Shared todayArtificial Intelligence SeriesIn-depth Research Report:Artificial Intelligence Topics Accelerate the large-scale application of artificial intelligence
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Report total: 42 pages.
Featured Report**: The School of Artificial Intelligence
Uncertainty drives innovation
To prepare for future disruption and withstand shocks, manufacturers are investing more in artificial intelligence (AD) technology, sustainable energy, and other technological innovations. About 90% of the high police officers said that improving the resilience of the ** chain is a top priority, and the annual investment in artificial intelligence has reached about 150 billion US dollars, while the ** chain leaders are investing in advanced analytics to connect data. Preparing for uncertainty has become the norm, with executives expecting disruption to increase by 15 to 25 percent over the next five years.
Geopolitical shifts have allowed advanced manufacturing to thrive in a market that was stagnant 30 years ago. For example, the growth of manufacturing in the United States has hovered around 1 for the past 20 years4% growth rate. 4 Now, digital technologies, sustainable features, and higher skill sets in advanced manufacturing and the ** chain are breathing new life into the market: Over the past five years, U.S. industry has generated a total shareholder return that is about 400 basis points higher than in the last 15 years.
Machine intelligence is defining the Fourth Industrial Revolution
The core purpose of this paper is to explore the inflection point of the Fourth Industrial Revolution by examining the innovations and methods of the latest lighthouses, but it helps to reflect on the four different industrial revolutions of human society in the first place. They provide important context to explain why machine intelligence is the natural culmination of this development—and when deployed in a manufacturing setting, machine intelligence has the potential to have an exponential impact along with other Fourth Industrial Revolution technologies such as wearables, cobots, and autonomous vehicles.
Chapter 2 uses the S-curve: from learning to doing
With the growing number of advanced use cases demonstrating the impact of lighthouses, there is less and less need for pilots and proof-of-concepts (POCs) for advanced technologies. Take Al, for example. It has enabled more than half of the "top use cases" in the last three Lighthouse cohorts, with only 10% in the top three cohorts, correspondingly, and 82% of Lighthouses designing new use cases, including AL use cases, from the day they have passed the "learning curve" and are no longer trying individual use cases. Instead, they use factories as pilots to show the expansion of the Fourth Industrial Revolution to the entire production network (and in some cases, the entire organization).
Lighthouse leads fast followers
The adoption of transformative technologies is accelerating, with Lighthouse focusing not just on one plant, but on 10 to 50 plants at a time. The business impact of transformation at scale will shape the competitive landscape in manufacturing, with improvements in cost, quality, service, agility, and sustainability exceeding the expected orders of magnitude for a single point of transformation, creating a maturity gap between those who are doing and those who are still learning.
This gap in maturity is evident in the wake of recent disruptions and fluctuations. Consider that 85% of lighthouses lost less than 10% of their revenues at the height of the Covid-2019 pandemic, compared to only 14% of other manufacturers. Lighthouses can react faster: Although they face the same ** chain risks, 65% of lighthouses are already doing dual-sourcing and adding inventory by 2022, compared to 24% for other companies.
From dozens of use cases to dozens of factories
With scale, the concept of use cases no longer involves one implementation, but dozens or even hundreds. The impact of transformation has increased tenfold, with ROI growing to almost twice that of a single point transformation, driven by cost and scale synergies and the need to relatively reduce or even eliminate one-to-one experimentation with new technologies.
Lessons for Leaders: A Six-Part Guide to Building the Engine of the Fourth Industrial Revolution
Lighthouse, like digital leaders in other industries,12 has gone through a six-part approach to drive its own transformation: First, they (1) strategize. They then built the ability to deliver data across (2 talent, (3) agile, (4) technology, and (5) data. Finally, they (6) implement change management.
They are now adapting this approach to fit the network and the size of the organization. It can be likened to driving a car.
They start by setting (1) a roadmap for the battle: GPS leads the organizational transformation, reinventing the organization with technology, and the roadmap sets to prioritize and prioritize the values at stake—both across use cases (at the site level) and factories (at the network level).
Then, they build the delivery capability, which is the engine that drives the transformation. Engine components – pistons, crankshafts, drivetrains, and timing belts – one is: (2) Programs to hire, train, and retain digital talent;and (3) an agile operating model that promotes speed, quality, and collaboration, often including digital studios;(4) Technical backbone.
With a clear, scalable, and distributed architecture, it makes it easy to deliver digital services and solutions;and (5) data architecture and governance to enable critical decisions and ensure quality, ease of consumption, and single reuse. Equally important to its function is the oil: as university technology providers, innovation incubators, public entities, and many other institutions develop best-in-class capabilities, the ecosystem collaborates to keep the engine running. In this recent cohort, each lighthouse listed ecosystem collaboration as a key enabler of its Fourth Industrial Revolution journey.
But competence alone is not enough. Whether at the site or network level, adoption and expansion are ensured through (6) effective change management: the steering wheel. This typically includes a conversion office, which nearly 70% of the lighthouses consider the most critical of the six.
These six enablers are proven in the digital and analytics transformation of every industry. 13 Lighthouses' early approach to scale shows that they are also suitable for manufacturers.
Look ahead to the next level of expansion
Having explored how the lighthouse achieves everything they have, it's time to focus on what's ahead. The next section of this article will look at the decisive factor of the Fourth Industrial Revolution – the business that has been injected into the lighthouse, and how it will supercharge existing technologies to unlock previously unattainable advancements for the manufacturing industry as a whole.
Report total: 42 pages.
Featured Report**: The School of Artificial Intelligence