Data analysis method and system based on digital supply platform

Abstract

The invention relates to the technical field of supply data analysis, in particular to a data analysis method and system based on a digital supply platform. Comprising the following steps: S1, acquiring a purchase demand of an enterprise, and performing related category analysis and related category combination according to the purchase demand; s2, performing market price collection according to the related categories, performing merging calculation on the market prices according to the related category combination, and performing difference numerical analysis on the related category combination in combination with the purchase demand; according to the method, comprehensive and accurate market price information is provided for enterprises through deep analysis of purchase demands and in combination with related category analysis and combination, the enterprises are assisted to make scientific decisions in the purchase process, and when the bid invitation price range is determined, the purchase demands, related category combination difference values and price factors are comprehensively considered, so that the bid invitation price range is determined. The bid invitation price not only meets the actual situation of the market, but also can meet the cost control requirement of an enterprise, and avoids the risk caused by too high or too low purchase price.

Description

Technical Field

[0001] The present invention relates to the technical field of supply data analysis, and in particular to a data analysis method and system based on a digital supply platform. Background Art

[0002] In the field of corporate procurement, purchasing decisions, cost control, and procurement efficiency have always been the focus of enterprises. Helping enterprises obtain the required materials and services and ensure the smooth progress of production operations usually relies on manual collection and organization of data and the use of simple statistical methods for analysis to assist in purchasing decisions.

[0003] At present, most companies reduce procurement prices by negotiating with suppliers, purchasing in bulk, or publishing bidding information on the Internet to attract suppliers to quote. However, with the intensification of market competition and the advent of the digital age, prices fluctuate frequently. Relying solely on negotiation and bulk purchasing has obvious limitations. It is difficult to deeply analyze the cost structure and price influencing factors, and it is impossible to fundamentally achieve effective cost reduction. The bidding method cannot cover all suppliers. Some suppliers are operating offline, with limited information flow efficiency and unable to obtain bidding information in a timely manner, resulting in a limited number of attracted suppliers. Therefore, a data analysis method and system based on a digital supply platform are proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a data analysis method and system based on a digital supply platform to solve the problems raised in the above background technology.

[0005] To solve the above technical problems, one of the objectives of the present invention is to provide a data analysis method based on a digital supply platform, comprising the following steps:

[0006] S1. Obtain the company's procurement needs and conduct relevant category analysis and combination based on the procurement needs;

[0007] S2. Collect market prices based on relevant categories, combine and calculate market prices based on relevant category combinations, analyze the difference between relevant category combinations and procurement needs, and analyze price factors based on the difference between different relevant category combinations and market prices.

[0008] S3. Generate a bidding price range based on procurement needs, combined with the differential values of different related product combinations and price factors, and provide feedback to the enterprise to adjust the bidding price range;

[0009] S4. Filter and obtain a list of suppliers based on the procurement requirements, combine the procurement requirements with the lower limit of the bidding price range, generate a purchase order, and publish it to the supplier list;

[0010] S5. Adjust the bidding price according to the supplier's quotation feedback, obtain the acceptance quotation of each supplier, and then sort the supplier list from low to high according to the corresponding acceptance quotation.

[0011] As a further improvement of the present technical solution, the S1 is connected to the enterprise management system, and the enterprise inputs the purchase details into the enterprise management system. Then S1 obtains the purchase details and summarizes the purchase details into purchase requirements.

[0012] As a further improvement of this technical solution, the steps of S1 are as follows:

[0013] S1.1. Obtain the product categories required for this purchase based on the purchase demand, and perform subordinate related category analysis based on the product categories to obtain the subordinate related categories of the product categories;

[0014] S1.2. Simultaneously, perform a secondary analysis of the lower-level related categories and perform a complete combination of the obtained lower-level categories. If a complete combination cannot be achieved, stop the analysis of the lower-level related categories. Otherwise, if the acquisition can be continued, continue until a complete combination cannot be achieved, thereby obtaining multiple related categories and corresponding related category combinations.

[0015] As a further improvement of this technical solution, the steps of S2 are as follows:

[0016] S2.1. Collect market prices based on the acquired relevant categories, obtain the corresponding market price for each relevant category, and then combine the corresponding market prices based on the relevant category combinations to obtain the market price corresponding to each relevant category combination;

[0017] S2.2. Perform a difference value analysis on relevant category combinations in conjunction with procurement requirements to obtain the difference values of the product categories corresponding to each relevant category combination and procurement requirements. Then, perform a price factor analysis on the difference data of each relevant category combination in conjunction with the corresponding market price and difference value to obtain the price factors corresponding to different difference values.

[0018] As a further improvement of the present technical solution, when obtaining the market price of each relevant category and combination of relevant categories, S2.1 and S2.2 both take the lowest bid as the representative market price.

[0019] As a further improvement of this technical solution, the steps of S3 are as follows:

[0020] S3.1. Generate a bidding price range based on procurement requirements, combined with the difference values for each relevant category combination and price factors. The bidding price range consists of an upper limit and a lower limit.

[0021] S3.2. Send the bidding price range to enterprises through the enterprise management system to collect adjustment opinions, and then update and adjust the bidding price range based on the adjustment opinions fed back by the enterprises.

[0022] As a further improvement of this technical solution, the steps of S4 are as follows:

[0023] S4.1. Obtain a list of suppliers and the products they supply, then filter the list of suppliers based on procurement requirements to obtain a list of suppliers that can produce the products that meet the procurement requirements.

[0024] S4.2. In the first price inquiry, the purchase demand is combined with the lower limit of the bidding price range to generate a purchase order, and the generated purchase order is sent to the supplier list after S4.1 screening.

[0025] As a further improvement of this technical solution, the steps of S5 are as follows:

[0026] S5.1. Collect supplier feedback on purchase orders and analyze the feedback. If the analysis indicates that the supplier is dissatisfied with the purchase order price, increase the bidding price and resubmit it to the supplier. Conversely, if the analysis indicates that the supplier is dissatisfied with other factors in the purchase order, send the other factors to the enterprise for review through the enterprise management system. Based on the review results, retain the supplier.

[0027] At the same time, suppliers with no feedback data on purchase orders will be retained;

[0028] S5.2. Obtain the purchase orders for each supplier that do not have feedback data, and use the tender price of the corresponding purchase order as the supplier's accepted quotation. Then, sort the supplier list from low to high based on the supplier's accepted quotation.

[0029] The lower the accepted bid, the higher the priority.

[0030] A second object of the present invention is to provide a data analysis system based on a digital supply platform, comprising any one of the above-mentioned data analysis methods based on a digital supply platform, including a procurement demand analysis module, a price analysis module, and a quotation management module;

[0031] The purchasing demand analysis module is used to obtain the purchasing demand of the enterprise and perform relevant category analysis and relevant category combination according to the purchasing demand;

[0032] The price analysis module is used to collect market prices based on relevant categories, and perform differential value analysis on relevant category combinations in combination with procurement requirements. At the same time, it performs price factor analysis based on the differential values of different relevant category combinations and market prices. Based on procurement requirements, it combines the differential values of different relevant category combinations and price factors to generate a bidding price range, and feeds back to the enterprise to adjust the bidding price range.

[0033] The quotation management module is used to filter and obtain a supplier list based on procurement requirements, combine the procurement requirements with the lower limit of the bidding price range to generate a purchase order and publish it to the supplier list, adjust the bidding price stage based on the supplier's quotation feedback, obtain the accepted quotation of each supplier, and then sort the supplier list from low to high according to the corresponding accepted quotation.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. A data analysis method and system based on a digital supply platform. Through in-depth analysis of procurement needs and combined with analysis and combination of related categories, it provides enterprises with comprehensive and accurate market price information, helping enterprises make scientific decisions during the procurement process. When determining the bidding price range, it comprehensively considers procurement needs, the difference values of related category combinations, and price factors, so that the bidding price is consistent with the actual market situation and meets the cost control needs of enterprises, avoiding the risks brought by excessively high or low procurement prices.

[0036] 2. A data analysis method and system based on a digital supply platform. This method determines the lower limit of the bidding price based on the lowest cost that meets procurement needs in the market. When screening suppliers, it combines procurement needs with the lower limit of the bidding price range, giving priority to suppliers with reasonable quotations that can meet the needs. This effectively reduces the company's procurement costs. At the same time, by continuously analyzing and adjusting supplier quotation feedback, the company further ensures that it obtains the most cost-effective procurement solution.

[0037] 3. A data analysis method and system based on a digital supply platform. This system enables rapid data collection, transmission, and processing through the digital platform, significantly shortening the time required for information acquisition and analysis in the procurement process. From acquiring procurement requirements and collecting market prices to generating purchase orders and sending them to suppliers, the entire process is efficient and orderly, reducing the tedious manual operations and improving procurement efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is the overall flow chart of the present invention;

[0039] Figure 2 A flowchart of obtaining related categories of a product category according to the present invention;

[0040] Figure 3 A flowchart of obtaining price factors corresponding to different difference values according to the present invention;

[0041] Figure 4 A flowchart showing that the bidding price range of the present invention consists of an upper limit price and a lower limit price;

[0042] Figure 5 A flowchart for obtaining a list of suppliers capable of completing production according to procurement requirements;

[0043] Figure 6 This is a flowchart of the present invention for retaining the supplier based on the audit results. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] like Figure 1 - Figure 6 As shown, one of the objectives of the present invention is to provide a data analysis method based on a digital supply platform, comprising the following steps:

[0046] S1. Obtain the company's procurement needs and conduct relevant category analysis and combination based on the procurement needs;

[0047] S1 connects to the enterprise management system, and the enterprise enters the purchase details into the enterprise management system. S1 then obtains the purchase details and summarizes the purchase details into purchase requirements. The specific steps are as follows:

[0048] Connecting to the enterprise management system: Using specific interfaces, network protocols, or data transmission tools, establish a data connection channel with the enterprise management system to ensure access to data resources within the system. For example, this can be done using the API interface of the enterprise intranet or establishing a connection through a secure network protocol (such as HTTPS).

[0049] Enterprise inputs purchase details: Relevant enterprise personnel (e.g., purchasing department staff) enter purchase details through the user interface (e.g., web interface, client software interface, etc.) provided by the enterprise management system in accordance with the format and requirements specified by the system. This information includes, but is not limited to, the name, specifications, quantity, quality standards, estimated purchase time, and delivery location of the purchased product.

[0050] Obtaining purchase details: After the connection is successful and the enterprise completes the information input, S1 extracts the entered purchase details from the database or data storage area of the enterprise management system through pre-set program logic.

[0051] The steps of S1 are as follows:

[0052] S1.1. Obtain the product categories required for this purchase based on the purchase demand, and perform subordinate related category analysis based on the product categories to obtain the subordinate related categories of the product categories;

[0053] S1.2. Simultaneously, perform a secondary analysis of the lower-level related categories and perform a complete combination of the obtained lower-level categories. If a complete combination cannot be achieved, stop the analysis of the lower-level related categories. Otherwise, if the analysis can be continued, continue until a complete combination cannot be achieved, thereby obtaining multiple related categories and corresponding related category combinations. The specific steps are as follows:

[0054] Determine the initial product categories: Extract the major product categories directly involved from the description of the procurement requirements;

[0055] First-level sub-category analysis: Based on a pre-established category hierarchy table (or knowledge base), find the sub-categories corresponding to each initial product category. For example, if the sub-categories of "computer" include "laptop" and "desktop computer," the found sub-categories are aggregated to form a first-level sub-category set for each initial product category.

[0056] Second-level and multi-level sub-category analysis: For each category in the first-level sub-category set, query the category hierarchy table again to obtain their respective sub-categories, which are the second-level sub-categories. For example, the sub-categories of "laptops" may include "thin and light laptops," "gaming laptops," and "business laptops."

[0057] Completeness Combination Judgment and Analysis Termination: After acquiring new subcategories in each round, determine whether a complete combination that conforms to procurement business logic can be formed based on these categories. If these subcategories cover the main types of the category in the market, the combination is considered complete. The judgment criteria can be determined based on common market classifications, industry standards, or internal procurement experience.

[0058] If a complete combination cannot be found, for example, for the "paper" category, only "A4 paper" is found, while other common and important paper categories in the market are not found, the analysis of sub-categories will continue. If the analysis confirms that there are no more meaningful sub-categories, that is, the analysis termination condition is met, the analysis of the category branch will be stopped;

[0059] Summarize related categories and combinations: All categories at different levels obtained through analysis are summarized to form a set containing multiple related categories. Based on the hierarchical relationship formed during the analysis process, the corresponding related category combinations are determined.

[0060] S2. Collect market prices based on relevant categories, combine and calculate market prices based on relevant category combinations, analyze the difference between relevant category combinations and procurement needs, and analyze price factors based on the difference between different relevant category combinations and market prices.

[0061] The steps of S2 are as follows:

[0062] S2.1. Collect market prices based on the acquired relevant categories, obtain the corresponding market price for each relevant category, and then combine and calculate the corresponding market prices based on the relevant category combination to obtain the market price corresponding to each relevant category combination. The specific steps are as follows:

[0063] Determine the collection channels: select online e-commerce platforms, industry vertical websites, direct quotations from suppliers, etc.

[0064] Collect prices for each category: For each relevant category, such as "computers," on selected channels, search and filter on e-commerce platforms to record product prices and price ranges for different brands, models, and configurations. Follow price updates and analysis from professional organizations on industry-specific websites. Obtain quotes from suppliers and organize them into tables containing information such as supplier name, quote, and delivery date.

[0065] Data cleaning and tidying: Checking price data and removing outliers that significantly deviate from the normal market price range, such as excessively low or high prices caused by merchant labeling errors;

[0066] Calculation of price for related category combinations: Determine the relevant category combinations and add up the sorted and cleaned market prices of each related category in the combination. The formula is as follows:

[0067]

[0068] Among them, P zu is the price of the relevant category combination, n is the number of relevant categories in the relevant category combination, P i is the price of the i-th related category;

[0069] S2.2. Perform a difference value analysis on relevant category combinations in conjunction with procurement requirements to obtain the difference values of the product categories corresponding to each relevant category combination and procurement requirements. Then, perform a price factor analysis on the difference data of each relevant category combination in conjunction with the corresponding market price and difference value to obtain the price factors corresponding to different difference values. The specific steps are as follows:

[0070] Identify the core category characteristics of the procurement requirements: Extract key information from the detailed description of the procurement requirements, determine the core characteristics of the product categories corresponding to the procurement requirements, and organize them into a set of quantifiable and comparable indicators, such as specific performance parameters, specifications, etc.

[0071] Analyze the characteristics of related category combinations: For each related category combination, extract the characteristics related to the product category of the procurement demand and quantify them into comparable indicators to form a characteristic indicator set of the related category combination;

[0072] Calculate difference values: Compare the characteristic indicators of the core categories of procurement requirements with those of the related category combinations one by one, calculate the difference values of each characteristic indicator of the core categories of procurement requirements for each related category combination, and summarize them to form a difference value set. Organize the market price data corresponding to each related category combination, and associate the calculated difference values with the corresponding related category combination to form a complete difference data set;

[0073] Conduct price factor analysis: Establish a price factor analysis model, with market price as the dependent variable and each difference value in the difference value set as the independent variable. By analyzing the model results, determine which difference values have a significant impact on the market price and the direction of the relationship, and obtain the price factors corresponding to different difference values. The formula is as follows:

[0074] P=β0+β1X1+β2X2+…+β j X j +ε;

[0075] Among them, P is the market price, that is, the dependent variable, X1, X2, ..., X j is a difference numerical variable, corresponding to different difference numerical indicators, and is an independent variable, β 0为 The intercept term in the regression equation represents the value of the market price when all difference numerical variables are 0, β1, β2, ..., β j为 The regression coefficient measures the degree and direction of the impact of each difference numerical variable X on the market price P. ε is the error term, which represents the impact of other factors not included in the model on the market price P in addition to the difference numerical variable.

[0076] When obtaining the market price of each relevant category and relevant category combination, S2.1 and S2.2 adopt the lowest quotation as the representative market price.

[0077] S3. Generate a bidding price range based on procurement needs, combined with the differential values of different related product combinations and price factors, and provide feedback to the enterprise to adjust the bidding price range;

[0078] The steps of S3 are as follows;

[0079] S3.1. Generate a bidding price range based on the procurement requirements, combined with the difference values for each relevant category combination and price factors. The bidding price range consists of an upper limit and a lower limit. The specific steps are as follows:

[0080] Organize basic data: Clearly sort out the detailed indicators of procurement requirements, including product specifications, quality standards, quantity requirements, delivery time, etc., quantify them into specific values or ranges, and summarize the previously calculated difference values between each relevant category combination and procurement requirements. These difference values cover the deviations between various product characteristics and procurement standards. Clarify the price impact relationship corresponding to different difference values obtained through price factor analysis;

[0081] Determine the floor price: Estimate the lowest cost in the market to meet purchasing requirements. First, select the lowest-priced combination that essentially meets the key indicators of purchasing requirements from relevant product combinations. Adjust the price based on the impact of the difference. For any difference between this combination and the purchasing requirements, calculate the price adjustment based on the price factor analysis results. If the combination falls below the purchasing requirements in certain performance indicators, these differences should result in a price reduction based on the price factor relationship.

[0082] Determine the ceiling price: Refer to the highest price on the market for products or services that fully meet or exceed the purchase requirements. From the relevant category combinations, find a combination that fully meets or even exceeds the purchase requirements and obtain its market price. If no combination fully meets the requirements, select the combination price that is closest and slightly higher than the purchase requirements. Consider possible additional cost factors, such as special quality requirements, urgent delivery, and other purchase requirements, which may incur additional costs. The ceiling price is the combination price plus the additional costs. The formula is as follows:

[0083]

[0084] Where ΔP down is the sum of the price reductions caused by the difference values, m is the number of difference values, w j is the price adjustment weight corresponding to the j difference values, Δx j is the jth difference value;

[0085] P lower =P zu,min +ΔP down ;

[0086] Among them, P lower is the lower price, P zu，min The lowest price for the relevant product category combination;

[0087] P upper =Pzu,max +ΔP up ;

[0088] Among them, P upper is the upper limit price, P zu，max ΔP is the price of the relevant category combination that fully meets or is closest to and slightly higher than the purchase demand. up is the total additional cost.

[0089] S3.2. Send the bidding price range to enterprises through the enterprise management system for adjustment feedback. Then, update and adjust the bidding price range based on the adjustment feedback from enterprises. The specific steps are as follows:

[0090] Sending the bidding price range: In the data analysis system, the generated bidding price range data is formatted to conform to the data receiving format requirements of the enterprise management system. The formatted bidding price range data is then sent to the enterprise management system through the established data interface.

[0091] Collecting Adjustment Opinions: After receiving the bidding price range data, the enterprise management system parses the data and converts it into a format that can be recognized and processed within the system. On the interface presenting the bidding price range, a dedicated input area or operation button is set up to facilitate enterprise personnel to enter adjustment opinions. For example, a text box can be provided for users to enter the reason for the adjustment and the desired price range, or a slider or numeric input box can be set up to allow users to directly adjust the price range.

[0092] Feedback on adjustment opinions: The enterprise management system sends the sorted adjustment opinion data back to the data analysis system through the same data interface as that used to send the bidding price range. After receiving the adjustment opinion data, the data analysis system parses the data and extracts key information, such as the new lower limit price and the new upper limit price, and updates the original bidding price range.

[0093] S4. Filter and obtain a list of suppliers based on the procurement requirements, combine the procurement requirements with the lower limit of the bidding price range, generate a purchase order, and publish it to the supplier list;

[0094] The steps for S4 are as follows:

[0095] S4.1. Obtain a list of suppliers and the products they supply, then filter the list of suppliers based on procurement requirements to obtain a list of suppliers that can produce the products that meet the procurement requirements.

[0096] In S4.2, during the first price inquiry, the purchase demand is combined with the lower limit of the bidding price range to generate a purchase order. The generated purchase order is then sent to the list of suppliers screened in S4.1. The specific steps are as follows:

[0097] Obtain basic supplier information: Establish a connection with the supplier information database through the enterprise resource planning (ERP) system, vendor management system (VMS), or other relevant data storage platforms to ensure the stability and security of data transmission. For example, use an encrypted database connection protocol to query and extract basic information of all suppliers from the database, including supplier name, contact information, address, etc., and obtain detailed information on each supplier's products, such as product name, specifications, model, production capacity, etc.

[0098] Screen suppliers based on procurement requirements: Detailed analysis of procurement requirements is performed, which is converted into specific screening criteria. The supplier list and their product information are then reviewed, and for each supplier, the supplier's products are checked to see if they meet the various criteria of the procurement requirements.

[0099] Generate a purchase order: Define the lower limit of the bidding price range, integrate key information in the procurement requirements, such as product name, specifications, quantity, quality requirements, etc., with the lower limit, and fill in the corresponding fields according to the standard format of the company's internal purchase order to generate a complete purchase order.

[0100] Send purchase orders: Select an appropriate method to send purchase orders to suppliers in the screened supplier list. Channels include email, electronic data interchange (EDI) system, and message push function in the supplier management system. Go through the screened supplier list and send the generated purchase order to each supplier according to the determined sending channel.

[0101] S5. Adjust the bidding price according to the supplier's quotation feedback, obtain the acceptance quotation of each supplier, and then sort the supplier list from low to high according to the corresponding acceptance quotation.

[0102] The steps for S5 are as follows:

[0103] S5.1. Collect supplier feedback on purchase orders and analyze the feedback. If the analysis indicates that the supplier is dissatisfied with the purchase order price, increase the bidding price and resubmit it to the supplier. Conversely, if the analysis indicates that the supplier is dissatisfied with other factors in the purchase order, send the other factors to the enterprise for review through the enterprise management system. Based on the review results, retain the supplier.

[0104] At the same time, suppliers with no feedback data on purchase orders will be retained. The specific steps are as follows:

[0105] Collect feedback data: When sending purchase orders, provide suppliers with clear and convenient feedback channels. For example, include a feedback link in the purchase order document that links to a dedicated online feedback form. Use scripts or the system's built-in monitoring function to monitor feedback channels in real time and collect new feedback data immediately upon submission.

[0106] Feedback analysis: Preprocess the feedback data, for example, converting the text feedback content into a unified character encoding and removing irrelevant formatting symbols and special characters. Build a library of price-related keywords, such as "low price," "price increase," and "high cost," as well as a library of other factor keywords, such as "too tight delivery time," "excessively high quality requirements," and "specification issues." Then, traverse the text content in the feedback data and use a string matching algorithm (such as the KMP algorithm) to check for price-related keywords. If so, it is determined that the price is unsatisfactory. If no price-related keywords are present, but keywords from the other factor keyword library are present, it is determined that the feedback is unsatisfactory due to other factors. For feedback that cannot be parsed through keyword matching, natural language processing (NLP) technologies, such as semantic analysis models, can be used to further determine the type of feedback.

[0107] Handling price dissatisfaction: The company pre-establishes price increase rules, such as a certain percentage increase, such as 10%. Alternatively, the company can determine a fixed price increase amount based on market price fluctuations and cost analysis. Based on the lower limit of the tender price after the increase, the company updates the price information in the purchase order, regenerates the purchase order document or message containing the new price, and resends it to the corresponding supplier through the original delivery channel. The formula is as follows:

[0108] P lower，new =P lower ×(1+r);

[0109] Among them, P lower，new is the new lower limit price, r is the price increase ratio;

[0110] Handling of other unsatisfactory factors: sort out the other unsatisfactory factors analyzed and form a clear text description. Through the data transmission function of the enterprise management system, the sorted feedback information of other factors will be sent to the relevant departments or personnel responsible for procurement review within the enterprise. The reviewers will evaluate the other feedback factors based on the company's procurement strategy, production plan and other factors. If the review result deems the conditions proposed by the supplier acceptable, such as agreeing to extend the delivery period, the supplier will be marked as retained in the supplier management system; if the review result deems it unacceptable, such as failing to meet the supplier's modification requirements for quality specifications, the supplier will be marked as eliminated in the system.

[0111] S5.2. Obtain the purchase orders for each supplier that do not have feedback data, and use the tender price of the corresponding purchase order as the supplier's accepted quotation. Then, sort the supplier list from low to high based on the supplier's accepted quotation.

[0112] The lower the accepted bid, the higher the priority. The specific steps are as follows:

[0113] Handling suppliers without feedback: Regularly check the supplier feedback data storage table and compare it with the list of suppliers to which purchase orders have been sent to identify suppliers that have not submitted feedback. For suppliers without feedback, use the tender price in the corresponding purchase order as the supplier's accepted offer. Create a new field or table in the database to record each supplier's accepted offer information.

[0114] Supplier sorting: Extract the accepted quotation data of each supplier from the database table that records the suppliers' accepted quotations, and use a sorting algorithm to sort the supplier list from low to high according to the accepted quotation. During the sorting process, the correspondence between the supplier information and its accepted quotation is maintained. After the sorting is completed, the supplier with the lowest accepted quotation is ranked first in the list and has the highest priority.

[0115] A second object of the present invention is to provide a data analysis system based on a digital supply platform, including any one of the above-mentioned data analysis methods based on a digital supply platform, including a procurement demand analysis module, a price analysis module, and a quotation management module;

[0116] The procurement demand analysis module is used to obtain the procurement needs of enterprises and conduct relevant category analysis and related category combinations based on the procurement needs;

[0117] The price analysis module is used to collect market prices based on relevant categories, and conduct differential value analysis on relevant category combinations in combination with procurement requirements. It also conducts price factor analysis based on the differential values of different relevant category combinations and market prices. Based on procurement requirements, the differential values of different relevant category combinations and price factors are combined to generate a bidding price range, and this information is fed back to the enterprise for adjustment of the bidding price range.

[0118] The quotation management module is used to filter and obtain a list of suppliers based on procurement requirements, combine the procurement requirements with the lower limit of the bidding price range to generate a purchase order and publish it to the supplier list, adjust the bidding price stage based on the supplier's quotation feedback, obtain the accepted quotation of each supplier, and then sort the supplier list from low to high according to the corresponding accepted quotation.

[0119] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A data analysis method based on a digital supply platform, characterized by: The steps include: S1. Obtain the company's procurement needs and conduct relevant category analysis and combination based on the procurement needs; S2. Collect market prices based on relevant categories, combine and calculate market prices based on relevant category combinations, analyze the difference between relevant category combinations and procurement needs, and analyze price factors based on the difference between different relevant category combinations and market prices. S3. Generate a bidding price range based on procurement needs, combined with the differential values of different related product combinations and price factors, and provide feedback to the enterprise to adjust the bidding price range; S4. Filter and obtain a list of suppliers based on the procurement requirements, combine the procurement requirements with the lower limit of the bidding price range to generate a purchase order, and publish it to the supplier list; S5. Adjust the bidding price according to the supplier's quotation feedback, obtain the acceptance quotation of each supplier, and then sort the supplier list from low to high according to the corresponding acceptance quotation.

2. The data analysis method based on a digital supply platform according to claim 1, characterized in that: The S1 is connected to the enterprise management system, and the enterprise inputs the purchase details into the enterprise management system. Then S1 obtains the purchase details and summarizes the purchase details into purchase requirements.

3. The data analysis method based on a digital supply platform according to claim 1, characterized in that: The steps of S1 are as follows: S1.

1. Obtain the product categories required for this purchase based on the purchase demand, and perform subordinate related category analysis based on the product categories to obtain the subordinate related categories of the product categories; S1.

2. Simultaneously, perform a secondary analysis of the lower-level related categories and perform a complete combination of the obtained lower-level categories. If a complete combination cannot be achieved, stop the analysis of the lower-level related categories. Otherwise, if the acquisition can be continued, continue until a complete combination cannot be achieved, thereby obtaining multiple related categories and corresponding related category combinations.

4. The data analysis method based on a digital supply platform according to claim 1, characterized in that: The steps of S2 are as follows: S2.

1. Collect market prices based on the acquired relevant categories, obtain the corresponding market price for each relevant category, and then combine the corresponding market prices based on the relevant category combinations to obtain the market price corresponding to each relevant category combination; S2.

2. Perform a difference value analysis on relevant category combinations in conjunction with procurement requirements to obtain the difference values of the product categories corresponding to each relevant category combination and procurement requirements. Then, perform a price factor analysis on the difference data of each relevant category combination in conjunction with the corresponding market price and difference value to obtain the price factors corresponding to different difference values.

5. The data analysis method based on a digital supply platform according to claim 4, characterized in that: When obtaining the market price of each relevant category and combination of relevant categories, S2.1 and S2.2 adopt the lowest bid as the representative market price.

6. The data analysis method based on a digital supply platform according to claim 1, characterized in that: The steps of S3 are as follows: S3.

1. Generate a bidding price range based on procurement requirements, combined with the difference values for each relevant category combination and price factors. The bidding price range consists of an upper limit and a lower limit. S3.

2. Send the bidding price range to enterprises through the enterprise management system to collect adjustment opinions, and then update and adjust the bidding price range based on the adjustment opinions fed back by the enterprises.

7. The data analysis method based on a digital supply platform according to claim 1, characterized in that: The steps of S4 are as follows: S4.

1. Obtain a list of suppliers and the products they supply, then filter the list of suppliers based on procurement requirements to obtain a list of suppliers that can produce the products that meet the procurement requirements. S4.

2. In the first price inquiry, the purchase demand is combined with the lower limit of the bidding price range to generate a purchase order, and the generated purchase order is sent to the supplier list after S4.1 screening.

8. The data analysis method based on a digital supply platform according to claim 1, characterized in that: The steps of S5 are as follows: S5.

1. Collect supplier feedback on purchase orders and analyze the feedback. If the analysis indicates that the supplier is dissatisfied with the purchase order price, increase the bidding price and resubmit it to the supplier. Conversely, if the analysis indicates that the supplier is dissatisfied with other factors in the purchase order, send the other factors to the enterprise for review through the enterprise management system. Based on the review results, retain the supplier. At the same time, suppliers with no feedback data on purchase orders will be retained; S5.

2. Obtain the purchase orders for each supplier that do not have feedback data, and use the tender price of the corresponding purchase order as the supplier's accepted quotation. Then, sort the supplier list from low to high based on the supplier's accepted quotation. The lower the accepted bid, the higher the priority.

9. A data analysis system based on a digital supply platform, used to implement the data analysis method based on a digital supply platform according to any one of claims 1 to 8, characterized in that: Including procurement demand analysis module, price analysis module and quotation management module; The purchasing demand analysis module is used to obtain the purchasing demand of the enterprise and perform relevant category analysis and relevant category combination according to the purchasing demand; The price analysis module is used to collect market prices based on relevant categories, and perform differential value analysis on relevant category combinations in combination with procurement requirements. At the same time, it performs price factor analysis based on the differential values of different relevant category combinations and market prices. Based on procurement requirements, it combines the differential values of different relevant category combinations and price factors to generate a bidding price range, and feeds back to the enterprise to adjust the bidding price range. The quotation management module is used to filter and obtain a supplier list based on procurement requirements, combine the procurement requirements with the lower limit of the bidding price range to generate a purchase order and publish it to the supplier list, adjust the bidding price stage based on the supplier's quotation feedback, obtain the accepted quotation of each supplier, and then sort the supplier list from low to high according to the corresponding accepted quotation.

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