A digital government informatization project whole life cycle quantitative management method and system

Abstract

The application relates to the technical field of project management, and provides a digital government informatization project full-life-cycle quantitative management method, which calculates an initial software cost of a project through a function point analysis and a cost estimation model, dynamically corrects the initial software cost of the project based on a demand change factor, and obtains real-time software cost of the project; based on a critical path method and a gradient boosting tree, the total construction period of a target digital government informatization project and key nodes of each stage are predicted; a performance index system of the whole stage of construction, operation and maintenance and retirement is constructed, and a project full-life-cycle performance comprehensive score is generated through a weighted summation calculation mode; based on a data center, cost, construction period and performance data of the whole process of the project are gathered, correlation analyzed and traceably stored, and data display and early warning prompt are realized through a visual module. The application improves the cost estimation accuracy, the construction period prediction accuracy and the performance evaluation accuracy, and the project management efficiency.

Description

Technical Field

[0001] This invention relates to the field of project management technology, and in particular to a method and system for quantitative management of the entire lifecycle of digital government information projects. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] The construction of digital government is the core of promoting the modernization of the national governance system and governance capabilities, and an important support for the implementation of the national digital strategy. With the continuous advancement of digital reform, governments at all levels are increasing their efforts in information technology construction. Digital government information technology projects are showing a development trend of increasing number of projects, expanding business coverage, increasing system architecture complexity, and enhanced cross-departmental collaboration. Digital government information technology projects have high requirements for accuracy and efficiency, which puts forward higher requirements for accurate calculation or prediction of costs, cycles, and performance throughout the project life cycle, as well as efficient management.

[0004] Currently, in the early cost assessment stage of digital government information projects, most cost estimates are based on static estimation models, resulting in significant discrepancies between the estimated and actual costs. In the project construction and implementation stage, the focus is on static task dependencies, neglecting key characteristics such as changes in requirements and the complexity of cross-departmental collaboration, leading to inaccurate project cycle predictions. In the project performance evaluation stage, there are issues with incomplete performance evaluation processes and inaccurate performance evaluation results. Summary of the Invention

[0005] To overcome the shortcomings of the existing technologies, this invention provides a method and system for quantitative management of the entire lifecycle of digital government information projects, aiming to solve the problems of inaccurate project cost assessment, low accuracy of project cycle prediction, low accuracy of project performance calculation, and low efficiency of project lifecycle management in the existing technologies.

[0006] To achieve the above objectives, the technical solution provided by the present invention is as follows: In a first aspect, the present invention provides a method for quantitative management of the entire lifecycle of digital government information projects, including: Obtain the requirements document, historical project data and personnel configuration information of the target digital government informatization project, and use function point analysis and cost estimation models to calculate the initial software cost of the project. Obtain the requirement change records for the current stage of the project, dynamically adjust the initial software cost of the project based on the requirement change factors, and obtain the real-time software cost of the project. Predict the total duration and key milestones of each stage of the target digital government informatization project based on the critical path method and gradient boosting tree; Construct a performance indicator system covering all stages of project initiation, construction, operation and maintenance, and decommissioning, and generate a comprehensive performance score for the entire project lifecycle through a weighted summation calculation method; Based on the data platform, cost, schedule, and performance data of the entire project process are aggregated, correlated, analyzed, and stored traceably, and the data is displayed and alerted through the visualization module.

[0007] As a further technical solution, the function point analysis specifically involves counting the five categories of function points in the requirements document: input data, output data, query operations, internal files, and external interfaces, to obtain the total number of function points.

[0008] As a further technical solution, the cost estimation model is the COCOMO II model, and the cost estimation model calculates the initial software cost of the project as follows: Input the total number of function points into the COCOMO II model, and combine it with complexity coefficients, technology stack coefficients, team capability coefficients, and government project-specific correction coefficients to calculate the initial software cost of the project, expressed as: ; in, This indicates the initial software cost of the project. Indicates the total number of function points. Indicates the complexity coefficient. Represents the technology stack coefficient. This represents the team's capability coefficient. This indicates a correction factor specific to government projects.

[0009] As a further technical solution, the requirement change factor includes change frequency, change scale, and change impact scope, expressed as follows: ; in, Indicates the demand change factor. Indicates the frequency of change. Indicates a change in scale. Indicates the scope of the change. , , This represents the weighting coefficient.

[0010] As a further technical solution, the critical path method specifically involves: adopting a work breakdown structure to decompose the target digital government informatization project into tasks such as project preparation, requirements analysis, system design, development and coding, integration and testing, online trial operation and acceptance interaction, and clarifying the duration, task dependencies, prerequisite tasks and successor tasks of each task. The earliest start time, earliest finish time, latest start time, and latest finish time of each task are calculated based on the critical path method to determine the critical path and critical nodes of the project. The critical path is the sequence of tasks with the longest total duration.

[0011] As a further technical solution, gradient boosting trees predict the total project duration and key milestones at each stage of the target digital government informatization project, specifically: The gradient boosting tree predicts the total duration and key milestones of the target digital government information project based on project type, technical architecture, number of developers, total number of functional points, frequency of requirement changes, and average duration of similar historical projects. The key milestones include the completion time of requirement analysis, system design, development and coding, online trial operation, and acceptance and delivery.

[0012] As a further technical solution, a performance indicator system is constructed for the entire process of project initiation, construction, operation and maintenance, and decommissioning. Specifically, the project initiation stage includes budget deviation rate and feasibility analysis pass rate; the construction stage includes schedule deviation rate, code defect rate, security vulnerability remediation completion rate, and requirement completion rate; the operation and maintenance stage includes system availability, service response time, user satisfaction, and operation and maintenance cost ratio; and the decommissioning stage includes data archiving integrity and asset recovery rate.

[0013] Secondly, this invention provides a quantitative management system for the entire lifecycle of digital government information projects, comprising: Cost Measurement Module: Used to obtain the requirements documents, historical project data and personnel configuration information of the target digital government informatization project, and to calculate the initial software cost of the project using function point analysis and cost estimation models; Obtain the requirement change records for the current stage of the project, dynamically adjust the initial software cost of the project based on the requirement change factors, and obtain the real-time software cost of the project. Cycle prediction module: used to predict the total duration and key milestones of each stage of the target digital government information project based on the critical path method and gradient boosting tree; Performance evaluation module: Used to build a performance indicator system for the entire project lifecycle, including project initiation, construction, operation and maintenance and decommissioning, and to generate a comprehensive performance score for the entire project lifecycle through a weighted summation calculation method; Data Platform Module: This module is used to aggregate, analyze, and traceably store cost, schedule, and performance data across the entire project process, and to display and provide early warnings through a visualization module.

[0014] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for quantitative management of the entire lifecycle of a digital government information project as described in the first aspect above.

[0015] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for quantitative management of the entire lifecycle of a digital government information project as described in the first aspect above.

[0016] As can be seen from the above technical solutions, the present invention has the following beneficial effects: Cost control dimension: Function point analysis is used to quantify the project development scale. The initial cost calculation is completed by combining the COCOMO II model adapted to government scenarios. At the same time, a demand change factor including change frequency, change scale, and impact scope is constructed to dynamically iterate and correct the cost. This can output the actual cost of the project in real time, greatly reduce the cost deviation caused by static estimation, identify cost risks in advance, and significantly reduce the probability of budget overruns in digital government projects.

[0017] Project duration prediction dimension: It integrates the Critical Path Method (CPM) to break down the entire project process tasks and lock in key schedule constraints. At the same time, it introduces a gradient boosting tree machine learning model, taking into account the characteristics of government projects in multiple dimensions such as project function scale, requirement change characteristics, team, architecture, etc., as model inputs. It takes into account both static engineering constraints and dynamic business changes, effectively improving the prediction accuracy of the total project duration and key nodes at each stage, and reducing project delays.

[0018] Performance evaluation dimensions: Breaking away from the limitations of traditional IT projects that only assess the project initiation and construction phases, we have constructed an evaluation framework covering the entire lifecycle of project initiation, construction, operation and maintenance, and decommissioning. We have built a quantitative indicator library around six dimensions: cost-effectiveness, schedule compliance, service quality, security compliance, user experience, and asset disposal. Through weighted algorithms, we output standardized comprehensive performance scores, achieving objective quantitative evaluation of the entire project lifecycle and multiple dimensions, thereby improving the completeness and accuracy of performance evaluation.

[0019] Data governance and comprehensive management dimension: Build a data platform adapted to government scenarios, adopt a multi-type hybrid storage architecture to aggregate and uniformly manage cost, schedule, and performance data throughout the entire process, establish a three-dimensional correlation model to achieve multi-indicator linkage analysis, rely on unique data identifiers to achieve full-process operation log traceability, and provide a supporting visualization module to automatically generate multi-dimensional analysis charts and push early warning information for indicators exceeding the standard, unify project data standards, simplify manual statistical workload, comprehensively improve the efficiency of refined and integrated management of digital government informatization projects, and at the same time meet the requirements of government project auditing, security and compliance retention. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating a method for quantitative management of the entire lifecycle of digital government information projects, as provided in Embodiment 1 of the present invention. Figure 2 This is a schematic diagram of the architecture of a quantitative management system for the entire lifecycle of digital government information projects, provided in Embodiment 2 of the present invention. Detailed Implementation

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0024] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0025] Example 1 like Figure 1 As shown in the figure, this embodiment provides a method for quantitative management of the entire lifecycle of digital government information projects, including: Obtain the requirements document, historical project data and personnel configuration information of the target digital government informatization project, and use function point analysis and cost estimation models to calculate the initial software cost of the project. Obtain the requirement change records for the current stage of the project, dynamically adjust the initial software cost of the project based on the requirement change factors, and obtain the real-time software cost of the project. Predict the total duration and key milestones of each stage of the target digital government informatization project based on the critical path method and gradient boosting tree; Construct a performance indicator system covering all stages of project initiation, construction, operation and maintenance, and decommissioning, and generate a comprehensive performance score for the entire project lifecycle through a weighted summation calculation method; Based on the data platform, cost, schedule, and performance data of the entire project process are aggregated, correlated, analyzed, and stored traceably, and the data is displayed and alerted through the visualization module.

[0026] The following content provides a more detailed introduction to the quantitative management method for the entire lifecycle of digital government information projects provided in this embodiment.

[0027] In step 1, the requirements document, historical project data, and personnel configuration information of the target digital government informatization project are obtained, and the initial software cost of the project is calculated using function point analysis and cost estimation models.

[0028] In one specific implementation, Function Point Analysis (FPA) involves counting the five categories of function points in the requirements document: input data, output data, query operations, internal files, and external interfaces, to obtain the total number of function points.

[0029] Specifically, the data input function includes 320 functions such as statistics on user-submitted items and data entry. Output data functions: 280 functions including query results and electronic certificates returned to users by the statistics system; Query operation functions: statistical multi-condition data retrieval, historical record query, etc., totaling 350 functions; Internal document functions include: statistical government data storage, configuration file management, etc., totaling 150 functions. External interface functionalities: statistical cross-departmental data sharing, third-party service integration, etc., totaling 100; The total number of function points is 320+280+350+150+100=1200.

[0030] Furthermore, the requirements document includes project functional requirements, non-functional requirements, interface requirements, etc. In one specific implementation, the cost estimation model is the COCOMO II model, and the cost estimation model calculates the initial software cost of the project as follows: Input the total number of function points into the COCOMO II model, and combine it with complexity coefficients, technology stack coefficients, team capability coefficients, and government project-specific correction coefficients to calculate the initial software cost of the project, expressed as: ; in, This indicates the initial software cost of the project. Indicates the total number of function points. Indicates the complexity coefficient. Represents the technology stack coefficient. This represents the team's capability coefficient. This indicates a correction factor specific to government projects.

[0031] Furthermore, the complexity coefficient C is graded according to the business complexity, data volume, and cross-departmental collaboration complexity of government projects, and is divided into three levels: simple, medium, and complex. The simple level C=0.8, the medium level C=1.0, and the complex level C=1.2.

[0032] The technology stack coefficient T is configured according to the type of technology architecture adopted by the project: monolithic architecture T=1.1, microservice architecture T=1.0, and cloud-native architecture T=0.9.

[0033] The team capability coefficient D is configured based on the project team's development experience and experience in implementing government projects. The coefficient is 1.2 for junior teams, 1.0 for intermediate teams, and 0.8 for senior teams.

[0034] Government Project-Specific Correction Coefficient The value range is 1.05-1.3, depending on the project's compliance requirements and security level configuration.

[0035] For example, with a total of 1200 functionalities, a complexity coefficient C=1.0 (medium complexity, involving multi-department collaboration); a technology stack coefficient T=1.0 (microservice architecture); a team capability coefficient D=1.0 (intermediate development team with experience in government project implementation); a government-specific cost adjustment coefficient K=1.1 (meeting Level 3 compliance requirements); and a unit price of 0.6 million yuan for each functionality, calculate the initial software cost of the project: =1200×1.0×1.0×1.0×1.1×0.6=7.92 million yuan.

[0036] In step 2, the requirement change records for the current stage of the project are obtained, and the initial software cost of the project is dynamically adjusted based on the requirement change factors to obtain the real-time software cost of the project.

[0037] In one specific implementation, the demand change factors include change frequency, change scale, and change impact scope, expressed as: ; in, Indicates the demand change factor. Indicates the frequency of change. Indicates a change in scale. Indicates the scope of the change. , , This represents the weighting coefficient.

[0038] For example, when collecting records of requirement changes during project construction, if the change frequency f=0.2 (2 changes per month), the change scale percentage s=0.1 (120 functional points changed), and the change impact scope coefficient r=0.3 (affecting core matters of application); assuming weighting coefficients λ1=0.3, λ2=0.4, and λ3=0.3, then the requirement change factor... 1 + 0.3 × 0.2 + 0.4 × 0.1 + 0.3 × 0.3 = 1.19; The initial software cost of the project was dynamically adjusted to obtain the real-time software cost of the project, which is C = 792 × 1.19 = 9,424,800 yuan.

[0039] Furthermore, weighting coefficients , , Configure according to the type of government service project, such as a government service platform project. Regulatory enforcement system project .

[0040] Change frequency This is the ratio of the number of requirement changes in the current phase of the project to the duration of the project phase; the scale of the change. The ratio of the number of changed function points to the total number of function points; the change impact range coefficient. The impact on a single core module is determined based on the scope of business affected by the change and the number of system modules. Affecting multiple core modules Impact on cross-departmental operations .

[0041] The real-time software cost for the project is: ; when When this indicates that a change in demand has led to an increase in costs, This indicates that demand optimization leads to cost reduction.

[0042] Meanwhile, the cost deviation rate can be calculated as follows: ; The cost per function point is: ; To enhance cost risk identification capabilities, a comprehensive cost risk coefficient is introduced to quantitatively integrate the impact of multiple factors.

[0043] in, This refers to the overall cost and risk coefficient. For demand change factors; Cost deviation rate; This represents the model prediction uncertainty, with a value ranging from 0 to 1.

[0044] The aforementioned cost deviation rate, unit function point cost, and comprehensive cost risk coefficient are all derived evaluation indicators further derived from the real-time cost C. First, the real-time cost value is calculated, and then deviation analysis, cost benchmarking, and risk level determination are conducted based on the real-time cost. The calculation results of the derived indicators are simultaneously sent to the performance evaluation module and data platform of this invention as input parameters for project performance scoring and cost anomaly early warning, providing comprehensive services for the quantitative management of the entire lifecycle of digital government projects.

[0045] Among them, the cost deviation rate CostDev relies on the real-time cost C and the initial cost. By comparing the differences, the cost fluctuation caused by changes in requirements is quantified, and the deviation of real-time costs from the budget is clearly reflected, serving as a fundamental indicator for judging whether costs are abnormal. The cost per function point (FPCost) is calculated by dividing the real-time total cost (C) by the project's functional scale (FP) to obtain the current cost per function point. Managers can use this indicator to assess whether the real-time cost is within a reasonable range for the industry. The overall cost risk coefficient... Demand change factor The calculation of cost deviation rate (CostDev) and model uncertainty is integrated, extending the simple numerical calculation of cost to the quantitative assessment of cost risk.

[0046] In step 3, the total duration and key nodes of each stage of the target digital government informatization project are predicted based on the critical path method and gradient boosting tree.

[0047] In one specific implementation, the critical path method is as follows: using a work breakdown structure, the target digital government informatization project is decomposed into tasks such as project preparation, requirements analysis, system design, development and coding, integration testing, online trial operation and acceptance interaction, and the duration, task dependencies, prerequisite tasks and successor tasks of each task are clearly defined. The Critical Path Method (CPM) is used to calculate the earliest start time, earliest finish time, latest start time, and latest finish time for each task, thereby determining the critical path and critical nodes of the project. The critical path is the sequence of tasks with the longest total duration.

[0048] In one specific implementation, gradient boosting trees predict the total duration and key milestones of each stage of a target digital government information project, specifically as follows: Gradient Boosting Tree (GBDT) uses information available during the project initiation phase as input features, including project type, technical architecture, number of developers, total number of functional points, frequency of requirement changes, and average duration of similar historical projects. It predicts the total duration and key milestones for each stage of the target digital government IT project. Key milestones include the completion time of requirements analysis, system design, development and coding, deployment and trial operation, and acceptance and delivery. Project type and technical architecture are basic information within the project initiation application materials. These can be extracted and entered into the system simultaneously with functional point statistics and cost calculations from the project initiation plan and feasibility study report, and are collected concurrently with data related to the total number of functional points and requirement changes.

[0049] Understandably, a gradient boosting tree is a trained gradient boosting tree algorithm that takes the features of the training set as input and the actual construction period as output to train the gradient boosting tree; then, it takes the test set as input and the actual construction period as output to obtain the test results. When the prediction deviation rate is lower than a set threshold, the gradient boosting tree training is complete; the input features of the project cycle to be predicted are input into the gradient boosting tree to output the total construction period of the project and the key nodes of each stage.

[0050] Specifically, the periodic prediction deviation rate is expressed as: ; in, For the periodic prediction deviation rate, To predict the construction period, This refers to the actual construction period.

[0051] Assuming a total project duration of 182 days, with 10 days for project initiation, 30 days for requirements analysis, 30 days for system design, 60 days for development and coding, 30 days for integration and testing, 20 days for trial operation, and 2 days for acceptance and delivery, then the key milestones are: 10 days for project initiation, 40 days for requirements analysis, 70 days for system design, 130 days for development and coding, 160 days for integration and testing, 180 days for trial operation, and 182 days for acceptance and delivery.

[0052] In step 4, as shown in Table 1, a performance indicator system is constructed for the entire project lifecycle, including project initiation, construction, operation and maintenance, and decommissioning. A comprehensive performance score for the entire project lifecycle is generated through a weighted summation calculation method.

[0053] In one specific implementation, a performance indicator system is constructed for the entire process of project initiation, construction, operation and maintenance, and decommissioning. Specifically, the project initiation stage includes budget deviation rate and feasibility analysis pass rate; the construction stage includes schedule deviation rate, code defect rate, security vulnerability remediation completion rate, and requirement completion rate; the operation and maintenance stage includes system availability, service response time, user satisfaction, and operation and maintenance cost ratio; and the decommissioning stage includes data archiving integrity and asset recovery rate.

[0054] Specifically, the performance indicators for the entire process of project initiation, construction, operation and maintenance and decommissioning are divided into eight major categories: cost-effectiveness, feasibility assessment, schedule compliance, service quality, safety compliance, demand fulfillment, user experience and asset disposal.

[0055] Table 1 Performance indicator system for each stage

[0056] The metrics data are connected to the project management system via an API interface, automatically collecting performance metrics data at each stage of project execution. For example, during the construction phase, data such as schedule deviation rate and code defect rate are automatically collected, and during the operation and maintenance phase, data such as system availability, service response time, and user satisfaction are automatically collected.

[0057] The collected values ​​are subjected to threshold verification. The actual values ​​are compared with the preset thresholds. The index data that exceeds the threshold range is marked as abnormal. For example, if the progress deviation rate exceeds ±5%, it is marked as progress abnormal. If the system availability rate is less than 99.9%, it is marked as service quality abnormal.

[0058] Based on the preset indicator weights, the scores of indicators at each stage are weighted and calculated to generate a comprehensive performance score for the entire project lifecycle, expressed as: ; in, This indicates the overall performance score. This represents the weight of the i-th indicator. This represents the score of the i-th indicator.

[0059] The score for a single indicator is expressed as follows: ; The performance anomaly index is expressed as: ; in, Indicates the performance abnormality index. This represents the weight of the i-th indicator. This represents the score of the i-th indicator. This represents the baseline threshold for the i-th indicator.

[0060] Assumptions: Project initiation phase: Feasibility analysis approval rate 100%, budget deviation rate 18.8%; Construction phase: Schedule deviation rate 3%, code defect rate 0.8‰, vulnerability remediation completion rate 100%, requirement completion rate 95%; During the operation and maintenance phase: system availability was 99.95%, average response time was 1.8 seconds, and user satisfaction was 92 points. Decommissioning phase: 100% data archiving integrity, 93% asset recovery rate; The collected data is subject to compliance verification. If the budget deviation rate exceeds the ±15% threshold, it is marked as an abnormal cost. Calculate the overall performance score using weighted averages: point.

[0061] The maximum score is 100 points, and the abnormal cost resulted in a lower overall score.

[0062] In step 5, the cost, schedule, and performance data of the entire project process are aggregated, correlated, analyzed, and stored traceably based on the data platform, and the data is displayed and alerted through the visualization module.

[0063] Project cost, construction period, and performance data are synchronized to the data platform. The data platform uses ETL tools to extract, clean, transform, and load data, eliminating data format differences and redundant data.

[0064] Establish a three-dimensional data association model of "project number - phase type - indicator type" to associate and bind cost, cycle, and performance data with project phase and business scenario; adopt a hybrid storage architecture, with relational databases (MySQL / PostgreSQL) storing structured indicator data, time series databases (InfluxDB / Prometheus) storing time series data (such as schedule changes and operation and maintenance monitoring data), and document databases (MongoDB) storing unstructured data (such as requirement documents and change records).

[0065] The formula for the degree of correlation and matching of three-dimensional data is: MatchD=(Nlink / Ntotal)×(Nvalid / Ntotal)×λ; MatchD represents the data association matching degree, Nlink represents the amount of associated data, Nvalid represents the amount of valid data, Ntotal represents the total amount of data, and λ represents the stage weight coefficient, with a value ranging from 0.8 to 1.2.

[0066] Generate a globally unique identifier (UUID) for each piece of data, record metadata such as data collection time, source module, operator, and modification log, and support traceability queries by project number, stage type, and indicator type to achieve "data traceability and accountability".

[0067] The visualization module generates multi-dimensional analysis charts, including cost trend comparison charts, schedule Gantt charts, performance radar charts, and heatmaps of abnormal indicators. Abnormal indicators (such as cost overruns of more than 10%, schedule delays of more than 5%, and performance scores below 60) are automatically identified and pushed to project managers via system messages, SMS, and emails. At the same time, optimization suggestions (such as requirement simplification, resource allocation, and operation and maintenance optimization) are generated.

[0068] Example 2 like Figure 2 As shown, this embodiment provides a quantitative management system for the entire lifecycle of digital government information projects, including: Cost Measurement Module: Used to obtain the requirements documents, historical project data and personnel configuration information of the target digital government informatization project, and to calculate the initial software cost of the project using function point analysis and cost estimation models; Obtain the requirement change records for the current stage of the project, dynamically adjust the initial software cost of the project based on the requirement change factors, and obtain the real-time software cost of the project. Cycle prediction module: used to predict the total duration and key milestones of each stage of the target digital government information project based on the critical path method and gradient boosting tree; Performance evaluation module: Used to build a performance indicator system for the entire project lifecycle, including project initiation, construction, operation and maintenance and decommissioning, and to generate a comprehensive performance score for the entire project lifecycle through a weighted summation calculation method; Data Platform Module: This module is used to aggregate, analyze, and traceably store cost, schedule, and performance data across the entire project process, and to display and provide early warnings through a visualization module.

[0069] Example 3 This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a quantitative management method for the entire lifecycle of a digital government information project as described in Embodiment 1.

[0070] The electronic device in this embodiment includes a processor, a memory, an input device, and an output device. The processor, memory, input device, and output device are coupled to each other via connectors. These connectors include various government data interfaces, project management system transmission buses, internal communication cables, etc., which are not limited in this respect. It should be understood that "coupling" in this embodiment refers to establishing data interaction and signal connections between components for digital government project management scenarios, including both direct physical connections and indirect connections through intermediate devices such as government cloud gateways and internal switches.

[0071] The processor can be one or more central processing units (CPUs), graphics processing units (GPUs), or embedded government-specific processors. In the case of multi-core or multi-processor groups, each core or processor can achieve data sharing and collaborative computing through a bus. It is used to execute the core logic in the method of this invention, such as function point quantification calculation, COCOMO II cost model calculation, GBDT cycle prediction model inference, and performance indicator weighted scoring, to adapt to the high concurrency and large data volume computing needs of digital government projects.

[0072] The memory is used to store computer program instructions and government project-specific data required to execute the present invention, including but not limited to: Random Access Memory (RAM): Used for temporary storage of running program code, real-time cost / cycle / performance data of the target project, and intermediate calculation results; Read-only memory (ROM): used to store core algorithm logic and basic configurations such as boot program, FPA function point counting rules, COCOMO II model parameters, and performance benchmark thresholds; Non-volatile storage media (such as government cloud hard drives and distributed storage): used for persistent storage of historical government informatization project datasets, performance benchmark libraries, weight files of trained GBDT periodic prediction models, and project lifecycle operation audit logs, etc., to meet the requirements of long-term data retention and compliance auditing for digital government projects.

[0073] The input device is used to acquire external data related to digital government projects, including: a batch import interface for project requirement documents, a personnel configuration information input interface, a historical government project cost / cycle dataset upload module, and an automatic synchronization component for requirement change records. It supports two modes: manual input and batch connection with government project management systems (such as OA and project management platforms).

[0074] The output device is used to display quantitative management results for government scenarios, including: a cost trend chart rendering module, a Gantt chart generation component for project duration, a performance radar chart visualization unit, an abnormal indicator early warning push interface, and a project full-cycle quantitative report export function. It can output cost estimation results, cycle prediction data, performance comprehensive scores, etc. in PDF, PNG or Excel format to meet the reporting, audit archiving and decision analysis needs of government departments.

[0075] Example 4 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for quantitative management of the entire lifecycle of a digital government information project as described in Embodiment 1.

[0076] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for quantitative management of the entire lifecycle of digital government information projects, characterized in that, include: Obtain the requirements document, historical project data and personnel configuration information of the target digital government informatization project, and use function point analysis and cost estimation models to calculate the initial software cost of the project. Obtain the requirement change records for the current stage of the project, dynamically adjust the initial software cost of the project based on the requirement change factors, and obtain the real-time software cost of the project. Predict the total duration and key milestones of each stage of the target digital government informatization project based on the critical path method and gradient boosting tree; Construct a performance indicator system covering all stages of project initiation, construction, operation and maintenance, and decommissioning, and generate a comprehensive performance score for the entire project lifecycle through a weighted summation calculation method; Based on the data platform, cost, schedule, and performance data of the entire project process are aggregated, correlated, analyzed, and stored traceably, and the data is displayed and alerted through the visualization module.

2. The method for quantitative management of the entire lifecycle of digital government information projects as described in claim 1, characterized in that, Function point analysis specifically involves counting the five categories of function points in the requirements document: input data, output data, query operations, internal files, and external interfaces, to obtain the total number of function points.

3. The method for quantitative management of the entire lifecycle of digital government information projects as described in claim 1, characterized in that, The cost estimation model is the COCOMO II model, and the cost estimation model calculates the initial software cost of the project as follows: Input the total number of function points into the COCOMO II model, and combine it with complexity coefficients, technology stack coefficients, team capability coefficients, and government project-specific correction coefficients to calculate the initial software cost of the project, expressed as: ； in, This indicates the initial software cost of the project. Indicates the total number of function points. Indicates the complexity coefficient. Represents the technology stack coefficient. This represents the team's capability coefficient. This indicates a correction factor specific to government projects.

4. The method for quantitative management of the entire lifecycle of digital government information projects as described in claim 1, characterized in that, Requirements change factors include change frequency, change size, and change impact scope, expressed as: ； in, Indicates the demand change factor. Indicates the frequency of change. Indicates a change in scale. Indicates the scope of the change. , , This represents the weighting coefficient.

5. The method for quantitative management of the entire lifecycle of digital government information projects as described in claim 1, characterized in that, The critical path method specifically involves using a work breakdown structure to decompose the target digital government informatization project into tasks such as project preparation, requirements analysis, system design, development and coding, integration and testing, online trial operation, and acceptance interaction, clearly defining the duration, task dependencies, prerequisite tasks, and successor tasks for each task. The earliest start time, earliest finish time, latest start time, and latest finish time of each task are calculated based on the critical path method to determine the critical path and critical nodes of the project. The critical path is the sequence of tasks with the longest total duration.

6. The method for quantitative management of the entire lifecycle of digital government information projects as described in claim 1, characterized in that, Gradient boosting tree prediction is used to determine the total project duration and key milestones for each stage of the target digital government information project. The gradient boosting tree predicts the total duration and key milestones of the target digital government information project based on project type, technical architecture, number of developers, total number of functional points, frequency of requirement changes, and average duration of similar historical projects. The key milestones include the completion time of requirement analysis, system design, development and coding, online trial operation, and acceptance and delivery.

7. The method for quantitative management of the entire lifecycle of digital government information projects as described in claim 1, characterized in that, Establish a performance indicator system covering the entire process from project initiation, construction, operation and maintenance, to decommissioning. Specifically, the initiation phase includes budget deviation rate and feasibility analysis pass rate; the construction phase includes schedule deviation rate, code defect rate, security vulnerability remediation completion rate, and requirement completion rate; the operation and maintenance phase includes system availability, service response time, user satisfaction, and operation and maintenance cost ratio; and the decommissioning phase includes data archiving integrity and asset recovery rate.

8. A quantitative management system for the entire lifecycle of digital government information projects, characterized in that, include: Cost Measurement Module: Used to obtain the requirements documents, historical project data and personnel configuration information of the target digital government informatization project, and to calculate the initial software cost of the project using function point analysis and cost estimation models; Obtain the requirement change records for the current stage of the project, dynamically adjust the initial software cost of the project based on the requirement change factors, and obtain the real-time software cost of the project. Cycle prediction module: used to predict the total duration and key milestones of each stage of the target digital government information project based on the critical path method and gradient boosting tree; Performance evaluation module: Used to build a performance indicator system for the entire project lifecycle, including project initiation, construction, operation and maintenance and decommissioning, and to generate a comprehensive performance score for the entire project lifecycle through a weighted summation calculation method; Data Platform Module: This module is used to aggregate, analyze, and traceably store cost, schedule, and performance data for the entire project process based on the data platform, and to display and provide early warnings through the visualization module.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements a quantitative management method for the entire lifecycle of digital government information projects as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements a quantitative management method for the entire lifecycle of digital government information projects as described in any one of claims 1-7.

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