An intelligent control platform for enterprise operation management based on parallel blockchain

Abstract

The present invention discloses an enterprise operation management intelligent control platform based on parallel blockchain, which belongs to the field of operation management control technology; by expanding, extending and analyzing each internal processing data analysis result of different target personnel in different target departments and each interaction data analysis result between different target personnel across departments, the overall processing status analysis results and the overall interaction status analysis results corresponding to all target personnel in the target department are integrated to implement periodic vertical overall processing status analysis and horizontal overall interaction status analysis on the department, and finally the vertical overall processing status analysis results and the horizontal overall interaction status analysis results of the target department are integrated to obtain the corresponding overall operation degree and analyze; the present invention is used to solve the technical problems of poor supervision dimension and depth of processing work within different departments of an enterprise and poor supervision dimension and depth of interaction work between departments in the existing solutions.

Description

Technical Field

[0001] The present invention relates to the field of operation management control technology, and in particular to an enterprise operation management intelligent control platform based on parallel blockchain. Background Art

[0002] Enterprise operations management refers to the effective planning, organization, coordination, control and evaluation of all aspects of the enterprise in order to achieve the enterprise's goals and enable its sustainable development; enterprise operations management covers production, procurement, sales, marketing, finance, human resources and other aspects.

[0003] When existing enterprise operation management and control solutions are implemented, they generally only process and analyze different types of monitored data and display them passively and intuitively. There is no active data mining and analysis of the vertical operation status within the department and the horizontal operation status between departments from different dimensions, and no targeted optimization management of the abnormal operation status corresponding to the abnormal department based on the data mining and analysis results. This leads to poor supervision dimensions and depth of processing work within different departments of the enterprise and poor supervision dimensions and depth of interactive work between departments. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent control platform for enterprise operation management based on parallel blockchain, which is used to solve the technical problems of poor supervision dimensions and depth of processing work within different departments of an enterprise and poor supervision dimensions and depth of interactive work between departments in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An enterprise operation management intelligent control platform based on parallel blockchain, including:

[0007] The local vertical and horizontal operation status supervision module is used to record and count the local work data of different target personnel in different target departments within the enterprise and the local interaction data between different target personnel across departments within the enterprise in real time, and to trace and analyze the real-time local processing status of the target personnel and the real-time local interaction status between different target personnel across departments, and obtain the local processing status analysis data set consisting of the local vertical processing status analysis data set and the local horizontal processing status analysis data set and upload it to the parallel blockchain for storage;

[0008] The overall vertical and horizontal operation status supervision module is used to integrate and calculate the local processing status analysis data sets of all target personnel in different target departments within the enterprise, implement periodic vertical operation status analysis, and integrate and calculate the local horizontal processing status analysis data sets of different target personnel across departments within the enterprise, implement periodic horizontal operation status analysis, obtain the overall vertical operation analysis data and overall horizontal operation analysis data corresponding to all target departments, and upload them to the parallel blockchain for storage;

[0009] The overall department operation management control module is used to dynamically control the overall operations of different target departments within the enterprise based on the overall vertical operation analysis data and the overall horizontal operation analysis data.

[0010] Preferably, when implementing a comprehensive monitoring and analysis of the real-time work data of different target personnel in different target departments of the enterprise, the real-time update of the target processing data that different target personnel are responsible for is monitored, and when the target processing data that the target personnel are responsible for is updated, a first processing start instruction is generated, and the corresponding target personnel is marked as the selected target personnel according to the first processing start instruction, and the target processing data updated by the selected target personnel is traceably analyzed.

[0011] Preferably, the corresponding processing interval time difference is obtained and analyzed based on the first processing time point when the selected target person starts to process the updated target processing data, so as to obtain the local longitudinal processing state analysis data of the selected target person composed of local processing normal labels or local processing abnormal labels; the local longitudinal processing state analysis data of all selected target persons constitute a local longitudinal processing state analysis data set.

[0012] Preferably, when implementing a comprehensive monitoring and analysis of the real-time interaction data between cross-departmental target personnel in different target departments of the enterprise, a second processing start instruction is generated when the target personnel communicate with the other party's staff across departments, and the staff of the interactive respondent is marked as a horizontal target personnel according to the second processing start instruction, and the interaction of the horizontal target personnel for feedback is traceably analyzed.

[0013] Preferably, the corresponding interaction interval time difference is obtained and analyzed according to the second processing time point when the horizontal target person replies to the target person's conversation, to obtain a local interaction normal label or a local interaction abnormal label;

[0014] All local interaction normal labels or local interaction abnormal labels when the horizontal target personnel communicate with the target personnel constitute the local horizontal processing state analysis data of the horizontal target personnel; the local horizontal processing state analysis data of all horizontal target personnel constitute the local horizontal processing state analysis data set.

[0015] Preferably, the tag identification values ​​associated with the local processing normal tag and the local interaction normal tag are both 0, and the tag identification values ​​associated with the local processing abnormal tag and the local interaction abnormal tag are both 1.

[0016] Preferably, all local processing status analysis data corresponding to the selected target person in the status evaluation cycle are counted and traversed, and the tag identification values ​​associated with all tags in all local processing status analysis data of the selected target person are obtained and summed to obtain the individual's overall processing status; the overall processing status of the corresponding selected target person in the status evaluation cycle is analyzed according to the individual's overall processing status to obtain a normal processing person or an abnormal processing person;

[0017] When analyzing the vertical operation status of different target departments within the status assessment cycle, the vertical operation degree corresponding to the target department is obtained according to the total number of normal processing personnel and the total number of abnormal processing personnel in the target department; the vertical operation degrees corresponding to different target departments are arranged in descending order and analyzed to associate all target departments with abnormal vertical operation status or normal vertical operation status;

[0018] The abnormal longitudinal operation status and normal longitudinal operation status associated with all targets constitute the overall longitudinal operation analysis data.

[0019] Preferably, all local interaction status analysis data corresponding to different target departments within the status evaluation cycle are counted and traversed, and the tag identification values ​​associated with all tags in all local processing status analysis data corresponding to different horizontal target personnel in the target department are obtained and summed to obtain the individual overall interaction status degree; the overall interaction status of the corresponding horizontal target personnel within the status evaluation cycle is analyzed according to the individual overall interaction status degree to obtain normal interaction personnel or abnormal interaction personnel;

[0020] When analyzing the horizontal operation status of different target departments within the status assessment cycle, the horizontal operation degree corresponding to the target department is obtained according to the total number of normal interaction personnel and the total number of abnormal interaction personnel in the target department; the horizontal operation degrees corresponding to different target departments are arranged in descending order and analyzed to associate all target departments with abnormal horizontal operation status or normal horizontal operation status;

[0021] The abnormal horizontal operation status and normal horizontal operation status associated with all targets constitute the overall horizontal operation analysis data.

[0022] Preferably, the vertical operation degree and the horizontal operation degree corresponding to different target departments within the status evaluation cycle are obtained and the overall operation degree corresponding to the target department is calculated and obtained;

[0023] If the overall operation degree is greater than the overall operation degree threshold, an overall operation abnormality label is generated and the corresponding target department is marked as the selected department for rectification. At the same time, the management personnel are prompted to make targeted rectifications to their subsequent employee work processing and employee cross-department interaction processing;

[0024] Otherwise, an overall normal operation label is generated and the corresponding target department is marked as an overall normal department.

[0025] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0026] The present invention implements periodic overall processing status analysis and overall interaction status analysis on different individuals by expanding and extending the results of each internal processing data analysis of different target personnel in different target departments and each interaction data analysis result between different target personnel across departments. Then, the overall processing status analysis results and the overall interaction status analysis results corresponding to all target personnel in the target department are integrated to implement periodic vertical overall processing status analysis and horizontal overall interaction status analysis on the department. Finally, the vertical overall processing status analysis results and the horizontal overall interaction status analysis results of the target department are integrated to obtain the corresponding overall operation degree and analyze it, thereby realizing multi-dimensional and multi-level data analysis and supervision of local processing operations and overall processing operations within different departments of the enterprise and local interaction operations and overall interaction operations between different departments, reducing the impact of data islands on data exchange between different departments of the existing enterprise, and improving the breadth and depth of enterprise operation management and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below in conjunction with the accompanying drawings.

[0028] Figure 1 This is a module block diagram of an enterprise operation management intelligent control platform based on parallel blockchain in the present invention.

[0029] Figure 2 This is a principle block diagram of the implementation of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 operation and maintenance personnel in this field without creative work are within the scope of protection of the present invention.

[0031] Example 1: Figure 1 and Figure 2As shown, the present invention is an enterprise operation management intelligent control platform based on parallel blockchain, including a local vertical and horizontal operation status supervision module and a parallel blockchain;

[0032] The local vertical and horizontal operation status supervision module is used to record and count the local work data of different target personnel in different target departments within the enterprise and the local interaction data between different target personnel across departments within the enterprise in real time, and to trace and analyze the real-time local processing status of the target personnel and the real-time local interaction status between different target personnel across departments, and obtain the local processing status analysis data set consisting of the local vertical processing status analysis data set and the local horizontal processing status analysis data set and upload it to the parallel blockchain for storage; including:

[0033] The local longitudinal and transverse operation status supervision module includes a local longitudinal operation status supervision unit and a local transverse operation status supervision unit;

[0034] When the real-time work data of different target personnel in different target departments of the enterprise are comprehensively monitored and analyzed through the local vertical operation status supervision unit, the real-time update of the target processing data that the different target personnel are responsible for is monitored. When the target processing data that the target personnel are responsible for is updated, a first processing start instruction is generated. According to the first processing start instruction, the corresponding target personnel is marked as the selected target personnel, and the target processing data updated by the selected target personnel is traced and analyzed;

[0035] It should be noted that, due to the different job attributes and work contents of different departments and different staff members, it is necessary to screen different departments and different staff members within the enterprise to obtain target departments and target personnel to implement targeted supervision and analysis. The screening requirements can be determined according to the actual operation and management needs of the enterprise. In addition, the target processing data corresponding to the target personnel is determined according to their job attributes and work contents. Through the target departments, target personnel and corresponding target processing data screened in the early stage, targeted monitoring and management of a large amount of daily operation data within the enterprise can be achieved, which improves the pertinence and reliability of subsequent enterprise operation management.

[0036] The present invention can be applied to business fields such as enterprise supply chain, production and manufacturing, equipment interconnection, internal and external collaborative office, and operational data analysis, mining and utilization. For example, the target department in the embodiment of the present invention can be an administrative department, the target personnel can be a human resources department, and the corresponding target processing data can be a resume received by a recruitment platform.

[0037] Obtaining the first processing time point at which the selected target person starts to process the updated target processing data, the unit of the first processing time point is accurate to seconds, calculating the processing interval time difference between the update time point when the target processing data is updated and the first processing time point, the unit of the processing interval time difference is seconds, and when determining the local processing state of the updated target processing data by the selected target person according to the processing interval time difference, comparing and classifying the processing interval time difference with the standard processing interval time difference;

[0038] The standard processing interval time difference is determined based on the average of all processing interval time differences corresponding to all the same selected target personnel in the enterprise history;

[0039] If the processing interval time difference is not greater than the standard processing interval time difference, a local processing normal label is generated and its associated label identification value is set to 0;

[0040] Otherwise, a local processing exception label is generated and its associated label identification value is set to 1; for example, the personnel processing receives the resume delivered in time;

[0041] The local processing normal label or the local processing abnormal label constitutes the local longitudinal processing status analysis data of the selected target person;

[0042] The local longitudinal processing state analysis data of all selected target persons constitute a local longitudinal processing state analysis data set;

[0043] In the embodiment of the present invention, by monitoring and analyzing the local processing of target processing data that different target personnel in different target departments are responsible for, it is possible to obtain the local processing status of target data of different target personnel each time, and to provide reliable local work processing data support for the subsequent overall operational status analysis of the corresponding target personnel and the corresponding target department, thereby achieving diversity and extensibility in the supervision of different target personnel in local vertical processing.

[0044] When the local horizontal operation status supervision unit conducts all-round monitoring and analysis of the real-time interaction data between cross-department target personnel in different target departments of the enterprise, a second processing start instruction is generated when the target personnel communicate with the staff of the other party across departments, and the staff of the interactive answering party is marked as a horizontal target personnel according to the second processing start instruction, and the feedback interaction of the horizontal target personnel is traced and analyzed; for example, the human resources of the target personnel contacts the supervisor of the department corresponding to the position to be recruited to confirm the specific interview time;

[0045] Obtain the second processing time point when the horizontal target person replies to the target person's conversation, the unit of the second processing time point is accurate to seconds, calculate the interaction interval time difference between the second processing time point and the time point when the second processing start instruction appears, the unit of the interaction interval time difference is accurate to seconds, and when determining the local interaction state of the horizontal target person when communicating across departments according to the interaction interval time difference, compare and classify the interaction interval time difference with the standard interaction interval time difference, the standard interaction interval time difference is determined according to the average of all historical interaction interval time differences of the horizontal target persons with whom the target person interacts;

[0046] If the interaction interval time difference is not greater than the standard interaction interval time difference, a local interaction normal label is generated and its associated label identification value is set to 0;

[0047] Otherwise, a local interaction abnormality label is generated and its associated label identification value is set to 1; for example, the supervisor of the department corresponding to the position to be recruited does not respond in time;

[0048] All local interaction normal labels or local interaction abnormal labels when the horizontal target personnel communicate with the target personnel constitute the local horizontal processing state analysis data of the horizontal target personnel;

[0049] The local lateral processing state analysis data of all lateral target personnel constitute a local lateral processing state analysis data set;

[0050] The local longitudinal processing state analysis data set and the local transverse processing state analysis data set constitute a local processing state analysis data set and are uploaded to the parallel blockchain for storage;

[0051] Among them, the parallel blockchain refers to building a new blockchain system on the original main blockchain system, which operates independently and in parallel with the main blockchain system; the parallel blockchain can be understood as an independent chain built outside the main chain, which can realize independent consensus mechanism, ledger management and smart contract functions, and is not affected by the transaction speed and security of the main chain; the main blockchain in the embodiment of the present invention is used to store all real-time operation data monitored and counted during the operation of the enterprise;

[0052] In the embodiment of the present invention, by monitoring and analyzing the communication data between cross-departmental target personnel between different target departments, it is possible to obtain the local processing status of the interaction data of different cross-departmental target personnel each time, and to provide reliable local interaction processing data support for the subsequent analysis of the overall operational status of the corresponding target personnel and the corresponding target department, thereby achieving diversity and extensibility in the supervision of different target personnel in local horizontal processing.

[0053] Embodiment 2: Based on the technical solution of Embodiment 1, it also includes an overall vertical and horizontal operation status supervision module, which is used to integrate and calculate and analyze the local processing status analysis data sets of all target personnel in different target departments within the enterprise to implement periodic vertical operation status analysis, and integrate and calculate and analyze the local horizontal processing status analysis data sets of different target personnel across departments within the enterprise to implement periodic horizontal operation status analysis, obtain the overall vertical operation analysis data and the overall horizontal operation analysis data corresponding to all target departments and upload them to the parallel blockchain for storage; including:

[0054] The overall vertical and horizontal operation status supervision module includes an overall vertical operation status supervision unit and an overall horizontal operation status supervision unit;

[0055] All local processing status analysis data corresponding to the selected target personnel in the status evaluation cycle are counted and traversed through the overall vertical operation status supervision unit. The unit of the status evaluation cycle is month, which can be one month. The tag identification values ​​associated with all tags in all local processing status analysis data of the selected target personnel are obtained and summed to obtain the overall processing status degree of the individual;

[0056] When determining the overall processing status of the corresponding selected target person within the status evaluation cycle according to the individual overall processing status, if the individual overall processing status is not greater than the standard processing status threshold, an overall processing normal label is generated and the corresponding selected target person is marked as a normal processing person; the standard processing status threshold is the average value corresponding to all individual overall processing statuses;

[0057] Otherwise, an overall processing exception label is generated and the corresponding selected target personnel are marked as exception handling personnel;

[0058] It should be noted that the corresponding individual overall processing status is obtained by expanding and integrating the local processing status analysis data of each target person selected in the early stage, and the overall processing status of the selected target person in the status evaluation cycle is analyzed and obtained according to the individual overall processing status. At the same time, reliable overall processing status data support for the target person can also be provided for the longitudinal operation status analysis of the target department corresponding to the selected target person;

[0059] When analyzing the vertical operation status of different target departments within the status assessment cycle, the total number of normal processing personnel N1 and the total number of abnormal processing personnel N2 in the target department are counted, and the vertical operation degree α corresponding to the target department is calculated by the formula α=N2 / (N1+N2);

[0060] It should be noted that the vertical operation degree is a value used to integrate and calculate the overall processing status analysis data of all target personnel in the target department within the status evaluation cycle to evaluate and classify their vertical operation status;

[0061] Arrange the vertical operation degrees corresponding to different target departments in descending order, obtain the average of all vertical operation degrees corresponding to all target departments and set it as the vertical operation degree threshold, and associate the target departments corresponding to the vertical operation degrees greater than the vertical operation degree threshold with abnormal vertical operation status;

[0062] Otherwise, the remaining target departments are associated with normal vertical operation status;

[0063] The abnormal longitudinal operation status and normal longitudinal operation status associated with all targets constitute the overall longitudinal operation analysis data;

[0064] In an embodiment of the present invention, all local processing status analysis data corresponding to different target personnel in the target department are integrated and calculated, and the results of the analysis are further integrated to obtain the vertical operating degree corresponding to the department. The vertical operating degree is used to analyze and classify the vertical operating status within the target department itself. This can provide reliable vertical operating status analysis data support for the subsequent overall operating status analysis of the target department, thereby improving the diversity of monitoring and analysis of different internal operating states of the enterprise and the reliability of data expansion and utilization.

[0065] Through the overall horizontal operation status supervision unit, all local interaction status analysis data corresponding to different target departments within the status evaluation cycle are counted and traversed, and the tag identification values ​​associated with all tags in all local processing status analysis data corresponding to different horizontal target personnel in the target department are obtained and summed to obtain the overall interaction status degree of the individual;

[0066] When determining the overall interaction status of the corresponding horizontal target person in the status evaluation cycle according to the individual's overall interaction status, if the individual's overall interaction status is not greater than the standard interaction status threshold, an overall interaction normal label is generated and the corresponding horizontal target person is marked as a normal interaction person; the standard interaction status threshold is the average value corresponding to all individual overall interaction statuses;

[0067] Otherwise, an overall processing exception label is generated and the corresponding selected target personnel are marked as abnormal interaction personnel;

[0068] When analyzing the horizontal operation status of different target departments within the status assessment cycle, the total number of normal interaction personnel N1' and the total number of abnormal interaction personnel N2' in the target department are counted, and the horizontal operation degree β corresponding to the target department is calculated by the formula β=N2' / (N1'+N2'+μ); where μ is the weight error factor of the abnormal interaction department;

[0069] It should be noted that the horizontal operation degree is a numerical value used to integrate and calculate the overall interaction status analysis data of all target personnel in the target department within the status evaluation cycle to evaluate and classify its horizontal operation status;

[0070] The steps for obtaining the abnormal interaction department weight error factor μ include:

[0071] Get the target department where the abnormal interaction personnel are located and mark it as the abnormal interaction department, and traverse and match the abnormal interaction department with the department weight table pre-stored in the main blockchain to obtain the corresponding department weight bq; the department weight table contains all departments in the enterprise and the associated department weight composition, and different departments are pre-set with a corresponding department weight. The specific value of the department weight can be determined based on the number of historical operational anomalies and the number of historical interaction anomalies;

[0072] Through the formula μ = ∑1 N2＇ bq calculates and obtains the weight error factor μ of all abnormal interaction departments corresponding to the abnormal interaction departments that appear during the status evaluation cycle;

[0073] Arrange the horizontal operation degrees corresponding to different target departments in descending order, obtain the average of all horizontal operation degrees corresponding to all target departments and set it as the horizontal operation degree threshold, and associate the target departments corresponding to the horizontal operation degrees greater than the horizontal operation degree threshold with abnormal horizontal operation status;

[0074] Otherwise, the remaining target departments will be associated with normal horizontal operation status;

[0075] The abnormal horizontal operation status and normal horizontal operation status associated with all targets constitute the overall horizontal operation analysis data;

[0076] In an embodiment of the present invention, all local interaction status analysis data corresponding to different target personnel interacting across departments are integrated and calculated, and the results of the analysis are further integrated to obtain the horizontal operation degree corresponding to the department. The horizontal operation degree is used to analyze and classify the horizontal operation status between different departments. This can provide reliable horizontal operation status analysis data support for the overall operation status analysis of subsequent target departments, reduce the impact of data islands on data exchange between different departments of the existing enterprise, and improve the diversity of interaction status monitoring and analysis between different departments of the enterprise and the reliability of data expansion and utilization.

[0077] Embodiment 3: Based on the technical solutions of Embodiments 1 and 2, an overall department operation management control module is further included, which is used to dynamically control the overall operation of different target departments within the enterprise according to the overall vertical operation analysis data and the overall horizontal operation analysis data; including:

[0078] Obtain the vertical operation degree α and horizontal operation degree β corresponding to different target departments within the status assessment cycle, and calculate the overall operation degree η corresponding to the target department through the formula η=ε1×α+ε2×β; where ε1 and ε2 are the influence weight coefficients corresponding to the vertical operation degree and the horizontal operation degree, respectively, 0<ε1<1, 0<ε2<1, ε1 can be taken as 0.384, and ε2 can be taken as 0.616;

[0079] If the overall operation degree is greater than the overall operation degree threshold, an overall operation abnormality label is generated and the corresponding target department is marked as the selected department for rectification. At the same time, the management personnel are prompted to make targeted rectifications to their subsequent employee work processing and employee cross-department interaction processing; the overall operation degree threshold is the average of all overall operation degrees corresponding to all target departments;

[0080] Otherwise, an overall normal operation label is generated and the corresponding target department is marked as an overall normal department.

[0081] In the implementation of the present invention, by expanding and extending the results of each internal processing data analysis of different target personnel in different target departments and each interaction data analysis result between different target personnel across departments, periodic overall processing status analysis and overall interaction status analysis are implemented for different individuals. Then, the overall processing status analysis results and overall interaction status analysis results corresponding to all target personnel in the target department are integrated to implement periodic vertical overall processing status analysis and horizontal overall interaction status analysis for the department. Finally, the vertical overall processing status analysis results and horizontal overall interaction status analysis results of the target department are integrated to obtain the corresponding overall operation degree and analyze it, thereby realizing multi-dimensional and multi-level data analysis and supervision of local processing operations and overall processing operations within different departments of the enterprise and local interaction operations and overall interaction operations between different departments, thereby improving the breadth and depth of enterprise operation management and control.

[0082] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0083] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0084] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0085] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0086] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the basic features of the present invention.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary operation and maintenance personnel in the field should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent control platform for enterprise operation management based on parallel blockchain, characterized in that: It includes a local vertical and horizontal operation status supervision module, which is used to record and count the local work data of different target personnel in different target departments within the enterprise and the local interaction data between different target personnel across departments within the enterprise in real time, and to trace and analyze the real-time local processing status of the target personnel and the real-time local interaction status between different target personnel across departments, and obtain a local processing status analysis data set consisting of a local vertical processing status analysis data set and a local horizontal processing status analysis data set and upload it to the parallel blockchain for storage; The overall vertical and horizontal operation status supervision module is used to integrate and calculate the local processing status analysis data sets of all target personnel in different target departments within the enterprise, implement periodic vertical operation status analysis, and integrate and calculate the local horizontal processing status analysis data sets of different target personnel across departments within the enterprise, implement periodic horizontal operation status analysis, obtain the overall vertical operation analysis data and overall horizontal operation analysis data corresponding to all target departments, and upload them to the parallel blockchain for storage; Among them, when analyzing the vertical operation status of different target departments within the status evaluation cycle, the total number of normal processing personnel N1 and the total number of abnormal processing personnel N2 in the target department are counted, and the vertical operation degree α corresponding to the target department is calculated by the formula α=N2 / (N1+N2); Arrange the vertical operation degrees corresponding to different target departments in descending order, obtain the average of all vertical operation degrees corresponding to all target departments and set it as the vertical operation degree threshold, and associate the target departments corresponding to the vertical operation degrees greater than the vertical operation degree threshold with abnormal vertical operation status; Otherwise, the remaining target departments are associated with normal vertical operation status; The abnormal longitudinal operation status and normal longitudinal operation status associated with all targets constitute the overall longitudinal operation analysis data; When analyzing the horizontal operation status of different target departments within the status assessment cycle, the total number of normal interaction personnel N1' and the total number of abnormal interaction personnel N2' in the target department are counted, and the horizontal operation degree β corresponding to the target department is calculated by the formula β=N2' / (N1'+N2'+μ); where μ is the weight error factor of the abnormal interaction department; Arrange the horizontal operation degrees corresponding to different target departments in descending order, obtain the average of all horizontal operation degrees corresponding to all target departments and set it as the horizontal operation degree threshold, and associate the target departments corresponding to the horizontal operation degrees greater than the horizontal operation degree threshold with abnormal horizontal operation status; Otherwise, the remaining target departments will be associated with normal horizontal operation status; The abnormal horizontal operation status and normal horizontal operation status associated with all targets constitute the overall horizontal operation analysis data; The overall department operation management control module is used to dynamically control the overall operation of different target departments within the enterprise based on the overall vertical operation analysis data and the overall horizontal operation analysis data; Among them, the vertical operation degree α and horizontal operation degree β corresponding to different target departments in the status assessment cycle are obtained, and the overall operation degree η corresponding to the target department is calculated by the formula η=ε1×α+ε2×β; where ε1 and ε2 are the influence weight coefficients corresponding to the vertical operation degree and the horizontal operation degree, respectively, 0<ε1<1, 0<ε2<1; If the overall operation degree is greater than the overall operation degree threshold, an overall operation abnormality label is generated and the corresponding target department is marked as the selected department for rectification. At the same time, the management personnel are prompted to make targeted rectifications to their subsequent employee work processing and employee cross-department interaction processing; the overall operation degree threshold is the average of all overall operation degrees corresponding to all target departments; Otherwise, an overall normal operation label is generated and the corresponding target department is marked as an overall normal department.

2. According to claim 1, an enterprise operation management intelligent control platform based on parallel blockchain is characterized in that: When implementing a comprehensive monitoring and analysis of the real-time work data of different target personnel in different target departments of the enterprise, the real-time update of the target processing data that different target personnel are responsible for is monitored, and when the target processing data that the target personnel are responsible for is updated, a first processing start instruction is generated, and the corresponding target personnel are marked as selected target personnel according to the first processing start instruction, and the target processing data updated by the selected target personnel is traced and analyzed.

3. According to claim 2, an enterprise operation management intelligent control platform based on parallel blockchain is characterized in that: According to the first processing time point when the selected target person starts to process the updated target processing data, the corresponding processing interval time difference is obtained and analyzed to obtain the local longitudinal processing state analysis data of the selected target person composed of local processing normal labels or local processing abnormal labels; the local longitudinal processing state analysis data of all selected target persons constitute a local longitudinal processing state analysis data set.

4. According to claim 1, an enterprise operation management intelligent control platform based on parallel blockchain is characterized in that: When implementing a comprehensive monitoring and analysis of the real-time interaction data between cross-departmental target personnel in different target departments of the enterprise, a second processing start instruction is generated when the target personnel communicate with the other party's staff across departments. According to the second processing start instruction, the staff of the interactive responding party is marked as a horizontal target personnel, and the feedback interaction of the horizontal target personnel is traced and analyzed.

5. According to claim 4, an enterprise operation management intelligent control platform based on parallel blockchain is characterized in that: According to the second processing time point when the horizontal target person replies to the target person's conversation, the corresponding interaction interval time difference is obtained and analyzed to obtain a local interaction normal label or a local interaction abnormal label; All local interaction normal labels or local interaction abnormal labels when the horizontal target personnel communicate with the target personnel constitute the local horizontal processing state analysis data of the horizontal target personnel; the local horizontal processing state analysis data of all horizontal target personnel constitute the local horizontal processing state analysis data set.

6. According to claim 5, an enterprise operation management intelligent control platform based on parallel blockchain is characterized in that: The label identification values ​​associated with the local processing normal label and the local interaction normal label are both 0, and the label identification values ​​associated with the local processing abnormal label and the local interaction abnormal label are both 1.

7. According to claim 6, an enterprise operation management intelligent control platform based on parallel blockchain is characterized in that: All local processing status analysis data corresponding to the selected target personnel within the status evaluation cycle are counted and traversed, and the label identification values ​​associated with all labels in all local processing status analysis data of the selected target personnel are obtained and summed up to obtain the individual's overall processing status; according to the individual's overall processing status, the overall processing status of the corresponding selected target personnel within the status evaluation cycle is analyzed to obtain normal processing personnel or abnormal processing personnel.

8. According to claim 6, an enterprise operation management intelligent control platform based on parallel blockchain is characterized in that: Count and traverse all local interaction status analysis data corresponding to different target departments within the status assessment cycle, obtain the label identification values ​​associated with all labels in all local processing status analysis data corresponding to different horizontal target personnel in the target department, and sum them up to get the individual's overall interaction status; analyze the overall interaction status of the corresponding horizontal target personnel within the status assessment cycle according to the individual's overall interaction status, and get normal interaction personnel or abnormal interaction personnel.

Images