The concepts Industry 4.0 in Europe, Made in China 2025 and smart manufacturing in the U.S. “all share a common goal—to create cyber-physical systems to innovate in manufacturing,” Bob Parker, senior VP for enterprise applications, data intelligence and services and industry research at IDC, said at Dassault Systèmes’ recent Manufacturing in the Age of Experience event. “And it’s really dependent on a set of new technologies like IoT (the Internet of Things) and artificial intelligence (AI). But getting on the Industry 4.0 bandwagon requires a convergence of operational technology (OT) and information technology (IT).”
The history of IT—evolved from the mainframe platform to the Internet platform and now to the digital platform—demonstrates that “as we bring (different platforms) together and incorporate innovation accelerators like IoT and AI, we create a multiplied innovation,” he said.
“It’s not just simple technologies; it’s the multiplied effect of all of them at scale”—which leads to greater autonomy and creates “the industry renaissance amongst the segments,” Parker added.
To understand how work will get done in the future, manufacturers today need to focus on the future of intelligence and the future of operations, both of which are related to data, he said.
‘Push intelligence down the front lines’
The future of intelligence promises improved productivity, which of course relates to operations.
“Although I would propose that perhaps it’s not productivity we need to think about,” Parker said. “Productivity is an older concept. We need to think about how to deal with complexity. We’re offering all of these new digital experiences, so now operations has to deliver on those promises the company is making to customers. It raises the level of complexity that operation executives have to deal with—which is why we like to refer to the future of operations as ‘resiliency at scale’.”
One definition in the marketplace for resilience is “the ability to adapt to changing circumstances while maintaining your central purpose,” he said. “Can you adjust your operations… in such a way that you’re keeping your purpose to people, to the planet, and to your profit?”
Beyond Industry 4.0, manufacturers “need to be simple at the core, diverse at the edge,” Parker said. While each manufacturer needs a standardized process across its factories, it also needs “to be able to push intelligence down the front lines”—to allow for some empowerment in decision making and some diversity at the edge.
“We also need tight feedback in terms of closing the loop, the decision making, and faster cycles. And we need to be able to move resources to where they’re needed if there’s a problem.”
The notion of resilience in manufacturing also includes factories that “naturally eliminate waste,” he added.
Make resiliency the core of operations
“The digital transformation opportunity is huge,” Parker said. “It will define our markets in the future.”
To transform quickly, he added, “operations needs to be built on the concepts of resiliency,” which means focusing not just on throughput but also dealing with “the complexity that a digital world brings.”
In the not-too-distant future, manufacturers that can establish “economies of intelligence” will gain a competitive advantage, Parker said. To do that, he suggested adopting a digital transformation platform that organizes everything a company is trying to do consistently.
To IDC, “the digital platform is made up of a set of services: One is around orchestrating the way data moves across your company integration services,” he said. “To be developer friendly, you need to give access to people who want to use the data to create value. So it needs to be based on microservices and… enable a new customer experience.”
Consider AR/VR, mobile devices and interfaces, Parker said. “Perhaps most important is the intelligent core” where data logs and AI capabilities are managed. “As providers go, it has to be broad and deep.”
Ford Motor long ago accomplished economies of scale as it spread material costs over high-volume production of the Model T, IDC’s Bob Parker said at a September industry conference in Shanghai.
“Then we transitioned to economies of scope: General Motors has Cadillac, Chevrolet and Buick,” and so it spreads costs over a number of different products, he said.
“As we moved into the late 1980s, Toyota realized they couldn’t match the capabilities of the Western European and U.S. OEMs, so they adopted lean and they adopted Six Sigma to be able to secure a system for continuous improvement,” Parker said. “They created economies of learning and they were able to offer cars at a very good price with very good fuel economy, which gave them a competitive advantage.”
In the digital economy and the “experience economy,” the competitive advantage is going to go to “companies that create economies of intelligence,” he said. “We don’t yet know who is going to establish that, whether it is a Korean OEM, Japanese OEM, U.S. OEM or (very likely) a Chinese OEM,” he said.
A first mover could be BMW Brilliance Automotive, a 16-year-old joint venture between the BMW Group and Brilliance China Automotive Holdings that “built a brand-new plant to be natively resilient,” in China’s Liaoning Province, Parker said.
“Traditionally, when I build an assembly plant, I set up lines to produce a single model—over and over again,” he said. “But this plant is able to do multiple configurations. They are able to do electric vehicles and combustion engine-based vehicles all in the same plant. They’re able to adapt to the market very quickly: They’re very resilient.”
IDC in September completed a survey of 790 manufacturers in Asia/Pacific excluding Japan—160 of whom run factories in China. Regarding the digital transformation in China, the survey focused on priorities and inhibitors, IDC’s Bob Parker said, speaking to people attending an industry conference in Shanghai that month.
Chinese manufacturers’ three top priorities, according to the survey:
Chinese manufacturers’ three top inhibitors:
Parker also showed a slide that listed Chinese priorities for creating value from data in decision-making, as well as related inhibitors.
The survey showed that manufacturers in China are “looking at intelligence and using data very broadly across a number of different areas to drive improvement,” he said.