The term “disruptive innovation” is nothing new. For 24 years, it has been a staple in the lexicons of business leaders from both small and large organizations. But in the years since its inception, the idea of disruptive innovation has strayed from its coiner’s original definition: a process by which a product or service takes root initially in simple applications at the bottom of a market and then relentlessly moves up market, eventually displacing established competitors.
The academic Clayton M. Christensen, who, with other colleagues, coined and analyzed disruptive innovation theory in 1995, now argues that the theory has been too broadly applied, often leading to undue criticism of the theory’s original intent. Further, he believes that this broad, misinterpreted umbrella definition of “disruption” has been applied to any situation where once-successful industries experience a shakeup. So, if not this definition, then how does disruptive innovation in 2019 apply to the new AI-centered, future-focused business climate?
Disruptive Innovation is Shaking Sectors—Albeit Differently
Change is the only constant, and this is just as true for businesses as it is individuals. But change (or, disruption) doesn’t come out of a vacuum; there are patterns business leaders can be aware of in order to recognize current disruption and to discern how susceptible their business is to future disruption. In 2018, Accenture outlined four periods of disruption in its Disruptability Index to illustrate these periods’ impact on different industries. They include:
Viability: Reborn industries with short-lived advantages spurred by higher rates of innovation
Durability: The sector’s well-established businesses benefit from consistent performance with only some disruptors
Volatility: Once-strong elements are weakened while large disrupters reveal new sources of value
Vulnerability: The sector’s weaknesses bring significant risks, and create hurdles to inhibit the disruptor’s penetration
A company’s position on the matrix reveals just how viable, volatile, durable, and/or vulnerable its industry is. For example, the software and platforms industry’s current level of disruption is highly volatile, while capital markets’ is experiencing mid- to low levels of vulnerability. Businesses may use the Disruptability Index to get a clearer picture of where their sector stands, affording them the data needed to make more informed decisions. However, the Index notes that disruption patterns observed in one sector are not “homogenous within the same sector,” highlighting that, within the automotive sector, its currently level of disruption was not equal to its susceptibility to future disruption.
Where’s Disruptive Innovation Headed?
A recent paper published by the Harvard Business Review goes further into which industries are most or least susceptible to any of the four periods; it took the Index’s median scores and used them as dividing points to cover the four periods of disruption. The authors concluded with how industries in the four periods can mitigate risks associated with (or capitalize on) its placement.
But what does that mean for near-term disruptive innovations? For the tech sector, Blockchain will likely play a much larger role in the day-to-day when it comes to identity and privacy issues; data breaches are becoming all too common, and companies are seeking ways to mitigate these risks. Blockchain may very well be the answer to the growing number of breaches.
AI will also continue to play an ever-increasing role in the workplace—and AI applications may begin fighting one another. The idea is that battles will test the digital image-making limits of each AI, both of which will learn/improve from the spar. But beyond fighting amongst themselves, disruptive AI applications will continue to alter a growing number of sectors. Machine learning will allow for digesting and churning out massive amounts of data in seconds, changing the way businesses understand data in real time.
Both in- and outside of the office, smart devices will become more prevalent—and IoT connectivity will become an integral part of the Fourth Industrial Revolution. These devices (and others) will contribute to the growing number AI-powered machines that will make humans’ lives easier. Even within the healthcare sector, AI is deepening its role; it can help healthcare professionals predict disease, identify health risks, and automate diagnostic tests, speeding up the process and providing greater accuracy. And for the manufacturing industry that supplies many of these disruptive devices? Processes will become more automated and optimized. Humans and robots will work side by side while more industrial robots become more widely available across different manufacturing sectors—but AI has a long way to go before it can replace the bulk of the human workforce.
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