In 2024, the Ministry of Industry and Information Technology and other nine departments jointly issued the "Work Plan for the Digital Transformation of the Raw Material Industry (2024-2026)", and the "Implementation Guide for the Digital Transformation of the Petrochemical Industry" attached to the "Plan" provides an action guide for the digitalization of the chemical industry. By 2026, the level of digital networking in the chemical industry will be significantly improved, the integration of data and reality will continue to deepen, the intelligent manufacturing capabilities of enterprises will be significantly enhanced, the platform services based on the industrial Internet will make positive progress, and the artificial intelligence engine for subdivided industries will take shape, moving from "deepening application" to "change leading", and continue to consolidate the leading position of the process industry. At the same time, the "Guide" puts forward a series of questions and answers to the implementation of digitalization, how to scientifically assess the current level of digitalization in the industry? How to improve the ability to develop industry scenarios and provide solutions? How to improve the level of intelligence in the industry? How to improve industry network and data security governance? How to promote the application of artificial intelligence in the industry?
The current state of digitalization in the chemical industry
Most of the chemical enterprises have problems such as weak ability to obtain real-time data such as physical parameters in the production process, especially process data such as material components, incomplete collection and aggregation, and in-depth value mining, which restricts the value of data elements.
The chemical industry lacks a unified and quantifiable index system to scientifically evaluate the current level of enterprise digitalization, resulting in an unclear foundation and unclear transformation path for the digital transformation of the industry.
Based on the above status quo and policies of enterprise digitalization, based on the current status of chemical enterprises, Paco Data has built a data analysis index system with industry characteristics to help enterprises quickly promote digital implementation. The data analysis index system of the industry involves all aspects of chemical enterprise finance, supply chain, planning, production, quality, equipment, safety, and process, so as to achieve the digitalization of production and operation, safety risk monitoring, and early warning.
From the massive data of chemical enterprises in the whole field, we should grasp two indicators to find the gap, and see which company in the chemical industry has more core competitiveness, we recommend the following two indicators:
Indicator 1: production capacity
In the chemical industry, production capacity is the key to victory. This is reflected in the financial report, there are two accounts, one is fixed assets and the other is under construction. In the final analysis, the chemical industry is still an asset-heavy industry, as long as fixed assets are involved, it is inevitable to release production capacity and increase revenue.
Indicator 2: Speed (speed of product sales, speed of payment collection)
The production capacity is sufficient, and the next step is to look at the speed of product sales and the speed of collection. If the sales and payment collection speed of the enterprise are fast, the revenue growth is fast, and the inventory turnover rate is getting faster, and the compound growth rate of receivables is declining as a whole. This shows that it can improve its own shipping speed and payment collection speed while increasing its revenue, and it also shows that the company's voice in the downstream has become stronger.
Looking at the whole industry as a whole, the chemical industry is very complex, and it is divided into coal chemical industry, oil chemical industry and natural gas chemical industry according to chemical raw materials. And 90% of the mainland's chemical products come from oil and natural gas. In recent years, enterprises above designated size in the petroleum and chemical industry have achieved a year-on-year growth rate of about 15% in their main business income. From the perspective of industry concentration, the overall concentration of the chemical industry is improving, and chemical products are also highly concentrated in a few products.
Compared with other industries or companies with stable product prices, the value analysis of listed companies in the chemical industry requires us to combine the characteristics of the industry and select the appropriate data indicators to judge.
Key indicators of digital operation in the chemical industry
Focusing on these two indicators, we can further design the gross profit margin index of the enterprise, which is the most direct indicator to understand the business prosperity of a chemical enterprise. Combined with the raw material prices that reflect the prosperity of the entire chemical industry chain, the key index system of chemical enterprises is constructed, so as to assist enterprises in making decisions on performance reversal and low prices. The details are as follows:
1. Production and sales: measure the company's growth
The growth rate of operating income of chemical enterprises is the result of the combined effect of sales volume changes and product price changes, because the price of chemical products is affected by the fluctuation of raw material prices, relying only on operating income indicators can not fully reflect the company's growth. For example, if the price of a product falls sharply, there is a possibility of a decline in operating income even if the product sales continue to grow. Therefore, we need to exclude the impact of operating income fluctuations caused by price fluctuations, and select product production and sales indicators to measure the company's growth.
2. Gross profit per unit of products: measure the profitability of the company's products
Different from products with stable sales prices, the profitability of chemical products also needs to consider the gross profit per unit of the product. Since the price of chemical products fluctuates with the price of raw materials, when the gross profit of the product remains unchanged and the price of raw material products rises or falls, the gross profit margin will decrease or increase accordingly, but the real profit of the product has not changed at this time, and the gross profit margin indicator cannot truly reflect the profitability of the enterprise. Therefore, the unit gross profit is usually selected as an indicator to analyze the real profitability and prosperity of the product.
3. The company's ROA (return on assets), etc.: the return on investment of industries with high barriers is higher
In terms of ROI, industries with high barriers to entry generally have relatively high ROAs. The production process of some important raw materials MDI is mastered by the head enterprises, and the process technology is strictly confidential, and the technical barriers are extremely high; The industry's oil refining and chemical production technology can be sold publicly, and there are no barriers to the transfer of product technology in the polyester polyester and coal chemical industries. From the perspective of return on investment, the return on investment of leading enterprises in the MDI industry is much higher than that of leading enterprises in the oil refining, polyester and coal chemical industries, reflecting the impact of industry technical barriers on corporate profitability and return on investment.
4. The growth rate of projects under construction: the prediction of the new supply of the industry and the prosperity of products
The prosperity of the chemical industry will generally experience a cycle of "insufficient production capacity - short supply - capacity expansion - oversupply", and with the change of supply and demand, the industry also shows a cycle of "prosperity-non-prosperity-prosperity". Generally speaking, it takes about 18 to 24 months for the new production capacity of chemical products to be put into operation, and the future prosperity of the product can be judged by studying the growth rate of the industry's construction projects in advance, and at the same time, combined with the change in demand, the future prosperity of the product can be judged. Specifically, when the industry is in a non-economic cycle, the willingness of enterprises to expand is weak, the growth rate of projects under construction slows down, and the growth rate of production capacity slows down; After the excess capacity is gradually digested, the industry has entered a boom cycle, the overall profitability of the industry has rebounded, and the profitability of enterprises has increased. Therefore, we can indirectly understand the new supply and product prosperity of the industry from the growth rate index of construction in progress.
The chemical industry fluctuates in cycles, and different chemical sub-sectors have different barriers, resulting in different returns on investment in different industries. In-depth analysis of indicators such as production and sales volume, gross profit per product unit, ROA, and growth rate of projects under construction of chemical enterprises can help investors better evaluate the profitability and future growth of chemical enterprises and make more accurate value judgments.
At present, big data and artificial intelligence, as strategic and forward-looking technologies leading a new round of scientific and technological revolution and industrial transformation, are accelerating the comprehensive penetration and integration of the economy and society, becoming a new means for the transformation and upgrading of the manufacturing industry and a new engine for the high-quality development of the industry. Since the 80s of the last century, the chemical industry has begun the application of DCS control system, and the long-term accumulation of a large amount of data has the natural advantage of developing and applying "large models". Therefore, chemical enterprises are driven by digital scenarios in all aspects such as data collection, data processing, and data assets, and lay solid data for the subsequent application and exploration of "large models" in the chemical industry, so as to improve the total factor productivity of the industry and empower high-quality development.
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