Intelligent Procurement Management Leads Industry Transformation

(By Song Pengfei)

Big data and machine learning technologies are disruptive and cutting-edge, seen as a significant driving force behind the new round of technological revolution and industrial transformation. They are expected to profoundly change the way humans produce and live, empowering innovation and development across various industries.

In recent years, the introduction of large models and rapid iterative evolution has given rise to a new wave of rapid development in artificial intelligence technology, with intelligent procurement systems being an indispensable field for the application of large models. Industry data indicates that by 2025, the global procurement management software market's annual growth rate is expected to remain above 10%, with the market size set to expand further. This growth is primarily attributed to the application of cutting-edge technologies such as big data, cloud computing, and machine learning, which make the automation and intelligentization of procurement processes possible, greatly enhancing procurement efficiency and quality. However, during this transformation process, the industry also faces many challenges and difficulties.

Complex and Tedious Processes with High Potential for Human Error

Traditional corporate procurement management often relied on cumbersome manual operations and complex approval processes. Research shows that, on average, a company's procurement cycle can span from several weeks to several months, with errors and delays caused by human factors accounting for more than 30%. This not only reduces procurement efficiency but also increases operational costs. At the same time, information flow in traditional procurement management is often not transparent enough, making it difficult to obtain key data such as supplier information and procurement progress in real time, thereby affecting the accuracy of risk control and decision-making.

In addition to this, the rapid changes in market demand and the instability of supply chains also pose significant challenges to corporate procurement. To address this issue, Mr. Huang Jianxin, Deputy Director of the Procurement Department of Guangzhou Liby Enterprise Group Co., Ltd., has independently developed a "Procurement Process Optimization System Based on Machine Learning," a "Procurement Information Supervision Platform Based on Big Data," and a "Comprehensive Evaluation System for Procurement Raw Materials Based on Cloud Computing." Due to their excellent performance and significant effects, these systems have quickly made a wide impact in the industry, setting a benchmark.

Technological Breakthroughs, an Innovative Leader in Procurement Management

"The main reason I developed intelligent procurement systems was for work efficiency. I have worked in the procurement department of Guangzhou Liby Group for over 10 years, and in the long-term work, I found many issues of low efficiency caused by processes and systems, so I thought about relying on big data technology to make some optimizations and improvements," Huang Jianxin said to the reporter. When mentioning the specific effects of these three systems and what they have improved, Huang Jianxin also elaborated: "The 'Procurement Process Optimization System Based on Machine Learning' utilizes advanced machine learning algorithms and technologies to achieve the automation and intelligentization of the procurement process. Through key steps such as data collection and analysis, demand forecasting, supplier evaluation, automated procurement decision-making, and continuous optimization, this system can provide comprehensive procurement management support for enterprises. In the past, when we made purchases, the process was very cumbersome, and there were many paper documents to fill out. We have made a lot of improvements in this regard."

Image: https://www.wdwire.com/wp-content/uploads/2024/06/image-46.png

(Figure: Huang Jianxin)

For the collection of orders and supplier information, after a large number of data experiments, he developed the "Procurement Information Supervision Platform Based on Big Data." This platform integrates massive data sources to achieve real-time collection, integration, analysis, and display of procurement information. Enterprises can clearly understand every link in the procurement process, including supplier information, procurement prices, quantities, and timing. At the same time, this platform can also predict and warn of the procurement process based on historical and real-time data, helping enterprises to discover potential risks and problems in a timely manner. "According to statistics, the accuracy of supplier selection for companies using this platform has increased by 40%, and procurement risks have been reduced by 30%, which is still very significant," Huang Jianxin said.

Not only that, but for the core of procurement selection and evaluation, he developed a "Comprehensive Evaluation System for Procurement Raw Materials Based on Cloud Computing" to assist enterprises in making choices. This system uses cloud computing technology to centrally store and manage information on various procurement raw materials. By thoroughly analyzing and evaluating this information, the system can provide enterprises with more scientific and reasonable suggestions for the selection of procurement raw materials. "According to user feedback, after adopting this system, the cost of enterprise procurement raw materials has been reduced by 15%, and the quality of procurement has also been improved," Huang Jianxin said.

Never Complacent, Still Striving

This outstanding representative in the industry is well aware of the rapid pace of technological development and market changes, so he always maintains a humble and enterprising attitude. Although he and his team have achieved remarkable results and brought revolutionary changes to corporate procurement management, Huang Jianxin does not dare to be complacent. "Only by continuously improving and innovating can we maintain a leading position and meet the constantly changing needs of the market and enterprises," Huang Jianxin said. Therefore, he has already started planning the subsequent improvements of the system, aiming to further enhance system performance, optimize user experience, and explore more innovative functions and application scenarios.

"Regarding the follow-up improvement plan, I believe we should start with three points: First, we will further optimize the system's algorithms and models to improve the accuracy and efficiency of data analysis and forecasting. This will help enterprises to grasp market dynamics and supplier situations more accurately and formulate more reasonable procurement strategies and plans. Second, we should pay attention to the continuous optimization of user experience. By collecting user feedback and continuously improving interface design, operation processes, and other aspects, we strive to make the system more user-friendly and convenient, improving user satisfaction. In addition, we will actively explore more innovative functions and application scenarios. For example, introducing artificial intelligence and Internet of Things technology into the system to achieve more intelligent procurement management and supply chain management. This will help enterprises further improve procurement efficiency, reduce costs, and optimize the performance of the entire supply chain," Huang Jianxin believes.

On the path to intelligent procurement management, Huang Jianxin and his team have demonstrated outstanding leadership and innovative spirit. They have not only successfully created a procurement management system of epoch-making significance but also brought significant economic benefits and competitive advantages to enterprises. However, as Huang Jianxin has shown, true success is not the end point, but a process of continuously pursuing excellence and innovation. Facing the future, Huang Jianxin and his team will continue to maintain a humble and enterprising attitude, constantly seeking technological breakthroughs and innovative application

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