How intelligent technologies rewrite the rules for success in the chemical industry

Even with the shift to the experience economy and all of the discussion of digital transformation, the chemical industry is still an asset-intensive industry—one that continues to grapple with many of the pressures of a commodity market. Many chemical companies continue to struggle with visibility into the downstream value chain, which hampers their ability to anticipate and react to supply chain disruption.

Producers still place tremendous emphasis on equipment effectiveness and asset performance. They want to increase production and maximize asset uptime. And they want to evolve from a reactive approach to asset management to a more proactive, data-driven paradigm. They also want to squeeze every ounce of efficiency out of their processes by linking production with their supply and demand value chain. And intelligent digital technologies can help in each of these areas—and more.

Achieving the best of both worlds

In essence, chemical companies have a foot in both worlds. At its core, the business is an asset-intensive production cycle, but companies also want to operate as digital entities. They want to leverage data across the entire product lifecycle to optimize product formulation, embrace new business models and revenue opportunities, and deliver the rich, personalized experiences their customers are now demanding.

By deploying intelligent digital technologies, chemical companies can analyze production process variables and asset performance in real time—and simulate their impact on product quality, costs, and yield. Through the predictive analysis that these technologies make possible, companies can better anticipate downstream supply chain disruptions and take corrective actions in real time. They can also use the data they collect to simulate and implement contingency plans on an ad hoc basis to mitigate risks along the entire supply chain. And with IoT connectivity, chemical companies can continuously monitor asset health, process quality, throughput, waste, emissions, and the other variables that inform better decision making.

Enabling more proactive business models

IoT devices and other intelligent technologies generate a significant quantity of data—data that chemical companies can use to predict the likelihood of asset failures and optimize maintenance planning. With the insight they gain, companies can also adjust their production plans, authenticate raw materials and automate tasks such as tank replenishment and fleet management. In essence, they can take a more proactive approach to mission-critical operations and accelerate their response to disruptions that threaten ongoing business.

Breaking down barriers within the enterprise and throughout the value chain

Siloed data and processes within the enterprise and across the supply chain can slow production and amplify the effects of disruption. The lack of integration also inhibits the process automation that’s key to keeping costs in check and accelerating cycle times. Intelligent digital technologies can help knit together disparate systems and functions by creating an asset intelligence network that improves visibility across the value chain. The insight gained paves the way to more accurate predictive models and experience management to better forecast demand and balance it with supply in real time. Through the sharing of real-time data these technologies collect, companies can streamline collaboration with their customers, suppliers, and service partners upstream and downstream.

Facilitating innovation and continuous improvement

Intelligent technologies are great at driving higher efficiency and productivity from existing assets. But chemical companies are also finding that they can be instrumental in developing new business models and revenue streams, including selling business value and outcome-oriented services and developing custom products for a “segment of one.”

Artificial intelligence and machine learning technologies can “learn” from existing data and predict future outcomes based on new data. Chemical companies can use these capabilities in areas such as cash management to boost automatic matching rates and free up finance professionals to focus on strategy and service quality. They can also use the same capabilities to automate HR talent screening to identify the best candidates in an increasingly competitive talent market.

Remote monitoring technologies are nothing new for chemical companies. But the next generation of solutions combine data collection with the artificial intelligence and machine learning capable of analyzing vast quantities of data to generate unprecedented insights that can affect business outcomes and inform strategy. Also, they make it easier to share data across the value chain to enable faster, more flexible, and more efficient shared processes to anticipate and respond to customer demand and drive down costs. Finally, they simplify the remote monitoring of assets to better predict maintenance needs and identify potential quality problems in manufacturing processes before they occur.

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