How AI in energy and utilities industries is powering transformation
AI is helping drive the transition to sustainable energy by improving operational efficiency, reducing costs, and boosting productivity.
Chemical companies serve as the foundation of virtually every manufacturing value chain, from those cranking out semiconductors or automobiles to producers of pharmaceuticals or food products. Companies across the economic spectrum could gain from studying chemical business strengths — in particular, how to squeeze out inefficiencies in high-volume process manufacturing.
But the chemical business can also take lessons from the many industries it serves. What are others doing to become more resilient and more profitable? What steps are they taking to stoke growth by building on existing strengths and introducing new business models?
Let’s look at four broad areas in which other industries are setting examples for chemical companies:
Chemical companies are no strangers to AI, particularly in research and development, where it’s increasingly harnessed in areas such as materials design, computational chemistry and reaction optimization. But others are demonstrating that opportunities abound outside the lab.
One of the most enticing areas of AI integration in manufacturing is in demand planning. No form of intelligence, biological or computational, can see the future. But AI’s ability to tease out trends from myriad data sources confers real demand-planning advantages.
That’s especially important in chemicals, where the ultimate drivers of demand can be diverse and several links away on the value chain (for example, cyclohexanone is used in making nylon as well as semiconductors, subjecting its demand patterns to the vagaries of fashion and computing).
Manufacturers doing AI-driven demand planning may operate in different markets, but they have two things in common. First, they’re getting data out of their silos and feeding AI as much data as they can get their hands on, including external and unstructured data.
And second, they’re doing it in the cloud, where AI works best. If there’s ever been a more pressing reason than AI’s emergence for chemical producers to move their core systems to the cloud, I’m not aware of it.
Perhaps the most obvious application of generative AI in manufacturing is in customer experience. Manufacturers of all stripes are now in the early stages of using GenAI to customer-tailor marketing based on customer preferences and using GenAI-powered chatbots for customer service. That brings us to customer centricity.
AI is helping drive the transition to sustainable energy by improving operational efficiency, reducing costs, and boosting productivity.
Chemicals is a commodity business with tight margins. There’s only so much wiggle room when competing on price. Given competitive pressures and global supply chains, that’s become close to universal in manufacturing. Companies across the board are leaning on customer centricity to differentiate themselves.
Today, that’s providing visibility into order processes, pushing out shipping updates and the like. Tomorrow, it’s going to be about understanding customer tastes to the point that you can predict them. As Steve Jobs put it, “Our job is to figure out what they’re going to want before they do.” That can pay off handsomely, as Apple’s 25% net margins demonstrate.
For chemicals companies with hundreds or thousands of customers, understanding customer tastes before they do will require AI-powered analytics. That sort of understanding can be the key to grasping which customers are most likely to respond to an upsell of a more expensive but more sustainable grade — and, if so, proactively sending test samples or otherwise wooing target customers.
Customer centricity is also the key to servitization. You have to understand your customers, their needs and those of your customers’ customers to determine what services you should offer with your product, which can range from collaborative innovation to logistics.
Learn how contextual selling helps organizations boost engagement by using real-time data to personalize the sales process for each buyer.
Oxford Economics and SAP surveyed 1,000 supply chain executives from around the world. A dozen industries, including chemicals, were represented. One of the central questions focused on visibility into supply chains.
Despite a recognition that supply chain partners are extensions of their own businesses, those reporting highly collaborative relationships with their suppliers started at 55% with respect to tier-1 suppliers, dropped to 32% for tier-2 suppliers and to 25% with tier-3 suppliers.
Given growing customer expectations of speed and precision, that’s not going to cut it. The semiconductor and the automotive businesses are doing something about that.
In semiconductors, RosettaNet serves as a vital linkage for various supply chain players. But chemical firms can learn as much from its strengths as its weaknesses: It’s a one-to-one system in an n-to-n environment, and the industry recognizes that, to truly unify supply chains into network of partners working together as a unified ecosystem operating with maximal efficiency, they need to build on RosettaNet’s success.
That’s the vision in the automotive businesses. Catena-X continues to develop secure, continuous data connectivity with multiple partners across a multitier supply chain for a common value-creation process. There are 172 partners involved as I write this, BASF among them.
Chemical companies should embrace such networks as participants, and in sectors where it makes sense, consider developing chemicals-centric analogs. Among many other advantages, such supply chain connectivity will be critical in meeting sustainability goals.
IDC research reveals the growing role of business networks and cross-industry collaboration in driving high-tech success.
Of course, for a chemical business to be sustainable, there must be sustainable business opportunities. It’s safe to say that opportunities will abound. Consider Unilever, whose planned 50% reduction of virgin plastic use by 2030 helps advance its goal of net-zero emissions across its value chain by 2039.
Crucial to such ambitious aims is a drive toward circularity as well as an ability to share standardized carbon-footprint data across the full scope of suppliers and their products. Companies such as Eastman and LyondellBasell have made progress in bringing plastic based on recycled feedstock to market, but there’s room for improvement.
Chemical companies can — and should — help push their own customers toward sustainability. A convergence of AI, customer centricity, supply chain connectivity and sustainability can help market new grades to the customer most likely to embrace them despite their price premium.[/h3]
The big takeaway for chemical firms is that other manufacturers are moving ahead, often quickly, along these four dimensions. Advances in each discrete area will have compounding effects across the others — and will increasingly impact competitiveness.
To invest in AI, customer centricity, supply chain connectivity and sustainability, as leading manufacturers are doing, may soon be tantamount to investing in staying in business at all.
Editor’s Note: This article first appeared in Processing and is republished here with permission.