Companies that can predict when a new technology will gain widespread market adoption have a huge advantage over competitors. Mark Gottfredson, a partner with Bain's Strategy practice, discusses how combining insights from four commonly used tools can help companies better predict if, when and how extensively a new technology will take off in the market.
Read the Bain Brief: Tipping Points: When to Bet on New Technologies
Read the transcript below.
MARK GOTTFREDSON: Blackberry lost 85% of its market value during a period when its revenue was actually growing by three times. And this is because people were beginning to recognize that they didn't have an answer to the iPhone. Similarly, Uber was first to market with ride sharing, and today they have competition, but they give about 10 times more rides than Lyft does. And their market cap is more than three times that of Lyft.
So the advantage of being able to see these things ahead of your competition is just huge in terms of the value that it can create for your company and your shareholders. So we have developed a new technique which brings four tools together, which are fairly commonly known tools but that, combined, dramatically increase the ability to forecast if a technology will take off, when it will take off and how steeply it will penetrate the market.
The first of those tools is the experience curve. Basically, the experience curve says that as you have more experience making something, as your total cumulative production increases, you can bring the costs down. And there's a point at which that cost might be below that of the thing that this technology is substituting for. That's what we would call the tipping point. The economic value of the new technology is better than what it is substituting for.
And that works great for things like, for example, fracking, and in the natural gas industry, we saw that fracking took off once the cost of fracking dropped below the market price for natural gas. But not every value proposition is as simple as a simple price. For example, music players are something that stayed about the same price as each generation came forward. But as you went from vinyl to cassette tapes to CDs to, ultimately, putting it on an iPod to streaming, in each case, the new technology provided some additional source of value.
So our second tool is called Elements of Value analysis. And basically what that is is it takes a Maslow's hierarchy of what people's needs are, and we've been able to develop a technology that allows us to put a value on how much people value each of those elements. That allows us to then say, OK, here's when this product will have a value that is greater than what it is substituting for, and gives us a much more sophisticated look in even complex value propositions. So once you've reached that point, the question then is, how fast will it penetrate the market and how deeply will it penetrate the market?
And for that, we use adoption curves. Traditionally, you might have thought of this as the S-curve, but it is how this thing ramps up over time. And what we've seen is, over the last century, the rate of uptake has increased quite dramatically. In fact, it used to be maybe 30 or 40 years for some products, but over the last few decades, that has shrunk to 8 to 12 years for a complete penetration of a product to take place.
And so one of the things you can do is you can compare this technology to similar technologies, and predict how rapidly it will go up. But there are things that could accelerate that or decelerate that, and we call that our accelerators and barriers analysis. So we look at things like consumer perceptions, we look at government regulation, we look at the economic perspectives out there. All of these things can drive whether something grows rapidly or slowly.
The four of these together give a powerful tool for being able to predict if a technology will take off, when it will take off, how rapidly it will take off, and even though there are uncertainties, we can then set up signposts so that a company can watch those signposts and develop a dynamic strategy to know what actions they should take as soon as they see that signpost flashing red, which allows them to get out in front of the competition.
Predictive tools can help companies gauge when new technologies will take off.