The steel industry has significantly transformed in the past decade. The demand for steel has expanded in industries such as automobile, engineering, infrastructure, steel production, and construction. As a result, the producers are facing immense pressure to control costs while also maintaining their supply chain. While doing this, they are also subject to fluctuations in the prices of raw materials and changing market conditions. The ongoing disruptions in the supply chain have made the process of procurement more complex than ever.
Earlier, the decisions related to procurement were based on relationships with the suppliers, historical pricing, experience of the procurement teams, and manual negotiations. While these methods have helped in the short run, they cannot fully help scale businesses in a competitive and fast-changing environment. The Indian steel industry is now making use of AI-based procurement to adapt to the ongoing business challenges.
How is Procurement Becoming More Data-Driven?
With the help of AI-powered procurement systems, companies are able to analyze large volumes of data and also identify recurring patterns. These patterns might not be immediately visible to the procurement teams.
The manufacturers of steel have to deal with multiple factors such as prices of raw materials, performance of the suppliers, transportation costs, level of inventory, requirements of the production teams, and the market demand. With the help of AI, all of these data points are brought together, and it gives a more comprehensive view of the procurement decisions. As a result, the manufacturers do not have to react to supply shortages or price changes after they occur. They can make use of AI-based data to forecast potential changes and accordingly make adjustments in the purchasing strategy. In this way, the procurement teams have moved from a reactive model to a more data-driven and proactive approach.
How Does it Give Better Price Visibility?
The manufacturers of steel are always subject to price volatility. The prices of the raw materials and the required inputs can change due to global commodity trends and the movement of currency. Apart from this, they can also change due to energy costs, geopolitical conditions, and changes in demand. By making use of the AI-powered procurement platforms, companies are able to analyze the historical data and real-time market data. It can help the teams understand the market conditions and make better decisions. In this way, the visibility around pricing is improved.
It helps strengthen the negotiations with the suppliers. The buyers are also able to get better access to more comprehensive market intelligence.
Smarter Discovery of Suppliers and Their Related Evaluation
The application of AI has helped significantly in the selection of suppliers. Steel manufacturers are bound to have a huge network of suppliers. Over time, the companies are also able to compare the performance of various suppliers and identify the potential risks, which might include inconsistency in quality or recurring delivery delays.
This does not mean that artificial intelligence will replace human decision-making. It can only give the procurement experts more information to support the selection of suppliers and negotiations.
How Does Demand Forecasting Become More Accurate?
In the steel industry, procurement and production planning are closely related. If a company orders too little of the raw material, it can lead to delays in production and force the business to make expensive purchases in the short run. On the other hand, ordering too much raw material can increase the working-capital cost and the inventory.
To improve demand forecasting, artificial intelligence can analyze the historical purchasing patterns, market demand, production schedule, and other relevant data. By forecasting more accurately, steel manufacturers can determine what raw materials they need and when they are most likely to need them. As a result, companies get a more balanced approach to inventory management.
How Can It Help Optimize Inventory and Reduce Costs?
In steel procurement, one of the most important applications of AI is the optimization of inventory. If a company holds an excess of inventory, it can tie up capital and increase the storage-related costs. If a company is not able to maintain a sufficient level of inventory, they are more likely to expose the manufacturer to price spikes and disruptions related to production.
AI-based systems are able to continuously analyze the inventory levels, lead times, procurement requirements, and patterns of consumption. By making use of the given insights, companies are able to identify opportunities and reduce excessive stock. This can help maintain a sufficient level of safety inventory. Some industries might operate on a large scale, and a small improvement in inventory efficiency can mean a significant amount of savings.
Will The Role of Human Beings Remain Relevant?
Despite the benefits offered with the application of AI, the need for human intervention and experienced procurement professionals will not be done away with. The whole process of steel procurement would still require complex commercial relationships, negotiations, strategic decisions, and quality considerations. All of these processes require human intervention. Therefore, AI should be employed as a decision-making tool rather than a complete replacement for the procurement teams.
In the coming years, we will require collaboration between people and technology. The procurement professionals should be able to focus on negotiations, strategic planning, and supplier relationships. On the other hand, AI should be focused on handling the data analysis, forecasting, routine decision support, and monitoring.
The Road Ahead
The adoption of artificial intelligence in the steel industry is not limited to the adoption of a simple digital tool. It has fundamentally transformed how manufacturers are now approaching sourcing, supplier management, and inventory. It has helped improve price visibility, strengthen the discovery of suppliers, enhance demand forecasting, and identify the risks related to the supply chain. With the integration of AI, steel manufacturers are able to make more informed and smarter decisions.
As companies are faced with greater cost pressure owing to the increased competition, only those companies that are able to make data-driven procurement decisions will be able to gain an important competitive advantage.
Authored by Dhananjay Goel, Managing Director, Enlight Metals