A demand-driven project operation collaborative management system and method

Abstract

This application relates to the field of project operation management technology, and in particular to a demand-driven project operation collaborative management system and method. The system uses a demand management module to perform structured parsing of user project requirements and generate demand data and user profiles; a project matching module matches project personnel qualifications, capabilities, and resources based on the demand data and user profiles, generating resource allocation results; a project collaborative execution module constructs a project workspace, records and tracks the project implementation process, forming execution trajectory data; and a project quality assessment module evaluates the project process and delivery results based on the execution trajectory data, outputting monitoring or alert information when anomalies or risks occur. This invention achieves closed-loop project operation management with precise allocation of project resources, traceable execution processes, and predictable risks, thereby significantly improving project implementation efficiency and delivery quality.

Description

Technical Field

[0001] This application relates to the field of project operation management technology, and in particular to a demand-driven project operation collaborative management system and method. Background Technology

[0002] In related technologies, with the continuous advancement of enterprise digital transformation and the widespread application of project-based business models, project operation management has become an important technical means for enterprises to integrate business needs, organize resource allocation, and achieve deliverables. Existing project operation management systems typically revolve around project process management, using information technology to process aspects such as project initiation, task allocation, progress tracking, and result delivery to support enterprises in basic control over the project execution process, thereby improving the standardization and visibility of project management.

[0003] However, existing project operation management technologies largely focus on process and event management during the project execution phase, generally lacking a holistic operational perspective starting from requirements. In key stages such as project requirement generation, requirement analysis, personnel qualification matching, resource allocation, and collaborative project execution, related functions are often scattered across different systems or rely on manual coordination. Requirement information is difficult to structure and model, and there is a lack of effective correlation between requirements and projects, personnel, and resources. This results in low project initiation efficiency, unclear role responsibilities, high communication costs, and difficulty in forming a complete closed-loop management system from requirement proposal to project delivery. Furthermore, in terms of project resource allocation and collaborative management, existing technologies typically rely on manual experience for personnel assignment and resource scheduling, lacking a systematic matching mechanism based on requirement characteristics, professional fields, and role qualifications, making it difficult to ensure the matching degree between the project implementation entity and project requirements.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose a demand-driven project operation collaborative management system and method to achieve closed-loop project operation management with precise allocation of project resources, traceable execution process, and early warning of risks, thereby significantly improving project implementation efficiency and delivery quality.

[0006] To achieve the above objectives, one aspect of this application proposes a demand-driven project operation collaborative management system, the system comprising: The requirements management module is used to receive project requirements initiated by users, perform structured parsing of the project requirements, generate requirement data, and construct user profiles corresponding to the requirement data. The project matching module is used to perform matching calculations on the role qualifications, professional capabilities and project resources of project participants based on the demand data and the user profile, to determine the project implementation entity and generate project resource allocation results. The project collaborative execution module is used to construct a project workspace based on the project resource configuration results, record the process and track the status of the project implementation, and form project execution trajectory data. The project quality assessment module is used to assess the quality of the project implementation process and delivery results based on the project execution trajectory data, generate project quality assessment results, and generate corresponding monitoring or prompt information when abnormal states or risk conditions are detected.

[0007] In some embodiments, the demand data includes user type information, professional field information, and basic project information.

[0008] In some embodiments, the demand management module includes: The requirement parsing unit is used to obtain the project requirements initiated by the user, perform structured parsing of the project requirements, and generate requirement element data. The demand modeling unit is used to standardize and encode the demand element data to construct the corresponding demand data model. A user profile building unit is used to generate a user profile corresponding to the project requirements based on the requirement data model, and to establish a connection between the user profile and the requirement data. The demand output unit is used to verify the demand data and the user profile, and output the demand data after the verification is successful.

[0009] In some embodiments, the standardization and encoding of the demand element data to construct a corresponding demand data model includes: The demand element data is categorized into customer type elements, professional field elements, and project basic elements. Based on the preset demand element coding rules, each type of demand element data is uniformly identified and coded to generate structured demand coding data. The demand coding data is mapped hierarchically to establish the relationships between demand elements and form a hierarchical structure of demand elements. Based on the demand coding data and the demand element hierarchy, a standardized demand data model is constructed.

[0010] In some embodiments, the project matching module includes: The resource qualification modeling unit is used to standardize the role types, professional qualification levels and service capabilities of project participants and project resources, and generate corresponding resource qualification models. The matching rule calculation unit is used to perform matching calculations based on the demand data, the customer profile and the resource qualification model, according to preset multi-dimensional matching rules, to generate a set of candidate project implementation entities. The priority determination unit is used to evaluate the priority of the candidate project implementation entity set and generate the target project implementation entity according to preset indicators; the preset indicators include qualification matching degree, historical project performance and response time. The matching result output unit is used to associate the target project implementation entity with the requirement data and output the project resource configuration result.

[0011] In some embodiments, the step of generating a candidate project implementation entity set by performing matching calculations based on the demand data, the customer profile, and the resource qualification model according to preset multi-dimensional matching rules includes: Based on the demand data, qualification constraint matching is performed on the role type, professional field matching relationship and qualification level in the resource qualification model to filter out candidate resource objects that meet the basic qualification conditions; Based on the historical service characteristics and project complexity characteristics in the customer profile, the capability adaptability of the candidate resource objects is calculated to generate a corresponding capability matching score. Based on the preset multidimensional matching weight rules, the qualification matching result, the ability matching score, and the historical project performance indicators are weighted and calculated to generate a comprehensive matching score result. The results of the comprehensive matching score are sorted, and resource objects that meet the preset threshold conditions are selected to form the candidate project implementation entity set.

[0012] In some embodiments, the multidimensional matching weight rules include: Based on different project needs and professional fields, pre-set the weight parameters corresponding to qualification matching results, ability matching scores, and historical project performance indicators; The weight parameters are adaptively adjusted based on the project complexity level and service timeliness requirements. When there is a preset qualification threshold constraint, the corresponding qualification matching dimension is set as a strong constraint weight so that resource objects that do not meet the qualification threshold will not participate in the comprehensive matching score calculation. The weight parameters are updated and corrected based on the feedback data generated from the project execution results.

[0013] In some embodiments, the project quality assessment module includes: The quality indicator construction unit is used to construct project quality assessment indicators based on the project execution trajectory data and according to preset assessment rules; the project quality assessment indicators include schedule compliance, delivery completeness, process compliance, and user feedback indicators. The quality scoring unit is used to calculate the project execution trajectory data based on the project quality assessment indicators and generate a project quality score result. An anomaly determination unit is used to compare the project quality score result with a preset threshold to determine whether the project is in an abnormal or risky state. The result output unit is used to output the project quality score result and generate corresponding monitoring or prompt information when it is determined that there is an abnormal or risky state.

[0014] In some embodiments, a permission security control module is also included, which is used to control the data access permissions and operation permissions of different project participants based on a role-based permission model.

[0015] To achieve the above objectives, another aspect of this application proposes an implementation method for the aforementioned system, the method comprising the following steps: Receive project requests initiated by users; The project requirements are structured and parsed to generate requirement data, and user profiles corresponding to the requirement data are constructed. Based on the demand data and the user profile, the roles, qualifications, professional abilities and project resources of the project participants are matched and calculated to determine the project implementation entity and generate project resource allocation results. The project workspace is constructed based on the project resource allocation results. Based on the project workspace, the project implementation process is recorded and its status is tracked to form project execution trajectory data. Based on the project execution trajectory data, the project implementation process and delivery results are evaluated for quality, project quality evaluation results are generated, and corresponding monitoring or prompt information is generated when abnormal states or risk conditions are detected.

[0016] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the system described above.

[0017] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the system described above.

[0018] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the system described above.

[0019] The embodiments of this application include at least the following beneficial effects: This application provides a demand-driven project operation collaborative management system and method. This solution uses a demand management module to perform structured parsing of user-initiated project demands and constructs user profiles corresponding to the demand data. This transforms subjective descriptions of project demands into standardized data, reducing misunderstandings and improving the accuracy and consistency of demand acquisition. Through a project matching module, based on demand data and user profiles, the system matches and calculates the roles, qualifications, professional capabilities, and project resources of project participants, generating project resource allocation results. This achieves a reasonable determination of project implementation entities and resources, improving the matching efficiency of project resource allocation. Through a project collaborative execution module, a project workspace is constructed based on the project resource allocation results. The project implementation process is recorded and its status tracked, forming project execution trajectory data. This makes the project execution process traceable and enhances the process control capabilities of collaborative project execution. Through a project quality assessment module, the project implementation process and delivery results are assessed based on the project execution trajectory data. Monitoring or alert information is generated when abnormal states or risk conditions are detected, enabling timely identification and control of project operation risks, thereby improving overall project operational efficiency and delivery quality. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of a demand-driven project operation collaborative management system provided in an embodiment of this application; Figure 2 This is a schematic diagram of the demand management module provided in an embodiment of this application; Figure 3 This is a schematic diagram of the project matching module provided in the embodiments of this application; Figure 4 This is a schematic diagram of the project quality assessment module provided in the embodiments of this application; Figure 5 This is a flowchart illustrating an implementation method for a demand-driven project operation collaborative management system provided in this application embodiment. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0022] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0023] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0024] Unless otherwise defined, 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 application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0025] This application provides a demand-driven project operation collaborative management system and method. The solution uses a demand management module to structurally analyze user-initiated project demands and construct user profiles corresponding to the demand data. This transforms subjective descriptions of project demands into standardized data, reducing misunderstandings and improving the accuracy and consistency of demand acquisition. A project matching module, based on demand data and user profiles, calculates and matches the roles, qualifications, professional abilities, and project resources of project participants, generating project resource allocation results. This ensures the rational determination of project implementation entities and resources, improving the efficiency of project resource allocation. A project collaborative execution module constructs a project workspace based on the project resource allocation results, records and tracks the project implementation process, forming project execution trajectory data. This makes the project execution process traceable and enhances the process control capabilities of collaborative project execution. A project quality assessment module evaluates the quality of the project implementation process and deliverables based on the project execution trajectory data. It generates monitoring or alert information when abnormal states or risk conditions are detected, enabling timely identification and control of project operation risks, thereby improving overall project operational efficiency and delivery quality.

[0026] This application provides a demand-driven project operation collaborative management system, relating to the field of project operation management technology. This demand-driven project operation collaborative management system can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing a demand-driven project operation collaborative management system, but is not limited to the above forms.

[0027] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0028] Figure 1 This is a schematic diagram of an optional module of a demand-driven project operation collaborative management system provided in an embodiment of this application. Figure 1 The system may include, but is not limited to: The requirements management module is used to receive project requirements initiated by users, perform structured parsing of project requirements, generate requirement data, and build user profiles corresponding to the requirement data. The requirement data includes user type information, professional field information, and basic project information.

[0029] Among them, reference Figure 2 As shown, the requirements management module includes: The requirement parsing unit is used to obtain project requirements initiated by users, perform structured parsing of project requirements, and generate requirement element data. The demand modeling unit is used to standardize and encode demand element data to build the corresponding demand data model. The user profile building unit is used to generate user profiles corresponding to project requirements based on the requirement data model, and to establish a connection between the user profiles and the requirement data. The requirement output unit is used to validate the requirement data and user profile, and output the requirement data after the validation is passed.

[0030] Standardize and encode the demand element data to construct the corresponding demand data model, including: The demand element data is categorized into customer type elements, professional field elements, and project basic elements. Based on the preset demand element coding rules, various types of demand element data are uniformly identified and coded to generate structured demand coding data; Map the hierarchical relationships of the demand coding data, establish the association between demand elements, and form a hierarchical structure of demand elements; Based on the demand coding data and the hierarchical structure of demand elements, a standardized demand data model is constructed.

[0031] In this embodiment, the requirements management module serves as the initial stage of the project operation process. It is responsible for structuring user-initiated project requirements and outputting standardized requirement data. The system first receives project requirement information input by the user through the requirement submission interface. This requirement information includes at least a project background description, expected service content, and the user's basic attribute information. Upon receiving this requirement information, the requirements management module generates a corresponding project requirement form, which serves as the basic data carrier for subsequent processing.

[0032] Specifically, the requirement parsing unit in the requirement management module parses the project requirement form, breaking down the user-input requirements into requirement element data. Requirement element data includes at least customer type elements, professional field elements, and project basic elements. Customer type elements reflect the user's customer category level, professional field elements identify the professional direction involved in the project, and project basic elements describe basic information such as project name, timeline, and delivery scope.

[0033] After the requirement elements are broken down, the requirement modeling unit in the requirement management module performs standardized coding on the requirement element data. First, based on preset requirement element coding rules, the requirement modeling unit uniformly identifies and codes customer type elements, professional domain elements, and project basic elements, generating structured requirement coding data. Then, it maps the requirement coding data to the corresponding hierarchical structure, establishing the association between the customer type hierarchical structure and the professional domain hierarchical structure, thereby forming a requirement element structure with a clear hierarchical relationship.

[0034] Based on the demand coding data and the hierarchical structure of demand elements, the demand modeling unit constructs a standardized demand data model. This demand data model includes at least demand type information, professional domain information, and customer attribute information, and manages basic project information as associated fields in a unified manner, giving project requirements a unified data structure and computable characteristics.

[0035] After the requirement data model is built, the user profile building unit in the requirement management module generates user profiles corresponding to the project requirements based on the requirement data model. The user profiles are based on basic customer information and are associated with customer type level identifiers and professional field level identifiers, thereby forming user profile data that corresponds one-to-one with the project requirements, and establishing a binding relationship between the user profiles and the requirement data model.

[0036] Finally, the requirement output unit in the requirement management module performs integrity verification on the requirement data model and user profile. When the verification confirms that the customer type elements, professional field elements and project basic elements are all complete and the coding is valid, the requirement data and user profile are published as a unified requirement output object, providing standardized input for subsequent project matching and project implementation processes.

[0037] The project matching module is used to match and calculate the roles, qualifications, professional capabilities, and project resources of project participants based on demand data and user profiles, determine the project implementation entity, and generate project resource allocation results. Among them, reference Figure 3 As shown, the project matching module includes: The resource qualification modeling unit is used to standardize the role types, professional qualification levels and service capabilities of project participants and project resources, and generate corresponding resource qualification models. The matching rule calculation unit is used to perform matching calculations based on demand data, customer profiles and resource qualification models, according to preset multi-dimensional matching rules, to generate a set of candidate project implementation entities. The priority determination unit is used to evaluate the priority of the candidate project implementation entities and generate target project implementation entities based on preset indicators, including qualification matching degree, historical project performance and response time. The matching result output unit is used to associate the target project implementation entity with the requirement data and output the project resource allocation result.

[0038] In this embodiment, the project matching module is used to match project participants and project resources after the requirements management module outputs requirements data and user profiles, thereby determining the project implementation entity and generating project resource allocation results. The project matching module takes structured requirements data (including customer type information, professional field information, and basic project information) and corresponding user profiles as input, and serves as the core connecting module for the project to move from the requirements phase to the implementation phase.

[0039] Specifically, the project matching module first performs standardized modeling of project participants and resources registered in the system using a resource qualification modeling unit. The modeling process includes at least the standardized organization of role types, professional qualification levels, and service capability information for project participants. Role types differentiate between project leaders, professional executors, and business collaborators; professional qualification levels reflect their competence levels within their respective professional fields; and service capability information characterizes the types of projects and service scope they can undertake. Through this process, a corresponding resource qualification model is generated for each individual or resource.

[0040] After completing the resource qualification modeling, the project matching module performs multi-dimensional matching calculations based on the demand data, user profiles, and resource qualification model through the matching rule calculation unit. The system compares the customer type information and professional field information in the demand data with the corresponding fields in the resource qualification model. When it detects that project participants do not meet the required role qualifications or professional field requirements of the project, the corresponding personnel are directly excluded; personnel who meet the basic qualification conditions are included in the candidate project implementation entity set to ensure that the matching results are executable.

[0041] Subsequently, the project matching module prioritizes the candidate project implementation entities through a priority determination unit, generating the final target project implementation entity. The priority assessment is based on a comprehensive judgment of indicators such as qualification matching, historical project performance, and response timeliness, selecting the implementation entity that best meets the current project requirements. Finally, the matching result output unit associates the target project implementation entity with corresponding requirement data, outputting the project resource allocation result, which serves as the basis for the subsequent project collaborative execution module to carry out project implementation.

[0042] Based on demand data, customer profiles, and resource qualification models, matching calculations are performed according to preset multi-dimensional matching rules to generate a set of candidate project implementation entities, including: Based on demand data, qualification constraint matching is performed on the role type, professional field matching relationship and qualification level in the resource qualification model to screen out candidate resource objects that meet the basic qualification conditions; By combining historical service characteristics and project complexity characteristics in the customer profile, the capability suitability of candidate resource objects is calculated, and corresponding capability matching scores are generated. Based on the preset multi-dimensional matching weight rules, the qualification matching results, ability matching scores and historical project performance indicators are weighted and calculated to generate a comprehensive matching score result. Based on the comprehensive matching score results, the resource objects that meet the preset threshold conditions are selected and sorted to form a set of candidate project implementation entities.

[0043] In this embodiment, the system first performs qualification constraint matching on project participants in the resource qualification model based on the demand data. Specifically, the system extracts the customer type information, professional field information, and role requirements required for the project from the demand data, and performs alignment and verification with the personnel role types, professional field coverage, and qualification levels recorded in the resource qualification model. For resource objects that do not meet the required role type, professional field matching relationship, or minimum qualification level requirements, the system directly excludes them according to hard constraint rules, retaining only resource objects that meet the basic qualification conditions, forming a preliminary set of candidate resource objects.

[0044] After completing the basic qualification screening, the system further evaluates the suitability of candidate resource objects for execution capabilities based on customer profiles. In practice, the system obtains historical service feature information from customer profiles and makes a comprehensive judgment on project complexity by combining it with basic project information. Subsequently, it compares the historical service features and project complexity features with the service capability information of candidate resource objects to evaluate their suitability in the current project scenario. This generates a corresponding capability matching score for each candidate resource object to reflect its adaptability to the current project requirements.

[0045] Based on this, the system uses preset multi-dimensional matching weight rules to weight the aforementioned qualification matching results, capability matching scores, and historical project performance indicators of candidate resources, generating a comprehensive matching score. The multi-dimensional matching weight rules are used to balance the influence of different evaluation dimensions in the comprehensive score and can be configured and adjusted according to project type or business scenario, ensuring that the comprehensive matching score truly reflects the candidate resources' overall performance in terms of qualifications, capabilities, and contract performance stability.

[0046] Finally, the system sorts the candidate resource objects based on the comprehensive matching score and filters them according to preset threshold conditions. The system prioritizes resource objects whose comprehensive matching scores meet the threshold requirements, and incorporates response time and current resource load into the sorting process to form the final set of candidate project implementation entities, which serves as the input for the subsequent target implementation entity determination process.

[0047] Multidimensional matching weight rules include: Based on different project needs and professional fields, pre-set the weight parameters corresponding to qualification matching results, ability matching scores, and historical project performance indicators; The weight parameters are adaptively adjusted based on the project complexity level and service timeliness requirements. When there are preset qualification threshold constraints, the corresponding qualification matching dimension is set as a strong constraint weight so that resource objects that do not meet the qualification threshold will not participate in the comprehensive matching score calculation. The weight parameters are updated and corrected based on the feedback data generated from the project execution results.

[0048] In this embodiment, the system pre-sets multi-dimensional matching weight rules for different project requirement types and professional field categories. Specifically, in the matching rule configuration layer, the system uses project requirement type and professional field category as distinguishing conditions to configure corresponding weight parameters for qualification matching results, ability matching scores, and historical project performance indicators, and manages them uniformly in a configurable manner. This allows different types of projects to load weight combinations that match their business characteristics, thereby achieving differentiated application of the matching strategy.

[0049] During the specific project matching process, the system comprehensively assesses the project's complexity level and service timeliness requirements based on basic project information and customer profile characteristics, and adaptively adjusts the weighting parameters accordingly. For projects with higher complexity or stricter delivery time requirements, the system increases the weighting of dimensions related to capability adaptability and contract fulfillment stability; for projects with lower complexity or routine services, the system maintains a weighting allocation primarily based on basic qualifications and routine matching dimensions to ensure that the matching results are commensurate with the actual project implementation difficulty.

[0050] When project requirements include explicit qualification threshold constraints, the system sets the corresponding qualification matching dimension as a strong constraint weight and prioritizes the qualification verification process. In practice, resource objects that do not meet the requirements for role type, professional field coverage, or minimum qualification level will be directly eliminated and will not participate in the subsequent comprehensive matching score calculation, thereby ensuring that all resource objects entering the matching result range meet the basic compliance and capability prerequisites for project implementation.

[0051] After project completion, the system generates feedback data based on the project execution trajectory, quality review results, and delivery feedback. This feedback data is then used to update and revise the multi-dimensional matching weight rules. Specifically, the system stores project execution results and the implementing entity's performance as historical performance data. Combined with the overall execution of similar projects, the system iteratively adjusts the weight parameters of relevant dimensions, thereby continuously optimizing the multi-dimensional matching weight rules through ongoing use and forming a closed-loop improvement mechanism for the matching strategy.

[0052] The project collaborative execution module is used to build a project workspace based on the project resource allocation results, record the process and track the status of the project implementation, and form project execution trajectory data. In this embodiment, the project collaborative execution module is used to uniformly host and collaboratively manage project resources during the project implementation phase, and serves as the core working platform for project execution. After receiving the project resource configuration results generated by the project matching module, this module automatically generates a unique project workspace for the corresponding project instance and binds the project implementation entity, collaborators, and related resources to the project workspace.

[0053] Specifically, the project workspace is used to centrally host various business elements in the project implementation process, including project member information, project phase divisions, task execution nodes, and project collaboration tools. Based on the project type and implementation plan, the system pre-sets corresponding process templates and collaboration tools within the project workspace, enabling project members to complete operations such as solution development, communication and collaboration, task advancement, and deliverables in a unified environment.

[0054] During project execution, the project collaboration module continuously records all actions taken by project members within the project workspace. These actions include at least task status changes, project file uploads and modifications, communication and information exchange, meeting or training participation records, and on-site work-related records. These actions are organized and stored chronologically to form project execution trajectory data, reflecting the complete status changes throughout the project implementation process.

[0055] Through this implementation method, the project collaborative execution module realizes the online, structured, and full-process traceability of the project implementation process, making the project execution behavior fully traceable and providing a reliable data foundation for subsequent project quality assessment, risk analysis, and project review.

[0056] The project quality assessment module is used to assess the quality of the project implementation process and deliverables based on project execution trajectory data, generate project quality assessment results, and generate corresponding monitoring or prompt information when abnormal states or risk conditions are detected.

[0057] Among them, reference Figure 4 As shown, the project quality assessment module includes: The quality indicator construction unit is used to construct project quality assessment indicators based on project execution trajectory data and according to preset assessment rules. The project quality assessment indicators include schedule compliance, delivery completeness, process compliance, and user feedback indicators. The quality scoring unit is used to calculate the project execution trajectory data based on the project quality assessment indicators and generate the project quality score results. The anomaly detection unit is used to compare the project quality score with a preset threshold to determine whether the project is in an abnormal or risky state. The results output unit is used to output the project quality score results and generate corresponding monitoring or prompt information when an abnormal or risky state is determined to exist.

[0058] In this embodiment, the project quality assessment module is used to evaluate the quality of the project execution process and delivery results during project implementation and after project delivery, and to automatically identify and alert on abnormal and risky states. The project quality assessment module uses the project execution trajectory data generated by the project collaborative execution module as its core input. This data includes at least task progress records, phase delivery records, communication and collaboration records, and user feedback information, providing a comprehensive data foundation for quality assessment.

[0059] Specifically, the project quality assessment module first constructs project quality assessment indicators based on project execution trajectory data through a quality indicator construction unit. This unit collects and organizes key node data from the project execution process according to pre-defined quality assessment rules, forming a multi-dimensional indicator system to reflect the project implementation quality. The project quality assessment indicators include at least the following: schedule compliance indicator, reflecting the degree to which the actual project progress matches the planned milestones; delivery completeness indicator, reflecting whether the project deliverables are consistent with the established delivery requirements; process compliance indicator, reflecting whether the project implementation process conforms to pre-defined procedures and standards; and user feedback indicator, reflecting customer satisfaction during the project implementation and delivery phases.

[0060] After constructing the quality assessment indicators, the project quality assessment module processes the project execution trajectory data through a quality scoring unit. Based on the assessment results of each quality assessment indicator, the quality scoring unit comprehensively analyzes the project implementation process and deliverables, generating corresponding project quality scores. These scores reflect the project's quality status at the current stage or throughout its overall lifecycle and serve as a crucial basis for subsequent anomaly detection.

[0061] Subsequently, the project quality assessment module compares the project quality score with preset thresholds using an anomaly detection unit to determine whether the project is in an abnormal or risky state. When a project quality score is detected to be below the corresponding threshold, or a key quality indicator shows a significant deviation, the system marks the project as abnormal or risky, indicating potential issues with the project's schedule, quality, or compliance.

[0062] Finally, the project quality assessment module outputs the project quality score through the results output unit, and generates corresponding monitoring or alert information when abnormal or risky conditions are identified. This monitoring or alert information can be pushed to project managers, project implementers, or relevant responsible persons to prompt them to pay attention to and address project risks in a timely manner, thereby achieving process-oriented monitoring of project quality and proactive intervention in problem-solving.

[0063] The system also includes a permission security control module, which controls the data access and operation permissions of different project participants based on a role-based permission model.

[0064] In this embodiment, the access control module is used to finely control the data access permissions and operation permissions of different project participants during project operation, so as to ensure project data security and clear project management boundaries.

[0065] Specifically, the access control module configures user permissions based on a role-based access control model. Different users are assigned different roles, such as project manager, project member, project enabler, or project manager, according to their responsibilities in the project. Each role corresponds to a preset set of permissions, which limits the scope of data they can access and the types of operations they can perform in the project workbench.

[0066] Regarding data access control, the permission security control module ensures that users can only access data content within projects they are involved in through project-level data isolation and row-level permission control mechanisms. When performing data queries, the system dynamically generates data filtering conditions based on the user's organization, role type, and project relationships, thereby achieving data isolation between different projects and differentiating data visibility between different roles within the same project.

[0067] Regarding access control, the access security control module performs real-time verification of users' critical operations, including project configuration modifications, resource adjustments, and quality review-related operations. When it detects that a user does not have the corresponding permissions, the system automatically restricts their operations, allowing them only to view or record data, thus preventing unauthorized project interference.

[0068] Furthermore, the access control module audits and records all access-related operations, creating a complete operation log for subsequent security audits and anomaly tracing. Through these implementation methods, data security control and accountability traceability are achieved in multi-role, multi-project parallel scenarios during project operation.

[0069] Please see Figure 5 This application also provides an implementation method for the above-described system, the method comprising the following steps: S1: Receive project requests initiated by users; S2: Perform structured parsing of project requirements, generate requirement data, and construct user profiles corresponding to the requirement data; S3: Based on demand data and user profiles, match and calculate the roles, qualifications, professional capabilities, and project resources of project participants to determine the project implementation entity and generate project resource allocation results; S4: Construct the project workspace based on the project resource allocation results; S5: Based on the project workspace, record the process and track the status of the project implementation to form project execution trajectory data; S6: Based on project execution trajectory data, perform quality assessment on the project implementation process and delivery results, generate project quality assessment results, and generate corresponding monitoring or prompt information when abnormal states or risk conditions are detected.

[0070] It is understood that the content of the above system embodiments is applicable to this method embodiment. The specific functions implemented in this method embodiment are the same as those in the above system embodiments, and the beneficial effects achieved are also the same as those achieved in the above system embodiments.

[0071] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the system described above. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0072] It is understood that the content of the above system embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above system embodiments, and the beneficial effects achieved are also the same as those achieved by the above system embodiments.

[0073] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the system described above.

[0074] It is understood that the content of the above system embodiments is applicable to this storage medium embodiment. The specific functions implemented by this storage medium embodiment are the same as those of the above system embodiments, and the beneficial effects achieved are also the same as those achieved by the above system embodiments.

[0075] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the system described above.

[0076] It is understood that the content of the above system embodiments is applicable to the present program product embodiments. The specific functions implemented by the present program product embodiments are the same as those of the above system embodiments, and the beneficial effects achieved are also the same as those achieved by the above system embodiments.

[0077] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0078] This application provides a demand-driven project operation collaborative management system and method. The solution uses a demand management module to structurally analyze user-initiated project demands and construct user profiles corresponding to the demand data. This transforms subjective descriptions of project demands into standardized data, reducing misunderstandings and improving the accuracy and consistency of demand acquisition. A project matching module, based on demand data and user profiles, calculates and matches the roles, qualifications, professional abilities, and project resources of project participants, generating project resource allocation results. This ensures the rational determination of project implementation entities and resources, improving the efficiency of project resource allocation. A project collaborative execution module constructs a project workspace based on the project resource allocation results, records and tracks the project implementation process, forming project execution trajectory data. This makes the project execution process traceable and enhances the process control capabilities of collaborative project execution. A project quality assessment module evaluates the quality of the project implementation process and deliverables based on the project execution trajectory data. It generates monitoring or alert information when abnormal states or risk conditions are detected, enabling timely identification and control of project operation risks, thereby improving overall project operational efficiency and delivery quality.

[0079] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0080] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0081] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0082] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0083] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A demand-driven project operation collaborative management system, characterized in that, The system includes: The requirements management module is used to receive project requirements initiated by users, perform structured parsing of the project requirements, generate requirement data, and construct user profiles corresponding to the requirement data. The project matching module is used to perform matching calculations on the role qualifications, professional capabilities and project resources of project participants based on the demand data and the user profile, to determine the project implementation entity and generate project resource allocation results. The project collaborative execution module is used to construct a project workspace based on the project resource configuration results, record the process and track the status of the project implementation, and form project execution trajectory data. The project quality assessment module is used to assess the quality of the project implementation process and delivery results based on the project execution trajectory data, generate project quality assessment results, and generate corresponding monitoring or prompt information when abnormal states or risk conditions are detected.

2. The system according to claim 1, characterized in that, The required data includes user type information, professional field information, and basic project information.

3. The system according to claim 1, characterized in that, The demand management module includes: The requirement parsing unit is used to obtain the project requirements initiated by the user, perform structured parsing of the project requirements, and generate requirement element data. The demand modeling unit is used to standardize and encode the demand element data to construct the corresponding demand data model. A user profile building unit is used to generate a user profile corresponding to the project requirements based on the requirement data model, and to establish a connection between the user profile and the requirement data. The demand output unit is used to verify the demand data and the user profile, and output the demand data after the verification is successful.

4. The system according to claim 3, characterized in that, The standardization and coding process for the demand element data, and the construction of the corresponding demand data model, includes: The demand element data is categorized into customer type elements, professional field elements, and project basic elements. Based on the preset demand element coding rules, each type of demand element data is uniformly identified and coded to generate structured demand coding data. The demand coding data is mapped hierarchically to establish the relationships between demand elements and form a hierarchical structure of demand elements. Based on the demand coding data and the demand element hierarchy, a standardized demand data model is constructed.

5. The system according to claim 1, characterized in that, The project matching module includes: The resource qualification modeling unit is used to standardize the role types, professional qualification levels and service capabilities of project participants and project resources, and generate corresponding resource qualification models. The matching rule calculation unit is used to perform matching calculations based on the demand data, the customer profile and the resource qualification model, according to preset multi-dimensional matching rules, to generate a set of candidate project implementation entities. The priority determination unit is used to evaluate the priority of the candidate project implementation entity set and generate the target project implementation entity according to preset indicators; the preset indicators include qualification matching degree, historical project performance and response time. The matching result output unit is used to associate the target project implementation entity with the requirement data and output the project resource configuration result.

6. The system according to claim 5, characterized in that, Based on the demand data, the customer profile, and the resource qualification model, a matching calculation is performed according to preset multi-dimensional matching rules to generate a set of candidate project implementation entities, including: Based on the demand data, qualification constraint matching is performed on the role type, professional field matching relationship and qualification level in the resource qualification model to filter out candidate resource objects that meet the basic qualification conditions; Based on the historical service characteristics and project complexity characteristics in the customer profile, the capability adaptability of the candidate resource objects is calculated to generate a corresponding capability matching score. Based on the preset multidimensional matching weight rules, the qualification matching result, the ability matching score, and the historical project performance indicators are weighted and calculated to generate a comprehensive matching score result. The results of the comprehensive matching score are sorted, and resource objects that meet the preset threshold conditions are selected to form the candidate project implementation entity set.

7. The system according to claim 6, characterized in that, The multidimensional matching weight rules include: Based on different project needs and professional fields, pre-set the weight parameters corresponding to qualification matching results, ability matching scores, and historical project performance indicators; The weight parameters are adaptively adjusted based on the project complexity level and service timeliness requirements. When there is a preset qualification threshold constraint, the corresponding qualification matching dimension is set as a strong constraint weight so that resource objects that do not meet the qualification threshold will not participate in the comprehensive matching score calculation. The weight parameters are updated and corrected based on the feedback data generated from the project execution results.

8. The system according to claim 1, characterized in that, The project quality assessment module includes: The quality indicator construction unit is used to construct project quality assessment indicators based on the project execution trajectory data and according to preset assessment rules; the project quality assessment indicators include schedule compliance, delivery completeness, process compliance, and user feedback indicators. The quality scoring unit is used to calculate the project execution trajectory data based on the project quality assessment indicators and generate a project quality score result. An anomaly determination unit is used to compare the project quality score result with a preset threshold to determine whether the project is in an abnormal or risky state. The result output unit is used to output the project quality score result and generate corresponding monitoring or prompt information when it is determined that there is an abnormal or risky state.

9. The system according to claim 1, characterized in that, It also includes a permission security control module, which is used to control the data access permissions and operation permissions of different project participants based on the role-based permission model.

10. A method for implementing the system according to any one of claims 1-9, characterized in that, The method includes the following steps: Receive project requests initiated by users; The project requirements are structured and parsed to generate requirement data, and user profiles corresponding to the requirement data are constructed. Based on the demand data and the user profile, the roles, qualifications, professional abilities and project resources of the project participants are matched and calculated to determine the project implementation entity and generate project resource allocation results. The project workspace is constructed based on the project resource allocation results. Based on the project workspace, the project implementation process is recorded and its status is tracked to form project execution trajectory data. Based on the project execution trajectory data, the project implementation process and delivery results are evaluated for quality, project quality evaluation results are generated, and corresponding monitoring or prompt information is generated when abnormal states or risk conditions are detected.

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