Project performance dynamic evaluation and optimization system and method based on full life cycle

Abstract

The invention discloses a project performance dynamic evaluation and optimization system and method based on a full life cycle in the technical field of project management, and the method comprises the steps: collecting multi-source data generated in each stage of the full life cycle of a project, and carrying out the standardization processing, the multi-source data comprising structured data and unstructured text data; taking a project ID as a unique business identifier, performing association fusion on the structured data after standardization processing and text data, and performing quantification processing on the text data to generate a fusion data set containing a numerical index; and based on the fused data set, in combination with the dynamic weight of the current stage determined through the project progress and the role contribution degree coefficient calculated based on the role behavior data, generating a comprehensive performance score of the project by using a preset performance calculation model. According to the invention, by constructing a multi-level closed-loop technical architecture, the limitations of standard stiffness and superficial data utilization in traditional project performance evaluation are broken through.

Description

Technical Field

[0001] This invention relates to a system and method for dynamic evaluation and optimization of project performance based on the entire project lifecycle, belonging to the field of project management technology. Background Technology

[0002] As enterprises deepen their digital transformation, project management models are gradually shifting from traditional offline control to fully online and refined management throughout the entire process. The amount of data generated throughout the project lifecycle is exploding, including structured data such as progress percentages, cost amounts, and quality inspection results, as well as unstructured text data such as customer feedback, quality notes, risk comments, and meeting minutes.

[0003] In existing technologies, project performance evaluation standards lack dynamic adaptation design for different stages, adopt fixed weight templates, and cannot be dynamically adjusted according to the differences in core objectives at each stage of the project life cycle. Furthermore, role contribution lacks quantitative support, and personnel value assessment relies on subjective scoring without objective data support. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a dynamic evaluation and optimization system and method for project performance based on the entire life cycle, which solves the problems of rigid evaluation standards and poor role quantification in the prior art.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0006] Firstly, this invention provides a method for dynamic evaluation and optimization of project performance based on the entire project lifecycle, including:

[0007] After collecting multi-source data generated at each stage of the project's entire lifecycle, standardization processing is performed. The multi-source data includes structured data and unstructured text data.

[0008] Using the project ID as the unique business identifier, the standardized structured data and text data are associated and fused, and the text data is quantified to generate a fused dataset containing numerical indicators.

[0009] Based on the fused dataset, combined with the dynamic weight of the current stage determined by the project progress and the role contribution coefficient calculated based on role behavior data, a project comprehensive performance score is generated using a preset performance calculation model.

[0010] Based on the project's overall performance score, performance dimensions below a preset threshold are selected as bottlenecks, and the root causes of these bottlenecks are traced through an association rule base to generate optimization solutions.

[0011] The optimization scheme is pushed to the corresponding business management system through the system interface, and driven to be transformed into specific business operation instructions for execution.

[0012] The system tracks and records the execution status of the optimization scheme and the project performance data after execution. Based on the tracking results, it calculates review indicators and automatically adjusts the parameters in the performance calculation model according to the comparison results of the review indicators and preset thresholds to optimize subsequent evaluation.

[0013] Furthermore, a comprehensive project performance score is generated, including:

[0014] The weighted total score for each stage dimension is calculated using the weighted scoring formula for that stage dimension. The formula is as follows:

[0015]

[0016] Among them, S dim The total score is calculated by weighting the dimensions for each stage, where k is the number of dimensions involved in the evaluation for the current stage. W represents the average score of the i-th dimension over the past t days. i,s Let represent the weight percentage of the i-th dimension in the current stage s.

[0017] Then, the overall contribution of the role is calculated according to the role contribution quantification formula, which is:

[0018]

[0019] Among them, C role For the overall contribution of the role, D c For the degree of relevance of duties, P c As for the contribution to the process, I r To affect the radiation level;

[0020] The overall project performance score is calculated using the following formula:

[0021]

[0022] Among them, S total S is the overall performance score for the project. dim The total score is weighted according to the stage dimension. This represents the average contribution of all roles in the project.

[0023] Furthermore, when calculating the weighted total score for the stage dimensions, the current stage is automatically identified based on the project progress threshold, and the weights of each dimension under that stage are retrieved from the pre-configured stage weight configuration table.

[0024] Furthermore, the text data is quantified, including: using an algorithm process that includes Chinese word segmentation, keyword matching, sentiment polarity analysis, and standardized scoring to convert the text content into a standardized numerical index of 0-10 points.

[0025] Furthermore, the bottleneck is traced to its root cause through an association rule base, including: mining dimensional relationships in historical data using the Apriori algorithm to construct the association rule base, and using the rule base to match and locate the core root cause of the bottleneck.

[0026] Furthermore, the optimization scheme is pushed to the corresponding business management system through the system interface, including: matching the optimization scheme to the corresponding business module by querying the preset bottleneck-business module mapping table, and generating a structured instruction containing operation steps, responsible roles and time nodes.

[0027] Furthermore, retrospective indicators are calculated based on the tracking results, specifically including:

[0028] The accuracy rate is calculated using the following formula:

[0029]

[0030] In the formula, To assess accuracy, N eff To ensure that the number of items whose scores are improved by at least a preset value after optimization, N total The total number of projects that participated in the review;

[0031] The execution success rate is calculated using the following formula:

[0032]

[0033] In the formula, To optimize the success rate of the solution execution, N comp N represents the number of optimization solutions to be completed as required. plan This represents the total number of optimized solutions generated.

[0034] When assessing accuracy Below 85% or the success rate of the optimization plan When the percentage falls below 70%, adjustments to the parameters in the performance calculation model are automatically triggered.

[0035] Secondly, this invention provides a dynamic evaluation and optimization system for project performance based on the entire lifecycle, including:

[0036] Multi-source data acquisition and processing module: used to collect multi-source data generated at each stage of the project's entire lifecycle and then perform standardized processing. The multi-source data includes structured data and unstructured text data.

[0037] Data fusion and quantification module: Used to associate and fuse the standardized structured data and text data with the project ID as the unique business identifier, and to quantify the text data to generate a fused dataset containing numerical indicators;

[0038] Dynamic evaluation calculation module: Based on the fused dataset, combined with the dynamic weight of the current stage determined by the project progress and the role contribution coefficient calculated based on role behavior data, and using a preset performance calculation model, it generates a comprehensive project performance score.

[0039] Bottleneck identification and optimization generation module: Based on the project's comprehensive performance score, it filters out performance dimensions below a preset threshold as bottlenecks, and uses an association rule base to trace the root causes of the bottlenecks and generate optimization solutions.

[0040] Business linkage execution module: used to push the optimization plan to the corresponding business management system through the system interface, and drive it to be transformed into specific business operation instructions for execution;

[0041] The review and iterative optimization module is used to track and record the execution status of the optimization scheme and the project performance data after execution. Based on the tracking results, it calculates review indicators and automatically adjusts the parameters in the performance calculation model according to the comparison results of the review indicators and preset thresholds to optimize subsequent evaluations.

[0042] Thirdly, the present invention provides a device for dynamic evaluation and optimization of project performance based on the entire life cycle, including a processor and a storage medium;

[0043] The storage medium is used to store instructions;

[0044] The processor is configured to operate according to the instructions to perform the steps of the method according to any of the foregoing.

[0045] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0046] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0047] I. This solution overcomes the limitations of rigid standards and superficial data utilization in traditional project performance evaluation by constructing a multi-level closed-loop technical architecture. Its core advantage lies in introducing a dynamic weight adaptation mechanism for each stage and a deep fusion mechanism of multi-source data. It can automatically adjust the evaluation focus according to the core objectives of each stage of the project lifecycle, and transform traditionally difficult-to-quantify unstructured text data into objective evaluation indicators, thereby achieving a high degree of alignment between evaluation standards and business objectives.

[0048] Second, this solution effectively addresses the pain points of subjective personnel value assessment and ambiguous problem identification by using a role contribution quantification model and a bottleneck root cause intelligent tracing mechanism. The system can quantify role contributions from multiple dimensions based on objective behavioral data and use association rule mining technology to penetrate surface problems and accurately locate the core causes of performance bottlenecks. This provides clear and reliable data support and directional guidance for the formulation of optimization measures, significantly improving the scientific nature and pertinence of management.

[0049] Third, this solution constructs a closed-loop iterative optimization system across the entire chain, realizing a self-circulation from problem identification and solution generation to implementation and feedback. The system can automatically transform optimization suggestions into specific executable business instructions, and through continuous tracking of execution results, drive the self-adjustment and optimization of evaluation model parameters. Ultimately, this enables the system to adapt to dynamic changes in business, ensuring the implementation of optimization suggestions and the sustainability of performance improvement. Attached Figure Description

[0050] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0051] Figure 1 This is a flowchart illustrating the dynamic evaluation and optimization method for project performance based on the entire lifecycle, as provided in Embodiment 1 of the present invention. Detailed Implementation

[0052] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0053] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0054] Example 1:

[0055] Please see Figure 1 This embodiment proposes a dynamic evaluation and optimization method for project performance based on the entire lifecycle. The core process of this embodiment follows a "six-layer closed-loop architecture," from bottom to top: multi-source data acquisition layer, data fusion processing layer, dynamic evaluation calculation layer, bottleneck identification and optimization layer, review and iteration layer, and business linkage layer. Each layer is linked through standardized data interfaces and unified business identifiers to form a fully automated closed loop. Specifically: the multi-source data acquisition layer collects multi-dimensional data throughout the project lifecycle, including structured and unstructured text data; the data fusion processing layer uses the project ID as a unique business identifier to link structured and unstructured text data; the dynamic evaluation calculation layer integrates multi-source fused data and performs comprehensive calculations based on stage weights and role contributions; the bottleneck identification and optimization layer filters low-scoring dimensions based on evaluation results and locates the core root causes of bottlenecks through an association rule base; the review and iteration layer tracks the execution effect of optimization solutions, calculates review indicators, and triggers automatic parameter adjustments; the business linkage layer pushes the optimization solutions to the business modules of the project management system for implementation. The specific execution steps of this solution are as follows:

[0056] S1. The multi-source data acquisition and standardization process begins at the multi-source data acquisition layer. First, the potential data acquisition module collects raw data generated throughout the entire project lifecycle (opportunities, pre-sales, implementation, and closure stages). Then, the raw data flows into the data standardization module for cleaning, deduplication, and formatting. The processed standard data is stored in the data storage module, preparing for subsequent integration.

[0057] S2. Multi-source data fusion and quantification occur at the data fusion processing layer. The data fusion processing module uses the project ID as a unique business identifier to extract and associate structured and unstructured text data from the storage module. For text data, the text quantification module converts it into numerical indicators using an algorithm of "Chinese word segmentation - keyword matching - sentiment polarity analysis - standardized scoring". Finally, the fusion quality verification module performs quality verification on the fused dataset to ensure data integrity and consistency before outputting it to the evaluation layer.

[0058] In this embodiment, the system employs a four-level algorithm—Chinese word segmentation, keyword matching, sentiment polarity analysis, and standardized scoring—to convert customer feedback text into a standardized score of 0-10. Simultaneously, the system uses the project ID as a unique identifier to link structured and unstructured text data, and removes outliers using the 3σ principle.

[0059] S3. Dynamic Performance Evaluation Calculation occurs at the dynamic evaluation calculation layer. The dynamic evaluation calculation module receives the fused data, initiates the evaluation calculation, and simultaneously invokes the dynamic weights for the current stage provided by the stage weight adaptation module, as well as the role contribution coefficients provided by the role contribution quantification module. The evaluation calculation is based on the stage dimension weighted scoring formula, the role contribution quantification formula, and the project comprehensive performance score formula. Finally, the performance evaluation result module generates the project comprehensive performance score. Wherein:

[0060] The weighted score formula for each stage dimension is:

[0061]

[0062] Among them, S dim The total score is calculated by weighting the dimensions for each stage, where k is the number of dimensions involved in the evaluation for the current stage. W represents the average score of the i-th dimension over the past t days. i,s Let be the weight percentage of the i-th dimension in the current stage s.

[0063] The formula for quantifying role contribution is:

[0064]

[0065] Among them, C role For the overall contribution of the role, D c For the degree of relevance of duties, P c As for the contribution to the process, I r To affect the radiation level.

[0066] The formula for the project's overall performance score is:

[0067]

[0068] Among them, S total S is the overall performance score for the project. dim The total score is weighted according to the stage dimension. This represents the average contribution of all roles in the project.

[0069] In this embodiment, during the weight adaptation stage, the system uses an automatic stage identification engine to determine the current stage based on the project progress threshold (e.g., progress <10% is the opportunity stage). Then, it retrieves the corresponding stage's dimension weights from the stage weight configuration table (stage_weight_config) and calculates the stage dimension weighted score by combining the average dimension scores over the past 30 days. In the contribution calculation stage, the system extracts data on role completion, process participation, and decision impact from the project management system, calculates responsibility correlation, process contribution, and impact radiation, and couples these into a comprehensive contribution score using weights (0.4:0.3:0.3).

[0070] It should be noted that in the dynamic performance evaluation calculation process, this scheme calculates the convergence degree of the stage goal to quantify the degree to which the current stage execution status approaches the final success of the project. Its value is derived by multiplying the weighted sum of the completion rates of key indicators within the stage, calibrated by the stage environmental complexity coefficient, by the deviation attenuation factor between the current status and the final success goal. The expression is as follows:

[0071]

[0072] In the formula, SGP s The value represents the project's closeness to its current stage goal (s). The closer this value is to 1, the better the project is performing in this stage. m represents the total number of key performance indicators (KPIs) in the current stage. P j,s The standardized score for the completion of the key performance indicator of stage j in the current stage s; I j,s Let E be the weight of the key performance indicator (KPI) of the j-th stage on the final project success. This value is a fixed weight derived from historical successful project data mining. s This represents the stage's environmental complexity coefficient, which is greater than 1 and is dynamically adjusted by the system based on the objective difficulty of the current stage; D s The deviation between the current state and the final goal is calculated by comparing the key data of the current project with the benchmark values ​​of historical successful projects at the same stage, using cosine similarity or Euclidean distance. The greater the deviation, the larger the value. max This is a preset maximum allowable deviation threshold used for D. s Normalization is performed.

[0073] S4. Performance Bottleneck Identification and Optimization Solution Generation: Based on the evaluation results, the process enters the bottleneck identification and optimization layer. The bottleneck identification module first filters out performance dimensions with scores below the threshold. Next, the root cause tracing module locates the core root cause of the bottleneck based on the association rule base. Subsequently, the optimization solution generation module generates preliminary optimization suggestions based on the root cause. The role assignment module assigns a clear responsible person to each suggestion. Finally, the optimization execution push module outputs a structured, fully accountable optimization solution.

[0074] In this embodiment, during the root cause tracing stage, the system sets association rules for each stage dimension through an association rule base, combines the Apriori algorithm to mine hidden relationships in historical data, verifies association conditions, and matches the core root cause.

[0075] S5. Optimization Solution Business Linkage and Implementation at the Business Linkage Layer. The business operation implementation module receives the optimization solution and automatically converts it into specific work orders, tasks, or process instructions in the project management system (such as PMO, CRM, delivery system) through the system API, driving actual operations and achieving closed-loop execution of optimization measures.

[0076] In this embodiment, the system matches the business modules corresponding to the optimization scheme through the bottleneck-business module mapping table, generates a structured scheme containing operation steps, responsible roles, and time nodes, and pushes it to the project management system through the API interface.

[0077] S6. Execution Effect Review and System Iteration: After the implementation of the plan, the process enters the review and iteration layer. The execution effect tracking module continuously monitors the execution status and business results of the plan. The review indicator calculation module calculates the "evaluation accuracy" and "execution success rate" based on the tracking data and the review formulas for evaluation accuracy and execution success rate. The iteration adjustment module judges the review indicators: if the indicator does not reach the preset threshold (e.g., accuracy < 85%), an adjustment instruction is triggered. The parameter configuration update module responds to the instruction and automatically adjusts the weights, rules, and other parameters in the evaluation model. The updated parameters will directly affect the calculation of the dynamic evaluation calculation module in the next cycle's S3 step, thereby achieving adaptive closed-loop optimization of the system. Specifically:

[0078] The formula for evaluating accuracy and execution success rate is as follows:

[0079] Assessment accuracy:

[0080] Execution success rate:

[0081] in, To assess accuracy, N eff To ensure that the number of items whose scores are improved by at least a preset value after optimization, N total The total number of projects participating in the review. To optimize the success rate of the solution execution, N comp N represents the number of optimization solutions to be completed as required. plan This represents the total number of optimized solutions generated.

[0082] In this embodiment, the system calculates the evaluation accuracy and execution success rate by tracking the execution status and score improvement value of the optimization scheme. When the evaluation accuracy is lower than 85% or the execution success rate is lower than 70%, the parameter adjustment engine is automatically triggered.

[0083] In summary, through the above technical solutions, this embodiment achieves full lifecycle coverage of project performance evaluation, multi-source data fusion, role value quantification, bottleneck root cause tracing, closed-loop iterative optimization, and business implementation, effectively solving the shortcomings of existing technologies.

[0084] Example 2:

[0085] The project performance dynamic evaluation and optimization system based on the entire life cycle can implement the project performance dynamic evaluation and optimization method based on the entire life cycle described in Example 1, including:

[0086] Multi-source data acquisition and processing module: used to collect multi-source data generated at each stage of the project's entire lifecycle and then perform standardized processing. The multi-source data includes structured data and unstructured text data.

[0087] Data fusion and quantification module: Used to associate and fuse the standardized structured data and text data with the project ID as the unique business identifier, and to quantify the text data to generate a fused dataset containing numerical indicators;

[0088] Dynamic evaluation calculation module: Based on the fused dataset, combined with the dynamic weight of the current stage determined by the project progress and the role contribution coefficient calculated based on role behavior data, and using a preset performance calculation model, it generates a comprehensive project performance score.

[0089] Bottleneck identification and optimization generation module: Based on the project's comprehensive performance score, it filters out performance dimensions below a preset threshold as bottlenecks, and uses an association rule base to trace the root causes of the bottlenecks and generate optimization solutions.

[0090] Business linkage execution module: used to push the optimization plan to the corresponding business management system through the system interface, and drive it to be transformed into specific business operation instructions for execution;

[0091] The review and iterative optimization module is used to track and record the execution status of the optimization scheme and the project performance data after execution. Based on the tracking results, it calculates review indicators and automatically adjusts the parameters in the performance calculation model according to the comparison results of the review indicators and preset thresholds to optimize subsequent evaluations.

[0092] Example 3:

[0093] This invention also provides a device for dynamic evaluation and optimization of project performance based on the entire life cycle, which can realize the method for dynamic evaluation and optimization of project performance based on the entire life cycle described in Embodiment 1, including a processor and a storage medium;

[0094] The storage medium is used to store instructions;

[0095] The processor is configured to operate according to the instructions to perform the steps of the following method:

[0096] After collecting multi-source data generated at each stage of the project's entire lifecycle, standardization processing is performed. The multi-source data includes structured data and unstructured text data.

[0097] Using the project ID as the unique business identifier, the standardized structured data and text data are associated and fused, and the text data is quantified to generate a fused dataset containing numerical indicators.

[0098] Based on the fused dataset, combined with the dynamic weight of the current stage determined by the project progress and the role contribution coefficient calculated based on role behavior data, a project comprehensive performance score is generated using a preset performance calculation model.

[0099] Based on the project's overall performance score, performance dimensions below a preset threshold are selected as bottlenecks, and the root causes of these bottlenecks are traced through an association rule base to generate optimization solutions.

[0100] The optimization scheme is pushed to the corresponding business management system through the system interface, and driven to be transformed into specific business operation instructions for execution.

[0101] The system tracks and records the execution status of the optimization scheme and the project performance data after execution. Based on the tracking results, it calculates review indicators and automatically adjusts the parameters in the performance calculation model according to the comparison results of the review indicators and preset thresholds to optimize subsequent evaluation.

[0102] Example 4:

[0103] This invention also provides a computer-readable storage medium that can implement the dynamic evaluation and optimization method for project performance based on the entire life cycle as described in Embodiment 1. The medium stores a computer program that, when executed by a processor, performs the steps of the following method:

[0104] After collecting multi-source data generated at each stage of the project's entire lifecycle, standardization processing is performed. The multi-source data includes structured data and unstructured text data.

[0105] Using the project ID as the unique business identifier, the standardized structured data and text data are associated and fused, and the text data is quantified to generate a fused dataset containing numerical indicators.

[0106] Based on the fused dataset, combined with the dynamic weight of the current stage determined by the project progress and the role contribution coefficient calculated based on role behavior data, a project comprehensive performance score is generated using a preset performance calculation model.

[0107] Based on the project's overall performance score, performance dimensions below a preset threshold are selected as bottlenecks, and the root causes of these bottlenecks are traced through an association rule base to generate optimization solutions.

[0108] The optimization scheme is pushed to the corresponding business management system through the system interface, and driven to be transformed into specific business operation instructions for execution.

[0109] The system tracks and records the execution status of the optimization scheme and the project performance data after execution. Based on the tracking results, it calculates review indicators and automatically adjusts the parameters in the performance calculation model according to the comparison results of the review indicators and preset thresholds to optimize subsequent evaluation.

[0110] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative and not exhaustive. All modifications within the scope of this invention or its equivalents are included in this invention.

[0111] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0113] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0114] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A project performance dynamic evaluation and optimization method based on the entire life cycle, characterized by: include: After collecting multi-source data generated at each stage of the project's entire lifecycle, standardization processing is performed. The multi-source data includes structured data and unstructured text data. Using the project ID as the unique business identifier, the standardized structured data and text data are associated and fused, and the text data is quantified to generate a fused dataset containing numerical indicators. Based on the fused dataset, combined with the dynamic weight of the current stage determined by the project progress and the role contribution coefficient calculated based on role behavior data, a project comprehensive performance score is generated using a preset performance calculation model. Based on the project's overall performance score, performance dimensions below a preset threshold are selected as bottlenecks, and the root causes of these bottlenecks are traced through an association rule base to generate optimization solutions. The optimization scheme is pushed to the corresponding business management system through the system interface, and driven to be transformed into specific business operation instructions for execution. The system tracks and records the execution status of the optimization scheme and the project performance data after execution. Based on the tracking results, it calculates review indicators and automatically adjusts the parameters in the performance calculation model according to the comparison results of the review indicators and preset thresholds to optimize subsequent evaluation.

2. The method for dynamic evaluation and optimization of project performance based on the entire life cycle as described in claim 1, characterized in that, Generate a comprehensive project performance score, including: The weighted total score for each stage dimension is calculated using the weighted scoring formula for that stage dimension. The formula is as follows: ； Among them, S dim The total score is calculated by weighting the dimensions for each stage, where k is the number of dimensions involved in the evaluation for the current stage. W represents the average score of the i-th dimension over the past t days. i,s Let represent the weight percentage of the i-th dimension in the current stage s. Then, the overall contribution of the role is calculated according to the role contribution quantification formula, which is: ； Among them, C role For the overall contribution of the role, D c For the degree of relevance of duties, P c As for the contribution to the process, I r To affect the radiation level; The overall project performance score is calculated using the following formula: ； Among them, S total S is the overall performance score for the project. dim The total score is weighted according to the stage dimension. This represents the average contribution of all roles in the project.

3. The method for dynamic evaluation and optimization of project performance based on the entire life cycle as described in claim 2, characterized in that, When calculating the weighted total score for the stage dimensions, the current stage is automatically identified based on the project progress threshold, and the weights of each dimension under that stage are retrieved from the pre-configured stage weight configuration table.

4. The method for dynamic evaluation and optimization of project performance based on the entire life cycle as described in claim 1, characterized in that, The text data is quantified, including: using an algorithm process that includes Chinese word segmentation, keyword matching, sentiment polarity analysis and standardized scoring to convert the text content into a standardized numerical index of 0-10.

5. The method for dynamic evaluation and optimization of project performance based on the entire life cycle as described in claim 1, characterized in that, The bottleneck is traced back to its root cause by using an association rule base, including: mining dimensional relationships in historical data using the Apriori algorithm to construct the association rule base, and using the rule base to match and locate the core root cause of the bottleneck.

6. The method for dynamic evaluation and optimization of project performance based on the entire life cycle as described in claim 1, characterized in that, The optimization scheme is pushed to the corresponding business management system through the system interface, including: matching the optimization scheme to the corresponding business module by querying the preset bottleneck-business module mapping table, and generating a structured instruction containing operation steps, responsible roles and time nodes.

7. The method for dynamic evaluation and optimization of project performance based on the entire life cycle as described in claim 1, characterized in that, The retrospective indicators are calculated based on the tracking results, specifically including: The accuracy rate is calculated using the following formula: ； In the formula, To assess accuracy, N eff To ensure that the number of items whose scores are improved by at least a preset value after optimization, N total The total number of projects that participated in the review; The execution success rate is calculated using the following formula: ； In the formula, To optimize the success rate of the solution execution, N comp N represents the number of optimization solutions completed as required. plan This represents the total number of optimized solutions generated. When assessing accuracy Below 85% or the success rate of the optimization plan When the percentage falls below 70%, adjustments to the parameters in the performance calculation model are automatically triggered.

8. A project performance dynamic evaluation and optimization system based on the entire life cycle, characterized by: include: Multi-source data acquisition and processing module: used to collect multi-source data generated at each stage of the project's entire lifecycle and then perform standardized processing. The multi-source data includes structured data and unstructured text data. Data fusion and quantification module: Used to associate and fuse the standardized structured data and text data with the project ID as the unique business identifier, and to quantify the text data to generate a fused dataset containing numerical indicators; Dynamic evaluation calculation module: Based on the fused dataset, combined with the dynamic weight of the current stage determined by the project progress and the role contribution coefficient calculated based on role behavior data, and using a preset performance calculation model, it generates a comprehensive project performance score. Bottleneck identification and optimization generation module: Based on the project's comprehensive performance score, it filters out performance dimensions below a preset threshold as bottlenecks, and uses an association rule base to trace the root causes of the bottlenecks and generate optimization solutions. Business linkage execution module: used to push the optimization plan to the corresponding business management system through the system interface, and drive it to be transformed into specific business operation instructions for execution; The review and iterative optimization module is used to track and record the execution status of the optimization scheme and the project performance data after execution. Based on the tracking results, it calculates review indicators and automatically adjusts the parameters in the performance calculation model according to the comparison results of the review indicators and preset thresholds to optimize subsequent evaluation.

9. A dynamic evaluation and optimization device for project performance based on the entire life cycle, characterized in that: Including processor and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1 to 7.

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