So, who’s winning? The disruptors or the incumbents? While incumbents often get a bad rap, the truth is that for every sector where technological change has enabled fleet-footed digital disruptors to innovate business models, there are even more where established players still prevail. (As an example of the latter, try to name your favorite web-based pharma giant.)
As the next major technological wave rolls forward—think artificial intelligence, the Internet of Things, blockchain—we believe many incumbents stand a good chance of prevailing yet again, provided they move fast and at scale.
The data is pretty clear on this score. McKinsey’s 2017 Global Digital Survey of over 1,600 executives identified a group of “reinvented incumbents” (companies embracing disruptive technologies). They invest three times more in the new wave of disruptive technologies than traditional incumbents do (Exhibit 1).
And it seems to be working. These reinvented incumbents are using many of their established advantages of scale and access to capital to achieve greater economic returns compared with their traditional counterparts (Exhibit 2).
While the first phase of Internet disruption was largely about removing unnecessary intermediaries from markets and creating digital-only businesses, the new wave can be boiled down to combining technologies to do radically new things. This multiplier effect is possible thanks to a perfect storm of hardware and software—such as sensors, deep learning, AI, next-generation chipsets, and virtual reality—that has reached sufficient maturity to enable new things (for example, autonomous vehicles) and new business models (such as virtual warehousing). The exponential growth in foundational technologies has led to cheaper computing power, data storage (Exhibit 3), and hardware components (Exhibit 4), making this new wave of technologies (relatively) accessible.
Incumbents are already driving new value by focusing on activities that these new technologies do well, primarily radical improvements in productivity, accuracy, and speed:
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Machine learning improves the accuracy of predicted outcomes or provides better recommendations. For example, researchers from New York University Langone Health used a classification algorithm to categorize lung nodules in CT scans 62% to 97% faster than a radiologist panel could.
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Industrial IoT enables efficient asset management. One mine operator with a large mining fleet deployed IoT sensors and sophisticated analytics that could prevent breakdowns by identifying, for example, problematic increases in engine temperatures. For each breakdown avoided, the company potentially could save $2-4 million a day.
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Autonomous and connected vehicles make the transportation of goods and people more efficient and safer. One heavy machine manufacturer developed autonomous trucks that improved productivity by 30%. These trucks could travel to destinations, haul material to dump points, and even report to maintenance autonomously.
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Virtual and augmented reality enables just-in-time access to crucial information. One aerospace manufacturer displayed detailed wiring instructions on smart glasses given to its technicians as part of a pilot program, reducing assembly time by 25% and decreasing production error rates significantly.