Digitization-based project management method and system

Abstract

The invention provides a project management method and system based on digitization, and relates to the field of project management. The method comprises the following steps: acquiring Q information nodes, P process nodes and R content nodes of each target employee; calling a project data set, and performing data mapping on the Q information nodes, the P process nodes and the R content nodes; based on the P flow node data sets, the Q information node data sets and the R content nodes, performing information overlapping analysis on the Q information nodes; performing simulation on each project node of the target employee by taking the Q information node overlapping coefficients as Q simulation project values; performing data volume analysis on P combined simulation units acquired by each target employee and execution simulation values thereof; and performing project management on each target employee based on the P project management subunits. According to the method and the system, the function of each employee can be reasonably arranged during project execution, so that better execution efficiency and execution quality can be achieved.

Description

Technical Field

[0001] The present invention relates to the field of project management, and in particular to a digital-based project management method and system. Background Art

[0002] As enterprises expand and projects become more diverse, project management becomes more and more complex. Traditional project management methods often rely on the experience and intuition of project managers and are difficult to cope with complex and changing project environments.

[0003] In recent years, digital technologies have developed rapidly, including big data, cloud computing, artificial intelligence, etc. These technologies provide new possibilities for project management, making more refined management possible. In the background technology, there may already be a certain digital infrastructure, such as project management software, data analysis platforms, etc., but these tools may not have been fully utilized for in-depth analysis and simulation.

[0004] In project management, employee performance evaluation is an important link. However, traditional performance evaluation methods are often highly subjective and difficult to accurately reflect employees' actual contributions and capabilities. Background technology may lack a scientific and objective employee performance evaluation system, resulting in a lack of data support for project management decisions.

[0005] As market competition intensifies, enterprises have higher and higher requirements for the accuracy of project management. The traditional extensive management method can no longer meet the needs of modern enterprises.

[0006] How to reasonably arrange the functions of each employee when executing a project to achieve better execution efficiency and quality. Summary of the invention

[0007] The purpose of the present invention is to provide a digital-based project management method and system, which can reasonably arrange the functions of each employee when executing a project to achieve better execution efficiency and execution quality.

[0008] To achieve the above object, the present invention provides a digital project management method, comprising the following steps: Collect Q information nodes, P process nodes and R content nodes of each target employee, where the attributes of the Q information nodes include the employee's completion quality, completion time, communication and collaboration ability, department attributes, and outstanding features during the project execution; the R content nodes include the required essential skills, completion time limit, and completion location; Retrieving a project data set, performing data mapping on the Q information nodes, the P process nodes, and the R content nodes, and obtaining Q information node data sets, P process node data sets, and R content node data sets; Based on the P process node data sets, the Q information node data sets and the R content nodes, information overlap analysis is performed on the Q information nodes, the number of information overlaps of each information node and the information overlap complexity of each overlap are determined, and K-line overlap coefficient analysis is performed to obtain the overlap coefficients of the Q information nodes, wherein the overlap coefficients of the Q information nodes reflect the overlap of associated designs of the Q information nodes under multiple process nodes and content nodes; Using the Q information node overlap coefficients as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and performing simulation in the order of project process nodes of the P process node data sets, combining information nodes and content nodes to form simulation units, and obtaining M simulation units, wherein each simulation unit has multiple information nodes and content nodes; The P combined simulation units and their execution simulation values ​​obtained by each target employee are analyzed for data volume to obtain the volume of P combined simulation units; Construct P project management sub-units of the target project management unit according to the P simulation unit volumes of each target employee; Project management is performed on each of the target employees based on the P project management subunits.

[0009] Preferably, the step of retrieving the project data set of the target industry, performing data mapping on the Q information nodes, P process nodes and R content nodes, and obtaining Q information node data sets, P process node data sets and R content node data sets includes: Using the employee information data as an index, searching the project data set to obtain the employee information data set; Matching the employee information data set with the attributes of the Q information nodes respectively to obtain the Q information node data sets, wherein each information node data set includes a grade score of the attribute of each information node; According to the project information data set, P process nodes and R content nodes are matched to obtain P process node data sets and R content node data sets, wherein each process node data set includes project stage data; each content node data set includes content features.

[0010] Preferably, based on the P process node data sets, the Q information node data sets and the R content nodes, information overlap analysis is performed on the Q information nodes, the number of information overlaps of each information node and the information overlap complexity of each overlap are determined, and a K-line overlap coefficient analysis is performed to obtain the overlap coefficients of the Q information nodes, including: Using the Q information nodes as indexes, the P process node data sets and the R content node data sets are searched respectively to obtain Q information overlapping data sets, wherein the information overlapping data in each information overlapping data set has a directional identifier; Determine Q information overlap times and Q information overlap complexity sets based on the Q information overlap data sets; An overlapping coefficient analysis is performed according to the Q information overlapping times and the Q information overlapping complexity sets to obtain the Q information node overlapping coefficients.

[0011] Preferably, the Q information node overlap coefficients are used as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and the simulation is performed in the order of the project process nodes of the P process node data sets, and the information nodes and content nodes are combined to form simulation units to obtain M simulation units, including: Based on the Q information node overlap coefficients as Q simulation project values, construct an execution simulation of the target employee's completed project; The simulation is performed in the project process node sequence of the P process node data sets until all contents in the P process node data sets are completed in the project process node sequence; During the execution simulation, each process node combines the information node of each target employee and the content node of each project to form K different simulation units, and scores each simulation unit according to the overlapping coefficient of Q information nodes to obtain N execution simulation values.

[0012] Preferably, N different simulation units are obtained, and then the method further comprises: Analyzing the N different simulation units and the N execution simulation values; Determine whether the N execution simulation values ​​are greater than a preset threshold, and if not, add the corresponding simulation unit into the simulation unit to be combined; Random information combination is performed on the simulation units to be combined, and N different simulation units are updated according to the combination results to obtain multiple stage combined simulation units.

[0013] Preferably, the method further comprises: obtaining a plurality of stage combination simulation units; Determine whether the execution simulation values ​​of the plurality of stage combined simulation units are less than a preset threshold value, and if so, add them into the combined simulation unit to be fused; Integrate the combined simulation units to be fused in the simulation units to be fused into the combined simulation units at adjacent stages respectively; After multiple combinations and fusions, when the execution simulation values ​​of the combined simulation units in multiple stages meet the preset threshold, P combined simulation units are obtained.

[0014] Preferably, data volume analysis is performed on the P combination simulation units and their execution simulation values ​​obtained for each target employee to obtain the volume of the P combination simulation units, including: According to the P combined simulation units of each target employee and their executed simulation values, data matching is performed on the P combined simulation units to obtain P combined simulation unit data sets; Information entropy is calculated for P combined simulation unit data sets to obtain P simulation information entropies, and the P simulation information entropies are used as the P combined simulation unit data set collective quantity.

[0015] A digital project management system, including The process node collection module is used to collect Q information nodes, P process nodes and R content nodes of each target employee, wherein the attributes of the Q information nodes include the employee's completion quality, completion time, communication and collaboration ability, department attributes, and outstanding features during the project execution process; the R content nodes include the required essential skills, completion time limit, and completion location; A process node data set acquisition module is used to retrieve a project data set, perform data mapping on the Q information nodes, P process nodes and R content nodes, and obtain Q information node data sets, P process node data sets and R content node data sets; An overlapping coefficient obtaining module is used to perform information overlapping analysis on the Q information nodes based on the P process node data sets, the Q information node data sets and the R content nodes, determine the number of information overlapping of each information node and the information overlapping complexity of each overlap to perform K-line overlapping coefficient analysis, and obtain the overlapping coefficients of the Q information nodes, wherein the overlapping coefficients of the Q information nodes reflect the overlapping of the associated designs of the Q information nodes under multiple process nodes and content nodes; a simulation unit obtaining module, for using the Q information node overlap coefficients as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and performing simulation in the order of project process nodes of the P process node data sets, combining information nodes and content nodes to form simulation units, and obtaining M simulation units, wherein each simulation unit has a plurality of information nodes and content nodes; The regional volume acquisition module is used to perform data volume analysis on the P combined simulation units and their execution simulation values ​​obtained for each target employee to obtain the volumes of the P combined simulation units; A project management subunit obtaining module, used to construct P project management subunits of the target project management unit according to the P simulation unit volumes of each target employee; A project management module is used to perform project management on each of the target employees based on the P project management subunits.

[0016] Therefore, the present invention adopts the above-mentioned digital-based project management method and system, and the technical effects are as follows: (1) Through automated data collection and analysis, the time and errors of manual processing are reduced, and the efficiency of project management is improved. Information overlap analysis and execution simulation can help project managers quickly identify key nodes and potential risks, thereby making more accurate management decisions.

[0017] (2) Through comprehensive analysis of employee capabilities, project requirements, and process nodes, resources can be allocated more reasonably to ensure that each task is performed by the most appropriate person. The process of random information combination and multiple fusion helps to discover the best team configuration and workflow, further improving resource utilization efficiency.

[0018] (3) Through accurate data analysis and simulation, it is possible to predict problems that may arise during project execution and formulate countermeasures in advance. The judgment of execution simulation values ​​and the construction of combined simulation units help ensure that the project is completed according to the expected quality, time and cost.

[0019] (4) The solution provides a large amount of quantitative data and analysis results, providing strong decision-making support for project managers. Information such as K-line overlap coefficient and execution simulation value can help project managers better understand project status and employee performance, thereby making more scientific management decisions.

[0020] (5) The program emphasizes continuous data collection and analysis, which helps companies accumulate project management experience and form a knowledge base. By comparing the performance of different projects and employees, it is possible to identify good practices and areas for improvement, thereby promoting the continuous optimization of project management methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A flowchart of a digital-based project management method of the present invention; Figure 2 This is a schematic diagram of a digital project management system according to the present invention. DETAILED DESCRIPTION

[0022] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0023] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0024] Embodiment 1 like Figure 1 As shown, a digital-based project management method includes the following steps: Collect Q information nodes, P process nodes and R content nodes of each target employee. The attributes of the Q information nodes include the employee's completion quality, completion time, communication and collaboration ability, department attributes, and outstanding features during the project execution process; the R content nodes include the required essential skills, completion time limit, and completion location; Retrieve the project data set, perform data mapping on Q information nodes, P process nodes, and R content nodes, and obtain Q information node data sets, P process node data sets, and R content node data sets, including: Using employee information data as an index, search the project data set to obtain the employee information data set; Matching the attributes of the Q information nodes with the employee information data set respectively to obtain Q information node data sets, wherein each information node data set includes a grade score of the attribute of each information node; According to the project information data set, P process nodes and R content nodes are matched to obtain P process node data sets and R content node data sets, wherein each process node data set includes project stage data; each content node data set includes content features.

[0025] Based on P process node data sets, Q information node data sets and R content nodes, information overlap analysis is performed on the Q information nodes, the number of information overlaps of each information node and the complexity of information overlap of each overlap are determined, and K-line overlap coefficient analysis is performed to obtain the overlap coefficients of the Q information nodes, where the overlap coefficients of the Q information nodes reflect the overlap of the associated designs of the Q information nodes under multiple process nodes and content nodes, including: Using Q information nodes as indexes, P process node data sets and R content node data sets are searched respectively to obtain Q information overlapping data sets, wherein the information overlapping data in each information overlapping data set has a directional identifier; Determine Q information overlap times and Q information overlap complexity sets based on the Q information overlap data sets; An overlapping coefficient analysis is performed according to the number of times Q information overlaps and the Q information overlapping complexity sets to obtain the overlapping coefficients of the Q information nodes.

[0026] The Q information node overlap coefficients are used as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and the simulation is performed in the order of the project process nodes of the P process node data sets. The information nodes and content nodes are combined to form simulation units, and M simulation units are obtained, wherein each simulation unit has multiple information nodes and content nodes, including: Based on the Q information node overlap coefficients as Q simulation engineering values, the execution simulation of the target employee's completed project is constructed; The simulation is performed in the project process node sequence of the P process node data sets until all contents in the P process node data sets are completed in the project process node sequence; During the execution of the simulation, each process node combines the information node of each target employee and the content node of each project to form K different simulation units, and scores each simulation unit according to the overlapping coefficient of Q information nodes to obtain N execution simulation values.

[0027] Obtaining N different simulation units, the method then further includes: Analyze N different simulation units and N execution simulation values; Determine whether the N executed simulation values ​​are greater than a preset threshold, if not, add the corresponding simulation unit into the simulation unit to be combined; The information of the simulation units to be combined is randomly combined, and N different simulation units are updated according to the combination results to obtain multiple stage combined simulation units.

[0028] A plurality of stage combination simulation units are obtained, and then the method further comprises: Determine whether the execution simulation values ​​of the combined simulation units of multiple stages are less than a preset threshold, and if so, add them into the combined simulation units to be fused; Integrate the combined simulation units to be fused in the simulation units to be fused into the combined simulation units at adjacent stages respectively; After multiple combinations and fusions, when the execution simulation values ​​of the combined simulation units in multiple stages meet the preset threshold, P combined simulation units are obtained.

[0029] The P combined simulation units and their execution simulation values ​​obtained by each target employee are analyzed for data volume to obtain the volume of P combined simulation units, including: According to the P combined simulation units of each target employee and their execution simulation values, data matching is performed on the P combined simulation units to obtain P combined simulation unit data sets; The information entropy of the P combined simulation unit data sets is calculated to obtain P simulation information entropies, and the P simulation information entropies are used as the collective quantity of the P combined simulation unit data.

[0030] Construct P project management sub-units of the target project management unit according to the P simulation unit volumes of each target employee; Project management is performed for each target employee based on P project management sub-units.

[0031] like Figure 2 As shown, a digital project management system includes: The process node collection module is used to collect Q information nodes, P process nodes and R content nodes of each target employee. The attributes of the Q information nodes include the employee's completion quality, completion time, communication and collaboration ability, department attributes, and outstanding features during the project execution process; the R content nodes include the required essential skills, completion time limit, and completion location; The process node data set acquisition module is used to retrieve the project data set, perform data mapping on Q information nodes, P process nodes and R content nodes, and obtain Q information node data sets, P process node data sets and R content node data sets; The overlapping coefficient obtaining module is used to perform information overlapping analysis on the Q information nodes based on the P process node data sets, the Q information node data sets and the R content nodes, determine the number of information overlapping of each information node and the information overlapping complexity of each overlapping, perform K-line overlapping coefficient analysis, and obtain the overlapping coefficients of the Q information nodes, wherein the overlapping coefficients of the Q information nodes reflect the overlapping of the associated designs of the Q information nodes under multiple process nodes and content nodes; A simulation unit acquisition module is used to use the Q information node overlap coefficients as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and perform simulation in the order of project process nodes of P process node data sets, combine information nodes and content nodes to form simulation units, and obtain M simulation units, wherein each simulation unit has multiple information nodes and content nodes; The regional volume acquisition module is used to perform data volume analysis on the P combined simulation units and their execution simulation values ​​obtained by each target employee to obtain the volume of P combined simulation units. A project management subunit acquisition module is used to construct P project management subunits of the target project management unit according to the P simulation unit volumes of each target employee; The project management module is used to perform project management on each target employee based on P project management sub-units.

[0032] Therefore, the present invention adopts the above-mentioned digital-based project management method and system to reasonably arrange the functions of each employee when executing the project to achieve better execution efficiency and execution quality.

[0033] 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, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A digital-based project management method, characterized in that: The following steps are involved: Collect Q information nodes, P process nodes and R content nodes of each target employee, where the attributes of the Q information nodes include the employee's completion quality, completion time, communication and collaboration ability, department attributes, and outstanding features during the project execution; the R content nodes include the required essential skills, completion time limit, and completion location; Retrieving a project data set, performing data mapping on the Q information nodes, the P process nodes, and the R content nodes, and obtaining Q information node data sets, P process node data sets, and R content node data sets; Based on the P process node data sets, the Q information node data sets and the R content nodes, information overlap analysis is performed on the Q information nodes, the number of information overlaps of each information node and the information overlap complexity of each overlap are determined, and K-line overlap coefficient analysis is performed to obtain the overlap coefficients of the Q information nodes, wherein the overlap coefficients of the Q information nodes reflect the overlap of associated designs of the Q information nodes under multiple process nodes and content nodes; Using the Q information node overlap coefficients as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and performing simulation in the order of project process nodes of P process node data sets, combining information nodes and content nodes to form simulation units, and obtaining M simulation units; The P combined simulation units and their execution simulation values ​​obtained by each target employee are analyzed for data volume to obtain the volume of P combined simulation units; Construct P project management sub-units of the target project management unit according to the P simulation unit volumes of each target employee; Project management is performed on each of the target employees based on the P project management subunits.

2. A digital project management method according to claim 1, characterized in that: Retrieving a project data set, performing data mapping on the Q information nodes, P process nodes, and R content nodes, and obtaining Q information node data sets, P process node data sets, and R content node data sets, including: Using the employee information data as an index, searching the project data set to obtain the employee information data set; Matching the employee information data set with the attributes of the Q information nodes respectively to obtain the Q information node data sets, wherein each information node data set includes a grade score of the attribute of each information node; According to the project information data set, P process nodes and R content nodes are matched to obtain P process node data sets and R content node data sets, wherein each process node data set includes project stage data; each content node data set includes content features.

3. A digital project management method according to claim 1, characterized in that: Based on the P process node data sets, the Q information node data sets and the R content nodes, information overlap analysis is performed on the Q information nodes, the number of information overlaps of each information node and the information overlap complexity of each overlap are determined to perform K-line overlap coefficient analysis, and the overlap coefficients of the Q information nodes are obtained, including: Using the Q information nodes as indexes, the P process node data sets and the R content node data sets are searched respectively to obtain Q information overlapping data sets, wherein the information overlapping data in each information overlapping data set has a directional identifier; Determine Q information overlap times and Q information overlap complexity sets based on the Q information overlap data sets; An overlapping coefficient analysis is performed according to the Q information overlapping times and the Q information overlapping complexity sets to obtain the Q information node overlapping coefficients.

4. A digital project management method according to claim 1, characterized in that: The Q information node overlap coefficients are used as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and the simulation is performed in the order of the project process nodes of the P process node data sets, and the information nodes and content nodes are combined to form simulation units to obtain M simulation units, including: Based on the Q information node overlap coefficients as Q simulation project values, construct an execution simulation of the target employee's completed project; The simulation is performed in the project process node sequence of the P process node data sets until all contents in the P process node data sets are completed in the project process node sequence; During the execution of the simulation, each process node combines the information node of each target employee and the content node of each project to form N different simulation units, and scores each simulation unit according to the overlapping coefficient of Q information nodes to obtain N execution simulation values.

5. A digital project management method according to claim 4, characterized in that: Obtaining N different simulation units, the method then further comprises: Analyzing the N different simulation units and the N execution simulation values; Determine whether the N execution simulation values ​​are greater than a preset threshold, and if not, add the corresponding simulation unit into the simulation unit to be combined; Random information combination is performed on the simulation units to be combined, and N different simulation units are updated according to the combination results to obtain multiple stage combined simulation units.

6. A digital project management method according to claim 5, characterized in that: The method further comprises: obtaining a plurality of stage combination simulation units; Determine whether the execution simulation values ​​of the plurality of stage combined simulation units are less than a preset threshold value, and if so, add them into the combined simulation unit to be fused; Integrate the combined simulation units to be fused in the simulation units to be fused into the combined simulation units at adjacent stages respectively; After multiple combinations and fusions, when the execution simulation values ​​of the combined simulation units in multiple stages meet the preset threshold, P combined simulation units are obtained.

7. A digital project management method according to claim 1, characterized in that: Perform data volume analysis on the P combined simulation units and their execution simulation values ​​obtained for each target employee to obtain the volume of the P combined simulation units, including: According to the P combined simulation units of each target employee and their executed simulation values, data matching is performed on the P combined simulation units to obtain P combined simulation unit data sets; Information entropy is calculated for P combined simulation unit data sets to obtain P simulation information entropies, and the P simulation information entropies are used as the P combined simulation unit data set collective quantity.

8. A digital project management system, characterized in that: include The process node collection module is used to collect Q information nodes, P process nodes and R content nodes of each target employee, wherein the attributes of the Q information nodes include the employee's completion quality, completion time, communication and collaboration ability, department attributes, and outstanding features during the project execution process; the R content nodes include the required essential skills, completion time limit, and completion location; A process node data set acquisition module is used to retrieve a project data set, perform data mapping on the Q information nodes, P process nodes and R content nodes, and obtain Q information node data sets, P process node data sets and R content node data sets; An overlapping coefficient obtaining module is used to perform information overlapping analysis on the Q information nodes based on the P process node data sets, the Q information node data sets and the R content nodes, determine the number of information overlapping of each information node and the information overlapping complexity of each overlap to perform K-line overlapping coefficient analysis, and obtain the overlapping coefficients of the Q information nodes, wherein the overlapping coefficients of the Q information nodes reflect the overlapping of the associated designs of the Q information nodes under multiple process nodes and content nodes; a simulation unit obtaining module, for using the Q information node overlap coefficients as Q simulation engineering values ​​to perform simulation on each project node of the target employee, and performing simulation in the order of project process nodes of the P process node data sets, combining information nodes and content nodes to form simulation units, and obtaining M simulation units, wherein each simulation unit has a plurality of information nodes and content nodes; The regional volume acquisition module is used to perform data volume analysis on the P combined simulation units and their execution simulation values ​​obtained for each target employee to obtain the volumes of the P combined simulation units; A project management subunit obtaining module, used to construct P project management subunits of the target project management unit according to the P simulation unit volumes of each target employee; A project management module is used to perform project management on each of the target employees based on the P project management subunits.

Images