Method and system for managing same-industry benchmarking information

Abstract

The invention discloses a same-industry benchmarking information management method and system, and relates to the technical field of data processing, and the method comprises the steps: respectively obtaining directly-collected data and offline data, which are collected by a business service layer and are related to same-industry benchmarking information, and receiving inspection results for the directly-collected data and the offline data; after the inspection results of the directly collected data and the offline data meet the inspection passing condition, storing the directly collected data and the offline data in a data storage layer according to a preset rule; and after a display instruction sent by the data access layer is received, calculating an overall score of each related enterprise corresponding to the stored direct collection data and the offline data according to a preset rule, and displaying the overall score of the related enterprise. According to the method and the device, the problems that accurate evaluation cannot be performed, the data timeliness is insufficient and the management is deficient when the same-industry benchmarking information is managed in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method and system for managing peer benchmarking information. Background Art

[0002] As a management method that discovers its own gaps and optimizes operation strategies by comparing and analyzing the business data, business processes, technological innovations, etc. of competitors or industry benchmark enterprises, peer benchmarking has become an important strategic tool for enterprises.

[0003] For example, in the financial field, banks adjust their risk control strategies and business layouts by benchmarking indicators such as deposit and loan sizes, non-performing loan ratios, and the proportion of intermediate business income of their peers; in the manufacturing industry, enterprises improve production processes and reduce costs by comparing data such as production efficiency, product quality, and supply chain costs of their peers.

[0004] However, the current enterprise benchmarking work is still in the stage of manual statistics and comparison of indicators, and it is impossible to accurately evaluate each enterprise, the timeliness of data is insufficient, and there is room for improvement in management standardization. Summary of the Invention

[0005] In view of this, an object of the present invention is to provide a method and system for managing peer benchmarking information, aiming to solve the problems of inaccurate evaluation, insufficient data timeliness, and lack of management in the management of peer benchmarking information in the prior art.

[0006] An object of the present invention is to provide a method for managing peer benchmarking information, which is applied to a peer benchmarking information management platform. The peer benchmarking information management platform includes a business service layer, a data access layer, and a data storage layer that are respectively communicatively connected to the business service layer. The method includes: Respectively obtain the direct collection data and offline data of peer benchmarking information collected by the business service layer, and receive the inspection results for the direct collection data and offline data; After the inspection results of the direct collection data and offline data meet the inspection passing conditions, store the direct collection data and offline data in the data storage layer according to preset rules; After receiving the display instruction sent by the data access layer, calculate the overall scores of the corresponding relevant enterprises for the stored direct collection data and offline data according to preset rules, and display the overall scores of the relevant enterprises.

[0007] Further, in the above method for managing peer benchmarking information, the step of storing the direct collection data and offline data in the data storage layer according to preset rules includes: Respectively establish a direct collection database, an offline database, and an intermediate score database for storing the direct collection data and offline data in the data storage layer; Extract the score data for calculating the overall score from the direct procurement data and off-line data according to the unique enterprise identifier corresponding to the direct procurement data and off-line data; Store the direct procurement data, off-line data, and score data in the corresponding direct procurement database, off-line database, and intermediate score database respectively.

[0008] Further, in the above method for managing peer benchmarking information, after the step of storing the direct procurement data, off-line data, and score data in the corresponding direct procurement database, off-line database, and intermediate score database respectively, the method further includes: Construct a query data chain according to the unique enterprise identifier, direct procurement data, off-line data, and score data, and store the query data chain in the intermediate score database; When calculating the overall score of an enterprise is required, determine the score data for calculating the overall score according to the query data chain, and determine the overall score of the enterprise according to the score data.

[0009] Further, in the above method for managing peer benchmarking information, the step of constructing a query data chain according to the unique enterprise identifier, direct procurement data, off-line data, and score data, and storing the query data chain in the intermediate score database includes: Perform hash operations on the information content of the direct procurement data and off-line data respectively to obtain a first hash value and a second hash value, and obtain a target hash value according to the first hash value and the second hash value according to a preset rule, so as to obtain a corresponding target data chain; Divide the target data chain into equal target sub-data chains according to a preset rule, and obtain the data ratio between the direct procurement data and the off-line data. According to the data ratio, select corresponding elements from the corresponding chain positions in the target sub-data chains respectively, and combine the target sub-data chains with the positions of the selected elements vacated to form an initial data chain; Use the unique enterprise identifier as the chain head to form a query data chain with the initial data chain, and leave the query data chain in the intermediate score database, where the query data chain is bonded with the data chain composed of the elements selected from the corresponding chain positions.

[0010] Further, in the above method for managing peer benchmarking information, the step of obtaining the data ratio between the direct procurement data and the off-line data, and selecting corresponding elements from the corresponding chain positions in the target sub-data chains according to the data ratio includes: Determine the target value with a larger value according to the data ratio, divide the target sub-data chain according to the ratio corresponding to the target value, or determine the target value with a smaller value according to the data ratio, and divide the target sub-data chain according to the ratio corresponding to the target value; The segmented target sub - data chain is segmented again according to the ratio corresponding to another target value, and then the segmentation positions of each segmentation are obtained, and corresponding elements are selected from among the segmentation positions of each segmentation.

[0011] Further, in the above - mentioned peer - benchmarking information management method, the steps of determining the target value with a larger value according to the data ratio, segmenting the target sub - data chain according to the ratio corresponding to the target value, or determining the target value with a smaller value according to the data ratio and segmenting the target sub - data chain according to the ratio corresponding to the target value include: When one of the target sub - data chains is initially segmented according to one of the target values in the data ratio, the adjacent target sub - data chain is initially segmented according to the other target value in the data ratio.

[0012] Further, in the above - mentioned peer - benchmarking information management method, the steps of respectively performing hash operations on the information contents of the direct - procurement data and the offline data to obtain a first hash value and a second hash value, and obtaining a target hash value according to a preset rule based on the first hash value and the second hash value to obtain the corresponding target data chain include: Perform a bit - wise exclusive - OR operation on the binary representations of the first hash value and the second hash value to obtain a new binary value, and perform a hash calculation on the binary value after the exclusive - OR operation using the same hash algorithm to obtain the target hash value.

[0013] Another object of the present invention is to provide a peer - benchmarking information management system, which is applied to a peer - benchmarking information management platform. The peer - benchmarking information management platform includes a business service layer, a data access layer, and a data storage layer that are respectively communicatively connected to the business service layer. The system includes: An acquisition module, which is used to respectively acquire the direct - procurement data and the offline data of the peer - benchmarking information collected by the business service layer, and receive the inspection results for the direct - procurement data and the offline data; A storage module, which is used to store the direct - procurement data and the offline data in the data storage layer according to a preset rule after the inspection results of the direct - procurement data and the offline data meet the inspection - passed condition; A display module, which is used to calculate the overall scores of the corresponding relevant enterprises for the stored direct - procurement data and the offline data according to a preset rule after receiving the display instruction sent by the data access layer, and display the overall scores of the relevant enterprises.

[0014] Another object of the present invention is to provide a readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the above - mentioned method are implemented.

[0015] Another object of the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored on the memory and running on the processor, wherein when the processor executes the program, the steps of the above method are implemented.

[0016] The present invention respectively obtains direct procurement data and offline data of peer benchmarking information collected by the business service layer, and receives the inspection results for the direct procurement data and offline data; after the inspection results of the direct procurement data and offline data meet the inspection passing conditions, the direct procurement data and offline data are stored in the data storage layer according to preset rules; after receiving the display instruction sent by the data access layer, calculate the overall scores of the corresponding relevant enterprises for the stored direct procurement data and offline data according to preset rules, and display the overall scores of the relevant enterprises. At the same time, obtain the direct procurement data and offline data to ensure the comprehensiveness and integrity of the data, which can more accurately reflect the true situation of each relevant enterprise. Inspect the direct procurement data and offline data, and only perform subsequent processing when the inspection results meet the inspection passing conditions, improving the accuracy and reliability of the data. Store the direct procurement data and offline data that pass the inspection according to preset rules, calculate the overall scores of the corresponding relevant enterprises for the stored direct procurement data and offline data, ensure the orderliness and standardization of data storage, facilitate subsequent query and analysis, and provide a unified and objective scoring standard. It solves the problems of inaccurate evaluation, insufficient data timeliness and lack of management in the prior art when managing peer benchmarking information. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a schematic flowchart of a method for managing peer benchmarking information provided by an embodiment of the present invention; Figure 2 is a structural block diagram of a system for managing peer benchmarking information provided by the third embodiment of the present invention.

[0018] The following specific embodiments will further illustrate the present invention in conjunction with the above drawings. SPECIFIC EMBODIMENTS

[0019] To facilitate the understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0020] It should be noted that when an element is referred to as "fixedly provided on" another element, it can be directly on the other element or there may also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used in this article are only for illustrative purposes.

[0021] Unless otherwise defined, all technical and scientific terms used in this article have the same meaning as commonly understood by those skilled in the technical field to which this invention belongs. The terms used in the specification of this invention are only for the purpose of describing specific embodiments and are not intended to limit this invention. The term "and / or" used in this article includes any and all combinations of one or more of the related listed items.

[0022] Embodiment 1 Please refer to Figure 1 , which shows the peer benchmarking information management method in the first embodiment of the present invention, applied to a peer benchmarking information management platform. The peer benchmarking information management platform includes a business service layer, a data access layer and a data storage layer that are respectively communicatively connected to the business service layer. The method includes steps S10 to S12.

[0023] Step S10: Respectively obtain the direct collection data and offline data of peer benchmarking information collected by the business service layer, and receive the inspection results for the direct collection data and offline data.

[0024] Among them, the business service layer is used to implement related business functions, such as data collection, etc. The data access layer is used to provide data access interfaces, and the data storage layer is used to store the relevant data collected, such as direct collection data and offline data.

[0025] In the business service layer, two types of data will be respectively collected: one is the direct collection data of peer benchmarking information obtained through direct methods. These data come from direct data acquisition channels such as system automatic collection and interface docking, and have characteristics such as real-time and automation; the other is offline data, that is, data that cannot be directly collected from the system. This type of data is collected through non-automated methods such as manual entry, digitalization of paper documents, and external data import. After these two types of data are collected, the system will receive the inspection results for the direct collection data and offline data. These inspection results are used to judge whether the collected data meets the preset standards and requirements, such as data integrity, accuracy, consistency, etc. Through this link, it can be ensured that the data for subsequent processing is reliable and effective, providing a basis for subsequent data storage, calculation and display operations.

[0026] Step S11, after the inspection results of the direct procurement data and the offline data meet the passing conditions, store the direct procurement data and the offline data in the data storage layer according to preset rules.

[0027] Among them, when the inspection results of the direct procurement data and the offline data collected by the business service layer reach the pre-set passing criteria after inspection, the system will store these data in the data storage layer according to the established rules. The preset rules here can include data classification, storage location allocation, etc., aiming to ensure that the data can be stored in an orderly and standardized manner for subsequent query, analysis, and processing.

[0028] Step S12, after receiving the display instruction sent by the data access layer, calculate the overall scores of the corresponding relevant enterprises for the stored direct procurement data and the offline data according to preset rules, and display the overall scores of the relevant enterprises.

[0029] Specifically, after receiving the display instruction sent by the data access layer, the system will calculate the overall scores for each relevant enterprise's indicators based on the preset calculation rules for these stored data. Among them, these preset rules cover various indicators and weights, such as work safety indicators, operation and management indicators, service quality indicators, etc. Each indicator has its corresponding deduction criteria and calculation methods. By calculating the deduction situations of each enterprise according to the rules, it can objectively reflect the performance of each enterprise in the same-industry benchmarking. After obtaining the deduction situations of each enterprise, the system will further summarize and calculate to obtain the overall scores of the relevant enterprises.

[0030] Finally, display these overall scores. The display methods may include but are not limited to presenting in the form of lists, charts, etc. on the system interface, so that relevant personnel can intuitively understand the rankings and performance of each enterprise in the same-industry benchmarking, providing strong data support for subsequent decision-making, evaluation, and improvement.

[0031] In summary, in the above-described embodiment of the peer benchmarking information management method of the present invention, by separately obtaining the direct procurement data and offline data of the peer benchmarking information collected by the business service layer, and receiving the inspection results for the direct procurement data and the offline data; after the inspection results of the direct procurement data and the offline data meet the passing conditions, storing the direct procurement data and the offline data in the data storage layer according to a preset rule; after receiving the display instruction sent by the data access layer, calculating the overall scores of the corresponding relevant enterprises for the stored direct procurement data and offline data according to a preset rule, and displaying the overall scores of the relevant enterprises, while obtaining the direct procurement data and the offline data to ensure the comprehensiveness and integrity of the data, which can more accurately reflect the true situation of each relevant enterprise, inspecting the direct procurement data and the offline data, and only performing subsequent processing when the inspection results meet the passing conditions, improving the accuracy and reliability of the data, storing the direct procurement data and the offline data that pass the inspection according to a preset rule, calculating the overall scores of the corresponding relevant enterprises for the stored direct procurement data and offline data, ensuring the orderliness and standardization of data storage, facilitating subsequent query and analysis, and providing a unified and objective scoring standard. It solves the problems in the prior art that there are difficulties in accurate evaluation, insufficient data timeliness and lack of management in the management of peer benchmarking information.

[0032] Embodiment 2 This embodiment also proposes a peer benchmarking information management method. The difference between the peer benchmarking information management method in this embodiment and the peer benchmarking information management method in Embodiment 1 is as follows: The step of storing the direct procurement data and the offline data in the data storage layer according to a preset rule includes: Separately establishing a direct procurement database, an offline database and an intermediate score database for storing the direct procurement data and the offline data in the data storage layer; According to the unique enterprise identifier corresponding to the direct procurement data and the offline data, extracting the score data for calculating the overall score from the direct procurement data and the offline data; Storing the direct procurement data, the offline data and the score data in the corresponding direct procurement database, offline database and intermediate score database respectively.

[0033] First, construct dedicated databases, namely the direct procurement database, the offline database, and the intermediate score database. Plan independent storage locations for different types of data to facilitate management and subsequent operations. Specifically, the direct procurement database is used to store directly collected direct procurement data, and the offline database is used to store offline data collected offline. Screen out the score data that is useful for calculating the overall score of the enterprise from the direct procurement data and the offline data, that is, select the key data information required when evaluating the enterprise's performance. The intermediate score database is used to store this key data information. Or, the score data is the score information corresponding to each indicator calculated after screening out the key data information, so that the subsequent rapid calculation of the overall score can be realized. After obtaining the corresponding data, store different types of data accurately and orderly into their respective corresponding databases.

[0034] Further, in some alternative embodiments of the present invention, after the step of separately storing the direct procurement data, the offline data, and the score data into the corresponding direct procurement database, the offline database, and the intermediate score database, the following steps are further included: Construct a query data chain based on the enterprise unique identifier, the direct procurement data, the offline data, and the score data, and store the query data chain into the intermediate score database; When calculating the overall score of the enterprise is required, determine the score data for calculating the overall score corresponding to the query data chain, and determine the overall score of the enterprise according to the score data.

[0035] Among them, after separately storing the direct procurement data, the offline data, and the score data into the corresponding databases, the next step is to use the enterprise unique identifier to integrate the direct procurement data, the offline data, and the score data of the same enterprise to construct a query data chain. After the construction is completed, store this query data chain into the intermediate score database. On the one hand, this query data chain is like an index. When calculating the overall score of the enterprise, it can be located to the query data chain according to the enterprise unique identifier, and then located to the corresponding score data in the intermediate score database, and the final overall score is calculated according to the score data. On the other hand, in order to improve the efficiency of score calculation, in the embodiments of the present invention, an intermediate score database is proposed. By screening and calculating the data, some basic score data is stored in it so that when calculating the score, the corresponding overall score can be directly obtained through the score data. However, although this method improves the calculation efficiency, it also faces a problem, that is, when the data in the intermediate score database is tampered with, it is very difficult to find that the data has been tampered with.

[0036] Therefore, in some alternative embodiments of the present invention, the step of constructing a query data chain based on the enterprise unique identifier, the direct procurement data, the offline data, and the score data, and storing the query data chain into the intermediate score database includes: The information content of the direct procurement data and the offline data are respectively used for hash operations to obtain a first hash value and a second hash value, and a target hash value is obtained according to the first hash value and the second hash value according to a preset rule, so as to obtain a corresponding target data chain; The target data chain is segmented into equal target sub-data chains according to a preset rule, and the data ratio between the direct procurement data and the offline data is obtained. According to the data ratio, corresponding elements are selected from the corresponding chain positions in the target sub-data chains respectively, and the positions of the target sub-data chains of the selected elements are vacated and then combined to obtain an initial data chain; The unique enterprise identifier is used as the chain head to form a query data chain with the initial data chain, and the query data chain is left in the intermediate score library. Among them, the query data chain is bonded with the data chain composed of the elements selected from the corresponding chain positions.

[0037] Among them, when forming the query data chain, a data chain that can be bonded with the query data chain will be formed at the same time. When querying the score, a latest data chain will be generated according to the same rule using the current data, and the data chain will be bonded and matched with the query data chain. Only after the bonding match passes can it be determined that the queried score data is accurate.

[0038] Specifically, first perform hash operations on the information content of the direct procurement data and the offline data respectively to obtain a first hash value and a second hash value, and then process these two hash values according to a specific preset rule to obtain a target hash value, and then generate a corresponding target data chain. The hash operation is an algorithm that converts data of any length into a fixed-length value. Here, it is used to generate a feature identifier for the data to ensure data integrity and traceability. Exemplarily, the binary numbers corresponding to the first hash value and the second hash value can be subjected to a bitwise exclusive OR operation. The bitwise exclusive OR operation is a logical operation. When the values of the two binary digits are different, the result is 1, and when they are the same, the result is 0. Through this operation, a new binary value is obtained. Then, use the same hash algorithm as the one used to generate the first and second hash values before to perform another hash calculation on this newly obtained binary value, and finally obtain the target hash value. Or perform a hash operation on the first hash value and the second hash value after confusion splicing to obtain the target hash value.

[0039] After obtaining the target data chain, the target data chain is segmented into equal parts of target sub-data chains according to preset rules, and the data ratio between the directly purchased data and the offline data is calculated. Exemplarily, the data ratio can be obtained based on the ratio of the data volumes (such as the number of bytes) of the directly purchased data and the offline data, or the ratio of the sum of the numerical values of the indicators contained in the directly purchased data and the offline data respectively. In actual implementation, elements are then selected from the corresponding chain positions of the target sub-data chains according to this ratio, and the positions of the selected elements are left vacant and then combined into an initial data chain. Then, the enterprise unique identifier is used as the chain head to form a query data chain with the initial data chain, and the query data chain is left in the intermediate scoring database, where the query data chain is bonded with the data chain composed of the elements selected from the corresponding chain positions. This is done to reasonably select data segments through the data ratio, and the vacant positions are for subsequent verification of data accuracy and integrity.

[0040] Among them, the steps of obtaining the data ratio between the directly purchased data and the offline data and respectively selecting corresponding elements from the corresponding chain positions of the target sub-data chains according to the data ratio include: Determine the target value with a larger numerical value according to the data ratio, and segment the target sub-data chain according to the ratio corresponding to the target value, or determine the target value with a smaller numerical value according to the data ratio, and segment the target sub-data chain according to the ratio corresponding to the target value; Segment the segmented target sub-data chain again according to the ratio corresponding to the other target value, then obtain the segmentation positions of each segmentation, and select the corresponding elements from the segmentation positions of each segmentation.

[0041] Specifically, assuming that the ratio of the directly purchased data to the offline data is 70%:30%, the target sub-data chain can be segmented according to either the "70%" or the "30%". When choosing to perform the initial segmentation of the target sub-data chain according to the ratio corresponding to the "larger target value (70%)", the target sub-data chain needs to be divided into two parts, where the part with the larger ratio accounts for 70% of the chain length, and the remaining 30% is the other part. For example, if the total length of the target sub-data chain is 100 elements, after segmentation according to the 70% ratio, the first 70 elements are one part, and the last 30 are the other part. The part of the first 70 elements is used as the target for the next segmentation, and then segmented using the 30% ratio. Record the segmentation positions after each segmentation, and select the corresponding elements from these segmentation positions.

[0042] In addition, in order to further improve the security of the query data chain, when selecting the segmentation ratio, when one of the target sub-data chains is initially segmented according to one of the target values in the data ratio, the adjacent target sub-data chain is initially segmented according to the other target value in the data ratio, that is, different segmentation strategies are adopted for multiple target sub-data chains.

[0043] In summary, in the above-mentioned embodiment of the peer benchmarking information management method of the present invention, by separately obtaining the direct procurement data and offline data of peer benchmarking information collected by the business service layer, and receiving the inspection results for the direct procurement data and offline data; after the inspection results of the direct procurement data and offline data meet the passing conditions, storing the direct procurement data and offline data in the data storage layer according to preset rules; after receiving the display instruction sent by the data access layer, calculating the overall scores of the corresponding relevant enterprises for the stored direct procurement data and offline data according to preset rules, and displaying the overall scores of the relevant enterprises. At the same time, obtaining the direct procurement data and offline data to ensure the comprehensiveness and integrity of the data, which can more accurately reflect the real situation of each relevant enterprise. Inspecting the direct procurement data and offline data, and only after the inspection results meet the passing conditions, proceeding with subsequent processing, improving the accuracy and reliability of the data. Storing the direct procurement data and offline data that pass the inspection according to preset rules, calculating the overall scores of the corresponding relevant enterprises for the stored direct procurement data and offline data, ensuring the orderliness and standardization of data storage, facilitating subsequent query and analysis, and providing a unified and objective scoring standard. It solves the problems of inaccurate evaluation, insufficient data timeliness, and lack of management in the prior art when managing peer benchmarking information.

[0044] Embodiment III Please refer to Figure 2 , which shows the peer benchmarking information management system proposed in the third embodiment of the present invention, applied to a peer benchmarking information management platform. The peer benchmarking information management platform includes a business service layer and a data access layer and a data storage layer that are respectively communicatively connected to the business service layer. The system includes: An acquisition module 100, configured to separately obtain the direct procurement data and offline data of peer benchmarking information collected by the business service layer, and receive the inspection results for the direct procurement data and offline data; A storage module 200, configured to store the direct procurement data and offline data in the data storage layer according to preset rules after the inspection results of the direct procurement data and offline data meet the passing conditions; A display module 300, configured to calculate the overall scores of the corresponding relevant enterprises for the stored direct procurement data and offline data according to preset rules and display the overall scores of the relevant enterprises after receiving the display instruction sent by the data access layer.

[0045] The functions or operation steps realized when the above modules are executed are substantially the same as those in the above method embodiment, and will not be elaborated here.

[0046] Embodiment IV On the other hand, the present invention also provides a readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in any one of the above Embodiment 1 to Embodiment 2 are implemented.

[0047] Embodiment 5 On the other hand, the present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the program, the steps of the method described in any one of the above Embodiment 1 to Embodiment 2 are implemented.

[0048] The technical features of each of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0049] Those skilled in the art can understand that the logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable storage medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable storage medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0050] More specific examples (non-exhaustive list) of computer-readable storage media include the following: an electrical connection part with one or more wirings (electronic device), a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable storage medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or processing it in other suitable ways if necessary, and then storing it in a computer memory.

[0051] It should be understood that each part of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0052] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0053] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims.

Claims

1. A peer benchmarking information management method, characterized in that, Applied to a peer benchmarking information management platform, the peer benchmarking information management platform includes a business service layer, a data access layer, and a data storage layer that are respectively communicatively connected to the business service layer. The method includes: Respectively obtain the direct collection data and offline data on peer benchmarking information collected by the business service layer, and receive the inspection results for the direct collection data and offline data; After the inspection results of the direct collection data and offline data meet the passing conditions, store the direct collection data and offline data in the data storage layer according to preset rules; After receiving the display instruction sent by the data access layer, calculate the overall scores of the corresponding relevant enterprises for the stored direct collection data and offline data according to preset rules, and display the overall scores of the relevant enterprises.

2. The peer benchmarking information management method according to claim 1, wherein The step of storing the direct collection data and offline data in the data storage layer according to preset rules includes: Respectively establish a direct collection database, an offline database, and an intermediate score database in the data storage layer for storing the direct collection data and offline data; Extract the score data for calculating the overall score from the direct collection data and offline data according to the enterprise unique identifier corresponding to the direct collection data and offline data; Store the direct collection data, offline data, and score data in the corresponding direct collection database, offline database, and intermediate score database respectively.

3. The peer benchmarking information management method according to claim 2, wherein After the step of storing the direct collection data, offline data, and score data in the corresponding direct collection database, offline database, and intermediate score database respectively, it further includes: Construct a query data chain according to the enterprise unique identifier, direct collection data, offline data, and score data, and store the query data chain in the intermediate score database; When calculating the overall score of an enterprise is required, determine the score data for calculating the overall score according to the query data chain, and determine the overall score of the enterprise according to the score data.

4. The peer benchmarking information management method according to claim 3, wherein The step of constructing a query data chain according to the enterprise unique identifier, direct collection data, offline data, and score data, and storing the query data chain in the intermediate score database includes: Respectively perform hash operations on the information content of the direct collection data and offline data to obtain a first hash value and a second hash value, and obtain a target hash value according to the first hash value and the second hash value according to preset rules to obtain a corresponding target data chain; Divide the target data chain into equal target sub-data chains according to preset rules, and obtain the data ratio between the direct collection data and offline data. According to the data ratio, select corresponding elements from the corresponding chain positions in the target sub-data chains respectively, and combine them after leaving vacancies in the positions of the target sub-data chains of the selected elements to obtain an initial data chain; Use the enterprise unique identifier as the chain head to form a query data chain with the initial data chain, and leave the query data chain in the intermediate score database, where the query data chain is bonded with the data chain composed of the elements selected from the corresponding chain positions.

5. The peer benchmarking information management method according to claim 4, wherein The step of obtaining the data ratio between the direct collection data and offline data, and selecting corresponding elements from the corresponding chain positions in the target sub-data chains respectively according to the data ratio includes: Determine the target value with a larger value according to the data ratio, and divide the target sub-data chain according to the ratio corresponding to the target value, or determine the target value with a smaller value according to the data ratio, and divide the target sub-data chain according to the ratio corresponding to the target value; Divide the divided target sub-data chain again according to the ratio corresponding to another target value, then obtain the division positions of each division, and select the corresponding elements from the division positions of each division.

6. The peer benchmarking information management method according to claim 5, wherein The step of determining the target value with a larger value according to the data ratio, dividing the target sub-data chain according to the ratio corresponding to the target value, or determining the target value with a smaller value according to the data ratio, and dividing the target sub-data chain according to the ratio corresponding to the target value includes: When one of the target sub-data chains is initially divided according to one of the target values in the data ratio, the adjacent target sub-data chain is initially divided according to the other target value in the data ratio.

7. The peer benchmarking information management method according to claim 4, wherein The step of respectively performing hash operations on the information contents of the direct procurement data and the offline data to obtain a first hash value and a second hash value, and obtaining a target hash value according to the first hash value and the second hash value according to a preset rule to obtain the corresponding target data chain includes: Perform a bitwise exclusive OR operation on the binary representations of the first hash value and the second hash value to obtain a new binary value, and perform hash calculation on the binary value after the exclusive OR operation using the same hash algorithm to obtain the target hash value.

8. An industry benchmarking information management system, characterized in that, Applied to a peer benchmarking information management platform, the peer benchmarking information management platform includes a business service layer, and a data access layer and a data storage layer respectively communicatively connected to the business service layer. The system includes: An acquisition module, configured to respectively acquire the direct procurement data and the offline data of the peer benchmarking information collected by the business service layer, and receive the inspection results for the direct procurement data and the offline data; A storage module, configured to store the direct procurement data and the offline data in the data storage layer according to a preset rule after the inspection results of the direct procurement data and the offline data meet the inspection passing conditions; A display module, configured to, after receiving a display instruction sent by the data access layer, calculate the overall scores of the corresponding relevant enterprises for the stored direct procurement data and the offline data according to a preset rule, and display the overall scores of the relevant enterprises.

9. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the program, the steps of the method described in any one of claims 1 to 7 are implemented.

Images