Project collaborative management method

Abstract

The invention discloses a project collaborative management method, and relates to the technical field of project management data processing. The method comprises the steps of determining a preset standard template library corresponding to a target project type in response to a management instruction of a target project; based on a preset standard template library, establishing an association relationship between the cost item of the target project and the progress task item of the target project; according to the association relationship and the actual execution data of the target project, constructing a collaborative analysis model reflecting the execution state of the target project; generating a cash flow table of the target project based on the collaborative analysis model, and predicting a future cash flow trend of the target project by using a time sequence analysis model; and identifying the execution risk of the target project through a preset collaborative judgment logic and triggering a corresponding risk early warning signal. According to the scheme, combined management of cost, funds and progress can be carried out on the project, and help is provided for improving project management efficiency and finding risk items in time.

Description

Technical Field

[0001] This invention relates to the field of project management data processing technology, and in particular to a project collaborative management method. Background Technology

[0002] Project management is the core of process management, and its key elements include cost control, schedule management, and cash flow monitoring. These elements directly affect the project's economic benefits and time constraints. In existing technologies, project management platforms typically employ a single-line management approach for cost, schedule, and cash, meaning these three elements are handled independently without an effective linkage mechanism. For example, one company's project management platform operates cost, schedule, and cash as independent modules: cost management focuses only on budgets and actual expenditures, schedule management tracks task completion, and cash management handles payment and receipt records separately. This separate management approach leads to a disconnect between business operations and data collection, resulting in inconsistencies between business and financial data. Specifically, cost data updates lag behind schedule changes, and cash receipts and payments records cannot reflect the project's actual progress in real time, causing distorted revenue and expenditure comparisons, delayed data collection, and inconsistencies between business and financial data. Furthermore, due to the lack of an automatic linkage mechanism, project execution risks (such as cost overruns, schedule delays, or cash shortages) cannot be promptly warned of. Managers can only rely on manual calculations and periodic reports to assess project status, which not only reduces management efficiency but also increases the risk of project failure.

[0003] Some improvement solutions attempt to partially integrate cost, schedule, and funding data through data interfaces or simple mappings. However, these solutions typically rely on manual configuration or static rules, failing to achieve dynamic correlation control. For example, some systems allow users to manually correlate cost items with schedule tasks, but this correlation is a weak mapping, unable to automatically adapt to project changes, and suffers from poor data consistency. Furthermore, cash flow forecasting is often based on historical data or extrapolation, failing to incorporate real-time schedule and cost data, resulting in low forecast accuracy. The root cause of these deficiencies lies in the lack of a unified, standardized data structure and strong correlation logic, making it impossible to automatically synchronize and interactively reference cost, schedule, and funding data.

[0004] How to jointly manage project costs, funding, and schedule is a key research topic in the industry. Summary of the Invention

[0005] This invention provides a project collaborative management method for joint management of project costs, funds, and schedules, thereby improving project management efficiency and helping to identify risks in a timely manner.

[0006] According to one aspect of the present invention, a project collaborative management method is provided, the method comprising:

[0007] In response to the management instructions of the target project, determine the target project type of the target project, and determine the preset standard template library corresponding to the target project type;

[0008] Based on the preset standard template library, a set of cost items and a set of schedule task items for the target project are generated, and the association between the cost items and the schedule task items of the target project is established.

[0009] Based on the aforementioned relationships and the actual execution data obtained during the execution of the target project, a collaborative analysis model reflecting the execution status of the target project is constructed.

[0010] Based on the collaborative analysis model, a cash flow statement for the target project is generated, and a time series analysis model is used to predict the future cash flow trend of the target project.

[0011] The system identifies the execution risks of the target project through a pre-set collaborative judgment logic and triggers the corresponding risk warning signal.

[0012] The technical solution of this invention, in response to management instructions for a target project, determines the target project type and a preset standard template library corresponding to the target project type; based on the preset standard template library, it generates a set of cost items and a set of schedule task items for the target project, and establishes a correlation between the cost items and schedule task items of the target project; it can quickly generate cost items and schedule task items and establish their correlation, achieving deep integration and unified expression of cost, schedule, and funds; based on the correlation and actual execution data obtained during the execution of the target project, it constructs a collaborative analysis model reflecting the execution status of the target project; based on the collaborative analysis model, it generates a cash flow statement for the target project and uses a time series analysis model to predict the future cash flow trend of the target project; through preset collaborative judgment logic, it identifies the execution risks of the target project and triggers corresponding risk warning signals, enabling joint management of project costs, funds, and schedule, thus helping to improve project management efficiency and promptly identify risk items.

[0013] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart of a project collaborative management method provided in Embodiment 1 of the present invention;

[0016] Figure 2 This is a flowchart of a project collaborative management method provided according to Embodiment 2 of the present invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 the invention 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.

[0019] Example 1

[0020] Figure 1 This is a flowchart of a project collaborative management method according to Embodiment 1 of the present invention. This embodiment is applicable to situations involving collaborative management and control of projects. The method can be executed by a project collaborative management device, which can be implemented in hardware and / or software. This project collaborative management device can be configured in electronic devices such as computers, servers, or tablet computers. Figure 1 As shown, the method includes:

[0021] Step 110: In response to the management instructions of the target project, determine the target project type and determine the preset standard template library corresponding to the target project type.

[0022] The target project can be a specific engineering project, R&D project, or business implementation project that requires collaborative management. It has a clear scope, budget, schedule, and execution process, such as a data center construction project or a software platform development project. This embodiment does not limit it.

[0023] The target project type can be a classification identifier for the target project based on industry attributes, implementation mode, or management characteristics, used to match the corresponding management template. Examples include power construction projects, building projects, computer system integration projects, and manufacturing production line construction projects. This type determines the cost structure, task decomposition method, and contract management rules that the project should adopt.

[0024] The preset standard template library can be a pre-built, structured data collection that corresponds one-to-one with the project type. It includes standardized cost item templates (e.g., cost account codes, budget fields), schedule task item templates (e.g., task codes, planned time), etc., which can be used to quickly initialize the basic management framework of a new project.

[0025] Optionally, in this embodiment, the preset standard template library may include: a standard cost item template library, a standard schedule task item template library, and a standard contract data template library; the standard cost item template library includes cost item code, cost item name, budget amount, and cost type; the standard schedule task item template library includes task code, task name, planned start time, planned end time, and task weight; the standard contract data template library includes contract code, contract amount, payment terms, and contract type.

[0026] Optionally, in this embodiment, after receiving an instruction to manage a target project, the target project pointed to by the instruction can be parsed first. Further, by reading the project's metadata (e.g., industry sector, deliverable type, contract type, historical similar project tags, etc.), and using preset classification rules or a lightweight classification model, the target project type can be determined (e.g., general contracting power project, construction project, agile software development project, or equipment procurement and installation project, etc.). It is understood that the project type is essentially a semantic tag used to index a preset standard template library pre-built and persistently stored in the system. This template library is a standardized management meta-model organized in structured data form, containing a set of cost item definitions, a set of schedule task item definitions, and optional contract and fund management specifications applicable to this type of project.

[0027] In one optional implementation of this embodiment, a standard cost item template library, a standard schedule task item template library, and a standard contract data template library can be established according to project type. The standard cost item template library includes information such as cost item code, cost item name, budget amount, and cost type, ensuring that all cost items are consistent and standardized. The standard schedule task item template library includes task code, task name, planned start time, planned end time, and task weight, facilitating accurate tracking of project progress. The establishment of this standardized template library effectively improves the systematization and standardization of project management, reducing data entry errors and information inconsistencies.

[0028] Optionally, in this embodiment, determining the preset standard template library corresponding to the target project type may include: acquiring historical project data, including cost records, schedule records, and contract records; cleaning and classifying the historical project data, with the classification based on the industry type to which the project belongs; based on the classified data, using cluster analysis to summarize the common characteristics of cost items and schedule task items for each project type; constructing a standard cost item template library based on the common characteristics of cost items, with cost item codes represented in a hierarchical structure; and constructing a standard schedule task item template library based on the common characteristics of schedule task items, with task weights calculated as the ratio of task duration to the total project duration.

[0029] In one optional implementation of this embodiment, historical project data of completed projects can be obtained in batches from an enterprise project management database or a historical project knowledge base. The data includes structured cost records (e.g., actual expenditure details of each cost item), progress records (e.g., actual start / end time and completion status of tasks), and contract records (e.g., contract amount, payment nodes, and supplier information). Subsequently, the obtained data is cleaned, including missing value filling, outlier removal, and field standardization (e.g., unified time format, currency unit, and task naming conventions). The projects are then tagged and classified according to a predefined industry classification system (e.g., power, construction, manufacturing, or energy).

[0030] Based on this, for each project subset, unsupervised clustering analysis algorithms can be applied to cost items and schedule task items respectively to identify frequently occurring and structurally stable cost item combinations and task decomposition patterns, thereby extracting representative common features of cost items (e.g., typical cost items and their hierarchical relationships) and common features of schedule task items (e.g., standard task sequences and critical path structures). Finally, a standard cost item template library is constructed based on these common features, where cost item coding adopts a tree-like hierarchical structure (e.g., 1.0 Engineering Costs - 1.1 Building Construction Costs - 1.1.1 Civil Engineering) to support multi-level budget control. A standard schedule task template library is also constructed, where the weight of each task is dynamically calculated based on the proportion of its planned duration to the total project duration (i.e., task weight = planned task duration / total planned project duration), which is used for subsequent schedule performance evaluation and resource allocation.

[0031] Furthermore, a standard schedule task item template library can be constructed based on the common characteristics of schedule task items. Each task item includes basic information such as task code, task name, planned start time, and planned end time. Task weight is calculated as the ratio of task duration to the total project duration. This means that the weight value of each task is evaluated based on its proportion of the total time, thus reflecting the importance of the task in the overall project schedule. For example, if a task's duration accounts for 30% of the total project duration, then the weight of that task is 30%. This calculation method can help to allocate resources more rationally and manage priorities.

[0032] For example, taking a large engineering group as an example, historical data was extracted from 200 projects completed over the past five years. After cleaning, the data was divided into two groups by industry: building construction and data center projects. Cluster analysis of the data center project subset revealed that over 90% of the projects included core tasks such as server room renovation, uninterruptible power supply (UPS) installation, cold aisle deployment, and network debugging. Furthermore, the cost structure generally included items such as equipment purchase costs (approximately 65%), installation and commissioning costs (approximately 20%), and design consulting fees (approximately 10%). Based on this, a standard template for data center projects can be automatically generated: cost item coding is set to a three-level structure, and the schedule task template includes the aforementioned high-frequency tasks. This template can then be directly used for the rapid initialization of new data center projects.

[0033] It should be noted that in this embodiment, the data for each item is obtained only after user authorization, and the method of acquisition is reasonable and legal.

[0034] Step 120: Based on the preset standard template library, generate the cost item set and schedule task set of the target project, and establish the association between the cost items and schedule task items of the target project.

[0035] Optionally, in this embodiment, after determining the preset standard template library corresponding to the target project type of the target project, a set of cost items and a set of schedule task items for the target project can be generated based on the determined preset standard library; furthermore, the association between the cost items and the schedule task items of the target project can be established.

[0036] The cost item set is a set of cost management units specific to the target project. It is generated by instantiating a standard cost item template. Each cost item corresponds to an accounting or management dimension that can independently aggregate budgets and actual expenditures.

[0037] The schedule task set is a concrete manifestation of the target project's WBS (Work Breakdown Structure). It is instantiated from the standard schedule task template, and each task represents an executable, traceable, and acceptable work package.

[0038] The relationship refers to the mapping and binding established between cost items and schedule task items. It is usually a one-to-many or many-to-one relationship, used to realize the dynamic linkage between cost occurrence and task execution.

[0039] In an optional implementation of this embodiment, after determining the target project type and loading the corresponding preset standard template library, the standard cost item template and schedule task item template in the template library can be instantiated to generate a cost item set and a schedule task item set specific to the target project. Each cost item inherits attributes such as subject code, budget amount, and cost type from the template, and each schedule task item inherits planning parameters such as task code, planned start / end time, and task weight.

[0040] Furthermore, based on predefined business mapping rules, strong semantic relationships can be automatically established between cost items and schedule task items, and a mapping table can be created to record the coding correspondence and mapping weight of each pair of related items.

[0041] In one optional implementation of this embodiment, a strong mapping relationship is established between cost items and schedule task items, with each cost item associated with at least one schedule task item. During association, the mapping weight is calculated based on the proportion of the cost item's budget amount in the overall project schedule budget. This mapping relationship ensures a close connection between project schedule and cost data, allowing changes in each cost to be directly reflected in changes in schedule tasks, thereby improving the accuracy of project budget control and ensuring close alignment between schedule and funding.

[0042] Step 130: Based on the correlation and the actual execution data obtained during the execution of the target project, construct a collaborative analysis model that reflects the execution status of the target project.

[0043] In this embodiment, after determining the correlation between the cost items and the schedule tasks of the target project, a collaborative analysis model reflecting the execution status of the target project can be constructed based on the correlation and the actual execution data obtained during the execution of the target project.

[0044] The actual execution data items can be dynamic operational data collected in real time by business systems (such as Enterprise Resource Planning (ERP), financial systems, and progress reporting platforms) during the implementation of the target project, including but not limited to: actual cost expenditure records, contract payment execution status, actual start / end time of tasks, work hour reporting, and cash inflow and outflow, etc. This embodiment does not limit them.

[0045] In this embodiment, the collaborative analysis model is a unified state representation model that integrates multi-dimensional data such as cost, schedule, funds and contracts. Its core is to align, aggregate and structure heterogeneous data that were originally scattered in different business modules, based on preset correlations, to form a digital twin of the project execution status with time consistency, logical consistency and computability, which is used to support advanced analysis functions such as risk identification and cash flow forecasting.

[0046] In one optional implementation of this embodiment, based on the established association between cost items and schedule task items, actual execution data is obtained from the project execution process, including actual cost expenditure records, contract payment execution records, and actual start and end times of tasks received through the data acquisition interface; the actual cost expenditure records are aggregated into the actual cost field in the cost data structure according to the cost account code; according to the correspondence between contract code and cost account code, the contract amount is decomposed into the corresponding cost item, and the actual payment amount in the contract data structure is updated in conjunction with the completion status of the schedule task items; the cash balance in the cash data structure is calculated based on the cumulative actual expenditure value in the cost data structure and the cumulative actual revenue value in the contract data structure; the actual start and end times of each task are obtained through the progress tracking module, the progress completion rate is calculated in conjunction with the planned working hours, and the progress deviation is calculated based on the difference between the actual end time and the planned end time; finally, the cost data structure, contract data structure, cash data structure, and schedule data structure are aligned and fused according to their association relationships to form a collaborative analysis model.

[0047] Step 140: Based on the collaborative analysis model, generate the cash flow statement of the target project, and use the time series analysis model to predict the future cash flow trend of the target project.

[0048] The time series analysis model can be a mathematical model used to process historical cash flow data sorted by time; for example, it can include moving average method and exponential smoothing method, whose input can be a historical net cash flow series and whose output can be the predicted value for several future periods.

[0049] Optionally, in this embodiment, the contract data structure and progress data structure can be read from the collaborative analysis model determined in the above steps. The contract data structure includes contract payment terms (including payment conditions, payment ratios, and planned payment times) and owner repayment terms associated with each cost item. The progress data structure includes the actual completion status or planned completion status of each progress task item. Based on the current completion status of the task item, it is determined whether the corresponding payment conditions are met. For payment terms that meet the conditions, the agreed amount is marked as a planned cash outflow and bound to the corresponding planned payment time point. Similarly, the planned cash inflow and its time point corresponding to the owner repayment are determined based on the milestone completion status. All confirmed planned cash inflow events and planned cash outflow events can be arranged in ascending order by timestamp and aggregated by daily, weekly, or monthly time granularity to generate a cash flow table containing a time column, cash inflow amount, cash outflow amount, and net cash flow (inflow minus outflow) field. Furthermore, the net cash flow values ​​for historical periods in the cash flow statement are extracted to form a one-dimensional time series. This series is then preprocessed, including imputation of missing values ​​and smoothing of outliers. The processed series is then input into a pre-loaded time series analysis model. This model fits historical patterns based on its internal algorithms (e.g., statistical models, machine learning models, or deep learning models) and performs forward inference, outputting a sequence of predicted net cash flow values ​​for the target project in a specified future period, thereby obtaining the future cash flow trend.

[0050] In one optional implementation of this embodiment, the set of schedule task items in the collaborative analysis model can be traversed. For each schedule task item, based on its relationship with the cost item, the corresponding payment and revenue terms in the contract data structure can be traced back to extract confirmed or planned cash inflow and cash outflow events. Each event record contains three core fields: amount, currency, and expected occurrence date. All events are sorted in ascending order by expected occurrence date and aggregated at the daily, weekly, or monthly granularity to generate a two-dimensional table containing a time column and a net cash flow column, which serves as the cash flow statement for the target project.

[0051] Furthermore, the net cash flow sequence over historical periods in the cash flow statement is extracted into a one-dimensional time series array and input into a pre-loaded time series analysis model instance. This model is a prediction algorithm container that supports univariate time series extrapolation, and its internal implementation can be any time series prediction method that conforms to the interface specification (e.g., statistical model, machine learning model, or deep learning model). After receiving the historical sequence, the model performs internal state initialization, parameter fitting, and forward inference processes, and outputs a future cash flow prediction sequence of length N, where each element corresponds to a predicted net cash flow value at a future time point. This prediction sequence, together with the cash flow statement, constitutes a complete description of the cash flow trend of the target project.

[0052] Step 150: Identify the execution risks of the target project through preset collaborative judgment logic and trigger the corresponding risk warning signal.

[0053] The preset collaborative judgment logic can be a set of pre-configured rule expressions or condition judgment procedures, used to jointly judge multiple indicators in the collaborative analysis model. For example, if the cost deviation is greater than threshold A and the schedule deviation is greater than threshold B, a composite risk signal is triggered.

[0054] Optionally, in this embodiment, structured data fields can be read from the collaborative analysis model determined in the above steps, including but not limited to: actual cost value and budgeted cost value under the cost dimension, actual task completion time and planned completion time under the schedule dimension, and current cash balance under the funding dimension; the above deviation value and balance value are used as input parameters and passed to a pre-configured collaborative judgment logic execution unit deployed in the system; the execution unit encapsulates a set of configurable judgment rules or conditional expressions, which are in the form of Boolean logic combinations, such as cost deviation greater than X and schedule deviation greater than Y or cash balance less than Z, where X, Y, and Z are preset constants or dynamic parameters; the execution unit performs rule-by-rule matching calculations on the input parameters, and when the condition of any rule is met, a structured risk warning signal object is generated, which contains a risk type identifier, trigger timestamp, associated project identifier, and original deviation value.

[0055] The technical solution of this embodiment, in response to the management instructions of the target project, determines the target project type and a preset standard template library corresponding to the target project type; based on the preset standard template library, it generates a set of cost items and a set of schedule task items for the target project, and establishes the association between the cost items and schedule task items of the target project; it can quickly generate cost items and schedule task items and establish their association, realizing the deep integration and unified expression of cost, schedule and funds; based on the association and the actual execution data obtained during the execution of the target project, it constructs a collaborative analysis model reflecting the execution status of the target project; based on the collaborative analysis model, it generates a cash flow statement for the target project, and uses a time series analysis model to predict the future cash flow trend of the target project; through preset collaborative judgment logic, it identifies the execution risks of the target project and triggers corresponding risk warning signals, enabling joint management of project costs, funds and schedule, helping to improve project management efficiency and timely identify risk items.

[0056] Example 2

[0057] Figure 2 This is a flowchart of a project collaborative management method according to Embodiment 2 of the present invention. This embodiment is a further refinement of the above technical solution, and the technical solution in this embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2 As shown, the method includes:

[0058] Step 210: In response to the management instructions of the target project, determine the target project type and determine the preset standard template library corresponding to the target project type.

[0059] Step 220: Based on the preset standard template library, generate the cost item set and schedule task set for the target project.

[0060] Optionally, in this embodiment, generating the cost item set and schedule task set of the target project based on a preset standard template library may include: calling a cost item template corresponding to the target project type from the preset standard template library and instantiating it to generate the cost item set of the target project; and calling a schedule task item template corresponding to the target project type from the preset standard template library and instantiating it to generate the schedule task set of the target project.

[0061] The cost item set includes cost item code, budget amount and cost type, etc.; the schedule task item set includes task code, planned start time, planned end time and task weight, etc., which are not limited in this embodiment.

[0062] In one optional implementation of this embodiment, based on the target project type, a set of cost item template records matching the target project type can be retrieved from a preset standard template library. This set is then iterated through, and each template record is instantiated—that is, a new cost item data object is created. The field values ​​from the template are copied to the corresponding attributes of this object, and a unique identifier for the target project is associated with it. All instantiated cost item objects are then aggregated into a cost item set for the target project. Similarly, based on the target project type, a corresponding set of schedule task item template records is retrieved from the preset standard template library. This set is then iterated through, and each template record is instantiated to generate a new schedule task item data object. Its attribute fields are populated, and it is bound to the target project. Finally, all instantiated schedule task item objects are combined into a schedule task item set for the target project.

[0063] The solution in this embodiment achieves automated construction of the project management infrastructure by calling cost item templates and schedule task item templates that match the target project type from a preset standard template library and instantiating them. This avoids manual entry of each item and ensures the standardization and consistency of the cost item system and schedule task decomposition. At the same time, the structured data generated based on the unified template provides a standardized and alignable data foundation for subsequent cost-schedule correlation, execution status modeling, and risk collaborative analysis, improving project initialization efficiency and management granularity.

[0064] Step 230: Establish the relationship between the cost items and the schedule tasks of the target project.

[0065] Optionally, in this embodiment, establishing the association between cost items and schedule task items of the target project may include: defining mapping rules, which are based on business logic relationships, mapping material procurement cost items to procurement task items, and labor cost items to construction task items; creating a mapping table, which stores cost item codes, task codes, and mapping weights; automatically loading the initial mapping relationship according to the mapping rules during the project initialization phase; and automatically triggering dynamic adjustment of the mapping relationship and recalculating the mapping weights of the affected cost items when schedule task items change during project execution.

[0066] In one possible implementation, the first step is to define mapping rules based on the business logic relationship between cost items and schedule tasks. The core of these mapping rules is to determine which schedule task corresponds to each type of cost item by analyzing the project's actual needs. For example, material procurement costs are typically closely related to procurement tasks, so mapping rules can associate material procurement costs with specific procurement tasks. Similarly, labor costs are usually related to construction tasks, and mapping rules need to ensure that labor costs are accurately mapped to their corresponding construction tasks. Through these mappings of business logic, a high degree of consistency and synergy between cost control and schedule management can be ensured.

[0067] Based on the defined mapping rules, a mapping table is created next. The main function of the mapping table is to store key information such as cost item codes, task codes, and mapping weights. Each cost item and schedule task item will have a corresponding mapping relationship in the table, and these mapping relationships also include mapping weights. Mapping weight is a quantitative indicator representing the strength of the association between a cost item and a schedule task item, typically determined by the ratio of task duration to cost. The mapping table provides data support for project execution, enabling the efficient and transparent display of the relationship between cost and schedule.

[0068] During the project initialization phase, the system automatically loads the initial mapping relationship between cost items and schedule tasks based on pre-defined mapping rules. This means that when the project starts, all known cost items and schedule tasks will automatically generate corresponding relationships based on business logic and be stored in the mapping table. This step reduces manual intervention and ensures that the project has a clear cost and schedule mapping framework from the beginning, laying the foundation for subsequent management and control.

[0069] During project execution, the mapping relationship needs to be dynamically adjusted as schedule tasks change. For example, if a schedule task is delayed for some reason, or its content changes, the previously mapped cost items may need to be reassessed and their mapping weights adjusted. The system automatically monitors these changes and triggers a dynamic adjustment mechanism to recalculate the mapping weights of the affected cost items. This process ensures that even if changes occur during project execution, the relationship between cost and schedule can still reflect the actual situation of the project in real time and accurately.

[0070] This embodiment's solution, by establishing a strong mapping relationship between cost items and schedule tasks, significantly improves the accuracy and flexibility of project management. First, the mapping rules, based on business logic, ensure a close connection between costs and schedules, avoiding deviations in cost and schedule management caused by misoperation or data distortion. Second, the mapping table clearly displays the association between each cost item and schedule task, facilitating real-time monitoring and adjustments by managers. During project execution, the dynamic adjustment mechanism of the mapping relationship ensures that project costs and schedules remain synchronized, responding promptly to project changes and reducing unnecessary waste and unreasonable resource allocation. Ultimately, this strong mapping relationship improves project management efficiency, enhances control and predictability during project execution, and provides a solid guarantee for the successful completion of the project.

[0071] Step 240: Based on the correlation and the actual execution data obtained during the execution of the target project, construct a collaborative analysis model that reflects the execution status of the target project.

[0072] Optionally, in this embodiment, a collaborative analysis model reflecting the execution status of the target project is constructed based on the correlation and the actual execution data obtained during the execution of the target project. This may include: obtaining actual cost expenditure records during the project execution process through a data acquisition interface, and aggregating the actual cost expenditure records into the actual cost field in the cost data structure according to the cost item code; associating the contract code with the cost item code, decomposing the contract amount into the corresponding cost item, and updating the actual payment amount in the contract data structure according to the completion status of the progress task item; accumulating the actual expenditure in the cost data structure and the actual income in the contract data structure to calculate the cash balance in the cash data structure; obtaining the actual start time and actual end time of the task through the progress tracking module, calculating the progress completion rate in combination with the planned working hours, and calculating the progress deviation based on the difference between the actual end time and the planned end time; and merging the cost data structure, contract data structure, cash data structure, and progress data structure based on the correlation to form a collaborative analysis model.

[0073] In this embodiment, the progress completion rate is calculated as follows: the actual completion time and planned completion time of the task are obtained, and the ratio of the actual completion time to the planned completion time is calculated; when the task contains multiple sub-tasks, the progress completion rates of each sub-task are weighted and summed based on the task weight of each sub-task to obtain the overall progress completion rate of the task.

[0074] In this embodiment, the cost deviation can be calculated as follows: obtain the actual cost and the budgeted cost; calculate the difference between the actual cost and the budgeted cost; calculate the ratio of the difference to the budgeted cost to obtain the cost deviation.

[0075] In an optional implementation of this embodiment, a data acquisition interface can be invoked to receive actual cost expenditure records generated during project execution from a financial system or expense reimbursement platform. Each record includes a cost item code, expenditure amount, and occurrence time. Further, the corresponding cost item in the target project's cost item set is matched according to the cost item code, and the expenditure amount is accumulated into the actual cost field of that cost item in the cost data structure. Further, contract data from the contract management system is read, and the total contract amount is proportionally or according to a fixed rule decomposed into one or more cost items based on the preset correspondence between contract codes and cost item codes. The current completion status of the progress task item is then used to determine if the payment conditions are met. If met, the corresponding amount is written into the actual payment amount field of the associated cost item in the contract data structure. Further, the actual cost fields of all cost items in the cost data structure are summed to obtain the cumulative actual expenditure value. Simultaneously, the actual revenue fields of all revenue-type contracts in the contract data structure are summed to obtain the cumulative actual revenue value. The difference between the two is stored in the funds balance field of the funds data structure. Meanwhile, the progress tracking module obtains the actual start and end times of each progress task item from the project management platform. Combined with the planned man-hours defined in the progress task item template, it calculates the progress completion rate and the time difference between the actual end time and the planned end time as the progress deviation. Finally, based on the mapping table of the relationship between cost items and progress task items, it aligns and horizontally concatenates the data records with the same association key in the cost data structure, contract data structure, funding data structure, and progress data structure to generate a unified data object set containing multi-dimensional fields. This set is the collaborative analysis model.

[0076] In one possible implementation, relevant data on actual cost expenditures (referred to as actual execution data in this embodiment) are collected in real time during project execution via a data acquisition interface. This data includes detailed breakdowns of various expenditures, such as material procurement and labor costs. Each expenditure is categorized according to its cost item code, and thus aggregated into the actual cost field within the cost data structure. This process ensures the accuracy and timeliness of the cost data, enabling project managers to monitor the actual cost status of the project at any time.

[0077] Furthermore, based on the contract code, the contract amount is broken down into specific cost items. The contract amount corresponding to each cost item is recorded in the contract data structure. As the schedule tasks are executed, when a task is completed, the system automatically updates the actual payment amount in the contract data structure according to the progress status. This process achieves a close connection between the contract amount and the progress task completion during project execution, ensuring the timeliness and accuracy of payments.

[0078] Furthermore, the actual expenditures in the cost data structure are summed with the actual revenues in the contract data structure to calculate the cash balance in the funds data structure. This allows for real-time monitoring of the project's cash flow, ensuring a balance between project funds and contract revenue. When project expenditures change, the system automatically adjusts the cash balance, providing project managers with a basis for fund allocation and management.

[0079] The progress tracking module allows you to obtain the actual start and end times of each task. Combined with planned work hours data, it calculates the progress completion rate. If the actual progress of a task deviates from the planned progress, a report is generated promptly, providing the progress deviation. Based on the difference between the actual end time and the planned end time, the progress deviation is calculated, thereby assessing whether the project is progressing as planned. This function ensures progress control in project management, promptly identifies problems in project progress, and takes corrective measures.

[0080] Step 250: Based on the collaborative analysis model, generate a cash flow statement for the target project, and use a time series analysis model to predict the future cash flow trend of the target project.

[0081] Optionally, in this embodiment, generating a cash flow statement for the target project based on the collaborative analysis model may include: summarizing the timing and amount of cash inflows and outflows corresponding to each progress task item according to the progress data structure and funding data structure in the collaborative analysis model, and arranging them in chronological order to generate the cash flow statement for the target project.

[0082] Optionally, in this embodiment, predicting the future cash flow trend of the target project using a time series analysis model may include: using historical cash flow data from the cash flow statement and planned progress information from the progress data structure as input, smoothing the input data and removing outliers; when the prediction period is short-term, using the moving average method to calculate the future cash flow trend, the moving average method uses the arithmetic mean of net cash flows over a predetermined number of past periods as the predicted value; when the prediction period is long-term, using the exponential smoothing method to calculate the future cash flow trend, the exponential smoothing method assigns different weights to historical data, with recent data having a greater weight than long-term data; comparing the predicted future cash flow trend with a capital safety threshold, and automatically triggering a cash flow risk warning when the predicted cash flow is lower than the capital safety threshold.

[0083] In one possible implementation, the system requires historical cash flow data and project schedule as the basis for forecasting. Historical cash flow data provides information on the project's past cash inflows and outflows, while the schedule shows the progress of each stage of the project. Next, the input data undergoes preprocessing, including data smoothing and outlier removal. Data smoothing removes short-term fluctuations and extracts long-term trends, ensuring greater data stability and predictability. Outlier removal eliminates abnormal fluctuations caused by data entry errors or special events, ensuring data accuracy and reliability.

[0084] Optionally, when making short-term cash flow forecasts, the moving average method can be used to calculate future cash flow trends. The moving average method uses the arithmetic mean of net cash flows over a predetermined number of periods to predict cash flows over a future period. For example, if data from the past three months is chosen as a reference, the cash flow trend for the next few months will be the average of the cash flows over the past three months. This method is suitable for short-term forecasting because cash flow trends tend to be relatively stable in the short term and are less affected by long-term factors.

[0085] Optionally, when making long-term cash flow forecasts, exponential smoothing can be used to process the data. Unlike moving averages, exponential smoothing assigns different weights to historical data, with more weight given to recent data than to older data. This method is better able to capture the impact of recent project progress on cash flow because long-term forecasts typically involve more external factors and uncertainties; giving more weight to recent data can improve forecast accuracy.

[0086] Optionally, after completing the cash flow trend forecast, the system compares the forecast results with a funding safety threshold. The funding safety threshold, determined based on the project's funding needs and risk assessment, represents the minimum level of security the project needs to maintain in its cash flow. If the forecasted cash flow is lower than this threshold, it means the project may face a funding shortage risk in the future. In this case, the system will automatically trigger a cash flow risk warning, reminding project managers to take timely measures, such as adjusting fund allocation or seeking additional financing.

[0087] This embodiment, by introducing a time series analysis model, can accurately predict the future cash flow trend of a project and effectively monitor the project's financial security. By combining moving average and exponential smoothing methods, the most suitable model can be selected for prediction based on the different characteristics of short-term and long-term forecasts, thereby improving forecast accuracy. Timely detection of cash flow falling below the financial security threshold helps managers take proactive measures for fund allocation or risk control, preventing project stagnation or delays due to funding shortages. Overall, this method enhances the accuracy and predictability of project financial management, improving project financial security and execution efficiency.

[0088] In one possible implementation, the actual completion time and planned time of the task can be obtained. Actual completion time refers to the actual working time invested during project execution, while planned time is the estimated time allocated to the task during the initial project planning. By comparing the actual completion time and planned time, it can be reflected whether the task is progressing as expected. If the actual completion time is greater than or equal to the planned time, it indicates that the task is progressing smoothly; if the actual completion time is insufficient, it indicates that the task may be behind schedule.

[0089] After obtaining the actual completed working hours and the planned working hours, the ratio between the two can be calculated. This ratio is a preliminary indicator of the progress completion rate. This ratio reflects the difference between the actual progress of the task execution and the planned progress. If the actual completed working hours are equal to the planned working hours, the progress completion rate is 100%, indicating that the task was completed as planned; if the actual working hours are insufficient, the progress completion rate is less than 100%.

[0090] Step 260: Identify the execution risks of the target project through preset collaborative judgment logic and trigger the corresponding risk warning signal.

[0091] The funding safety threshold is determined as follows: historical cash flow data of the project is obtained, including historical monthly expenditures and historical funding gap records; the average and standard deviation of historical monthly expenditures are calculated; the frequency of funding shortage events is statistically analyzed based on historical funding shortage event records; the standard deviation and frequency are normalized to obtain dimensionless risk component values; the risk coefficient is determined based on the risk component values, and the product of the historical monthly expenditure average and the risk coefficient is used as the funding safety threshold.

[0092] In one alternative implementation, a cost deviation threshold can be set, which is a percentage of the total project budget. The cost deviation threshold is set by analyzing the project's budget and establishing an acceptable range for cost fluctuations. If the actual expenditures deviate from the budget by more than this threshold, it can be considered a risk of cost overrun, triggering a corresponding early warning mechanism. In this way, it is possible to detect the risk of budget overruns in real time during project execution, ensuring timely adjustments are made.

[0093] Next, a schedule deviation threshold can be set, which is a percentage of the total project duration. This threshold determines whether the project is behind schedule. The difference between the actual and planned progress can be monitored in real time, and a delay warning will be triggered when the deviation exceeds the threshold. This mechanism helps project managers identify potential delays promptly, preventing projects from failing to complete on time.

[0094] To ensure project funding security, a funding security threshold can be set. This threshold is obtained by multiplying the project's average monthly expenditure by a risk coefficient. The risk coefficient is determined based on the project's risk assessment results. The purpose of the funding security threshold is to monitor the project's funding balance in real time, ensuring that the project's cash flow will not be disrupted. If the funding balance falls below the set security threshold, the system will trigger a funding shortage warning. This helps project managers promptly identify the risk of insufficient funds and take effective fund allocation measures.

[0095] During project execution, cost deviations in the cost data structure, schedule deviations in the schedule data structure, and cash balances in the funding data structure can be monitored in real time. An alert is automatically triggered whenever any of these deviations exceeds a set threshold. The alert information includes the deviation type (e.g., cost overrun, schedule delay, or funding shortage), the deviation value (e.g., the amount exceeding the budget or the number of days of delay), and recommended adjustment measures. Recommended adjustment measures may include adjusting resource allocation, rescheduling the schedule, or increasing funding to promptly adjust the project direction and avoid serious project risks.

[0096] In this embodiment, through the application of intelligent correlation control logic, the project can achieve comprehensive monitoring of costs, schedules, and funds, ensuring coordination and synchronization between various stages. Early warning mechanisms for cost deviations, schedule deviations, and funding shortages can promptly identify potential problems in project execution and provide project managers with targeted adjustment suggestions. This not only helps managers identify and handle risks early in the project, avoiding budget overruns, delays, or even funding chain disruptions, but also improves project execution efficiency and success rate. The application of the intelligent early warning system greatly enhances the project's risk management capabilities, ensuring the project proceeds smoothly under triple control of budget, schedule, and funding, thereby improving the scientific nature and accuracy of overall project management.

[0097] In one possible implementation, historical cash flow data for the project can be collected. This data includes historical monthly expenditure records and historical funding gap records. The historical monthly expenditure records reflect the project's cash outflows over past months, while the historical funding gap records document funding gap events that occurred during project execution due to insufficient funds. This data provides a foundation for subsequent risk analysis.

[0098] Furthermore, based on historical monthly expenditure data, the average and standard deviation of monthly expenditures can be calculated. The average reflects the general situation of project spending, while the standard deviation reflects the degree of fluctuation in expenditures. A larger standard deviation indicates that project spending fluctuates significantly, which may be related to the project's risk and uncertainty. Calculating the standard deviation helps to understand the stability of spending, thus providing a basis for risk assessment.

[0099] In this embodiment, by analyzing historical funding gap records, the frequency of funding shortage events can be determined. This frequency indicates how often funding shortages occur during the execution of historical projects. Furthermore, the system calculates the average funding gap amount per event, i.e., the average amount of the gap during each funding shortage. This metric helps to understand the severity of funding shortages and their impact on the project's cash flow.

[0100] Furthermore, a risk coefficient is determined through a weighted calculation, combining the standard deviation of historical monthly expenditures and the frequency of funding shortage events. Specifically, the standard deviation of monthly expenditures reflects the risk of fluctuations in funding expenditures, while the frequency of funding shortage events and the average amount of the shortfall reflect the degree of risk of insufficient funding. By using a weighted calculation, both risk factors can be comprehensively considered to arrive at a comprehensive risk coefficient. A higher risk coefficient indicates greater uncertainty in project fund management and a higher risk of funding shortages.

[0101] In this way, project managers can accurately assess project funding risks, providing a scientific basis for project funding arrangements and risk control. First, analysis of historical cash flow data can reveal potential funding risks and predict possible funding shortages in advance. Second, the combination of standard deviation and funding gap makes the risk coefficient calculation more accurate, comprehensively reflecting the volatility of project expenditures and the possibility of funding shortages. Finally, the introduction of the risk coefficient makes project funding management more targeted, enabling the implementation of corresponding risk response measures, such as increasing cash reserves and adjusting expenditure plans, thereby ensuring stable project cash flow, reducing funding risks during project execution, and improving project efficiency and success rate.

[0102] In project management, tasks often comprise multiple subtasks, each with varying importance within the overall task, typically distinguished by task weights. To obtain the overall task completion rate, a weighted sum of the completion rates of each subtask is needed. The completion rate of each subtask is the ratio of its actual completed hours to its planned hours, while the weight of each subtask is determined by its importance within the overall task. By using a weighted sum, the completion status of each subtask can be comprehensively considered, resulting in a more accurate overall task completion rate.

[0103] This calculation method provides a more comprehensive reflection of the project's actual progress, especially in complex projects where tasks are typically broken down into multiple subtasks, each with varying workloads and importance. By weighted summing of the completion rates of each subtask, the overall project progress can be accurately assessed, avoiding the risk of drawing misleading conclusions based solely on the progress of a single subtask. Furthermore, this method can reflect deviations in task execution in real time, providing timely decision support for project managers. This helps adjust the project schedule, optimize resource allocation, and ensure on-time project completion. This method offers high flexibility and adaptability, making it suitable for managing various complex project tasks and effectively supporting progress monitoring and control.

[0104] In one possible implementation, actual costs and budgeted costs can be extracted from the project's cost data structure. Actual costs refer to the expenses actually incurred in the project, which, for example, may include all invested funds, resources, and labor costs. Budgeted costs are the expected costs set at the beginning of the project based on the plan, including budgeted expenditures for each stage. Obtaining these two sets of data provides the necessary basis for subsequent cost variance calculations.

[0105] After obtaining the actual cost and the budgeted cost, the difference between the two is calculated. This difference reflects the degree of deviation between the project's actual expenditures and the original budget. If the actual cost is greater than the budgeted cost, it indicates that the project has overspent; if the actual cost is less than the budgeted cost, it indicates that the project has saved money. This difference provides a basis for further analysis of cost deviations.

[0106] Next, the ratio between the difference and the budgeted cost is calculated to obtain the cost variance. Cost variance is a percentage value representing the degree to which the actual cost deviates from the budgeted cost. This ratio helps measure the project's performance in budget control. A positive variance rate indicates that the project has overspent, while a negative variance rate indicates savings. Using this ratio, project managers can clearly understand the project's financial performance and take appropriate adjustments based on the actual situation.

[0107] By comparing actual costs with budgeted costs, project managers can gain intuitive financial feedback. Calculating cost variances allows project managers to promptly identify problems in cost control, pinpointing stages or phases with significant budget deviations, thus enabling targeted budget adjustments or fund reallocation. Furthermore, cost variance calculations help the project management team conduct cost forecasting and risk assessment, optimize project resource allocation, and improve the efficiency of project fund utilization. Overall, cost variance calculations help projects maintain financial stability, preventing project schedules or quality from being affected by uncontrolled costs, and ensuring projects are completed smoothly within budget.

[0108] Optionally, in this embodiment, after triggering a funding shortage warning, the process may further include: automatically generating a funding allocation suggestion plan, which includes the suggested allocation amount, the source project for allocation, and the allocation time point; pushing the funding allocation suggestion plan to the project management personnel for confirmation and review; and executing an automatic funding allocation operation according to the confirmation instruction from the project management personnel.

[0109] Optionally, in this embodiment, after a funding shortage warning is triggered, a funding allocation suggestion plan can be automatically generated based on the project's funding needs, current funding balance, and project funding allocation rules. The funding allocation suggestion plan includes three key components:

[0110] Suggested allocation amount: Based on the degree of fund shortage, the system calculates the amount of funds that need to be allocated to ensure that the shortage can be replenished.

[0111] Fund allocation source projects: The system determines the source projects for fund allocation based on the cash flow between projects. This is usually done intelligently based on the remaining funds and priority of each project to ensure the rationality and feasibility of the funding source.

[0112] Allocation time nodes: To ensure that funds are available at critical moments, the system will set allocation time nodes, that is, the specific time arrangement for fund allocation, to ensure that the allocation process is efficient and does not affect the project schedule.

[0113] After generating a proposed fund allocation plan, it can be sent to project management personnel for confirmation and review. Project management personnel can view the detailed information of the proposed plan through the system, including the suggested allocation amount, source projects, and timelines, to assess its feasibility and rationale. If necessary, project management personnel can modify the plan or provide adjustment suggestions.

[0114] Optionally, in this embodiment, after the project management personnel confirm the proposed fund allocation plan, the fund allocation operation can be automatically executed according to the personnel's instructions. During the fund allocation process, the system will ensure that funds are transferred from designated source projects to projects with funding shortages according to a preset process, and complete the allocation task at the specified time node. This process requires no manual intervention, improving the efficiency and accuracy of fund allocation.

[0115] The technical solution of this invention establishes a standardized cost item template library and schedule task item template library, and associates cost items with schedule task items through strong mapping relationships, forming a unified data structure and strong correlation logic. This method ensures real-time synchronization and interactive referencing of cost, schedule, and funding data. This invention achieves automatic calculation based on schedule and cost data, updates project cost, schedule, and funding information in real time, and ensures that business data and financial data remain consistent. Furthermore, based on strong mapping relationships, changes in cost items, schedule task items, and cash flow data are synchronized instantly. This invention introduces intelligent correlation control logic to automatically monitor and warn of various project risks. When cost deviations, schedule deviations, or cash balances reach set thresholds, the system can automatically trigger an early warning mechanism, reminding project managers to make timely adjustments, avoiding the inefficient methods of relying on manual calculations and periodic reports, and significantly improving the response speed and accuracy of project management. This invention uses a time series analysis model, combined with real-time schedule and cost data, to perform dynamic cash flow forecasting. This model can more accurately predict the cash flow trend of a project, especially under different forecast periods in the short and long term. By using appropriate moving average methods and exponential smoothing methods, it effectively improves the accuracy of forecasts and provides a scientific basis for financial management. This invention employs dynamic mapping rules, supporting automatic adjustment of mapping relationships and recalculation of the impact cost item mapping weights during project execution. This enables the system to adapt to project changes and automatically adjust relationships, thereby improving data consistency and real-time performance.

[0116] To better understand the project collaboration management method involved in this embodiment, an example is used below, which mainly includes the following:

[0117] 1) Establish a standard CBS (Cost Items) template library and WBS (Work Schedule Items) template library based on the characteristics of the project;

[0118] 2) Establish a strong mapping and strong association between CBS and WBS;

[0119] 3) The project's cost data structure, contract data structure, and financial data structure are formed through standard CBS;

[0120] 4) By establishing a strong correlation between the project's CBS and WBS, a project schedule data structure is formed;

[0121] 5) Due to the high consistency of system data, the system's built-in intelligent correlation control logic can automatically and accurately warn of risks in the project execution process, such as over-cost risks, cash flow risks, and potential risks such as mismatch between progress and payment.

[0122] 6) Fund management relies on the project schedule, which is the main thread of the project. Fund inflows and outflows are based on the completed work volume in the CBS (Content Management System) accounts, while the schedule is based on the completion time in the WBS (Work Schedule) accounts. Because the system implements a strong mapping relationship between CBS and WBS, the matching between project fund inflows and outflows and project schedule can be accurately determined. The system can also automatically generate cash flow statements based on project costs, contracts, actual progress, and payment status, monitoring the project's financial status and predicting project cash flow.

[0123] The solution of this invention establishes a standard CBS template library and WBS template library, achieving a strong mapping relationship between CBS and WBS. This allows for one-time entry of cost items and interactive referencing of contract and funding items; automatic generation of schedule items; and automatic generation of cash flow statements based on contract amounts, payment amounts, and schedule plans. This enables the interconnected control of project costs, funding, and schedule. It achieves the goals of project progress monitoring, project cost control, project risk early warning, and project funding prediction throughout the entire project lifecycle.

[0124] In the technical solutions of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of project data (such as cost items, schedule task items, etc.) all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0125] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0126] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A project collaboration management method, characterized by, The method comprises: in response to the management instruction of the target project, determining the target project type of the target project, and determining the preset standard template library corresponding to the target project type; based on the preset standard template library, generating the cost item set and the progress task item set of the target project, and establishing the association between the cost item of the target project and the progress task item of the target project; according to the association and the actual execution data obtained in the execution process of the target project, a collaborative analysis model reflecting the execution state of the target project is constructed; based on the collaborative analysis model, the cash flow table of the target project is generated, and the time series analysis model is used to predict the future cash flow trend of the target project; through the preset collaborative judgment logic, the execution risk of the target project is identified and the corresponding risk warning signal is triggered.

2. The project collaboration management method according to claim 1, characterized in that, The preset standard template library comprises: a standard cost item template library, a standard progress task item template library and a standard contract data template library; the standard cost item template library comprises cost subject code, cost subject name, budget amount and cost type; the standard progress task item template library comprises task code, task name, planned start time, planned end time and task weight; the standard contract data template library comprises contract code, contract amount, payment condition and contract type; The determination of the preset standard template library corresponding to the target project type comprises: obtaining historical project data, which comprises cost records, progress records and contract records; cleaning and classifying the historical project data; wherein, the classification is based on the industry type of the project; based on the classified data, the cost item common characteristics and the progress task item common characteristics of each project type are induced by using clustering analysis method; based on the cost item common characteristics, the standard cost item template library is constructed, and the cost subject code adopts hierarchical structure representation; based on the progress task item common characteristics, the standard progress task item template library is constructed, and the task weight is calculated by the ratio of task duration to total project duration.

3. The project collaboration management method of claim 1, wherein, Based on the preset standard template library, the cost item set and the progress task item set of the target project are generated, comprising: calling the cost item template corresponding to the target project type from the preset standard template library, and instantiating to generate the cost item set of the target project; wherein, each cost item in the cost item set comprises cost subject code, budget amount and cost type; calling the progress task item template corresponding to the target project type from the preset standard template library, and instantiating to generate the progress task item set of the target project; wherein, each progress task item in the progress task item set comprises task code, planned start time, planned end time and task weight.

4. The project collaboration management method according to claim 3, wherein, The association between the cost item of the target project and the progress task item of the target project is established, comprising: defining a mapping rule, which maps material procurement type cost items to procurement type task items and labor type cost items to construction type task items based on business logic relationship; creating a mapping table, which stores cost item code, task code and mapping weight; In the project initialization phase, automatically load the initial mapping relationship according to the mapping rule; In the project execution process, when the progress task item changes, automatically trigger the dynamic adjustment of the mapping relationship, and recalculate the mapping weight of the affected cost item.

5. The project collaboration management method of claim 1, wherein, The collaborative analysis model reflecting the execution state of the target project is constructed according to the association relationship and the actual execution data obtained in the target project execution process, including: Obtain the actual cost expenditure record in the project execution process through the data acquisition interface, and collect the actual cost expenditure record into the actual cost field in the cost data structure according to the cost subject code; According to the contract code associated with the cost subject code, the contract amount is decomposed to the corresponding cost item, and the actual payment amount in the contract data structure is updated according to the completion state of the progress task item; Cumulative actual expenditure in cost data structure and actual income in contract data structure, calculate the balance of funds in funds data structure; Obtain the actual start time and actual end time of the task through the progress tracking module, calculate the progress completion rate combined with the planned working hours, and calculate the progress deviation according to the difference between the actual end time and the planned end time; Fuse the cost data structure, contract data structure, funds data structure and progress data structure based on the association relationship to form the collaborative analysis model.

6. The project collaboration management method according to claim 5, wherein, The progress completion rate is calculated by: Obtain the actual completion working hours and the planned working hours of the task, and calculate the ratio of the actual completion working hours to the planned working hours; When the task contains multiple subtasks, the progress completion rates of each subtask are weighted and summed based on the task weight of each subtask to obtain the progress completion rate of the whole task; The cost deviation is calculated by: Obtain the actual cost and the budget cost; Calculate the difference between the actual cost and the budget cost; Calculate the ratio of the difference to the budget cost to obtain the cost deviation.

7. The project collaboration management method of claim 1, wherein, The cash flow table of the target project is generated based on the collaborative analysis model, including: According to the progress data structure and the funds data structure in the collaborative analysis model, summarize the time points and amounts of the cash inflow and cash outflow corresponding to each progress task item, and arrange them in chronological order to generate the cash flow of the target project.

8. The project collaboration management method of claim 7, wherein, The future cash flow trend of the target project is predicted using a time series analysis model, including: Use the historical cash flow data in the cash flow table and the planned progress information in the progress data structure as input, and perform smoothing and outlier removal on the input data; When the prediction period is short, use the moving average method to calculate the future cash flow trend, which uses the arithmetic mean of a predetermined number of past cash net flow values as the prediction value; When the prediction period is long, use the exponential smoothing method to calculate the future cash flow trend, which gives different weights to historical data, with recent data having greater weight than distant data; Compare the predicted future cash flow trend with the funds safety threshold, and automatically trigger a cash flow risk warning when the predicted cash flow is lower than the funds safety threshold.

9. The project collaboration management method of claim 1, wherein, The execution risk of the target project is identified by the preset cooperative judgment logic, and a corresponding risk warning signal is triggered, comprising: setting a cost deviation threshold, a progress deviation threshold and a fund safety threshold; determining the cost deviation, the progress deviation and the fund balance in the cooperative analysis model in real time, triggering a cost overrun warning when the cost deviation exceeds the cost deviation threshold, triggering a progress delay warning when the progress deviation exceeds the progress deviation threshold, and triggering a fund shortage warning when the fund balance is lower than the fund safety threshold; wherein the fund safety threshold is determined by the following method: obtaining project historical fund flow data, including historical monthly expenditure and historical fund gap records; calculating the average value and the standard deviation of the historical monthly expenditure; based on the historical fund shortage event records, the occurrence frequency of the fund shortage events is counted; the standard deviation and the occurrence frequency are normalized respectively to obtain the dimensionless risk component value; determining a risk coefficient based on the risk component value, and taking the product of the average value of the historical monthly expenditure and the risk coefficient as the fund safety threshold.

10. The project collaboration management method of claim 9, wherein, After triggering the fund shortage warning, the method further comprises: automatically generating a fund allocation suggestion scheme, the fund allocation suggestion scheme including a suggested allocation amount, an allocation source project and an allocation time node; pushing the fund allocation suggestion scheme to the project management personnel for confirmation and audit; executing an automatic fund allocation operation according to the confirmation instruction of the project management personnel.

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