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Industry Disruption Is Creating A Minefield Of Value Traps For Investors

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By Bryan Hong – full bio below

  • A growing group of technology companies, including Amazon, Alphabet, and Uber, are creating large waves of disruption in multiple industries
  • The market thus far continues to reward these companies and discount the valuations of incumbent firms within the industries being disrupted, creating what appear to be a number of deep-value opportunities
  • Most of these investments are value traps, and investments in these firms often reflect a misunderstanding of how much more rapidly technological disruption is occurring than before

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The term "disruption" has become a popular expression to describe a specific type of firm competition that can affect the profitability of and, in many cases, very survival of firms. Although the term is used quite broadly now, I’ll define disruption as any type of technological change that leads to the survival of incumbents being challenged. Unlike the conceptually simpler types of competitive threats such as dealing with rivals who charge lower prices or who sell better quality products, disruption is more complex and potentially more severe. The reason for this is because disruption today often makes the entire business model of a firm less valuable, if not completely inferior to the point of being unprofitable, but in the beginning this is usually not obvious.1 Once disruption is evident however, incumbent firms are often left with the hard choices of either having to execute dramatic changes to their entire business with an unclear probability of success, or to simply try to run a good business and hope the ultimate damage to profitability won’t be as bad as feared. Trapped in this corner, incumbent firms facing disruption understandably often shrink dramatically or disappear entirely.

Today, there is an unprecedented level of industry disruption happening in our economy, led by a group of technology firms that include Amazon (NASDAQ: AMZN), Alphabet (NASDAQ: GOOG), and Uber. The speed of disruption is also occurring much more quickly than in any period of human history. In a 2015 survey of global business leaders conducted by the Global Center for Digital Business Transformation at IMD business school found that respondents believed that 40% of all incumbents in each industry would be displaced by disruption within the next five years.2
To understand why this is the case, it’s useful to first consider how new product innovations are ultimately adopted into mainstream society. One can break down this process into several stages.

Stages of new product innovation

Invention. When a novel new product innovation is created, it is often inferior in a number of ways to the competing products that are already out on the market. For example, the first digital camera was invented (ironically) by a Kodak engineer in 1975, and was as large as a toaster, took 20 seconds to take a picture, and captured very low quality images.3 At the time, it was understandable that film-based camera manufacturers didn’t panic about their survival.

“Take-off” in the number of firms. When new inventions appear in the market and hold potential promise (although are not yet perfected), other firms eventually enter the market with their own versions of the product. This “take-off” typically results in a period where consumers witness substantial improvements in product quality and performance.

Sales “take-off” to mainstream adoption. Once the product is improved sufficiently to be superior to the products originally in the market before the invention, sales then increases dramatically and the new product becomes adopted by the mainstream.

The relevance of describing this breakdown is that the historical data we have on innovations has suggested that this is usually a very long process, taking roughly a decade or longer. Although the first digital camera might have been invented in 1975, Kodak’s profits actually peaked in 1999, 24 years later.4 That’s plenty of time to buy dips based on fears of disruption without seeing its costs.

Academic research, however, has pointed out a long-term trend that investors should be aware of. In a study by professors Rajshree Agarwal and Barry Bayus, they examined how long many of history’s most important inventions, such as the sewing machine and mobile phones, took to advance from invention to sales take-off.5 They find a striking decrease in the length of time inventions took to experience a sales take-off as time has progressed. In their study, the average number of years between the commercialization and sales take-off of innovations before and after World War II fell from 18.7 years to just 10.25 years. The digital camera is clearly an exception, and not the rule.

There are two important things to highlight from this study. First, because they find that what predicts the increase in sales of a new product innovation is a preceding increase in the number of firms producing the product, one indicator of how quickly a disruption might become a serious threat would be to observe whether a “take-off” in the number of firms offering a new product or service has taken place already. Second, their study did not include any innovations invented after 1979. So, the average number of years between the creation and sales take-off of new innovations is likely to be much shorter now in 2017. Part of this is due to the nature of startups in our digital world—before the 21st century, firms often required large capital expenditures and infrastructure to expand (e.g. stores and factories). Today, relatively little capital is needed for many technology startups to generate explosive growth.

These trends have been reflected in the stock price performance of a number of sectors, both in rewarding the disruptors and hurting traditional incumbents who are facing disruption. Based on pure financial analysis, a number of firms facing disruption look relatively cheap, on both a historical and absolute basis, and have attracted interest from a number of prominent hedge fund investors. Certainly if disruption was not a concern, these bets would probably pay off handsomely with enough patience.

As one example, consider the contrast between Amazon and department store Macy’s (NYSE: M). Amazon is expected to become the largest apparel retailer sometime this year, while Macy’s continues to suffer in both market share and profitability.6 Hedge funds Starboard Value and Greenlight Capital (run by David Einhorn) took long positions in Macy’s in 2015 and 2016 respectively, likely because even a casual read of the financials would make the company seem like a good value, especially if one could think of ways to unlock additional value from the company’s real estate assets.7 Both investors have since exited their positions at substantial losses.

I can go through the standard arguments of why Amazon has a number of competitive advantages over Macy’s, but I suspect both Starboard and Greenlight saw the same potential issues on the horizon. The key insight in this situation is that disruption now occurs much more quickly than in the past, leaving incumbent firms even less time to adapt, and investors assuming stability of revenues (and ultimately earnings and cash flows) for too long. Or worse, investors may assume that firms like Macy’s will return to their previous level of performance. While possible (investing is about probabilities, so anything could happen), in cases of disruption this very rarely ever happens because the headwinds are just too strong. The point is that disruption makes your entire business model permanently less valuable.

Another industry that is in an earlier stage of disruption is the car rental business, traditionally dominated by companies such as Hertz (NYSE: HTZ) and Avis (NASDAQ: CAR). Prominent investor Carl Icahn continues to have a long position in Hertz, while a number of hedge funds including SRS Investment management are long Avis.89 Both stocks are significantly lower primarily due to used car prices rather than disruption, but I would argue that the industry in its current form is vulnerable to disruption both by ridesharing apps such as Uber, as well as new carsharing services offered by the automakers themselves such General Motors’ (NYSE: GM) Maven.

The biggest issue is that, used car sales aside, renting a car becomes progressively less compelling as a value proposition the cheaper and more convenient that ridesharing and carsharing become. As an example, let’s consider ridesharing. Uber already wins today with convenience on multiple fronts: You can call a car to pick you up immediately from your phone, there is no need to worry about parking when you arrive at your destination, and payment is automatic through the app. Contrast this with the experience of renting a car: Filling out a series of forms, worrying about insurance coverage, finding parking everywhere you go, needing to make sure the gas tank is full when you return to avoid further charges, and the need to reserve the car for a preset period of time. And, if you are unhappy with the service, that’s yet another hassle.

While there certainly are tradeoffs at the moment between the two options, imagine what the evolution of Uber will look like relative to the car rental companies. As more drivers continue to sign up for Uber, it will become easier and faster for users to find a nearby ride, regardless of their location. As self-driving cars continue to improve, they will become mainstream (look for the “take-off” in the number of firms), and it’s logical to think that Uber will be a big beneficiary, given its rich amount of data (did you notice how Uber now tracks your location at all times?) and analytical capabilities. A fleet of self-driving cars with rich location data on users is a giant optimization problem, but one that can be steadily solved with better and better methods. That might make the average cost of an Uber ride even lower, which could mean lower prices for rides as well.

By contrast, car rental companies have essentially no data on users once they leave the lot. That limits the power of analytics to help them optimize operations or find additional revenue sources. They inevitably will have to adapt, which is already underway. Avis has recently announced that it will expand its “connected car” fleet, and improve upon several of the pain points of renting a car using new technology. Hertz has reached an agreement with Lyft to allow Lyft drivers to rent cars for ridesharing purposes. However, even with these changes, aggregate demand for car rentals is likely to only decrease, and pricing power will likely be constrained by services such as Uber. If self-driving cars become mainstream, it might make more sense to have cars come mostly on demand to keep utilization as high as possible, instead of sitting in lots. That sounds a lot like what Uber does already, leaving questions about what to do with the physical locations with big parking lots. And if companies like Hertz and Avis did operate more and more like Uber, what competitive advantage would they have against Uber?

In this world, while successful adaptation by incumbents is possible (IBM (NYSE: IBM) has done it several times), in most cases the only question left is the degree of the decline, and how soon disruption will have a substantial impact on revenues and the bottom line. Given what we know about innovation speeds and disruption, one might guess sooner rather than later.

Author: Bryan Hong

Author Bio:

Visiting Assistant Professor at The Wharton School, University of Pennsylvania and Assistant Professor at Ivey Business School, PhD in Business Administration at the University of California-Berkeley. Professor Hong's research how firms create and capture value from competitive advantages over rivals.

1 The term was originally coined by Harvard Business School professor Clayton Christensen. The original mention of the term can be found in this article: https://hbr.org/1995/01/disruptive-technologies-catching-the-wave

2 Source: http://www.imd.org/globalassets/dbt/docs/digital-vortex
3 Source: https://hbr.org/2016/07/kodaks-downfall-wasnt-about-technology

4 Source: http://www.economist.com/node/21542796
5 Source: Agarwal, R., & Bayus, B. L. (2002). The market evolution and sales takeoff of product innovations. Management Science, 48(8), 1024-1041.

6 Source: http://www.businessinsider.com/amazon-becomes-the-biggest-clothing-retailer-in-the-us-2016-10
7 Source: https://www.fool.com/investing/2017/05/27/why-i-wont-go-near-brick-and-mortar-apparel-stocks.aspx?yptr=yahoo

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