Defining the Tipping Point.
In this column, I'm taking a slightly different approach, looking at a term that is less used than perhaps it should be--tipping point. The term entered popular consciousness almost two decades ago, via Malcolm Gladwell's 2000 book; Gladwell defines a tipping point as "the moment of critical mass, the threshold, the boiling point." More generally, it is the moment at which some slow change in a system becomes irreversible, triggering dramatic, and sometimes unexpected, consequences. Gladwell likely borrowed the term from sociology--it was adopted in the 1960s to describe the phenomenon of white flight--but its roots are in physics. Originally, it described the point at which a thermostat would toggle a mechanical switch. It's a popular term just now in climate change discussions--scientists are trying to determine the tipping point for atmospheric carbon, the point beyond which global warming is irreversible. Gladwell used tipping point to describe the way an idea (or a product) can percolate along in culture, known to only a few, and then suddenly erupt everywhere, changing the way an entire culture thinks or acts apparently overnight.
Gladwell's concept of tipping point relied on the concept of social contagion; he was among the first to popularize the metaphor of virality for the way ideas spread. As Gladwell sees it, ideas, like viruses, are transmitted by a few influential people through their networks; at a certain point, so many people have heard an idea that it becomes pervasive, inescapable, just as a virus becomes an epidemic. Some thinkers debate the aptness of the analogy (see Sarah Frankel's article on the debate), but it does provide a way of thinking about how ideas--or products--gain traction.
But whether it's a virus, an idea, or a product, the progress of an epidemic is unpredictable; it's difficult to tell where an idea might catch attention, or whether a product will be "sticky" enough to become more than a fad. The history of innovation is rife with very smart people who missed big ideas. DEC president Ken Olsen is famous for saying he could see no reason anyone would have a computer in the home (although the quote may be apocryphal or not Olsen's; see Quote Investigator's account of its provenance). Many others have gotten it at least as wrong: IBM CEO Thomas Watson foresaw a global market for "maybe five computers," and Western Union's leaders dismissed the telephone as "inherently of no value to us," citing the new machine's many shortcomings. The president of the Michigan Savings Bank, advising against an investment in the Ford Motor Company, dismissed the automobile as "a novelty--a fad." If you're interested in more such horror stories, see List25's "25 Famous Predictions That Were Proven to Be Horribly Wrong."
These companies missed the boat for one reason: they failed to see past the technical maturity of a new technology to its game-changing potential. The telephone did, indeed, have many shortcomings in 1876; in 1903, automobiles were slow and loud and dangerous--not to mention ruinously expensive. And there were no obvious markets for either product. As Ford himself is rumored to have said, "If I had asked people what they wanted, they would have said faster horses." (This quote, too, is probably apocryphal; Patrick Vlaskovits details his fruitless efforts to run the source down in an HBR article on the shortcomings of Ford's model.)
Other companies--companies with all the right technology and even a little bit of foresight--miss tipping points out of fear. Fear of cannibalization kept Kodak from embracing digital cameras, an industry the company was naturally positioned to lead. (Kodak's downfall has been widely discussed; Chunka Mui offers a good summary in Forbes.) As Greg Satell details, also in Forbes, Blockbuster refused an overture from Netflix at least partly out of fear of upending its business model, which relied heavily on late fees.
Still others have made their fortunes by anticipating a tipping point, or by figuring out how to create it. Henry Ford made the automobile a possibility for the middle class, and in the process reshaped the transportation industry. Steve Jobs figured out that people wanted something between their iPhone and a full-scale laptop and created the tablet computer market.
Satell ultimately describes Blockbuster's failure as a failure to understand the power of networks--networks of consumers, specifically--to grow, or kill, the company. Netflix grew largely by word of mouth; early adopters told their friends how great the concept worked (and how much they loved not having to pay late fees), and those friends listened. Eventually, that advantage came to outweigh the disadvantages of not having a physical store where customers could browse videos.
Satell's analysis points not to Gladwell but to an older model for the diffusion of ideas: Everett Rogers's diffusion of innovations model. Rogers introduced the adoption curve we all know, from innovators to early adopters, through early and late majorities, to laggards. Rogers, a sociologist, tracked how innovations gained momentum as more and more people got comfortable with the new ideas. He built on the threshold model developed by sociologists to describe how collective behavior emerges; the threshold model suggests that an individual's behavior is determined by the behavior of others around him or her. Once a certain number of people engage in a given behavior or make a given decision, it becomes much more likely than any other person will. This is the threshold--and it's also Gladwell's tipping point.
By now some number of you are impatiently waiting for me to get to the point: that what we are describing here is essentially disruption. And that's kind of true. The tipping point is where disruption becomes inevitable, where incumbents must adapt quickly or die. In some cases, it may be the point at which adaptation is impossible--Blockbuster made a late attempt to eliminate late fees and add an online service, but Netflix had already grabbed the market.
But there is one critical distinction: disruption has typically been characterized as an attribute of technology or of the market; tipping points are about people and the relationships between them. Clayton Christensen coined the term to refer to the phenomenon of technically inferior but "good-enough" technical options undermining the competitive advantage of even the strongest incumbents by serving customers who were not attracted by the incumbents' higher-end offerings. Today, the discussion has expanded to a wider consideration of the market, but it still doesn't focus on people as such. Like John Farrell's analysis for Forbes, in partnership with KPMG, disruption analyses focus on identifying "weak signals" in the midst of "marketplace noise" through ethnographic research and trends analysis. Ron Adner and Rahol Kapoor, in their HBR article, pinpoint the weakness of such an analysis: "Although we have become quite savvy about determining whether a new innovation poses a threat, we have very poor tools for knowing when such a transition will happen."
By contrast, Gladwell--and before him, Rogers and threshold model scholars--looks at how people are connected to each other and how those connections spread ideas and behaviors. This kind of analysis has little to do with technical attributes or even with market trends; if the right people adopt a product, and share their find with others in their network, they can propel a sleepy niche brand to the top of the market. Glad-well offers as an example Hushpuppies, which had been a quiet little shoe brand until key influencers began wearing its shoes in the 1970s. Suddenly, Hushpuppies were everywhere. No trend analysis, no technology scouting could have predicted that outcome.
We are likely on the cusp of at least one tipping point. We all know, for instance, that artificial intelligence is likely to change business and daily life radically. But how? Where is the first mainstream breakthrough going to come from? And when is the right time to make the big bet? First movers can gain a massive advantage, but those who jump too early can lose it all. We'll talk more in my next column about tools for tracking and predicting tipping points.
In this space, we offer a series of summaries on key topics, with pointers to important resources, to keep you informed of new developments and help you expand your repertoire of tools and ideas. We welcome your contributions, in the form of suggestions for topics and of column submissions.
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