6.9 The Predictive Model of Disruptive Innovation

Marcos Antonio de Lima Filho, PhD.

The previous sections have explored some of Christensen’s failed predictions, such as his assessment of the iPhone and his forecast that regional jet manufacturers would disrupt Boeing and Airbus. In this section, I investigate the magnitude of such inaccuracies by analysing the stock values of the companies directly involved in such projections. For instance, since January 2007, Apple stock has risen by an astonishing 5,800%. This remarkable growth took place despite Christensen’s assertion that, according to his theory, “Apple won’t succeed with the iPhone” (McGregor, 2007).

Embraer and Bombardier are two examples of potential disruptors that ultimately fell short, as explored in the previous section. In 2004, Christensen and his team posed the question, “Can Boeing and Airbus withstand the assault from regional jet manufacturers such as Bombardier and Embraer?” Their conclusion was clear: “Regional jet manufacturers pose a legitimate disruptive threat to the industry's leading manufacturers, Boeing and Airbus” (Christensen et al., 2004, p. 129). However, since 2004, Bombardier and Embraer stocks have mostly experienced negative performance (see Figure 6.9.1). Bombardier’s stock plummeted more than 80% in 2015, after its CSeries regional jet failed to secure orders.

Based on his predictive model, Christensen claimed that “innovation theories suggest that Boeing and Airbus will continue to miss much of the industry’s real growth and face increasing pressure unless they take proactive corrective action to adapt to the disruptive forces” (Christensen et al., 2004, p. 132). Contrary to this prediction, Boeing and Airbus have outperformed Embraer and Bombardier, despite their continuous focus on “sustaining strategies”. Boeing’s stock has risen up to 800%, while Airbus’ stock has surpassed 600%.

Just like the jet engine, Apple also violated the premise that disruptions arise only from low-end segments. The first 8GB iPhone cost $600 at launch, even with a two-year contract. At these high prices, Christensen did not hesitate to declare that “the iPhone is a sustaining technology”. Because Apple was entering the mobile handset market with a so-called “sustaining innovation”, he also anticipated that the company would fail. With this approach, Apple broke the third rule of Christensen’s predictive model, which Raynor (2011) summarised as follows:

1. An incumbent that launches a sustaining innovation (one intended to meet the needs of its current customers) can expect to succeed.

2. An incumbent that seeks to disrupt its own markets can expect to fail.

3. An entrant that launches a sustaining innovation (one that targets the most valuable segments of an established market) can expect to fail.

4. An entrant that launches a disruption can expect to succeed.

Accordingly, Christensen asserted that “the prediction of the theory would be that Apple won’t succeed with the iPhone. They’ve launched an innovation that the existing players in the industry are heavily motivated to beat” (McGregor, 2007). Since this interview, however, Apple’s stock price has increased by more than 5,500% since 2007 (see Figure 6.9.2).

These unexpected stock performances, ranging from 500% to 5,500%, along with other anomalous cases, highlight an odd mismatch between facts and a theory that was purportedly capable of predicting stock performance. Michael Raynor, who co-authored The Innovator’s Solution with Christensen as a sequel to The Innovator’s Dilemma, touted that “there are some data to suggest that Disruption can be used successfully in this way” (Raynor, 2011).

The magnitude of these contradictory findings is substantial, as Christensen’s theory was intended to explain “the processes through which disruptive technologies supplant older technologies” (Christensen, 1997). Furthermore, his predictive model was supposed to assist companies and managers to achieve growth and market leadership (Christensen, 2006). In other words, disruption theory was designed to “predict ex ante whether an innovation will disrupt the leaders” (Christensen, 2006). However, in practice, the market shifts triggered by Apple were far more disruptive than Christensen could have foreseen. The launch of the iPhone transformed the entire mobile industry, leading to the decline or disappearance of once-dominant mobile handset companies (see also Figure 6.5.1).

In the aviation industry, Christensen predicted that regional jet makers would continue to rise upmarket, eventually posing a threat to Boeing and Airbus. Ironically, shortly after he made this prediction in 2004, the demand for regional aircraft began a cycle of decline that has continued ever since (Figure 6.8.2). The regional segment contracted to a third of its former size, forcing Embraer and Bombardier into a price-driven competition that negatively impacted their stock performance. This fall in regional jet sales took place despite Boeing and Airbus not taking any of Christensen’s suggested proactive measures.

In science, this type of mismatch between empirical data and existing theories usually sends theorists back to the drawing board (Mui, 2016). Despite this accumulation of anomalies, Christensen maintained in the preface to the 2016 edition of The Innovator’s Dilemma that “the theory of disruption continues to yield predictions that are quite accurate, in an astounding range of industries”. Michael Raynor has even suggested that disruption theory could be used to predict stock performance, arguing that if a method demonstrates superior returns in identifying winners, it is valid (Raynor, 2011). However, the data examined in this section contradicts such claims.