College procurement risk management and fund early warning system in multi-supplier environment

Abstract

The invention belongs to the technical field of college purchase risk management, and discloses a college purchase risk management and fund early warning system in a multi-supplier environment. The invention provides a college purchase risk management and fund early warning system in a multi-supplier environment. The system comprises a supplier management module, a purchase plan scientific making module, a fund early warning and monitoring module and a data statistical analysis and decision support module. According to the invention, a set of integrated purchase risk management and fund early warning system is constructed, the overall efficiency of college purchase management is improved through a digital whole process, risks occurring in the purchase process can be effectively identified and managed, and unnecessary expenditure is reduced through accurate fund management; therefore, high efficiency, transparency and compliance of college purchasing activities are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of university procurement risk management, and in particular relates to a university procurement risk management and funding early warning system in a multi-supplier environment. Background Art

[0002] In a multi-supplier environment, university procurement activities face many challenges, including supplier selection, risk prevention and control, and funding management. This system integrates computer network information systems and data analysis technology to achieve standardization and transparency of procurement processes, and improve risk prevention and control capabilities and funding management levels.

[0003] The supplier management system is the core pillar of the procurement process in colleges and universities. It cleverly uses computer network information systems to build a comprehensive supplier database, which not only gathers key information such as supplier qualifications, market reputation, product performance parameters and real-time prices, but also uses data analysis technology to scientifically evaluate and screen out suppliers with excellent quality and good reputation, thereby significantly reducing the potential risks in the procurement process. In terms of procurement risk management, the system introduces an expert bid evaluation group review mechanism to conduct a comprehensive and in-depth risk analysis of procurement projects. At the same time, with the help of advanced data analysis technology, the system has built an efficient risk warning model that can keenly capture high-risk projects and links. Once the preset risk threshold or indicator is triggered, the alarm will be automatically sounded immediately to remind relevant personnel to take countermeasures quickly, effectively curbing the spread of risks.

[0004] The funding early warning system accurately sets the funding budget threshold according to the actual needs of the procurement project and implements uninterrupted monitoring of funding usage. Once funding usage approaches or exceeds the budget red line, the system will immediately issue a warning signal to ensure the rational use and strict control of funds. The system also provides a detailed funding usage analysis report, providing colleges and universities with a clear and intuitive overview of funding usage, helping them optimize funding allocation strategies and improve funding efficiency.

[0005] In a multi-supplier environment, university procurement data has the characteristics of wide sources and diverse formats. How to effectively integrate this data and share it across departments and systems is a major challenge. Although current technologies provide solutions for data integration and interface docking, they still face complex issues such as data standardization and authority management in practical applications. It is necessary to further optimize data integration strategies, strengthen data standardization, and ensure data accuracy and security. At the same time, a sound authority management mechanism should be established to ensure legal access to and use of data.

[0006] In actual application, due to the complexity and variability of procurement projects, it is difficult for the model to accurately predict all risks. It is necessary to introduce more advanced data analysis technologies, such as machine learning and deep learning, to improve the prediction accuracy and adaptability of the model, strengthen the continuous optimization and iteration of the model, and ensure its effectiveness and reliability in actual application.

[0007] Procurement in universities often requires connecting with different suppliers, managing diverse procurement categories, supervising the use of high-value funds, and ensuring financial transparency. Non-digital management methods often make it difficult to achieve comprehensive monitoring of procurement process risks, especially in the context of multi-supplier cooperation, where information asymmetry, price fluctuations, and contract execution risks are more frequent. These factors, coupled with the complexity of fund use, can easily lead to problems such as reduced procurement efficiency, rising costs, and abuse of funds.

[0008] The general method is to enter the procurement information into the existing financial system and asset management system, proofread and audit it after entry, and manually export and count it periodically; but the manual entry system is severely fragmented, time-consuming and labor-intensive, lacks flexibility, and the data accuracy and response efficiency are highly dependent on the operator himself, and once an error occurs, it is difficult to trace the source.

[0009] Through the above analysis, the problems and defects of the prior art are as follows:

[0010] The general method is to enter the procurement information into the existing financial system and asset management system, proofread and audit it after entry, and manually export and count it periodically; but the manual entry system is severely fragmented, time-consuming and labor-intensive, lacks flexibility, and the data accuracy and response efficiency are highly dependent on the operator himself, and once an error occurs, it is difficult to trace the source. Summary of the invention

[0011] In view of the problems existing in the prior art, the present invention provides a university procurement risk management and funding early warning system in a multi-supplier environment.

[0012] The present invention is implemented in this way: a university procurement risk management and funding early warning system in a multi-supplier environment includes:

[0013] The supplier management module is connected with the scientific procurement plan formulation module, the funding early warning and monitoring module, and the data statistical analysis and decision support module to establish a supplier archive database, including basic supplier information, available equipment types, relevant industry qualifications, previous supply conditions, and after-sales service evaluation, providing data support for procurement plan formulation;

[0014] The module for scientifically formulating procurement plans is connected with the supplier management module, the funding early warning and monitoring module, and the data statistical analysis and decision support module to scientifically plan procurement plans based on the supplier archive database;

[0015] The funding warning and monitoring module is connected with the supplier management module and the scientific procurement plan formulation module. It is used to monitor and calculate the funding usage in real time according to the procurement plan and budget, set the warning threshold, and immediately trigger the warning mechanism once an abnormality or overspending risk is found, prompting the management personnel to intervene and make adjustments;

[0016] The data statistical analysis and decision support module is connected with the supplier management module and the scientific procurement plan formulation module for information sharing, process monitoring and data analysis, providing data support for procurement management decisions; the system has a built-in data statistical analysis module to conduct in-depth mining and statistical analysis of procurement data, provide decision support for management, and optimize procurement strategies and indicator allocation.

[0017] Further, the supplier management module method is as follows:

[0018] 1) Supplier rating mechanism, which rates suppliers based on a comprehensive evaluation of their supply quality, price, delivery date and service attitude, providing a reference for purchasing decisions;

[0019] 2) The supplier blacklist system records and blacklists suppliers who have committed illegal or irregular acts, restricting them from participating in subsequent procurement activities.

[0020] Furthermore, the procurement plan scientific formulation module method is as follows:

[0021] 1) Risk assessment model, which quantitatively evaluates potential risks in the procurement process based on historical data and expert experience;

[0022] 2) Intelligent supplier recommendation engine, which introduces artificial intelligence and machine learning algorithms, automatically recommends the most suitable supplier combination based on historical procurement data and supplier performance; the system can adaptively learn and optimize the recommendation algorithm. As data accumulates, the accuracy and scientificity of the recommendations will gradually improve, helping managers make procurement decisions more efficiently.

[0023] Further, the funding warning and monitoring module method is as follows:

[0024] 1) Dynamic budget adjustment mechanism, which allows appropriate adjustment of budget thresholds according to the actual situation of the procurement project to ensure flexibility and rationality in the use of funds;

[0025] 2) Fund usage report generation module, which automatically generates fund usage reports, including budget execution status, fund usage details and early warning information, for review by relevant departments;

[0026] 3) Multi-dimensional risk assessment and dynamic response mechanism: Add multi-dimensional risk assessment, including market price fluctuations, supply chain disruptions, and equipment technology update risks, to further enrich the application scenarios of the risk model; after identifying potential risks, the system can automatically generate response strategies and adjustment suggestions, including adjusting procurement priorities or finding alternative suppliers, to enhance the system's resilience.

[0027] Furthermore, the funding warning and monitoring module method also includes: procurement process automation and blockchain technology application, combining procurement process automation technology; through blockchain technology, ensuring the transparency of the procurement process and the non-tamperability of the data.

[0028] Further, the data statistical analysis and decision support module method is as follows:

[0029] 1) Process monitoring function: real-time monitoring of each link in the procurement process to ensure the standardization and transparency of the procurement process;

[0030] 2) Data analysis function: conduct in-depth mining and analysis of procurement data to provide data support for procurement management decisions.

[0031] Another object of the present invention is to provide a method for university procurement risk management and funding early warning in a multi-supplier environment, including:

[0032] Step 1: Establish a supplier archive database through the supplier management module, including basic information of suppliers, available equipment types, relevant industry qualifications, previous supply status, and after-sales service evaluation, to provide data support for the formulation of procurement plans;

[0033] Step 2: Scientifically plan the procurement plan based on the supplier archive database through the procurement plan scientific formulation module;

[0034] Step 3: Use the funding warning and monitoring module to monitor and calculate funding usage in real time based on procurement plans and budgets, set warning thresholds, and immediately trigger the warning mechanism once an abnormality or overspending risk is found, prompting management personnel to intervene and make adjustments;

[0035] Step 4: Provide data support for procurement management decisions through information sharing, process monitoring and data analysis of the data statistical analysis and decision support modules; the system has a built-in data statistical analysis module to conduct in-depth mining and statistical analysis of procurement data, provide decision support for management, and optimize procurement strategies and indicator allocation.

[0036] Another object of the present invention is to provide a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the university procurement risk management and funding warning method in a multi-supplier environment.

[0037] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the steps of the university procurement risk management and funding warning method in a multi-supplier environment.

[0038] Another object of the present invention is to provide an information data processing terminal, which is used to implement the university procurement risk management and funding early warning system in the multi-supplier environment.

[0039] In combination with the above technical solutions and the technical problems solved, please analyze the advantages and positive effects of the technical solutions to be protected by the present invention from the following aspects:

[0040] First, in view of the technical problems existing in the above-mentioned prior art and the difficulty of solving the problems, the technical solutions to be protected by the present invention and the results and data during the research and development process are closely combined to analyze in detail and deeply how the technical solutions of the present invention solve the technical problems, and some creative technical effects brought about after solving the problems. The specific description is as follows:

[0041] The present invention integrates and shares data in university procurement management, and innovatively builds an integrated and scalable data integration platform. The platform supports access to a wide range of data sources, including systems, files, and databases from different suppliers, and achieves automatic data capture and efficient conversion through preset adapters or API interfaces.

[0042] The present invention has developed a detailed data standardization system to ensure the consistency of the data access platform in terms of format, coding and semantics, laying a solid foundation for subsequent data processing and analysis. The platform's built-in data cleaning and verification module further improves the accuracy and integrity of the data.

[0043] The present invention improves integration efficiency. The automated and standardized data processing process greatly shortens data integration time, reduces labor costs, and significantly improves work efficiency. It enhances data availability. The unified data standards promote data interoperability and reusability, providing strong support for cross-departmental collaboration and decision-making. It strengthens data security. The refined authority management and security protection measures effectively prevent the risk of data leakage and ensure the sensitivity and compliance of procurement data.

[0044] In order to cope with the complexity of risk assessment in procurement projects, the present invention integrates advanced data analysis technologies such as machine learning and deep learning into the risk assessment model. Through big data analysis technology, the model can deeply explore the potential laws and patterns in historical data and improve the predictive ability of complex procurement projects. The model has self-learning and optimization functions, and can automatically adjust parameters and structures according to new project data and feedback results to achieve continuous iteration and upgrading. In addition, an expert knowledge base is established to digitize the experience and knowledge of experts in the field and combine it with the algorithm model to build a human-computer collaborative risk assessment system, which further improves the adaptability and accuracy of the model.

[0045] The present invention improves the prediction accuracy. The application of intelligent algorithms enables the risk assessment model to more accurately identify the risk factors and changing trends in procurement projects, providing universities with more reliable risk warnings and decision-making basis; enhances adaptability. The dynamic learning and optimization mechanisms ensure that the model can flexibly respond to changes in the procurement environment and maintain its effectiveness and reliability in practical applications; promotes knowledge inheritance. The establishment of an expert knowledge base not only retains valuable expert experience, but also promotes the dissemination and sharing of knowledge within the organization, thereby improving the overall risk management level.

[0046] The present invention constructs an integrated procurement risk management and funding early warning system, which improves the overall efficiency of university procurement management by digitizing the entire process, effectively identifies and manages risks arising in the procurement process, and reduces unnecessary expenses through precise fund management, thereby ensuring the efficiency, transparency and compliance of university procurement activities.

[0047] 1. Improve procurement efficiency: Through scientific planning of procurement plans and online bidding and evaluation, reduce manual intervention and human errors and improve procurement efficiency.

[0048] 2. Reduce procurement risks: Establish a comprehensive supplier management and risk assessment mechanism to reduce information asymmetry and contract performance risks.

[0049] 3. Optimize the use of funds: monitor the use of funds in real time, realize effective early warning and control of funds, and avoid abuse and overspending of funds.

[0050] 4. Improve decision support: Through data statistical analysis and decision support modules, provide management with accurate data support and decision-making basis, and optimize procurement strategies and indicator allocation.

[0051] Second, the expected benefits and commercial value of the technical solution of the present invention after transformation are as follows: In a multi-supplier environment, university procurement often faces multiple challenges such as supplier reputation, price fluctuations, supply stability, and contract execution risks. The present invention can monitor various risk points in the procurement process in real time through an intelligent risk assessment and early warning mechanism, issue early warning signals in a timely manner, and help the management of universities to respond quickly and take measures, thereby significantly reducing procurement risks and ensuring procurement quality and efficiency. The system conducts in-depth mining of supplier quotations, historical transaction data, market price trends, etc. through big data analysis and intelligent algorithms, providing scientific procurement decision support for universities, which can not only ensure the rationality of procurement prices and avoid unnecessary cost waste, but also further reduce overall operating costs by optimizing procurement plans, inventory management, etc. The system automatically processes a large amount of procurement data, reduces manual intervention, and improves the transparency and efficiency of the procurement process. The integrated funding early warning function can plan capital flow in advance, ensure that procurement projects are completed on time and in quality, and avoid project delays or cancellations due to funding shortages, thereby improving the overall management efficiency of universities. The system supports comprehensive evaluation of supplier performance, including supply quality, delivery on-time rate, after-sales service and other dimensions, which helps colleges and universities to screen high-quality suppliers and establish long-term and stable cooperative relationships. This data-based supplier management mechanism can enhance colleges and universities' bargaining power and risk control capabilities in the supply chain.

[0052] By implementing the system of the present invention, colleges and universities can significantly improve the level of procurement management, optimize resource allocation, and improve the efficiency of fund use, thereby showing stronger competitiveness and attractiveness in the education service market, and attracting more high-quality students and partners. Efficient, transparent, and honest procurement management helps to enhance the social image and public trust of colleges and universities, and enhance brand value. This is of great significance to colleges and universities in terms of enrollment, scientific research cooperation, and international exchanges. The system of the present invention provides a new digital solution for college procurement management, and promotes the transformation of colleges and universities to intelligent and refined management. The innovation of business models is not only applicable to colleges and universities, but also provides a model for reference for other educational institutions and even a wider range of public service fields. By reducing procurement costs and improving management efficiency, the system directly brings significant economic benefits to colleges and universities, promotes fair competition, resource optimization and other social effects, and also helps to promote the healthy development of the entire education industry and achieve a win-win situation of economic and social benefits.

[0053] The technical solution of the present invention solves the technical problem that people have been eager to solve but have never succeeded: in the field of higher education, procurement activities are an important link to ensure teaching, scientific research and daily operations, and their complexity and risks are becoming increasingly prominent. Especially in a multi-supplier environment, university procurement faces multiple challenges such as supplier management, cost control, and risk prevention and control. Among them, complexity management, university procurement projects usually involve multiple departments and links, the relationships are intricate and difficult to coordinate and manage effectively; uncertainty management, external factors such as production technology, market conditions, policies and regulations frequently change, resulting in low predictability of procurement projects and increased risks; integrity and compliance risks, suppliers fail to perform, fraud and non-compliance with procurement procedures frequently occur, directly damaging the economic interests and reputation of universities; funding management difficulties, the lack of effective monitoring and early warning mechanisms for the use of funds, easily leading to overspending, waste and other problems.

[0054] By integrating modern information technology and management concepts, a comprehensive management platform integrating supplier management, risk prevention and control, and funding warning is constructed. The supplier management module establishes a high-quality supplier database, conducts comprehensive evaluation and classification management of suppliers, and realizes dynamic update and real-time monitoring of supplier information. Through data analysis, suppliers with good reputation, reasonable price and reliable quality are screened to reduce procurement risks. The risk prevention and control module builds a risk warning system to timely identify and warn potential risks in the procurement process through data analysis and monitoring. At the same time, combined with the internal management system of colleges and universities and government procurement regulations, risk response strategies and measures are formulated to ensure the compliance and security of procurement activities. The funding warning module establishes a funding use monitoring and warning mechanism to track and analyze the funding use of procurement projects in real time. By setting warning thresholds and rules, when the funding use is close to or exceeds the budget, the system automatically issues a warning signal to remind relevant personnel to adjust the procurement plan and funding use plan in time.

[0055] Through the design of systematic and standardized management processes, the whole chain and all-round management of procurement activities can be achieved. Seamless connection between modules and data sharing improve management efficiency and coordination. Using advanced technologies such as big data and artificial intelligence, real-time monitoring and analysis of external factors can be carried out to improve the predictability and risk prevention and control capabilities of procurement projects. At the same time, by flexibly adjusting procurement strategies and supplier selection, the risks brought by uncertainty can be reduced. A strict supplier evaluation and review mechanism is established to ensure the reliability of supplier qualifications and reputation. At the same time, the construction of internal management systems is strengthened to ensure the compliance and transparency of procurement activities and reduce integrity risks and compliance risks. Through the establishment of a funding early warning system, real-time monitoring and early warning of the use of procurement funds are achieved. This helps colleges and universities better understand the use of funds, adjust procurement plans and budget arrangements in a timely manner, and avoid overspending and waste.

[0056] Third, the technical solution of the present invention solves the problems of complex procurement management in colleges and universities, high risk of overspending, unscientific supplier selection, lack of transparency in procurement process, etc. in the prior art in industrial application, and has achieved significant technical progress in the following aspects:

[0057] 1. Systematization and transparency of supplier management: Traditional supplier management relies on manual records, with incomplete information and untimely updates, which easily leads to unscientific procurement decisions. The present invention achieves comprehensive management of supplier information by establishing a supplier archive database, including qualifications, historical supply records, after-sales service and other information. This makes the procurement process more transparent, provides more sufficient basis for selecting suppliers, avoids procurement quality or service problems caused by unsuitable suppliers, and significantly improves the scientificity and efficiency of procurement management.

[0058] 2. Intelligent formulation of procurement plans: In the prior art, procurement plans often rely on manual decision-making, which is prone to unreasonable plans or over-budget situations. The present invention uses a scientific procurement plan formulation module to intelligently plan procurement plans based on historical procurement data, supplier information and budget constraints, automatically match suitable suppliers, and avoid blind procurement or over-budget problems. This module improves the accuracy and rationality of procurement plans and effectively reduces human errors in procurement.

[0059] 3. Real-time monitoring and early warning of fund use: Overspending or unreasonable use of funds in university procurement is often a management difficulty. The fund early warning and monitoring module of the present invention tracks the use of funds in real time, sets early warning thresholds, and can automatically trigger alarms when funds are used abnormally, reminding managers to make timely adjustments and interventions. This function improves the accuracy and controllability of fund management, ensures that funds are used within a reasonable range, and avoids waste and overspending.

[0060] 4. Intelligent data statistics and decision support: Traditional procurement management data is often scattered and not fully utilized. The present invention uses data statistical analysis and decision support modules to deeply mine and analyze big data in the procurement process, provide data support, decision-making suggestions and optimization plans for management, and help university managers formulate more scientific and feasible procurement strategies. This module significantly improves the level of intelligent procurement management, optimizes procurement processes and funding allocation, and further promotes the refinement and intelligence of management decisions.

[0061] Through the above-mentioned technological innovations, the present invention effectively solves the problems of complex procurement management, poor financial control, unreasonable supplier selection, etc. in a multi-supplier environment in universities, significantly improves the transparency, intelligence and scientificity of procurement management, and achieves remarkable technological progress. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1It is a structural block diagram of a university procurement risk management and funding warning system in a multi-supplier environment provided by an embodiment of the present invention.

[0063] Figure 2 This is an interface diagram of a university procurement risk management and funding early warning system in a multi-supplier environment provided by an embodiment of the present invention.

[0064] Figure 3 This is an interface diagram of a university procurement risk management and funding early warning system in a multi-supplier environment provided by an embodiment of the present invention.

[0065] Figure 4 It is a detailed flow chart of a method for university procurement risk management and funding warning in a multi-supplier environment provided by an embodiment of the present invention.

[0066] Figure 5 The present invention provides a flowchart of financial budget management.

[0067] Figure 1 In: 1. Supplier management module; 2. Scientific procurement plan formulation module; 3. Fund warning and monitoring module; 4. Data statistical analysis and decision support module. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0069] like Figure 1 As shown, a university procurement risk management and funding early warning system in a multi-supplier environment provided by an embodiment of the present invention includes:

[0070] Supplier management module 1, scientific procurement plan formulation module 2, funding warning and monitoring module 3, data statistical analysis and decision support module 4.

[0071] The supplier management module 1 is connected with the scientific procurement plan formulation module 2, the funding warning and monitoring module 3, and the data statistical analysis and decision support module 4 to establish a supplier archive database, including basic supplier information, available equipment types, relevant industry qualifications, previous supply conditions, and after-sales service evaluation, to provide data support for procurement plan formulation;

[0072] The procurement plan scientific formulation module 2 is connected with the supplier management module 1, the funding warning and monitoring module 3, and the data statistical analysis and decision support module 4, and is used to scientifically plan the procurement plan based on the supplier archive database;

[0073] The funding warning and monitoring module 3 is connected with the supplier management module 1 and the procurement plan scientific formulation module 2, and is used to monitor and calculate the funding usage in real time according to the procurement plan and budget, set the warning threshold, and immediately trigger the warning mechanism once an abnormality or overspending risk is found, prompting the management personnel to intervene and make adjustments;

[0074] The data statistical analysis and decision support module 4 is connected with the supplier management module 1 and the scientific procurement plan formulation module 2 for information sharing, process monitoring and data analysis, and provides data support for procurement management decisions; the system has a built-in data statistical analysis module for in-depth mining and statistical analysis of procurement data, providing decision support for management and optimizing procurement strategies and indicator allocation.

[0075] The college procurement risk management and funding early warning system under a multi-supplier environment of the present invention is mainly integrated with supplier management, procurement planning, funding monitoring and data analysis functions through information technology in industrial applications to achieve efficient procurement process management and risk prevention and control. The system first establishes a supplier archive through the supplier management module, and records in detail the basic information, qualification certification, supply history and after-sales service of each supplier, providing comprehensive data support for the formulation of subsequent procurement plans. This function not only improves the transparency of supplier management, but also helps the procurement department to better select suitable suppliers and avoid procurement risks caused by improper selection of suppliers.

[0076] Secondly, the module for scientifically formulating procurement plans combines the data from the supplier archives and analyzes the actual needs of various departments in colleges and universities to scientifically plan procurement plans. This module intelligently recommends the best procurement strategy based on historical procurement data and current needs, and controls the total procurement amount according to the budget, effectively reducing the risk of blind procurement and budget overruns. At the same time, the system can automatically match the right supplier for each procurement project based on the supplier's qualifications and past performance, ensuring the accurate execution of the procurement plan and reducing delays or quality problems caused by supplier problems.

[0077] The funding warning and monitoring module is the core risk prevention and control link of the system. By real-time monitoring of the use of funds for procurement projects, the system can promptly capture the risk of abnormal use of funds or budget overruns. When the fund consumption is close to the budget, the system will automatically trigger the warning mechanism to remind relevant managers to intervene and adjust to prevent fund overruns or unreasonable expenditures. At the same time, managers can dynamically adjust procurement plans based on real-time monitoring data to ensure the rational use and efficient allocation of funds.

[0078] Finally, the data statistics analysis and decision support module provides data support and optimization suggestions for management through in-depth mining and statistical analysis of the data of all procurement projects. The system can generate detailed procurement reports, analyze the efficiency of capital use, supplier performance and potential risk points in the procurement process, and provide a basis for university management to formulate more scientific procurement strategies. This module effectively helps universities optimize procurement processes, allocate funding resources, and extract effective information from data to support long-term decision-making.

[0079] The supplier management module method provided by the embodiment of the present invention is as follows:

[0080] 1) Supplier rating mechanism, which rates suppliers based on a comprehensive evaluation of their supply quality, price, delivery date and service attitude, providing a reference for purchasing decisions;

[0081] 2) The supplier blacklist system records and blacklists suppliers who have committed illegal or irregular acts, restricting them from participating in subsequent procurement activities.

[0082] The procurement plan scientific formulation module method provided by the embodiment of the present invention is as follows:

[0083] 1) Risk assessment model, which quantitatively evaluates potential risks in the procurement process based on historical data and expert experience;

[0084] 2) Intelligent supplier recommendation engine, which introduces artificial intelligence and machine learning algorithms, automatically recommends the most suitable supplier combination based on historical procurement data and supplier performance; the system can adaptively learn and optimize the recommendation algorithm. As data accumulates, the accuracy and scientificity of the recommendations will gradually improve, helping managers make procurement decisions more efficiently.

[0085] The funding warning and monitoring module method provided by the embodiment of the present invention is as follows:

[0086] 1) Dynamic budget adjustment mechanism, which allows appropriate adjustment of budget thresholds according to the actual situation of the procurement project to ensure flexibility and rationality in the use of funds;

[0087] 2) Fund usage report generation module, which automatically generates fund usage reports, including budget execution status, fund usage details and early warning information, for review by relevant departments;

[0088] 3) Multi-dimensional risk assessment and dynamic response mechanism: Add multi-dimensional risk assessment, including market price fluctuations, supply chain disruptions, and equipment technology update risks, to further enrich the application scenarios of the risk model; after identifying potential risks, the system can automatically generate response strategies and adjustment suggestions, including adjusting procurement priorities or finding alternative suppliers, to enhance the system's resilience.

[0089] The funding warning and monitoring module method provided by the embodiment of the present invention also includes: procurement process automation and blockchain technology application, combining procurement process automation technology; through blockchain technology, ensuring the transparency of the procurement process and the non-tamperability of the data.

[0090] The data statistical analysis and decision support module method provided by the embodiment of the present invention is as follows:

[0091] 1) Process monitoring function: real-time monitoring of each link in the procurement process to ensure the standardization and transparency of the procurement process;

[0092] 2) Data analysis function: conduct in-depth mining and analysis of procurement data to provide data support for procurement management decisions.

[0093] like Figure 4 As shown, the method for university procurement risk management and funding early warning in a multi-supplier environment provided by an embodiment of the present invention includes:

[0094] S101, establish a supplier archive database through the supplier management module, including basic information of suppliers, available equipment types, relevant industry qualifications, previous supply status, and after-sales service evaluation, to provide data support for the formulation of procurement plans;

[0095] S102, scientifically plan the procurement plan based on the supplier archive database through the procurement plan scientific formulation module;

[0096] S103, through the funding warning and monitoring module, the use of funds is monitored and calculated in real time according to the procurement plan and budget, and warning thresholds are set. Once an abnormality or overspending risk is found, the warning mechanism is immediately triggered to prompt management personnel to intervene and make adjustments;

[0097] S104 provides data support for procurement management decisions through information sharing, process monitoring and data analysis of data statistical analysis and decision support modules; the system has a built-in data statistical analysis module to conduct in-depth mining and statistical analysis of procurement data, provide decision support for management, and optimize procurement strategies and indicator allocation.

[0098] Another object of the present invention is to provide a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the university procurement risk management and funding warning method in a multi-supplier environment.

[0099] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the steps of the university procurement risk management and funding warning method in a multi-supplier environment.

[0100] Another object of the present invention is to provide an information data processing terminal, which is used to implement the university procurement risk management and funding early warning system in the multi-supplier environment.

[0101] The present invention is specifically implemented:

[0102] The purpose of the present invention is to provide a university procurement risk management and funding early warning system in a multi-supplier environment, which is implemented by the following technical means:

[0103] 1. Supplier management system: Establish a supplier archive database, including basic information of suppliers, types of available equipment, relevant industry qualifications, previous supply status, after-sales service evaluation, etc., to provide data support for the formulation of procurement plans.

[0104] 1) Supplier rating mechanism, which rates suppliers based on comprehensive evaluations of their supply quality, price, delivery time, and service attitude, to provide a reference for purchasing decisions;

[0105] 2) The supplier blacklist system records and blacklists suppliers who have committed illegal or irregular acts, restricting them from participating in subsequent procurement activities.

[0106] 2. Scientific formulation of procurement plan: Based on the supplier archive database, scientifically plan the procurement plan to improve the scientificity and economy of procurement equipment planning.

[0107] 1) Risk assessment model, based on historical data and expert experience, to quantitatively assess the potential risks in the procurement process.

[0108] 2) Intelligent supplier recommendation engine, which introduces artificial intelligence and machine learning algorithms, automatically recommends the most suitable supplier combination based on historical procurement data and supplier performance. The system can adaptively learn and optimize the recommendation algorithm. As data accumulates, the accuracy and scientificity of the recommendations will gradually improve, helping managers make procurement decisions more efficiently.

[0109] 3. Fund warning and monitoring: According to the procurement plan and budget, the fund usage is monitored and calculated in real time, and the warning threshold is set. Once an abnormality or overspending risk is found, the warning mechanism is immediately triggered to prompt management personnel to intervene and make adjustments.

[0110] 1) Dynamic budget adjustment mechanism, which allows appropriate adjustment of budget thresholds according to the actual situation of the procurement project to ensure flexibility and rationality in the use of funds;

[0111] 2) Fund usage report generation module automatically generates fund usage report, including budget execution status, fund usage details and early warning information, for review by relevant departments.

[0112] 3) Multi-dimensional risk assessment and dynamic response mechanism: Add multi-dimensional risk assessment, including market price fluctuations, supply chain disruptions, equipment technology update risks, etc., to further enrich the application scenarios of risk models. After identifying potential risks, the system can automatically generate response strategies and adjustment suggestions, such as adjusting procurement priorities or finding alternative suppliers, to enhance the system's resilience.

[0113] 4) Procurement process automation and blockchain technology application, combined with procurement process automation technology, to achieve full process automation from demand proposal to contract signing, reducing errors and inefficiencies caused by human operations. Through blockchain technology, the transparency of the procurement process and the immutability of data are ensured, further enhancing the security and credibility of the system and providing a trust environment for all parties.

[0114] 4. Data statistical analysis and decision support: As an integrated platform for the above systems, it realizes information sharing, process monitoring and data analysis, and provides data support for procurement management decisions. The system has a built-in data statistical analysis module to conduct in-depth mining and statistical analysis of procurement data, provide decision support for management, and optimize procurement strategies and indicator allocation.

[0115] 1) Process monitoring function: real-time monitoring of each link in the procurement process to ensure the standardization and transparency of the procurement process;

[0116] 2) Data analysis function: conduct in-depth mining and analysis of procurement data to provide data support for procurement management decisions.

[0117] 1. Improve procurement efficiency: Through scientific planning of procurement plans and online bidding and evaluation, reduce manual intervention and human errors and improve procurement efficiency.

[0118] 2. Reduce procurement risks: Establish a comprehensive supplier management and risk assessment mechanism to reduce information asymmetry and contract performance risks.

[0119] 3. Optimize the use of funds: monitor the use of funds in real time, realize effective early warning and control of funds, and avoid abuse and overspending of funds.

[0120] 4. Improve decision support: Through data statistical analysis and decision support modules, provide management with accurate data support and decision-making basis, and optimize procurement strategies and indicator allocation.

[0121] Alternative technology solutions

[0122] 1. Data entry, manual entry and informatization.

[0123] 2. Risk management, manual export and statistics.

[0124] 3. Funding warning, manual review and intervention.

[0125] Key technical points

[0126] 1. Use the integrated platform to automatically connect to the existing business-finance integration approval system.

[0127] 2. Use an integrated platform to connect the approval system, procurement system and asset management system.

[0128] 3. Use big data to monitor, analyze and display procurement status and statistical information in real time, and retain all traceable records for auditing.

[0129] 4. Use artificial intelligence technology to predict and evaluate procurement risks, determine management plans, and provide decision support.

[0130] 5. Use an integrated platform to record suppliers’ past information, display ratings and blacklists, and provide risk control.

[0131] The intelligent procurement management platform integrates multiple functional modules such as supplier management, procurement process control, risk identification and assessment, and funding warning, providing one-stop procurement management services for users such as universities. The platform supports cloud deployment and multi-user concurrent operations to ensure data security and real-time performance. Fund management is seamlessly connected to the procurement management platform to track the use of procurement funds in real time, including budget allocation, expenditure records, balance warnings, etc. By setting warning thresholds, the software can automatically issue alarms when funds are about to be overspent or abnormal fluctuations occur, ensuring the rationality and compliance of fund use. Provide customized data analysis reports for universities to help schools gain an in-depth understanding of the overall situation of procurement activities, including supplier performance, procurement cost analysis, and funding efficiency. Through visual charts and data analysis models, management can more intuitively grasp the key indicators of procurement management and provide strong support for the formulation of scientific and reasonable procurement strategies.

[0132] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0133] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A procurement risk management and funding early warning system for universities in a multi-supplier environment, characterized by: include: Supplier management module, scientific procurement plan formulation module, funding warning and monitoring module, data statistical analysis and decision support module; The supplier management module is connected with the scientific procurement plan formulation module, the funding early warning and monitoring module, and the data statistical analysis and decision support module to establish a supplier archive database, including basic supplier information, available equipment types, relevant industry qualifications, previous supply conditions, and after-sales service evaluation, providing data support for procurement plan formulation; The module for scientifically formulating procurement plans is connected with the supplier management module, the funding early warning and monitoring module, and the data statistical analysis and decision support module to scientifically plan procurement plans based on the supplier archive database; The funding warning and monitoring module is connected with the supplier management module and the scientific procurement plan formulation module. It is used to monitor and calculate the funding usage in real time according to the procurement plan and budget, set the warning threshold, and immediately trigger the warning mechanism once an abnormality or overspending risk is found, prompting the management personnel to intervene and make adjustments; The data statistical analysis and decision support module is connected with the supplier management module and the scientific procurement plan formulation module to share information, monitor processes and analyze data, providing data support for procurement management decisions; The system has a built-in data statistical analysis module to conduct in-depth mining and statistical analysis of procurement data, provide decision support for management, and optimize procurement strategies and indicator allocation.

2. The university procurement risk management and funding early warning system in a multi-supplier environment as described in claim 1 is characterized by: The supplier management module method is as follows: 1) Supplier rating mechanism, which rates suppliers based on a comprehensive evaluation of their supply quality, price, delivery date and service attitude, providing a reference for purchasing decisions; 2) The supplier blacklist system records and blacklists suppliers who have committed illegal or irregular acts, restricting them from participating in subsequent procurement activities.

3. The university procurement risk management and funding early warning system in a multi-supplier environment as claimed in claim 1 is characterized by: The method for scientifically formulating the procurement plan module is as follows: 1) Risk assessment model, which quantifies the potential risks in the procurement process based on historical data and expert experience; 2) Intelligent supplier recommendation engine, which introduces artificial intelligence and machine learning algorithms, automatically recommends the most suitable supplier combination based on historical procurement data and supplier performance; the system can adaptively learn and optimize the recommendation algorithm. As data accumulates, the accuracy and scientificity of the recommendations will gradually improve, helping managers make procurement decisions more efficiently.

4. The university procurement risk management and funding early warning system in a multi-supplier environment as claimed in claim 1 is characterized in that: The funding warning and monitoring module method is as follows: 1) Dynamic budget adjustment mechanism, which allows appropriate adjustment of budget thresholds according to the actual situation of the procurement project to ensure flexibility and rationality in the use of funds; 2) Fund usage report generation module, which automatically generates fund usage reports, including budget execution status, fund usage details and early warning information, for review by relevant departments; 3) Multi-dimensional risk assessment and dynamic response mechanism: Add multi-dimensional risk assessment, including market price fluctuations, supply chain disruptions, and equipment technology update risks, to further enrich the application scenarios of the risk model; after identifying potential risks, the system can automatically generate response strategies and adjustment suggestions, including adjusting procurement priorities or finding alternative suppliers, to enhance the system's resilience.

5. The university procurement risk management and funding early warning system in a multi-supplier environment as described in claim 4 is characterized by: The funding warning and monitoring module method also includes: procurement process automation and blockchain technology application, combining procurement process automation technology; through blockchain technology, ensuring the transparency of the procurement process and the non-tamperability of the data.

6. The university procurement risk management and funding early warning system in a multi-supplier environment as claimed in claim 1 is characterized by: The data statistical analysis and decision support module method is as follows: 1) Process monitoring function: real-time monitoring of each link in the procurement process to ensure the standardization and transparency of the procurement process; 2) Data analysis function: conduct in-depth mining and analysis of procurement data to provide data support for procurement management decisions.

7. A method for university procurement risk management and funding warning in a multi-supplier environment implementing the university procurement risk management and funding warning system in a multi-supplier environment as described in any one of claims 1 to 6, characterized in that: The procurement risk management and funding early warning methods for universities in the multi-supplier environment include: Step 1: Establish a supplier archive database through the supplier management module, including basic information of suppliers, available equipment types, relevant industry qualifications, previous supply status, and after-sales service evaluation, to provide data support for the formulation of procurement plans; Step 2: Scientifically plan the procurement plan based on the supplier archive database through the procurement plan scientific formulation module; Step 3: Use the funding warning and monitoring module to monitor and calculate funding usage in real time based on procurement plans and budgets, set warning thresholds, and immediately trigger the warning mechanism once an abnormality or overspending risk is found, prompting management personnel to intervene and make adjustments; Step 4: Provide data support for procurement management decisions through information sharing, process monitoring and data analysis of the data statistical analysis and decision support modules; the system has a built-in data statistical analysis module to conduct in-depth mining and statistical analysis of procurement data, provide decision support for management, and optimize procurement strategies and indicator allocation.

8. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the university procurement risk management and funding warning method in a multi-supplier environment as described in claim 7.

9. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the university procurement risk management and funding warning method in a multi-supplier environment as described in claim 7.

10. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the university procurement risk management and funding warning system in a multi-supplier environment as described in any one of claims 1-6.

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