How AI can help manufacturers revamp their supply chains and be more sustainable

There has been plenty for the manufacturing industry to be concerned about in recent times. The ongoing effects of the pandemic and, more recently, the war in Ukraine have exposed supply chain vulnerabilities that are forcing companies to adapt quickly. Those who don’t are faced with the unwelcome prospect of being unable to get their goods onto store shelves or being left with a costly overstock in their warehouses.

And yet, there are causes for optimism. Despite the challenges, the manufacturing industry continued to grow in 2022. Meanwhile, a new survey carried out by the Manufacturing Alliance reveals the majority of manufacturing CEOs believe the supply chain challenges that have troubled businesses for the past couple of years are improving. The path to growth is open.

The key, of course, is finding it. Only those manufacturers that continue to adapt will thrive, and AI plays a major role in revolutionizing operations. In a rapidly changing world, technology holds the key to everything, from increasing efficiency and boosting productivity to enhancing sustainability and driving growth.

Smart operations

AI can help improve visibility and efficiency by monitoring the flow of information, services, and goods across the entire manufacturing operation. This makes forecasting far more reliable, as it is based on data from hundreds of production assets, including automatic processing equipment like robotic packing machines. Add to this the intelligence derived from the use of machine learning to optimize supply and demand, and the increased consistency can help manufacturers counter the unpredictability of an ever more uncertain operating environment.

The same can be said for operations where technology has the potential to be a powerful ally in helping businesses become leaner and less subject to volatility. For example, cognitive AI offers manufacturers a single, holistic view of the supply chain and helps remove bottlenecks in operations using real-time data. Meanwhile, the use of augmented reality (AR) and virtual reality (VR) to emulate processes and simulate tests lets firms identify (and, crucially, prepare for) potential risks, vulnerabilities, and errors that could disrupt production lines in advance.

And even before goods go into full production, AI can help train robots to work more efficiently—a process that BMW innovated with NVIDIA through its virtual factory. Additionally, a fifth of manufacturers are already experimenting with or actively developing a metaverse platform for their products and services.

Shipping and warehousing, usually among the largest expenses for manufacturers, are also no exception. From IoT devices and sensors to AI-enabled visibility systems, firms now have the opportunity to gather and analyze vast amounts of data regarding vehicle performance and provide complete tracking of products from the factory to the shop floors of dealers and retailers. They can then use these insights to boost agility, streamline costs, and optimize their logistics network.

Saving money and the planet

Yet the potential benefits of AI extend beyond just operational concerns, directly impacting two areas that are no doubt front of mind for any manufacturing company.

The first is profitability. According to recent Accenture research, only 12 percent of firms have advanced their AI maturity enough to achieve superior growth and business transformation. But those who do could potentially double their revenue from 12 percent to 24 percent by 2024, significantly boosting their bottom line and benefiting employees, shareholders, and customers alike.

The second is ESG where AI serves as a crucial gateway to better performance. According to the International Energy Agency, industrial activity is responsible for a significant share of the world’s carbon emissions and energy usage, meaning companies have a responsibility to act sustainably and report transparently on their results. AI algorithms can deliver accurate recommendations for balancing energy consumption and raw material usage, while other AI-based tools can track emissions throughout an organization’s value chain. Both help ensure firms are actively shrinking their environmental footprint while remaining compliant with tightening legislation.

In one particularly stark example shared by Blake Moret, the CEO of Rockwell Automation, an automation company used AI to discover that 40 percent of energy consumption by one of its machines occurred when it was not producing anything. This single insight enabled the company to power down the equipment when it was not in use and dramatically cut both costs and emissions.

Building better relationships

With all the focus on yields, factory efficiency, and optimal warehousing levels, it can be easy to forget the importance of customer experience in manufacturing. Yet as with everything discussed so far, CX too is ripe for AI innovation.

Every successful manufacturer needs strong relationships with its suppliers, distributors, and customers. However, for most firms, customer loyalty remains a considerable challenge. Zendesk research shows that 61 percent of customers will walk away after a single bad experience, and 72 percent of manufacturing leaders agree that customer service is a critical business priority.

The good news is that the solutions are out there. Manufacturers can easily scale their operations and transform their CX with AI-powered automation and self-service tools. An omnichannel support platform that integrates all brands, global contact centers, and support channels into one service solution can help transform the customer experience—driving loyalty, advocacy, and, ultimately, growth. For example, Siemens is the biggest manufacturer in Europe for industry, energy, healthcare, and infrastructure. The company partnered with Zendesk to help centralize and analyze all its customer data.

Shaping the future

Of course, the manufacturing industry should not expect smooth sailing in the years ahead. The ongoing economic and geopolitical uncertainty and the transition to a hybrid future of work continue to throw up new and evolving challenges. Many of these factors are beyond manufacturers’ control, making it even more important that they are as proactive as possible in shaping their own future where they can.

Their ability to do so is rooted in data and technology. Whether it is optimizing operations, sharpening decision-making, enhancing sustainability performance, or improving customer experiences, deploying AI-based tools and solutions offers firms the chance to improve nearly every aspect of their operations without incurring huge overheads.

At a time when supply chains have become increasingly complex, the solution is smart infrastructure. And that takes AI.