Emerging technologies such as artificial intelligence, the Internet of Things (IoT), blockchain, and digital assistants are helping manufacturers keep up with changes in how goods flow, the availability of labor, and trade volatility.
Research shows that the use of these technologies, collectively known as Industry 4.0 when applied to manufacturing, is helping businesses take leadership positions in their respective industries and increase profits more quickly than do peers who don’t adopt these technologies.
Adopters of these technologies are seeing significant growth in profitability and market share, according to research by the Enterprise Strategy Group and Oracle.
Industry 4.0 data
A few data points from the research:
- 84 percent of organizations are actively using at least one AI, IoT, blockchain, or digital assistant in their operations.
- Organizations that are adopting AI and other emerging technologies in finance and operations are seeing 80 percent faster growth in profits than laggards.
- Organizations have shortened their time to produce and fulfill orders by an average of more than six business days as a result of incorporating IoT data into their supply chain systems and workflows.
- Thanks to AI-enabled optimization of the supply chain, organizations report a 25 percent reduction in fulfillment errors, a 30 percent reduction in stock-outs, and a 26 percent reduction in manufacturing downtime.
“This study makes it clear that emerging technologies have passed the trial phase and are moving toward a state of widespread adoption,” says John McKnight, EVP of research and analyst services at the Enterprise Strategy Group. “In most cases, benefits exceed expectations.”
“AI, IoT, blockchain and digital assistant capabilities enable organizations to innovate faster and adapt to the increased pace of change, creating significant competitive advantage and driving increased profit,” says Juergen Lindner, senior vice president of SaaS product marketing at Oracle. “Organizations that sit on the sidelines risk their business relevance.”
These technologies provide, for example, more efficient ways of rerouting trucks so that pickups and deliveries occur at locations where labor availability hasn’t been curtailed, and at locations that haven’t been impacted by closed or slowed border crossings. They are also used to conduct preventive maintenance on manufacturing equipment that would otherwise represent hundreds of thousands of dollars in direct and opportunity costs.
Noble Plastics, a contract manufacturer of injection molding products, uses Oracle IoT cloud service to pull production data from its robots and molding machines, and then uses anomaly-detection algorithms to help keep tabs on machine health, maintenance requirements, and parts quality. “These KPIs are critical,” says Scott Rogers, Noble Plastics technology director. “The power of machine learning is being able to analyze millions of product and machinery characteristics, predict if a machine or process is going to break down, and then help us avoid making bad parts.”
Likewise, automotive parts manufacturer Titan International is taking advantage of Oracle’s integrated finance, supply chain, and manufacturing applications to break down information silos and use the latest advancements in machine learning and IoT technology to improve user engagement, collaboration, and performance.
“To better support our customers, we needed to move from multiple systems to a single platform that would give us better visibility into our business,” says Jeff Blattner, director of IT at Titan. “Oracle Cloud Applications give us access to constant innovation and enables us to benefit from emerging technology, such as IoT, to gain an advantage over the market.”
Emerging technologies that are natively embedded into the applications that customers use to run financial reporting, operations, or supply chains allow companies to realize the value of these applications immediately. “This is much more impactful than spinning off DIY ‘science projects’ that end up being sidecars to the mission critical applications,” Lindner says. “Specifically, machine learning as a subcategory of AI is where we see a lot use cases and consequently productize this directly into the applications. When businesses don’t have to create bespoke systems, they can harness the value of these technologies across the enterprise.”
Blockchain is another critical technology that enables product tracking and condition monitoring for supply chains and multi-tier visibility for a network of trading partners. “This kind of visibility is hugely important to business resiliency. With a trend toward prebuilt enterprise-ready apps based on blockchain, manufacturers can transform for Industry 4.0 capabilities with less risk,” Lindner says.