Ucommune, 110–111 UCWeb, 200 URWork, 110 US-China trade imbalance, 15 Ushi, 107 US IPOs, 131 US market, 46 US privacy laws, 7 US venture fund performance, 130 V Valentine, Don, 132, 139 VC Dixon Doll, 155 Venture capital market of China, 12, 130–158, 224 AI startups, 166 center of gravity for venture investing, 158 cross-border investors, 145–146 digital Silk Road, 136–139 funding for Asian companies, 148 history as a budding venture superpower, 139–140 investment returns, 141 investments in tech companies, 132–135 NEA’s China investing, 141–143 Sino—US Venture investment, 135–136, 146–148 venture firms, 150–158 Video streaming market, 2, 6, 19, 60, 83, 85, 154 Viomi, 77 VIPShop, 189–190 Vipshop, 156 Virtual gifts, 6 Virtual reality, 19 Visa, 32 Visualead, 56 Vivendi, 64 Vivo, 76 Vizio, 54 Volvo, 204 W Waimai, 60 Waldorf Astoria Hotel, 54 Walmart, 57–58 Wang Xing, 43, 89, 91, 94–95, 97 Wang Yi, 169 Wanka Online, 148 Warburg Pincus, 38 Warner Brothers, 51 Wayne Shiong, 121 Waze, 51 WeChat, 1–2, 29, 31, 34–35, 41–43, 46, 82, 106, 115, 144, 177, 187, 191, 197 WeChat Moments, 85 WeChat Pay, 5, 19, 32, 63, 182–183 WeDefend, 170 Wedo, 110 WeFlex, 170 Weibo, 35, 47, 82, 168, 197 Weiner, Jeff, 105–106 Weixin, 41 Wei-Ying Ma, 89 Wei Zhou, 121, 134 WeLab, 170–171 WeReach, 170 WeWork, 15, 104, 111 WeWork China, 108–111 WeWork Go, 109 WhatsApp, 1, 43, 51 Whitman, Meg, 85 William Li, 200, 206 Williams, David, 52 Wilson Sonsini Goodrich and Rosati (WSGR), 142–143 Wonder Woman, 52 Woo Space, 110 Workingdom, 110 Wu Xiaoguang, 199 X Xiadong Jiang, 172 Xia Huaxia, 92 Xiaodong Jiang, 142 Xiaomi, 20–21, 68–70, 75, 138, 141, 153, 168 business model, 76–79 core strength of, 73 customers, 72 growth, 72–73 international market, 79–80 Mi Home store locations, 73–74 mobile phone features, 70–71 range of internet-connected devices, 71 sales, 75–76 US market, 73–74 Xiaomi Finance, 80 Xiaonei, 95 Xiaopeng He, 122 Xiaozhu, 116 Xi Jinping, 12, 47, 208 Xpeng Motors, 19, 196–197, 200, 203–206 XPerception, 164 XTMD, 69 Xu Li, 161, 168–169 Y Yahoo!

Democratizing innovation
by Eric von Hippel
Published 1 Apr 2005

Current efforts by manufacturers to build technologies into the products they sell that restrict the way these products are used can undercut users’ traditional freedom to modify what they purchase. This in turn can raise the costs of innovation development by users and so lessen the amount of user innovation that is done. For example, makers of ink-jet printers often follow a razor-and-blade strategy, selling printers at low margins and the ink cartridges used in them at high margins. To preserve this strategy, printer manufacturers want to prevent users from refilling ink cartridges with low-cost ink and using them again. Accordingly, they may add technical modifications to their cartridges to prevent them from functioning if users have refilled them.

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At the same time, the ongoing shift of product-development activities from manufacturers to users is painful and difficult for many manufacturers. Open, distributed innovation is “attacking” a major structure of the social division of labor. Many firms and industries must make fundamental changes to long-held business models in order to adapt. Further, governmental policy and legislation sometimes preferentially supports innovation by manufacturers. Considerations of social welfare suggest that this must change. The workings of the intellec- Introduction and Overview 3 tual property system are of special concern.

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The custom semiconductor industry was an early adopter of toolkits. In 2003, more than $15 billion worth of semiconductors were produced that had been designed using this approach. Manufacturers that adopt the toolkit approach to supporting and channeling user innovation typically face major changes in their business models, and important changes in industry structure may also follow. For example, as a result of the introduction of toolkits to the field of semiconductor manufacture, custom semiconductor manufacturers—formerly providers of both design and manufacturing services to customers—lost much of the work of custom product design to customers.

Big Data: A Revolution That Will Transform How We Live, Work, and Think
by Viktor Mayer-Schonberger and Kenneth Cukier
Published 5 Mar 2013

The aircraft engine-maker Rolls-Royce completely transformed its business over the past decade by analyzing the data from its products, not just building them. From its operations center in Britain, the company continuously monitors the performance of more than 3,700 jet engines worldwide to spot problems before breakdowns occur. It used data to help turn a manufacturing business into a razor-and-blades one: Rolls-Royce sells the engines but also offers to monitor them, charging customers based on usage time (and repairs or replaces them in case of problems). Services now account for around 70 percent of the civil-aircraft engine division’s annual revenue. Startups as well as old stalwarts in new business areas are positioning themselves to capture vast streams of data.

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For Etzioni’s next startup, one can presume that he’ll try to supply the data himself, since the value has migrated from the expertise to the idea and is now moving to the data. Business models are being upended as the value shifts to those who control the data. The European carmaker that struck the intellectual property deal with its supplier had a strong in-house data-analysis team but needed to work with an outside technology vendor to uncover insights from the data. The tech firm was paid for its work, but the carmaker kept the bulk of the profits. Sniffing opportunity, however, the tech company has tweaked its business model to share some of the risk and reward with clients. It has experimented with working for a lower fee in return for sharing some of the wealth that its analysis unleashes.

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Big data changes the nature of business, markets, and society, as we describe in Chapters Six and Seven. In the twentieth century, value shifted from physical infrastructure like land and factories to intangibles such as brands and intellectual property. That now is expanding to data, which is becoming a significant corporate asset, a vital economic input, and the foundation of new business models. It is the oil of the information economy. Though data is rarely recorded on corporate balance sheets, this is probably just a question of time. Although some data-crunching techniques have been around for a while, in the past they were only available to spy agencies, research labs, and the world’s biggest companies.

Fabricated: The New World of 3D Printing
by Hod Lipson and Melba Kurman
Published 20 Nov 2012

In fact, the cost of plastic printing material quickly adds up to become a significant part of the cost of running a 3D printer. Most 3D printer manufacturers provide their own proprietary material. At ABC Imaging when John showed me buckets full of commercial-grade printing powder, he likened the cost of 3D printing plastic to the infamous “razor and blades” business model. “It’s like Gillette,” he said. “They give away the razor but you can only get the cartridges that fit from Gillette.” The fact that industrial 3D printing technology is optimized to print proprietary vendor-specific 3D printing materials either dampens or drives innovation, depending on who you ask.

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Despite these advantages, 3D printed manufacturing offers no economies of scale. Like any extreme personality characteristic, the fact that 3D printing fails to provide economies of scale is both its biggest weakness, but also its biggest strength. Harnessing economies of scale is critical to a company whose business model is based on selling large volumes of a commodity product that earns razor-thin margins. However, if a company’s business model is based on selling small numbers of unique, constantly changing or custom-made high margin products, 3D printed production (like the platypus) represents an evolutionary leap forward. 3D printing and design technologies make design and manufacturing more nimble.

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In other words, opportunity lies in business models where profits are not reliant on economies of scale. Imagine, for example, if my car mechanic (a great skeptic of the existence of car repair that is good, fast, and cheap) decided to venture into a new line of business: 3D printing car tires. This would be a bold business strategy for him, given that car tires are a classic, mass-produced commodity product. In a corner of the greasy hanger where he fixes cars, he would install a 3D printer that could create precise shapes in high-grade, durable tire rubber. Out of the gate, let’s suppose his first business model would be to make and sell 3D printed tires identical to the brand name tires sitting in his inventory.