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Given the importance of technology and processes in the chemical industry, excellence in supply chain management arguably plays a key role in creating an edge. To stay ahead of their competitors, it is imperative for chemical companies to have a smooth and efficient supply chain. This implies coordination across aspects of the supply chain function, starting from getting the raw materials from the vendors to the delivery of the final product to the end customers.

The advancements in artificial intelligence (AI) have contributed significantly to the evolution of supply chain management. AI combines the benefits of a machine’s efficiency with a human’s common sense to optimize supply chain processes, and the chemical industry has been open in adopting these advancements in its operations.

According to a survey by IBM, 80% of executives are of the opinion that AI will bring about great success to the chemical industry in the next 3 years.

Why is it necessary to optimize chemical supply chains?

The chemical industry is critical for any economy. It supplies the raw materials used in the production of multiple goods across industries. In fact, 96% of all manufactured goods from paints to pharmaceuticals, cement to cosmetics in the world depend upon chemicals.

The chemical industry being interconnected with manufacturing across different sectors, a smooth supply chain becomes imperative.

The core of operations in the chemical industry is Material Resource Planning (MRP) and an efficient supply chain is essential to ensure the cycle of material and money is balanced. This involves multiple repetitive processes which have patterns and trends. And mastering these patterns and trends ensures the availability of optimal raw material for manufacturing and equally meeting demand on time and without any errors.

While operating on a small scale, companies can still get away with inefficiencies in the supply chain. But to scale up production and tap the growing demand for chemicals, companies need to ensure their supply chain is lean and optimized.

What are the main issues with chemical supply chain management?

Every growing industry is characterized by an increase in participants and a high level of competition. The chemical industry is no different. More and more companies are understanding the potential of chemicals—they are scaling up production to take advantage of the increased demand.

Scaling up does not come without its own set of challenges, though. Some of the pain points in chemical supply chain management are as follows.

  • Lack of visibility

The chemical industry cannot function on its own. The components of the ecosystem it operates in are highly interdependent Different parties are involved. Raw materials come from different vendors. Finished products are sent to many buyers across different industries.

At any point in time, several workflows are in motion. It is difficult to keep track of everything that is happening, particularly if the operations are on a large scale.

  • Production planning

Chemical manufacturing is not the easiest process in the book. Specific materials are required and the production process must be strictly adhered to. Accuracy is a must for the production of top-quality products.

It is difficult to get visibility of the production process, given the intricacies involved. There may be a delay with some material or an issue with the machinery. All these add to the production time and increase delays.

  • Quality assurance

It is not enough to just complete the production process. Stringent standards have to be followed to guarantee the quality of the products. With industrial chemicals, even minor deviations can affect the finished product.

Maintaining quality standards has a strong bearing on the revenues. Any dip in quality can severely affect the bottom line.

How can AI improve chemical supply chain management?

The chief advantage of AI is that it can automate the repetitive tasks in the supply chain. For example, data entry, record updates, reminders, and status checks can be delegated entirely to AI-based tools.

The strategic application of AI in chemical supply chain management can transform the division of labor. The time-consuming manual tasks can be outsourced, freeing up bandwidth to focus on core operations and growth strategy.

Some benefits of using AI are listed below.

  • Productive capacity

AI can help in identifying areas of under-utilization in the manufacturing cycle. It provides a complete overview of which machine is working how many hours. Companies can visualize the entire process like a flow and optimize productive capacity.

  • Cost-effectiveness

Using AI can help save on employee costs by automating tasks and reducing manual dependence. The strategic use of software cuts down on any losses caused by manual errors. It can also help cut down on production time and reduce the manufacturing cycle.

  • Predictive forecasting accuracy

Raw material procurement patterns, consumer buying behaviour and seasonality cycles are impertinent in the chemical industry and this is further aggravated by heavy fluctuation in the raw material pricing. AI-based tools help in analyzing demand and supply patterns based on which production can be planned. Accurate forecasting will contribute to bringing down inventory costs and increasing the turnover rate.

  • Innovation and product development

The strategic use of AI in the product development process can cut down on the time-to-market drastically. Enhancing efficiency in every step speeds up both the product development time and the market launch.

  • Feedstock risk management

The sourcing of raw materials happens across the world with different lead times and different price points. The hedging eco-system offers a wide variety of derivative instruments through commodity exchange markets. AI tools can enable decision makers in the chemical industry to avail of such derivative instruments in hedging their risks and (thereby) protecting profitability.

To conclude

That AI can boost efficiency is no doubt true. What remains to be seen is how long it will take for the use of AI in chemical supply chain management to be commonplace.

Currently, the adoption rate is low. Based on published information, less than 50% of companies in the chemical sector use AI for their supply chain management. However, the popularity of AI is expected to increase in the next few years.

AI and machine learning can apply to various areas, like research and development, product creation, inventory management, and health standards. The use cases are only set to increase in the future.

For more on Business Research, connect with R. Subramaniam, Executive VP, Avalon Global Research.