The acceleration of globalization has opened up a new market for manufacturing enterprises in chemical industry. US based chemical manufacturing companies are selling products and chemicals to emerging markets. In fact, the total global demand for chemicals is $5 trillion, half of which comes from emerging markets.
However, with the arrival of new opportunities, the chemical industry, especially the whole value chain, is facing new and different challenges.
1: Price fluctuation of raw materials and commodities
Chemical manufacturing enterprises are vulnerable to sudden changes in the prices of raw materials, energy and other commodities. For example, fluctuations in the price of crude oil or natural gas, which account for 50% of chemical companies’ production costs, have a significant impact on their bottom line. Carrying a large number of different chemicals in inventory also makes it difficult to track changes in costs and prices.
To control rising costs and maintain a healthy bottom line, chemical companies need to have a comprehensive view of their supply chain. They need to understand the volatility of raw materials and commodity prices in order to integrate them into their resource planning systems. This enables them to adjust the supply chain, find efficiency in the market and make better purchasing decisions.
2: Higher quality control risk
The chemical industry is a highly regulated industry, and governments and regulatory bodies, such as the globally harmonized system of classification and labelling of chemicals (GHS), strictly comply with the regulations. The purpose is to ensure the protection of the environment and human health during the processing, including use and transportation of chemicals. chemical companies need to solve and comply with these requirements in the procurement phase of the supply chain.
Moreover, with the rise of social media and stricter consumer protection programs, the risk of quality control failure and initiating product recalls has never been so high. Negative news and public supervision will greatly damage the brand image, leading to the loss of goodwill and long-term negative impact. Chemical companies also need to have visibility into their entire production process to quickly identify substandard batches and track the root cause of the problem.
3: Managing massive data
Data management in chemical companies is becoming more and more difficult and complex. Pricing and information quality of raw materials and goods from suppliers, from governments and regulatory agencies, regulatory and compliance requirements with customer agreements and contracts, and manufacturing data and operations – all of which generate large amounts of data that must be classified, processed, business insight and leveraged.
However, many chemical companies and manufacturers still lack systems and it infrastructure to access critical information. For example, some chemical companies do not have complete information to accurately determine the end-to-end cost of each product from purchase to delivery. As a result, they cannot correctly judge which products contribute positively to profits and which do not perform well.
Saving big data solutions
Big data solutions enable chemical companies to overcome these challenges and develop advanced supply chain management methods. The integration capability of big data solutions enables chemical companies to integrate pricing and quality information from different sources into their systems. This enables them to effectively track price fluctuations and changes in the quality of raw materials and goods from suppliers.
The data mining capability of big data solutions enables chemical companies to quickly identify problems and potential problems in the whole value chain, and quickly track their root causes. This also makes it easier for chemical companies to comply with regulatory requirements.
The analysis and visualization capabilities of big data solutions simplify a lot of information, enabling chemical companies to transform data into operational insights. In addition, the predictive power of big data solutions can help them predict possible outcomes and make better data-based decisions.