Project management monitoring method and system based on multi-stage analysis

Abstract

The invention discloses a multi-stage analysis-based project management monitoring method and system, and relates to the technical field of project management and monitoring, and the method comprises the steps: determining a project management monitoring target and range, collecting project management data information, and recognizing and analyzing key indexes related to a project. Comparing the key indexes with historical project data to predict a potential trend, performing analysis stage division on the key indexes, designing an analysis template in each stage, collecting and arranging related data, evaluating the key indexes in each stage according to the collected data, making a decision based on an evaluation result, and adjusting a project plan. Adjusting information is fed back to the next analysis stage, a continuous improvement process is established, and a project management strategy is dynamically adjusted. According to the method, through multi-stage data collection and analysis and deep identification and prediction of key indexes, the project state can be monitored more accurately, potential risks can be predicted, and a project management strategy can be adjusted dynamically.

Description

Technical Field

[0001] The present invention relates to the technical field of project management and monitoring, and in particular to a project management monitoring method and system based on multi-stage analysis. Background Art

[0002] In the field of project management, with the acceleration of global economic integration and the intensification of corporate competition, the importance of project management monitoring methods has become increasingly prominent. Traditional project management monitoring methods often rely on the experience and intuition of project managers to track project progress through regular meetings and reports. However, these methods have certain limitations in dealing with the dynamic changes and uncertainties of complex projects. In recent years, although some project management systems have begun to adopt data analysis technology, these systems often only focus on a single stage or specific indicators and lack comprehensive monitoring and prediction of the entire life cycle of the project.

[0003] Existing project management monitoring technologies have the following deficiencies in practical applications: first, they often fail to effectively integrate data from various stages of the project, resulting in a lack of comprehensiveness and consistency in monitoring results; second, existing technologies are not deep enough in identifying and analyzing key project indicators, making it difficult to accurately predict project development trends; third, existing methods lack a dynamic adjustment mechanism in the project monitoring process, and once a project deviates, it is difficult to intervene and adjust in a timely and effective manner; in addition, the assessment and management of project risks are often not sophisticated enough to provide strong support for project decision-making. Summary of the invention

[0004] In view of the above-mentioned existing problems, the present invention provides a project management monitoring method and system based on multi-stage analysis, which is used to solve the problems in the prior art that the monitoring results lack comprehensiveness and consistency, it is difficult to intervene and adjust in a timely and effective manner, it is difficult to accurately predict project development trends and it is impossible to provide strong support for project decision-making.

[0005] To solve the above technical problems, a project management monitoring method based on multi-stage analysis is proposed, including:

[0006] Determine the objectives and scope of project management monitoring, collect project management data information, identify and analyze key indicators related to the project, and compare key indicators with historical project data to predict potential trends; divide key indicators into analysis stages, and design analysis templates for each stage, collect and organize relevant data, and evaluate key indicators of each stage based on the collected data; make decisions and adjust project plans based on evaluation results, feed back adjustment information to the next analysis stage, establish a continuous improvement process, and dynamically adjust project management strategies.

[0007] As a preferred solution of the project management monitoring method based on multi-stage analysis described in the present invention, the collection of project management data information includes identifying the main stakeholders in the project, collecting stakeholders' expectations, requirements and success criteria for the project, clarifying the project goals, recording and organizing the goals, determining the main tasks, subtasks and deliverables of the project, identifying the boundary conditions of the project, collecting project progress data, resource data, cost data, quality data and risk data, and identifying and analyzing key indicators related to the project.

[0008] The progress data includes task start and end dates, and milestone completion status; the resource data includes human resources, equipment utilization, and material consumption; the cost data includes budget, actual expenditure, and cost deviation; the quality data includes defect rate, customer feedback, and compliance inspection results; the risk data includes other risks, the probability of risk occurrence, and impact assessment.

[0009] The identification and analysis of key indicators related to the project includes determining preliminary key indicators with reference to industry standards and best practices, evaluating the relevance and measurability of the indicators based on project needs and objectives, and ultimately determining schedule deviation, cost deviation, completion percentage and customer satisfaction.

[0010] As a preferred solution of the project management monitoring method based on multi-stage analysis described in the present invention, wherein: the prediction of potential trends includes collecting data of historical projects in a unified data format and processing missing values, comparing and analyzing key indicators with historical project data, and predicting potential trends;

[0011] The comparative analysis includes determining a set of key indicators and historical indicators, calculating the average and standard deviation of the indicators, calculating the degree of deviation of the KPI of the current project from the historical data, and drawing a time series graph and a box plot to visualize the KPI data;

[0012] The prediction of potential trends also includes dynamic regression analysis of historical project data, creation of trend analysis models and model simulation, periodic adjustment of influencing factors to form weighted prediction functions, and comparison of prediction results with actual project progress to perform error prediction, and evaluation of model accuracy through regression diagnostic graphs;

[0013] The trend analysis model formula is:

[0014] KPIs t =β0+β1·t+β2·KPIs t-1 +∈

[0015] Among them, KPIs tis the key performance indicator at time point t, β0 is the intercept of the regression model, β1 is the time trend coefficient, t is the time variable, β2 is the lag effect coefficient, ∈ is the random error term, KPIs t-1 is the key performance indicator at time point t-1;

[0016] The weighted prediction function formula is:

[0017] KPIs forecast =α·KPIs t +(1-α)·KPIs historical

[0018] Among them, KPIs forecast is the predicted key performance indicator value, α is the weighting coefficient, KPIs t is the key performance indicator at time point t, KPIs historical are the key performance indicator values ​​in historical projects.

[0019] As a preferred solution of the project management monitoring method based on multi-stage analysis described in the present invention, the design of the analysis template includes dividing the analysis stages of key indicators into the initial stage, the planning stage, the implementation stage and the closing stage according to the natural development stage of the project, the goals of each stage and the main tasks, and designing an analysis template in each stage.

[0020] The design analysis template includes the design project name, stage time, main responsible person, specific data type and source, and uses data sorting tools to centralize the data, define the KPI of each stage according to the project characteristics, select the analysis method, and clean and classify the data as needed.

[0021] As a preferred solution of the project management monitoring method based on multi-stage analysis described in the present invention, wherein: the key indicators of each stage are evaluated, including collecting and collating relevant data, aggregating the KPI of each stage according to the collected data, evaluating the key indicators of each stage, the end result of each stage can be used as the input data of the next stage, obtaining the overall key performance indicator value of the project, introducing the time factor and the risk adjustment coefficient to obtain the revised key performance indicator value, and using the revised result to iteratively update and adjust the subsequent stages of the project;

[0022] The formula for obtaining the overall key performance indicator value of the project is:

[0023]

[0024] Among them, KPI overall is the overall key performance indicator value of the project, w i is the weight of the i-th stage, KPI iis the key performance indicator value of the i-th stage, i = A, B, C and D, A, B, C and D are the stages of evaluation, and i is the variable index;

[0025] The revised overall key performance indicator value formula for the project is:

[0026]

[0027] Among them, KPI adjusted is the revised overall key performance indicator value of the project, KPI overall is the overall key performance indicator value of the project, λ is the stage contribution factor, t1 is the time, and R is the risk adjustment coefficient.

[0028] As a preferred solution of the project management monitoring method based on multi-stage analysis described in the present invention, wherein: the decision-making and adjustment of the project plan includes: the user viewing the generated analysis report in the system, the user confirming the validity of the current evaluation result, identifying the key issues that need decision-making and adjustment through the analysis of indicators, and selecting a decision plan for the problem, formulating a specific adjustment plan according to the selected decision plan, implementing the adjustment plan and recording the adjustment information;

[0029] The validity of the evaluation results includes verifying the original data source, reviewing the process records, comparing the actual results with the industry standards to set the comprehensive deviation threshold of the decision-making plan. When the comparison error is greater than the deviation threshold, it is necessary to use statistical methods to analyze the cause of the error and check the results;

[0030] The decision-making scheme selection includes collecting optional decision-making schemes, creating a decision matrix, listing the advantages and disadvantages of each scheme, scoring according to different evaluation criteria, and selecting the decision-making scheme with the highest score; the optional decision-making schemes include reallocating resources, changing the project timeline, handling budget overruns, and adding quality audits and testing links;

[0031] The standard formula for judging whether a decision-making plan needs to be adjusted is:

[0032]

[0033] Where G is the comprehensive bias score of the adjustment decision, v j For each KPI weight, KPI actual,j (t is the actual value of the jth KPI, KPI benchmark,j (t) is the benchmark value of the jth KPI, is the deviation rate, and n is the total number of KPIs.

[0034] As a preferred solution of the project management and monitoring method based on multi-stage analysis described in the present invention, the dynamically adjusting project management strategy includes feeding back adjustment information to the next analysis stage, monitoring the equipment failure rate and processing speed in real time during the project implementation process, establishing a continuous improvement process, and dynamically adjusting the project management strategy;

[0035] The dynamic adjustment of the project management strategy also includes, when the failure rate exceeds 5% or the processing speed drops by more than 10%, immediately calling the backup equipment and adjusting the project cycle, and automatically triggering the equipment maintenance procedure, adjusting the project management strategy, and real-time monitoring of the equipment operation status after the adjustment until the failure rate is less than or equal to 5% and the processing speed drops by less than or equal to 10%.

[0036] Another object of the present invention is to provide a project management monitoring system based on multi-stage analysis. The present invention realizes comprehensive monitoring of the entire life cycle of the project through multi-stage analysis; the system of the present invention collects and accurately analyzes various types of project management data, and through standardization and modeling, provides in-depth analysis of key project indicators, helps the project team understand the project status, and uses historical data and advanced analysis technology to predict potential trends in order to respond to challenges in advance; at the same time, a dynamic adjustment mechanism is designed to adjust management strategies in real time according to project progress and changes in the external environment, optimize the decision-making process, and assist project managers in making scientific and reasonable decisions by creating a decision matrix and comprehensive deviation scoring.

[0037] As a preferred solution of the project management monitoring system based on multi-stage analysis described in the present invention, it is characterized by including a project management goal definition module, a key indicator identification module, a trend forecasting and comparative analysis module, a project plan adjustment module and a dynamic adjustment project management module.

[0038] The project management objective definition module is used to determine the monitoring objectives and scope of the project, identify the main tasks, subtasks and deliverables of the project, and clarify the boundary conditions of the project.

[0039] The key indicator identification module is used to collect and organize multi-dimensional project management data information, identify and analyze the key indicators of the project, and evaluate the relevance and measurability of the indicators.

[0040] The trend forecasting and comparative analysis module is used to generate potential trends by comparative analysis of key indicators and historical data, establish a trend analysis model using dynamic regression analysis, simulate and forecast the development of the project, and evaluate the impact of different decisions. Through the error prediction formula, the forecast results are compared with the actual progress.

[0041] The project plan adjustment module is used to make decisions based on the analysis results, adjust the project plan, collect and evaluate optional decision plans, analyze the advantages and disadvantages of each plan by creating a decision matrix, select the best decision plan based on the score, and dynamically record and feedback the adjustment information.

[0042] The dynamically adjusted project management module is used to monitor the equipment failure rate and processing speed in real time during the project implementation process, obtain dynamic data, and automatically take upgrade and maintenance measures when the failure rate or processing speed reaches a preset threshold, adjust the project management strategy in time, and optimize the project management strategy through continuous process improvement.

[0043] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of a method described in project management monitoring based on multi-stage analysis are implemented.

[0044] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a method described in a project management monitoring method based on multi-stage analysis are implemented.

[0045] Beneficial effects of the present invention: The present invention determines the objectives and scope of project management monitoring, collects comprehensive project management data information, identifies and analyzes key indicators related to the project, compares the key indicators with historical project data to predict potential trends, thereby achieving accurate positioning of project objectives and early identification of risks, providing a clear direction and basis for project monitoring, and effectively preventing and responding to potential problems; then, by identifying major stakeholders and collecting their expectations, needs and success criteria, the comprehensiveness and accuracy of project monitoring data are ensured, and the consistency between project objectives and stakeholder expectations is improved; in addition, historical data comparative analysis and dynamic regression analysis are used to predict the future status of the project, providing decision-making support for the project team, reducing uncertainty, and improving the project's ability to cope with future challenges; designing analysis templates and dividing key indicator analysis stages according to project development stages and objectives, achieving standardization and systematization of monitoring, improving data analysis efficiency and quality, and ensuring the smooth realization of project objectives at all stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. 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 work, among which:

[0047] Figure 1An overall flow chart of a project management and monitoring method based on multi-stage analysis provided by an embodiment of the present invention.

[0048] Figure 2 A system solution flow chart of a project management and monitoring system based on multi-stage analysis is provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0050] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0051] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is mutually exclusive with other embodiments, either individually or selectively.

[0052] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0053] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0054] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0055] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides a project management monitoring method based on multi-stage analysis, including:

[0056] S1: Determine the objectives and scope of project management monitoring, collect project management data information, identify and analyze key indicators related to the project, and compare key indicators with historical project data to predict potential trends.

[0057] The collection of project management data information includes identifying the main stakeholders in the project, collecting the expectations, requirements and success criteria of the stakeholders for the project, clarifying the project goals, recording and organizing the goals, determining the main tasks, subtasks and deliverables of the project, identifying the boundary conditions of the project, collecting project progress data, resource data, cost data, quality data and risk data, and identifying and analyzing key indicators related to the project;

[0058] The progress data includes task start and end dates, and milestone completion status; the resource data includes human resources, equipment utilization, and material consumption; the cost data includes budget, actual expenditure, and cost deviation; the quality data includes defect rate, customer feedback, and compliance inspection results; the risk data includes other risks, probability of risk occurrence, and impact assessment;

[0059] The identification and analysis of key indicators related to the project includes determining preliminary key indicators with reference to industry standards and best practices, evaluating the relevance and measurability of the indicators based on project needs and objectives, and ultimately determining schedule deviation, cost deviation, completion percentage and customer satisfaction.

[0060] It should be noted that the prediction of potential trends includes collecting data from historical projects in a unified data format and processing missing values, comparing and analyzing key indicators with historical project data, and predicting potential trends;

[0061] The comparative analysis includes determining a set of key indicators and historical indicators, calculating the average and standard deviation of the indicators, calculating the degree of deviation of the KPI of the current project from the historical data, and drawing a time series graph and a box plot to visualize the KPI data;

[0062] The comparative analysis formula is:

[0063]

[0064] Among them, Z is the standardized difference between the current key indicator and the historical indicator, KPIs current is the key performance indicator of the current project, μ historical is the average value of the key performance indicators of historical projects, σ historical is the standard deviation of the key performance indicators of historical projects;

[0065] The prediction of potential trends also includes dynamic regression analysis of historical project data, creation of trend analysis models and model simulation, periodic adjustment of influencing factors to form weighted prediction functions, and comparison of prediction results with actual project progress to perform error prediction, and evaluation of model accuracy through regression diagnostic graphs;

[0066] The trend analysis model formula is:

[0067] KPIs t =β0+β1·t+β2·KPIs t-1 +∈

[0068] Among them, KPIs t is the key performance indicator at time point t, β0 is the intercept of the regression model, β1 is the time trend coefficient, t is the time variable, β2 is the lag effect coefficient, ∈ is the random error term, KPIs t-1 is the key performance indicator at time point t-1;

[0069] The weighted prediction function formula is:

[0070] KPIs forecast =α·KPIs t +(1-α)·KPIs historical

[0071] Among them, KPIs forecast is the predicted key performance indicator value, α is the weighting coefficient, KPIs t is the key performance indicator at time point t, KPIs historical is the key performance indicator value in the historical project;

[0072] The error prediction formula is:

[0073] Q=KPIs forecast -KPIs actual

[0074] Where Q is the difference between the predicted value and the actual value, KPIs forecast For the predicted key performance indicator values, KPIs actual is the actual observed KPI value.

[0075] S2: Divide the key indicators into analysis stages, design analysis templates for each stage, collect and organize relevant data, and evaluate the key indicators of each stage based on the collected data.

[0076] Furthermore, the design of the analysis template includes dividing the analysis phase of the key indicators into an initial phase, a planning phase, an implementation phase and a closing phase according to the natural development phase of the project, the objectives and main tasks of each phase, and designing an analysis template in each phase;

[0077] The design analysis template includes the design project name, stage time, main responsible person, specific data type and source, and uses data sorting tools to centralize the data, define the KPI of each stage according to the project characteristics, select the analysis method, and clean and classify the data as needed.

[0078] Furthermore, the key indicators of each stage of the evaluation include collecting and organizing relevant data, aggregating the KPI of each stage based on the collected data, evaluating the key indicators of each stage, and the end result of each stage can be used as input data for the next stage to obtain the overall key performance indicator value of the project, introduce time factors and risk adjustment coefficients to obtain revised key performance indicator values, and use the revised results to iteratively update and adjust the subsequent stages of the project;

[0079] The formula for obtaining the overall key performance indicator value of the project is:

[0080]

[0081] Among them, KPI overall is the overall key performance indicator value of the project, w i is the weight of the i-th stage, KPI i is the key performance indicator value of the i-th stage, i = A, B, C and D, A, B, C and D are the stages of evaluation, and i is the variable index;

[0082] The revised overall key performance indicator value formula for the project is:

[0083]

[0084] Among them, KPI adjusted is the revised overall key performance indicator value of the project, KPI overall is the overall key performance indicator value of the project, λ is the stage contribution factor, t1 is the time, and R is the risk adjustment coefficient.

[0085] S3: Make decisions and adjust project plans based on evaluation results, feed back adjustment information to the next analysis phase, establish a continuous improvement process, and dynamically adjust project management strategies.

[0086] Further, the making of decision and adjusting the project plan includes: the user viewing the generated analysis report in the system, the user confirming the validity of the current evaluation results, identifying key issues that require decision and adjustment through the analysis of indicators, selecting a decision plan for the problem, formulating a specific adjustment plan based on the selected decision plan, implementing the adjustment plan and recording the adjustment information;

[0087] The validity of the evaluation results includes verifying the original data source, reviewing the process records, comparing the actual results with the industry standards to set the comprehensive deviation threshold of the decision-making plan. When the comparison error is greater than the deviation threshold, it is necessary to use statistical methods to analyze the cause of the error and check the results;

[0088] The decision-making scheme selection includes collecting optional decision-making schemes, creating a decision matrix, listing the advantages and disadvantages of each scheme, scoring according to different evaluation criteria, and selecting the decision-making scheme with the highest score; the optional decision-making schemes include reallocating resources, changing the project timeline, handling budget overruns, and adding quality audits and testing links;

[0089] The standard formula for judging whether a decision-making plan needs to be adjusted is:

[0090]

[0091] Where G is the comprehensive bias score of the adjustment decision, v j For each KPI weight, KPI actual,j (t) is the actual value of the jth KPI, KPI benchmark,j (t) is the benchmark value of the jth KPI, is the deviation rate, and n is the total number of KPIs.

[0092] Furthermore, the dynamic adjustment of the project management strategy includes feeding back the adjustment information to the next analysis stage, monitoring the equipment failure rate and processing speed in real time during the project implementation, establishing a continuous improvement process, and dynamically adjusting the project management strategy;

[0093] Obtaining the equipment failure rate includes real-time monitoring of equipment failure and maintenance records, and calculating the equipment failure rate. The formula is:

[0094]

[0095] Among them, F is the equipment failure rate, K is the number of equipment failures, and I is the total equipment operation time;

[0096] The formula for obtaining the device processing speed is:

[0097]

[0098] Among them, V is the processing speed of the equipment, S is the total number of processed jobs, and T is the total processing time of the job;

[0099] The dynamic adjustment of the project management strategy also includes, when the failure rate exceeds 5% or the processing speed drops by more than 10%, immediately calling the backup equipment and adjusting the project cycle, and automatically triggering the equipment maintenance procedure, adjusting the project management strategy, and real-time monitoring of the equipment operation status after the adjustment until the failure rate is less than or equal to 5% and the processing speed drops by less than or equal to 10%.

[0100] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0101] Example 2, reference Figure 2 , which is the second embodiment of the present invention, provides a project management monitoring system based on multi-stage analysis, including a project management goal definition module 100, a key indicator identification module 200, a trend forecasting and comparative analysis module 300, a project plan adjustment module 400 and a dynamic adjustment project management module 500.

[0102] The project management objective definition module 100 is used to determine the monitoring objectives and scope of the project, identify the main tasks, subtasks and deliverables of the project, and clarify the boundary conditions of the project.

[0103] The key indicator identification module 200 is used to collect and organize multi-dimensional project management data information, identify and analyze key indicators of the project, and evaluate the relevance and measurability of the indicators.

[0104] The trend prediction and comparative analysis module 300 is used to generate potential trends by comparative analysis of key indicators and historical data, establish a trend analysis model using dynamic regression analysis, simulate and predict the development of the project, and evaluate the impact of different decisions, and compare the predicted results with the actual progress through the error prediction formula.

[0105] The project plan adjustment module 400 is used to make decisions based on the analysis results, adjust the project plan, collect and evaluate optional decision plans, analyze the advantages and disadvantages of each plan by creating a decision matrix, select the best decision plan based on the score, and dynamically record and feedback adjustment information.

[0106] The dynamically adjusted project management module 500 is used to monitor the equipment failure rate and processing speed in real time during the project implementation process, obtain dynamic data, and automatically take upgrade and maintenance measures when the failure rate or processing speed reaches a preset threshold, adjust the project management strategy in time, and optimize the project management strategy through continuous process improvement.

[0107] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0108] Embodiment 3, the third embodiment of the present invention, is different from the first two embodiments in that:

[0109] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0110] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0111] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0112] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

Claims

1. A project management monitoring method based on multi-stage analysis, characterized in that: include, Determine the objectives and scope of project management monitoring, collect project management data information, identify and analyze key indicators related to the project, and compare key indicators with historical project data to predict potential trends; Divide the key indicators into analysis stages, design analysis templates for each stage, collect and organize relevant data, and evaluate the key indicators of each stage based on the collected data; Make decisions and adjust project plans based on evaluation results, feed back adjustment information to the next analysis phase, establish a continuous improvement process, and dynamically adjust project management strategies.

2. A project management and monitoring method based on multi-stage analysis as claimed in claim 1, characterized in that: The collection of project management data information includes identifying the main stakeholders in the project, collecting the expectations, requirements and success criteria of the stakeholders for the project, clarifying the project goals, recording and organizing the goals, determining the main tasks, subtasks and deliverables of the project, identifying the boundary conditions of the project, collecting project progress data, resource data, cost data, quality data and risk data, and identifying and analyzing key indicators related to the project; The progress data includes task start and end dates, and milestone completion status; the resource data includes human resources, equipment utilization, and material consumption; the cost data includes budget, actual expenditure, and cost deviation; the quality data includes defect rate, customer feedback, and compliance inspection results; the risk data includes other risks, probability of risk occurrence, and impact assessment; The identification and analysis of key indicators related to the project includes determining preliminary key indicators with reference to industry standards and best practices, evaluating the relevance and measurability of the indicators based on project needs and objectives, and ultimately determining schedule deviation, cost deviation, completion percentage and customer satisfaction.

3. A project management and monitoring method based on multi-stage analysis as claimed in claim 2, characterized in that: The prediction of potential trends includes collecting data of historical projects to unify the data format and process missing values, comparing and analyzing key indicators with historical project data, and predicting potential trends; The comparative analysis includes determining a set of key indicators and historical indicators, calculating the average and standard deviation of the indicators, calculating the degree of deviation of the KPI of the current project from the historical data, and drawing a time series graph and a box plot to visualize the KPI data; The prediction of potential trends also includes dynamic regression analysis of historical project data, creation of trend analysis models and model simulation, periodic adjustment of influencing factors to form weighted prediction functions, and comparison of prediction results with actual project progress to perform error prediction, and evaluation of model accuracy through regression diagnostic graphs; The trend analysis model formula is: KPIs t =β0+β1·t+β2·KPIs t-1 +∈ Among them, KPIs t is the key performance indicator at time point t, β0 is the intercept of the regression model, β1 is the time trend coefficient, t is the time variable, β2 is the lag effect coefficient, ∈ is the random error term, KPIs t-1 is the key performance indicator at time point t-1; The weighted prediction function formula is: KPIs forecast =α KPIs t +(1-α)·KPIs historical Among them, KPIs forecast is the predicted key performance indicator value, α is the weighting coefficient, KPIs t is the key performance indicator at time point t, KPIs historical are the key performance indicator values ​​in historical projects.

4. A project management and monitoring method based on multi-stage analysis as claimed in claim 3, characterized in that: The design of the analysis template includes dividing the analysis phases of the key indicators into the initial phase, the planning phase, the implementation phase and the closing phase according to the natural development phase of the project, the objectives and main tasks of each phase, and designing the analysis template in each phase; The design analysis template includes the design project name, stage time, main responsible person, specific data type and source, and uses data sorting tools to centralize the data, define the KPI of each stage according to the project characteristics, select the analysis method, and clean and classify the data as needed.

5. A project management and monitoring method based on multi-stage analysis as claimed in claim 4, characterized in that: The key indicators of each stage of the evaluation include collecting and organizing relevant data, aggregating the KPI of each stage based on the collected data, evaluating the key indicators of each stage, and the end result of each stage can be used as the input data of the next stage to obtain the overall key performance indicator value of the project, introduce the time factor and risk adjustment coefficient to obtain the revised key performance indicator value, and use the revised result to iteratively update and adjust the subsequent stages of the project; The formula for obtaining the overall key performance indicator value of the project is: Among them, KPI overall is the overall key performance indicator value of the project, w i is the weight of the i-th stage, KPI i is the key performance indicator value of the i-th stage, i = A, B, C and D, A, B, C and D are the stages of evaluation, and i is the variable index; The revised overall key performance indicator value formula for the project is: Among them, KPI adjusted is the revised overall key performance indicator value of the project, KPI overall is the overall key performance indicator value of the project, λ is the stage contribution factor, t1 is the time, and R is the risk adjustment coefficient.

6. A project management and monitoring method based on multi-stage analysis as claimed in claim 5, characterized in that: The making of decision and adjusting the project plan includes: the user viewing the generated analysis report in the system, the user confirming the validity of the current evaluation results, identifying key issues that require decision and adjustment through the analysis of indicators, selecting a decision plan for the problem, formulating a specific adjustment plan based on the selected decision plan, implementing the adjustment plan and recording the adjustment information; The validity of the evaluation results includes verifying the original data source, reviewing the process records, comparing the actual results with the industry standards to set the comprehensive deviation threshold of the decision-making plan. When the comparison error is greater than the deviation threshold, it is necessary to use statistical methods to analyze the cause of the error and check the results; The decision-making scheme selection includes collecting optional decision-making schemes, creating a decision matrix, listing the advantages and disadvantages of each scheme, scoring according to different evaluation criteria, and selecting the decision-making scheme with the highest score; the optional decision-making schemes include reallocating resources, changing the project timeline, handling budget overruns, and adding quality audits and testing links; The standard formula for judging whether a decision-making plan needs to be adjusted is: Where G is the comprehensive bias score of the adjustment decision, v j For each KPI weight, KPI actual,j (t) is the actual value of the jth KPI, KPI benchmark,j (t) is the benchmark value of the jth KPI, is the deviation rate, and n is the total number of KPIs.

7. A project management and monitoring method based on multi-stage analysis as claimed in claim 6, characterized in that: The dynamic adjustment of the project management strategy includes feeding back the adjustment information to the next analysis stage, monitoring the equipment failure rate and processing speed in real time during the project implementation, establishing a continuous improvement process, and dynamically adjusting the project management strategy; The dynamic adjustment of the project management strategy also includes, when the failure rate exceeds 5% or the processing speed drops by more than 10%, immediately calling the backup equipment and adjusting the project cycle, and automatically triggering the equipment maintenance procedure, adjusting the project management strategy, and real-time monitoring of the equipment operation status after the adjustment until the failure rate is less than or equal to 5% and the processing speed drops by less than or equal to 10%.

8. A system using a project management and monitoring method based on multi-stage analysis as claimed in any one of claims 1 to 7, characterized in that: It includes project management goal definition module, key indicator identification module, trend forecasting and comparative analysis module, project plan adjustment module and dynamic adjustment project management module; The project management objective definition module is used to determine the monitoring objectives and scope of the project, identify the main tasks, subtasks and deliverables of the project, and clarify the boundary conditions of the project; The key indicator identification module is used to collect and organize multi-dimensional project management data information, identify and analyze the key indicators of the project, and evaluate the relevance and measurability of the indicators; The trend prediction and comparative analysis module is used to generate potential trends by comparing key indicators with historical data, establish a trend analysis model using dynamic regression analysis, simulate and predict the development of the project, and evaluate the impact of different decisions. Through the error prediction formula, the prediction results are compared with the actual progress; The project plan adjustment module is used to make decisions based on the analysis results, adjust the project plan, collect and evaluate optional decision plans, analyze the advantages and disadvantages of each plan by creating a decision matrix, select the best decision plan based on the score, and dynamically record and feedback the adjustment information; The dynamically adjusted project management module is used to monitor the equipment failure rate and processing speed in real time during the project implementation process, obtain dynamic data, and automatically take upgrade and maintenance measures when the failure rate or processing speed reaches a preset threshold, adjust the project management strategy in time, and optimize the project management strategy through continuous process improvement.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a project management and monitoring method based on multi-stage analysis as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a project management and monitoring method based on multi-stage analysis as described in any one of claims 1 to 7 are implemented.

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