Purchase method and system based on data driving, terminal and storage medium

Abstract

The invention discloses a purchase method and system based on data driving, a terminal and a storage medium, and the method comprises the steps: obtaining the data of each business system in an enterprise and the data of an external market, and constructing a purchase data warehouse according to the obtained data; mining and analyzing the data in the purchase data warehouse by using a data mining algorithm and tool, and performing prediction and analysis based on a sales prediction model and an inventory management strategy model; generating a purchase strategy report according to the analyzed and output sales prediction data, the inventory management strategy and the supplier evaluation result; purchasing is carried out based on the purchasing strategy report, visual monitoring is carried out on the whole process of order purchasing, and real-time monitoring and early warning are carried out on key indexes and risk points in the purchasing process. According to the invention, the purchase cost is reduced and the supply chain efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of industrial Internet technology, and in particular to a data-driven procurement method, system, terminal and storage medium. Background Art

[0002] With the intensification of market competition and the increasing diversification of consumer demand, companies need a more accurate and efficient procurement method to adapt to market changes and enhance their competitiveness.

[0003] In traditional procurement management, companies rely primarily on the experience and intuition of purchasing staff to make purchasing decisions. This approach presents numerous problems: Firstly, due to a lack of accurate understanding of market demand, procurement quantities can easily mismatch actual demand, leading to inventory backlogs or stockouts. Secondly, the procurement process lacks systematicity and scientificity, making it difficult to effectively control procurement costs and optimize supply chain operations.

[0004] Therefore, the existing technology needs to be improved. Summary of the Invention

[0005] The technical problem to be solved by the present invention is that, in response to the defects of the existing technology, the present invention provides a data-driven procurement method, system, terminal and storage medium to solve the problem that traditional procurement management methods cannot achieve effective control of procurement costs and optimized operation of the supply chain.

[0006] The technical solutions adopted by the present invention to solve the technical problems are as follows: In a first aspect, the present invention provides a data-driven procurement method, comprising: Obtain data from various business systems within the enterprise and external market data, and build a procurement data warehouse based on the acquired data; Use data mining algorithms and tools to mine and analyze the data in the procurement data warehouse, and perform forecasting and analysis based on sales forecast models and inventory management strategy models; Generate procurement strategy reports based on sales forecast data, inventory management strategies, and supplier evaluation results generated from analysis; Procurement is carried out based on the procurement strategy report, the entire process of the procurement order is visually monitored, and key indicators and risk points in the procurement process are monitored and warned in real time.

[0007] In one implementation, acquiring data from various business systems within the enterprise and external market data, and building a procurement data warehouse based on the acquired data, includes: Obtain historical sales data, inventory data, procurement data, and supplier data through various business systems within the enterprise; Obtain market data, industry trend data, and macroeconomic data from external sources through web crawlers and API interfaces; According to the acquired data, the procurement data warehouse is constructed by combining relational database and non-relational database.

[0008] In one implementation, the use of data mining algorithms and tools to perform in-depth mining and analysis of the data in the procurement data warehouse includes: Use the data mining algorithms and tools to conduct in-depth mining and analysis of the data in the procurement data warehouse to identify potential patterns and relationships in the data; Based on the potential rules and relationships, find the sales correlation between different products; Through cluster analysis, suppliers are classified according to different characteristics, differentiated supplier management strategies are formulated, and the supplier evaluation results are output.

[0009] In one implementation, the forecasting and analysis based on the sales forecast model and the inventory management strategy model includes: Integrate multiple machine learning algorithms and statistical analysis methods to build the sales forecast model and the inventory management strategy model; Based on the set parameters and business scenarios, select the corresponding algorithm for model training and optimization to obtain the optimized sales forecast model and optimized inventory management strategy model; Perform sales forecasting based on the optimized sales forecasting model and output the sales forecast data; An inventory management analysis is performed based on the optimized inventory management strategy model, and the inventory management strategy is output.

[0010] In one implementation, generating a procurement strategy report based on the sales forecast data, inventory management strategy, and supplier evaluation results outputted from the analysis includes: Based on the output sales forecast data, the inventory management strategy and the supplier evaluation results, the procurement time, procurement quantity, procurement frequency and supplier selection information of each product are generated in the form of charts and text to obtain the procurement strategy report.

[0011] In one implementation, generating a procurement strategy report based on the sales forecast data, inventory management strategy, and supplier evaluation results output from the analysis further includes: Based on the sales forecast data and the optimized inventory management model, combined with the company's cost control goals and service level requirements, operations research and optimization theory are used to dynamically optimize the procurement strategy in the procurement strategy report.

[0012] In one implementation, the procurement is performed based on the procurement strategy report, the entire process of the procurement order is visually monitored, and key indicators and risk points in the procurement process are monitored and warned in real time, including: Real-time connection to the enterprise's internal procurement execution system, external supplier information system, and logistics transportation system enables visual monitoring of the purchase order placement, confirmation, production, transportation, and warehousing processes; Based on preset early warning rules and thresholds, real-time monitoring and early warning are carried out on key indicators and risk points in the procurement process, and monitoring and early warning information of the procurement process is output.

[0013] In a second aspect, the present invention provides a data-driven procurement system, comprising: Data source module, used to obtain data from various business systems within the enterprise and external market data; Data storage module, used to build a procurement data warehouse based on the acquired data; A data mining module, used to mine and analyze the data in the procurement data warehouse using data mining algorithms and tools; Predictive modeling module, used for forecasting and analysis based on sales forecast models and inventory management strategy models; The procurement strategy generation module is used to generate procurement strategy reports based on the sales forecast data, inventory management strategies, and supplier evaluation results output by the analysis; A procurement process monitoring module is used to conduct procurement based on the procurement strategy report and to visually monitor the entire process of the procurement order; The intelligent early warning module is used to monitor and warn key indicators and risk points in the procurement process in real time.

[0014] In a third aspect, the present invention provides a terminal comprising: a processor and a memory, wherein the memory stores a data-driven procurement program, and when the data-driven procurement program is executed by the processor, it is used to implement the operation of the data-driven procurement method as described in the first aspect.

[0015] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a data-driven procurement program, and when the data-driven procurement program is executed by a processor, it is used to implement the operation of the data-driven procurement method as described in the first aspect.

[0016] The present invention adopts the above technical solution to achieve the following effects: By acquiring data from various business systems within the enterprise and external market data, the present invention can build a procurement data warehouse based on the acquired data, and use data mining algorithms and tools to deeply mine and analyze the massive data in the procurement data warehouse to discover the potential patterns and correlations in the data; at the same time, through sales forecasting models and inventory management strategy models, forecasts and analyses are carried out to find the optimal procurement strategy plan, provide a scientific basis for enterprise decision-making, and maximize procurement benefits; and by real-time connection between the enterprise's internal procurement execution system and external supplier information systems, logistics and transportation systems, etc., the entire process of purchase order placement, confirmation, production, transportation, warehousing, etc. can be visually monitored to ensure a smooth and efficient procurement process; the present invention achieves a reduction in procurement costs and an improvement in supply chain efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0018] Figure 1 It is a flow chart of the data-driven procurement method in the present invention.

[0019] Figure 2 It is the overall system flow chart of the present invention.

[0020] Figure 3 It is a functional principle diagram of a terminal in one implementation of the present invention.

[0021] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the present invention more clear and distinct, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0023] Exemplary Methods With the intensification of market competition and the increasing diversification of consumer demand, companies need a more accurate and efficient procurement method to adapt to market changes and enhance their competitiveness.

[0024] In traditional procurement management, companies rely primarily on the experience and intuition of purchasing staff to make purchasing decisions. This approach presents numerous problems: Firstly, due to a lack of accurate understanding of market demand, procurement quantities can easily mismatch actual demand, leading to inventory backlogs or stockouts. Secondly, the procurement process lacks systematicity and scientificity, making it difficult to effectively control procurement costs and optimize supply chain operations.

[0025] In response to the above technical problems, an embodiment of the present invention provides a data-driven procurement method, which includes: obtaining data from various business systems within the enterprise and external market data, and building a procurement data warehouse based on the obtained data; using data mining algorithms and tools to mine and analyze the data in the procurement data warehouse, and performing predictions and analysis based on sales forecast models and inventory management strategy models; generating a procurement strategy report based on the sales forecast data, inventory management strategies, and supplier evaluation results output by the analysis; purchasing based on the procurement strategy report, visually monitoring the entire process of the procurement order, and performing real-time monitoring and early warning of key indicators and risk points in the procurement process. The present invention reduces procurement costs and improves supply chain efficiency.

[0026] like Figure 1 As shown, an embodiment of the present invention provides a data-driven procurement method, comprising the following steps: Step S100: Acquire data from various business systems within the enterprise and external market data, and build a procurement data warehouse based on the acquired data.

[0027] In this embodiment, the data-driven procurement method is implemented through a data-driven procurement system.

[0028] This embodiment involves the refined management of corporate procurement behavior, aiming to reduce procurement costs and improve supply chain efficiency. Figure 2 As shown, the data-driven procurement system of this embodiment specifically includes: a data layer, an analysis layer, a decision layer, and an application layer.

[0029] First, in this embodiment, the data of various business systems within the enterprise and the external market data are obtained based on the data layer, and a procurement data warehouse is constructed based on the obtained data; among them, the data of various business systems within the enterprise are also referred to as internal data, and the external market data is data obtained from the external network or non-local system database, also referred to as external data.

[0030] Specifically, in one implementation of this embodiment, step S100 includes the following steps: Step S101: Obtain historical sales data, inventory data, procurement data, and supplier data through various business systems within the enterprise; Step S102: Obtain market data, industry trend data, and macroeconomic data from the outside through web crawlers and API interfaces; Step S103: constructing the procurement data warehouse based on the acquired data by combining relational database and non-relational database.

[0031] In this embodiment, the data layer specifically includes: a data source module, a data storage module and a data security module.

[0032] In the process of acquiring internal and external data, the data source module is used to connect with various business systems within the enterprise to automatically extract historical sales data, inventory data, procurement data, supplier data, etc. Among them, the various business systems within the enterprise include: ERP (enterprise management) system, CRM (customer relationship management) system, SCM (supply chain management) system; at the same time, market data, industry trend data and macroeconomic data are obtained from the outside through web crawlers, API interfaces, etc. to ensure the comprehensiveness and timeliness of the data.

[0033] After acquiring internal and external data, the procurement data warehouse is constructed using the data storage module. Specifically, this approach utilizes a combination of relational databases (such as MySQL and Oracle) and non-relational databases (such as MongoDB and HBase). Relational databases are used to store structured data (such as sales order tables and inventory ledgers), while non-relational databases are used to store semi-structured or unstructured data (such as market research reports and supplier evaluation documents). This approach meets the storage requirements of diverse data types and provides efficient data query and access performance.

[0034] After constructing the procurement data warehouse, we use a data security module to encrypt and store it. Specifically, we encrypt the data stored in the warehouse and implement strict access rights and authentication mechanisms to prevent data leakage, tampering, and unauthorized access. Furthermore, we regularly perform data backup and recovery tests to ensure data security and reliability, and to safeguard the stable operation of the procurement system.

[0035] like Figure 1 As shown, an embodiment of the present invention provides a data-driven procurement method, comprising the following steps: Step S200: using data mining algorithms and tools to mine and analyze the data in the procurement data warehouse, and performing prediction and analysis based on the sales forecast model and inventory management strategy model.

[0036] In this embodiment, the data in the procurement data warehouse is mined and analyzed based on the analysis layer, and sales forecast and inventory management strategy analysis is performed, thereby outputting sales forecast data, inventory management strategy and supplier evaluation results.

[0037] Specifically, in one implementation of this embodiment, step S200 includes the following steps: Step S201: Using the data mining algorithms and tools, deeply mine and analyze the data in the procurement data warehouse to determine the potential patterns and relationships in the data; Step S202: Finding sales correlations between different products based on the potential rules and correlation relationships; Step S203: Classify suppliers according to different characteristics through cluster analysis, formulate differentiated supplier management strategies, and output the supplier evaluation results.

[0038] In this embodiment, the analysis layer specifically includes: a data mining module, a prediction modeling module, and a strategy optimization module.

[0039] During the in-depth mining and analysis of the data in the procurement data warehouse, the data mining module utilizes data mining algorithms and tools to deeply mine and analyze the massive amounts of data in the procurement data warehouse, uncovering underlying patterns and relationships within the data. For example, through association rule mining, sales correlations between different products can be identified, providing a reference for product portfolio procurement and inventory management; through cluster analysis, suppliers can be categorized according to different characteristics to facilitate the development of differentiated supplier management strategies.

[0040] This embodiment uses data mining algorithms and tools to mine and analyze the data in the procurement data warehouse, which can quickly find potential patterns and correlations in the data, formulate differentiated supplier management strategies, and output the supplier evaluation results.

[0041] Specifically, in one implementation of this embodiment, step S200 further includes the following steps: Step S204: Integrate multiple machine learning algorithms and statistical analysis methods to build the sales forecast model and the inventory management strategy model; Step S205: Select the corresponding algorithm to perform model training and optimization based on the set parameters and business scenarios to obtain an optimized sales forecast model and an optimized inventory management strategy model; Step S206, performing sales forecasting based on the optimized sales forecasting model and outputting the sales forecast data; Step S207: performing inventory management analysis based on the optimized inventory management strategy model and outputting the inventory management strategy.

[0042] In this embodiment, after mining and analyzing the data in the procurement data warehouse, a sales forecast model and an inventory management strategy model are constructed using a predictive modeling module, and sales forecast and inventory management strategy analysis is performed. Specifically, a variety of machine learning algorithms and statistical analysis methods, such as time series analysis, multivariate linear regression, neural networks, and support vector machines, are first integrated to construct the sales forecast model and inventory management strategy model. Then, based on user-defined parameters and business scenarios, the system automatically selects appropriate algorithms for model training and optimization, and provides model evaluation and verification functions to help users select the optimal forecast model and improve the accuracy and reliability of forecast results. Finally, sales data is forecasted using the optimized sales forecast model, and the sales forecast data is output. The corresponding inventory management strategy is also output using the optimized inventory management strategy model.

[0043] After outputting sales forecast data and inventory management strategies, the subsequently generated procurement strategies are dynamically optimized through the strategy optimization module.

[0044] like Figure 1 As shown, an embodiment of the present invention provides a data-driven procurement method, comprising the following steps: Step S300: Generate a procurement strategy report based on the sales forecast data, inventory management strategy, and supplier evaluation results output by the analysis.

[0045] In this embodiment, a procurement strategy report is generated based on the decision-making layer, and monitoring and early warning of the subsequent procurement process are carried out; wherein, in the process of generating the procurement strategy report, the procurement strategy report is mainly generated based on the sales forecast data, inventory management strategy and supplier evaluation results output by the analysis layer.

[0046] Specifically, in one implementation of this embodiment, step S300 includes the following steps: Step S301, based on the output sales forecast data, the inventory management strategy and the supplier evaluation results, the purchase time, purchase quantity, purchase frequency and supplier selection information of each product are generated in the form of charts and text to obtain the purchase strategy report.

[0047] In this embodiment, the decision-making layer includes: a procurement strategy generation module, a procurement process monitoring module, and an intelligent early warning module.

[0048] The procurement strategy generation module automatically generates a detailed procurement strategy report based on sales forecast data, inventory management strategies, and supplier evaluation results output by the analysis layer. This report includes information such as the procurement time, quantity, frequency, and supplier selection recommendations for each product. The report is presented to users in intuitive charts and text, allowing them to quickly understand the basis for procurement decisions and operational guidelines.

[0049] Specifically, in one implementation of this embodiment, step S300 further includes the following steps: Step S302 , based on the sales forecast data and the optimized inventory management model, combined with the enterprise's cost control objectives and service level requirements, and using operations research and optimization theory, dynamically optimize the procurement strategy in the procurement strategy report.

[0050] In this embodiment, after the procurement strategy generation module generates a procurement strategy report, the strategy optimization module in the analysis layer dynamically optimizes the generated procurement strategy report. Specifically, based on sales forecast results and inventory management models, combined with the company's cost control objectives and service level requirements, the procurement strategy is dynamically optimized using operations research and optimization theory. For example, by simulating cost-effectiveness and inventory performance under different purchase batches, purchase times, and supplier selection combinations, the optimal procurement strategy solution is found, providing a scientific basis for corporate decision-making and maximizing procurement efficiency.

[0051] like Figure 1 As shown, an embodiment of the present invention provides a data-driven procurement method, comprising the following steps: Step S400: Procurement is carried out based on the procurement strategy report, the entire process of the procurement order is visually monitored, and key indicators and risk points in the procurement process are monitored and warned in real time.

[0052] In this embodiment, the procurement process monitoring module based on the above-mentioned decision-making layer performs visual monitoring of the entire process of the procurement order, and the intelligent early warning module based on the above-mentioned decision-making layer performs real-time monitoring and early warning of key indicators and risk points in the procurement process.

[0053] Specifically, in one implementation of this embodiment, step S400 includes the following steps: Step S401: Connecting to the enterprise's internal procurement execution system, external supplier information system, and logistics transportation system in real time to visually monitor the purchase order placement, confirmation, production, transportation, and warehousing process; Step S402: Based on preset warning rules and thresholds, real-time monitoring and warning are performed on key indicators and risk points in the procurement process, and monitoring and warning information of the procurement process is output.

[0054] In this embodiment, the procurement process monitoring module provides real-time connectivity between the company's internal procurement execution system (such as a P2P system) and external supplier information systems, logistics and transportation systems, and other systems to visually monitor the entire purchase order process, from placement and confirmation to production, transportation, and warehousing. This allows users to monitor the progress of procurement tasks at any time through the system interface, promptly identifying and addressing potential issues and ensuring a smooth and efficient procurement process.

[0055] The intelligent early warning module provides real-time monitoring and early warning of key indicators and risk points in the procurement process based on predefined early warning rules and thresholds. For example, if a supplier's delivery is delayed for longer than a certain period, inventory levels fall below safety stock, or market price fluctuations exceed a preset range, the system automatically triggers an early warning signal and notifies relevant personnel via email, text message, or system message, prompting them to take timely countermeasures to reduce procurement risks and losses.

[0056] In this embodiment, corresponding user operations, interface display and other functions are implemented through the application layer, wherein the application layer includes: a user interface module, a report analysis module and a mobile application module.

[0057] The user interface module provides personalized workstations and interfaces for users of different roles (such as purchasing managers, procurement specialists, warehouse managers, and financial personnel). The interface is simple, intuitive, and easy to use, supporting multi-device access (desktop, mobile, etc.), allowing users to manage and operate procurement anytime, anywhere. For example, purchasing managers can use the app to view procurement strategy reports, monitor procurement process progress, and approve purchase orders. Purchasing specialists can communicate with suppliers, sign procurement contracts, and track logistics. Warehouse managers can monitor inventory status in real time and schedule goods in and out of the warehouse.

[0058] Report Analysis Module: This module provides extensive report generation and analysis capabilities to meet users' multi-dimensional query, statistics, and analysis needs for procurement data. Users can customize report templates based on various dimensions, such as time, product, supplier, and region. The system automatically extracts relevant data from the database and generates intuitive report charts (such as bar charts, line charts, and pie charts), helping users gain a deeper understanding of procurement operations and performance indicators, providing data support for decision-making. For example, through procurement cost analysis reports, users can understand price trends and procurement cost structures of different suppliers, providing a basis for supplier negotiations and cost control. Through inventory turnover analysis reports, users can evaluate the efficiency and effectiveness of inventory management and adjust inventory strategies in a timely manner.

[0059] Mobile Application Module: Develop mobile applications (such as mobile apps) that allow users to receive procurement-related information and handle urgent matters anytime, anywhere on their mobile devices. Mobile apps offer core functions such as purchase order inquiries, approvals, message alerts, inventory inquiries, and logistics tracking. They synchronize data with desktop systems in real time, ensuring consistency and continuity across users' operations across devices, improving work efficiency and responsiveness. For example, while out of the office for a meeting, purchasing managers can use mobile apps to promptly approve purchase orders, avoiding delays that could impact procurement progress. Warehouse managers can also use mobile apps to quickly check inventory quantities and locations while on-site, improving the efficiency and accuracy of goods in and out of the warehouse.

[0060] This embodiment achieves the following technical effects through the above technical solution: This embodiment acquires data from various business systems within the enterprise and external market data, and can build a procurement data warehouse based on the acquired data. It also uses data mining algorithms and tools to deeply mine and analyze the massive data in the procurement data warehouse to discover potential patterns and correlations in the data. At the same time, it uses sales forecasting models and inventory management strategy models to conduct forecasts and analyses, find the optimal procurement strategy plan, provide a scientific basis for enterprise decision-making, and maximize procurement benefits. In addition, through real-time connection between the enterprise's internal procurement execution system and external supplier information systems, logistics and transportation systems, etc., it can visually monitor the entire process of purchase order placement, confirmation, production, transportation, warehousing, etc., to ensure a smooth and efficient procurement process. This embodiment reduces procurement costs and improves supply chain efficiency.

[0061] Exemplary devices Based on the above embodiment, the present invention further provides a data-driven procurement system, comprising: Data source module, used to obtain data from various business systems within the enterprise and external market data; Data storage module, used to build a procurement data warehouse based on the acquired data; A data mining module, used to mine and analyze the data in the procurement data warehouse using data mining algorithms and tools; Predictive modeling module, used for forecasting and analysis based on sales forecast models and inventory management strategy models; The procurement strategy generation module is used to generate procurement strategy reports based on the sales forecast data, inventory management strategies, and supplier evaluation results output by the analysis; A procurement process monitoring module is used to conduct procurement based on the procurement strategy report and to visually monitor the entire process of the procurement order; The intelligent early warning module is used to monitor and warn key indicators and risk points in the procurement process in real time.

[0062] This embodiment achieves the following technical effects through the above technical solution: This embodiment acquires data from various business systems within the enterprise and external market data, and can build a procurement data warehouse based on the acquired data. It also uses data mining algorithms and tools to deeply mine and analyze the massive data in the procurement data warehouse to discover potential patterns and correlations in the data. At the same time, it uses sales forecasting models and inventory management strategy models to conduct forecasts and analyses, find the optimal procurement strategy plan, provide a scientific basis for enterprise decision-making, and maximize procurement benefits. In addition, through real-time connection between the enterprise's internal procurement execution system and external supplier information systems, logistics and transportation systems, etc., it can visually monitor the entire process of purchase order placement, confirmation, production, transportation, warehousing, etc., to ensure a smooth and efficient procurement process. This embodiment reduces procurement costs and improves supply chain efficiency.

[0063] Based on the above embodiment, the present invention further provides a terminal, whose principle block diagram can be shown as follows: Figure 3 shown.

[0064] The terminal includes: a processor, memory, interface, display screen and communication module connected via a system bus; wherein the processor of the terminal is used to provide computing and control capabilities; the memory of the terminal includes a computer-readable storage medium and an internal memory; the computer-readable storage medium stores an operating system and a computer program; the internal memory provides an environment for the operation of the operating system and computer program in the computer-readable storage medium; the interface is used to connect to external devices; the display screen is used to display corresponding information; and the communication module is used to communicate with a cloud server or other devices.

[0065] When the computer program is executed by a processor, it is used to implement operations based on a data-driven procurement method.

[0066] It will be understood by those skilled in the art that Figure 3 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the solution of the present invention, and does not constitute a limitation on the terminal to which the solution of the present invention is applied. The specific terminal may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0067] In one embodiment, a terminal is provided, comprising: a processor and a memory, wherein the memory stores a data-driven procurement program, and when the data-driven procurement program is executed by the processor, it is used to implement the operations of the above data-driven procurement method.

[0068] In one embodiment, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a data-driven procurement program, and when the data-driven procurement program is executed by a processor, it is used to implement the operations of the above data-driven procurement method.

[0069] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile storage medium. When executed, the computer program can include the processes in the above-described method embodiments. Any reference to memory, storage, database, or other media used in the various embodiments provided herein may include both non-volatile and volatile memory.

[0070] In summary, the present invention provides a data-driven procurement method, system, terminal, and storage medium, including: acquiring data from various business systems within an enterprise and external market data, and constructing a procurement data warehouse based on the acquired data; using data mining algorithms and tools to mine and analyze the data in the procurement data warehouse, and performing predictions and analyses based on sales forecasting models and inventory management strategy models; generating a procurement strategy report based on the sales forecast data, inventory management strategies, and supplier evaluation results output from the analysis; and conducting procurement based on the procurement strategy report, visually monitoring the entire procurement order process, and performing real-time monitoring and early warning of key indicators and risk points in the procurement process. The present invention reduces procurement costs and improves supply chain efficiency.

[0071] It should be understood that the application of the present invention is not limited to the above examples. For those skilled in the art, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A data-driven procurement method, characterized in that: include: Obtain data from various business systems within the enterprise and external market data, and build a procurement data warehouse based on the acquired data; Use data mining algorithms and tools to mine and analyze the data in the procurement data warehouse, and perform forecasting and analysis based on sales forecast models and inventory management strategy models; Generate procurement strategy reports based on sales forecast data, inventory management strategies, and supplier evaluation results generated from analysis; Procurement is carried out based on the procurement strategy report, the entire process of the procurement order is visually monitored, and key indicators and risk points in the procurement process are monitored and warned in real time.

2. The data-driven procurement method according to claim 1, characterized in that: The acquisition of data from various business systems within the enterprise and external market data, and the construction of a procurement data warehouse based on the acquired data, includes: Obtain historical sales data, inventory data, procurement data, and supplier data through various business systems within the enterprise; Obtain market data, industry trend data, and macroeconomic data from external sources through web crawlers and API interfaces; According to the acquired data, the procurement data warehouse is constructed by combining relational database and non-relational database.

3. The data-driven procurement method according to claim 1, characterized in that: The use of data mining algorithms and tools to conduct in-depth mining and analysis of the data in the procurement data warehouse includes: Use the data mining algorithms and tools to conduct in-depth mining and analysis of the data in the procurement data warehouse to identify potential patterns and relationships in the data; Based on the potential rules and relationships, find the sales correlation between different products; Through cluster analysis, suppliers are classified according to different characteristics, differentiated supplier management strategies are formulated, and the supplier evaluation results are output.

4. The data-driven procurement method according to claim 1, characterized in that: The forecasting and analysis based on the sales forecast model and inventory management strategy model includes: Integrate multiple machine learning algorithms and statistical analysis methods to build the sales forecast model and the inventory management strategy model; Based on the set parameters and business scenarios, select the corresponding algorithm for model training and optimization to obtain the optimized sales forecast model and optimized inventory management strategy model; Perform sales forecasting based on the optimized sales forecasting model and output the sales forecast data; An inventory management analysis is performed based on the optimized inventory management strategy model, and the inventory management strategy is output.

5. The data-driven procurement method according to claim 1, characterized in that: The sales forecast data, inventory management strategy and supplier evaluation results output by the analysis are used to generate a procurement strategy report, including: Based on the output sales forecast data, the inventory management strategy and the supplier evaluation results, the procurement time, procurement quantity, procurement frequency and supplier selection information of each product are generated in the form of charts and text to obtain the procurement strategy report.

6. The data-driven procurement method according to claim 1, characterized in that: The generation of a procurement strategy report based on the sales forecast data, inventory management strategy, and supplier evaluation results output by the analysis also includes: Based on the sales forecast data and the optimized inventory management model, combined with the company's cost control goals and service level requirements, operations research and optimization theory are used to dynamically optimize the procurement strategy in the procurement strategy report.

7. The data-driven procurement method according to claim 1, characterized in that: The procurement is carried out based on the procurement strategy report, the entire process of the procurement order is visually monitored, and the key indicators and risk points in the procurement process are monitored and warned in real time, including: Real-time connection to the enterprise's internal procurement execution system, external supplier information system, and logistics transportation system enables visual monitoring of the purchase order placement, confirmation, production, transportation, and warehousing processes; Based on preset early warning rules and thresholds, real-time monitoring and early warning are carried out on key indicators and risk points in the procurement process, and monitoring and early warning information of the procurement process is output.

8. A data-driven procurement system, characterized in that: include: Data source module, used to obtain data from various business systems within the enterprise and external market data; Data storage module, used to build a procurement data warehouse based on the acquired data; A data mining module, used to mine and analyze the data in the procurement data warehouse using data mining algorithms and tools; Predictive modeling module, used for forecasting and analysis based on sales forecast models and inventory management strategy models; The procurement strategy generation module is used to generate procurement strategy reports based on the sales forecast data, inventory management strategies, and supplier evaluation results output by the analysis; A procurement process monitoring module is used to conduct procurement based on the procurement strategy report and to visually monitor the entire process of the procurement order; The intelligent early warning module is used to monitor and warn key indicators and risk points in the procurement process in real time.

9. A terminal, characterized in that: include: A processor and a memory, wherein the memory stores a data-driven procurement program, and when the data-driven procurement program is executed by the processor, it is used to implement the operation of the data-driven procurement method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a data-driven procurement program, which, when executed by a processor, is used to implement the operation of the data-driven procurement method according to any one of claims 1 to 7.

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