Enterprise human property data and business scene linkage method

Abstract

The invention relates to an enterprise human property data and business scene linkage method, which comprises the following steps of: after detecting an enterprise target business scene event, determining three types of data elements of human resources, finance and assets according to an event type and a business target, and generating a participation degree parameter reflecting element participation depth and response priority; state conflict identification is carried out on the multi-source human property data corresponding to the parameters, whether permission conflicts, version conflicts or logic conflicts exist or not is judged according to a preset conflict assertion rule, a priority judgment system is appointed through a chain-of-responsibility judgment mechanism, and manual arbitration is carried out if the conflicts cannot be eliminated; and when the data state is legal, calculating the linkage sensitivity of each element based on the participation degree parameter, determining a task execution sequence, and implementing dynamic response suppression on the high-dependency elements to generate a task scheduling sequence. And finally, sequentially calling a cross-system semantic contrast rule for the execution instructions in the sequence, and if semantic inconsistency or packaging abnormity is judged, triggering instruction rollback or suspension processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of enterprise informatization, in particular to a method for linking enterprise personnel, financial and material data with business scenarios. BACKGROUND

[0002] The prior art such as the data flow conversion method, device and financial and tax integration platform of the integrated platform disclosed in CN120013262A, although it proposes a relatively complete closed-loop system in the aspects of structuring, classifying, risk control and encryption processing of financial data, still has multiple key deficiencies in the current method for linking enterprise "personnel, financial and material data" with "business scenarios". The patent mainly focuses on the data recognition, risk extraction and processing strategy of financial information, and although it realizes the cross-system financial data flow conversion through the RPA module, CL module and iPaaS module, it does not perform unified linkage modeling processing on the key personnel resources and asset allocation data in enterprise management, especially in the aspects of person-post matching, equipment adjustability and task timeliness dynamic decision factors, and there is a serious gap. This flow path with financial data as the only core cannot support the scheduling decision-making needs across business domains, is easy to form a data island or a business barrier, and thus causes problems such as task response delay, resource waste or operation redundancy management. The technology overemphasizes the standard conversion and static classification and sorting of structured data in the processing process, but does not introduce dynamic judgment logic oriented by business scenario triggering. In real business processes, events often have high timeliness and multi-target orientation, for example, budget adjustment simultaneously triggers post reconstruction and asset transfer linkage behavior.

[0003] Only through the CL module to generate strategies according to the sorting, the intelligent judgment and order priority arbitration ability for multiple target conflicts in the business context are lacked, it is difficult to support the primary and secondary task decision-making under the complex event chain, and it is difficult to cope with the dynamic game relationship between the cost control target and the resource matching target. The conflict control in the scheme only reflects the risk data and key data dimension at the data level, and does not form a linkage mechanism based on the integrity of the data state. The current enterprise collaboration system often involves permission conflicts, process progress misalignment and version mismatch problems when processing personnel, financial and material data. Although the data security monitoring module introduces strategic encryption, the setting of risk judgment and processing priority depends on the recognition of a single module, lacks the design of a responsibility chain perspective arbitration mechanism, and is difficult to solve the problem of inconsistent data ownership of source systems, insufficient conflict attribution judgment of multi-source data, and does not configure a scenario remediation branch for manual intervention, leading to the interruption or processing error of the automated process under abnormal conditions.

[0004] Although the process is relatively complete in the closed loop, there is a lack of sensitive quantitative mechanism before the task is executed, and the execution task order cannot be reasonably optimized based on the task dependency, resource scarcity and timeliness factors. Especially in high-concurrency business processes, the system cannot identify which tasks should be scheduled first and which resources should be suppressed in response, causing operation queue congestion and cross-system call failure problems. Without introducing a semantic consistency comparison mechanism, in the face of inconsistent field definitions or ambiguous operation semantics between multiple systems, the original solution only performs interfacing based on the iPaaS interface layer, lacks the ability to perform deep semantic auditing on execution instructions, and is prone to cause system operation failure or semantic conflicts. SUMMARY

[0005] The purpose of the present application is to provide an enterprise human, financial and material data and business scenario linkage method, so as to solve some of the problems and deficiencies pointed out in the background art.

[0006] The technical scheme adopted by the present application to solve the above technical problems is as follows: an enterprise human, financial and material data and business scenario linkage method, comprising: when a target business scenario event in the operation of an enterprise is detected, determining the human resource data, financial data and asset data three types of elements involved according to the event type and business target, and generating a participation parameter reflecting the participation depth and response priority of the elements; Performing state conflict identification on the multi-source human, financial and material data corresponding to the participation parameter, judging whether there is a permission conflict, version conflict or logical contradiction according to the preset conflict assertion rule, and specifying a priority decision system through a responsibility chain decision mechanism, if the conflict cannot be excluded, then entering the manual arbitration branch; Under the premise that the data state is legal, the linkage sensitivity of each human, financial and material element is calculated based on the participation parameter, the task execution order is determined, and dynamic response suppression is implemented on the elements with high dependency to generate a task scheduling sequence; then the execution instructions in the task scheduling sequence are called in sequence cross-system semantic comparison rules, if the instruction semantics are inconsistent or encapsulated abnormally, then trigger instruction rollback or suspension processing.

[0007] Further, the process of determining the human resource data includes classifying and identifying post information, personnel qualifications, on-duty state and resource occupation; the process of determining the financial data includes determining budget state, expense category, cost center and approval chain state; and the process of determining the asset data includes identifying asset use state, occupation information, life cycle state and allocability.

[0008] Further, the conflict assertion rules include at least one of a permission conflict assertion rule, a process state assertion rule, and an information version assertion rule; the responsibility chain decision mechanism includes a rule set for deciding according to a business domain priority of the system; and the responsibility chain decision mechanism compares a business domain, a data authority level, and a timestamp credibility of each system before performing decision, to determine a system for priority decision.

[0009] Further, the entering the manual arbitration branch includes generating a conflict context description and pushing a decision request to a manual approval node; and the calculation of the linkage sensitivity includes performing a combination judgment of a task dependency degree, a resource scarcity degree, and a processing timeliness sensitivity factor, and calculating a comprehensive linkage sensitivity of the task based on a dynamic weighted integral function as follows:

[0010] Wherein: is the comprehensive linkage sensitivity of the task; is a time window in which the task can be executed; is a time is a task dependency degree at the time; is a resource scarcity degree coefficient; is a processing timeliness index; , , , , , are configurable weights and form parameters for adjusting the influence curve of the task dependency degree, the resource scarcity degree, and the processing timeliness in the sensitivity calculation, so that the sensitivity result is adjustable and adaptive; and the semantic comparison rule set includes at least one of an action intention matching rule, a field meaning matching rule, and a cross-system terminology consistency rule, for performing semantic consistency verification on the cross-system execution instruction.

[0011] Further, the control of the instruction rollback includes reverse resetting of the executed partial operation to restore the initial state; the instruction suspension control includes marking the instruction as a to-be-executed state and suspending the calling flow of the instruction in the target system; and the business scenario event includes at least one of a project change event, a budget adjustment event, a post adjustment event, or an asset state change event.

[0012] Further, the identification of the event type includes category judgment based on an event trigger source system, an event field, and an event time window; the business target includes at least one of a cost control target, a human resource matching target, and an asset allocation target; and before generating the participation parameter, the influence range of the event is spread to determine the actual involvement range of the three elements.

[0013] Further, in the event type identification process, when the event trigger source system is inconsistent with the event field, field priority judgment is performed, and the business action recorded in the event field is taken as the final basis for event classification; when the event belongs to the intersection interval of multiple time windows, the time window corresponding to the shortest response period is used to determine the event category.

[0014] Further, in the case of missing event fields, the system performs a completion judgment logic based on the trigger source system to infer the corresponding business category of the event; when the event trigger source system is inconsistent with the historical event source of the same type, the abnormal source determination logic is executed, and the event is marked as an abnormal event category.

[0015] Further, when there are multiple candidate business targets, the system performs target conflict judgment to select a single business target by identifying the business intent field; when the cost control target and the manpower matching target both satisfy the trigger condition, the cost control target is taken as the priority business target.

[0016] Further, the target conflict judgment includes: analyzing the content in the business intent field, in the case that the business intent field contains cost constraint indication information, setting the business target as the cost control target; in the case that the business intent field contains both cost constraint indication information and manpower gap identification, performing sequential judgment according to the appearance order of the cost constraint indication information and the manpower gap identification in the business intent field to determine the final setting of the business target.

[0017] The beneficial effects of the present application are: through systematic judgment of event type, business target and event influence range, human resource data, financial data and asset data three types of elements involved can be accurately identified at the first time of business scene triggering, and participation degree parameters are generated according to the participation degree of each element, realizing the structured expression of multi-dimensional business elements across systems. By introducing conflict assertion rules and responsibility chain arbitration mechanism, automatic judgment and arbitration can be realized when there are permission conflicts, version inconsistencies or state conflicts in multi-source data, so that the data legality and business consistency can be guaranteed before linkage execution, avoiding the problems of resource mismatch and business interruption caused by false linkage.

[0018] In the linkage execution process, the dynamic priority control of task scheduling is realized through the comprehensive sensitivity calculation of task dependency, resource scarcity and processing timeliness, and the executable and conflict-free task scheduling sequence is generated combined with the dynamic response suppression mechanism, so as to improve the collaborative efficiency of human, financial and material resources in complex business scenarios. In addition, the action intention matching, field meaning matching and term consistency judgment rules set can perform semantic verification on cross-system execution instructions, ensuring that the instruction execution behavior maintains consistent meaning between different business systems. When the linkage instruction content does not meet the semantic consistency requirement, the system can execute instruction rollback or suspension control to ensure the controllability and business continuity of the linkage process. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 The enterprise human, financial and material data and business scene linkage processing flowchart of the application.

[0020] Figure 2 The enterprise data element linkage processing flowchart of the application.

[0021] Figure 3 The event type and business target determination flowchart of the application.

[0022] Figure 4 The enterprise expansion task data flow and abnormal processing flowchart of embodiment 1 of the application.

[0023] Figure 5 The business target determination and scheduling adjustment flowchart under the multi-event driving of embodiment 2 of the application. DETAILED DESCRIPTION

[0024] The specific embodiments of the application will be described in detail below with reference to the accompanying drawings.

[0025] The specific embodiments of the application will be described in detail below with reference to the accompanying drawings. Figure 1The enterprise human, financial and material data and business scene linkage method and system monitor business events in the running process of the enterprise to identify whether there is a target business scene event that needs to trigger linkage processing. The detection of events can be based on the existing information system log of the enterprise, the state change record generated by the business process engine or the action signal generated by the task management system. When any source issues identifiable business event trigger information, the system enters the business scene analysis process. The system determines the event type and business target in the process of analyzing the event. The event type can be determined by the system to which the event belongs, the business action field and the time characteristics of the event occurrence. The business target can consist of budget control requirements, human resource allocation requirements or asset allocation requirements. The system establishes a corresponding relationship between the event and the target through a rule library or a preset mapping relationship. After confirming the event type and the business target, the system extracts human resource data, financial data and asset data involved in the event. These data come from the human system, financial system and asset system of the enterprise. The system determines which personnel positions, budget subjects or equipment and material types are involved in the event through field matching, permission verification and data filtering methods to clarify the participation range of the three types of elements. In order to make the subsequent linkage calculation quantifiable, the system generates a participation parameter for each type of element. This parameter reflects the participation depth and response priority of the element in the scene. The participation depth is used to represent the closeness of the relationship between the element and the event, and the response priority is used to represent the processing order of the element in the linkage execution process. The formation of the participation parameter can combine the importance of the element, the urgency of the event and the resource occupation of the element in the current business state. The system weights and combines these factors to obtain a parameter set suitable for linkage scheduling.

[0026] The system reads data records associated with the participation parameter from multiple business systems and checks the permission state, version state and business logic state of these data one by one. The permission state check is used to identify whether the access permissions of the same element in different systems are consistent. If the permission setting of a system is lower than the required permission of the business scene, it is determined that there is a permission conflict. The version state check is used to identify whether there is an update delay, repeated submission or inconsistency between systems. If the version number or modification time of the same element recorded in different systems is inconsistent, it is determined that there is a version conflict. The business logic state check is used to identify whether there is a contradictory state that does not conform to the business process. The post state of the human resource data has been marked as off-duty, but is still in the pending execution state in the project task system, or the asset has entered the scrap process but is still in the available state in the financial system. Such inconsistency is determined to be a logical contradiction.

[0027] The system uniformly judges the above three types of conflicts according to a preset conflict assertion rule base. The assertion rule defines the conflict detection method and the corresponding processing requirements through a conditional expression. When the system confirms the existence of a conflict according to the rule base, it will start a chain-of-responsibility decision mechanism to select the priority decision system. The chain-of-responsibility decision mechanism identifies the system with the most decision-making power by comparing the business domain authority level, data reliability indicators, and record time sequence of each business system. The system compares the decision conditions of each business system in order according to the chain-of-responsibility order and selects the system that meets the conditions and has the highest authority level as the priority decision system. If the conflict is of the correctable type, the system can synchronize low-version data or standardize permission status through built-in rules, then call the processing result of the priority decision system and complete conflict exclusion. If the conflict is of the unprocessable type, the key fields recorded in multiple systems are mutually contradictory and cannot be inferred correctly through algorithms, the system enters the manual arbitration branch and generates a conflict context explanation. The conflict context includes conflict element identification, conflict system source, field difference details, and recommended processing direction. The system pushes the explanation to the configured manual approval node to allow manual final decision on the conflict and returns the decision result to the system to complete the subsequent linkage process.

[0028] The system reads the participation depth of human resource elements, financial elements, and asset elements and response priority information in the participation parameter, and combines the dependency structure of the business task, the current availability of resources, and the timeliness requirements of task processing to quantitatively calculate the linkage sensitivity of each type of element. The system fuses the three types of factors through a preset nonlinear calculation model, so that elements with higher task dependency, greater resource scarcity, or more urgent timeliness requirements obtain higher values in the sensitivity result. According to the calculated linkage sensitivity, the system generates a task execution order and implements dynamic response suppression for elements with complex dependency relationships or long linkage chains. Through delay scheduling, priority adjustment, or concurrent restriction, the system avoids triggering too many tasks of highly dependent elements in a short time to form a stable and executable task scheduling sequence.

[0029] The system performs cross-system semantic consistency verification on each task in the task scheduling sequence after generating the sequence. The verification process sequentially calls action intent matching rules, field meaning matching rules, and term consistency rules to ensure that the instructions have a unified business expression across different business systems. Action intent matching is used to identify whether the business behavior represented by the instruction is consistent with the semantic constraints of the target system. Field meaning matching is used to confirm that the field meanings contained in the instruction are consistent with the data definitions of each system. Term consistency rules are used to ensure that business terms used across systems do not have ambiguity. When any rule identifies that the instruction has semantic inconsistency, field meaning deviation, or encapsulation format exception, the system triggers instruction rollback or suspension processing. Rollback processing is used to restore the executed instruction to its pre-execution state, and suspension processing is used to place the instruction in a pending execution state and abort its invocation process in the target system.

[0030] In conjunction with the accompanying Figure 2 When identifying human resource data, the system classifies post information, determines the role of the post in the event through post type, post responsibility, and post position in the business process. Then, the system identifies personnel qualifications, determines whether the current personnel have the ability to undertake corresponding tasks through the skill level, qualification certificate, experience, and training records possessed by the personnel. The system also determines the on-duty state of personnel to determine whether the personnel are in available, leave, off-duty, or project occupation state, and determines their participation possibility. The system also analyzes the occupation of human resources, evaluates whether there is a conflict or overload of resources according to the number of projects currently participated by the personnel, the scheduling plan, and the task load.

[0031] When identifying financial data, the system analyzes the budget status, determines whether the event has financial execution conditions through the budget balance, budget freeze, and budget allocation structure. The system further determines the expense category, identifies whether it belongs to the range of allowed expenses through the subject type, expense nature, and degree of association with the event. The system also verifies the cost center, determines whether it can bear related expenses through the authorized range, expense attribution, and budget bearing capacity of the cost center. The system also confirms the approval chain status, determines the compliance and executability of the event in the financial process through the progress of the approval node, the integrity of the approval authority, and the validity of the approval result.

[0032] In identifying asset data, the system determines the use state of the asset, and determines its allocability by whether the asset is currently in use, in repair, in disuse, or in scrap processing. The system further verifies asset occupancy information, and confirms whether the asset can be released or reassigned by asset allocation records, occupancy duration, and use department relationship. The system analyzes the asset lifecycle state, and determines whether the asset is suitable for the business scenario to be executed by the asset procurement date, depreciation, and maintenance cycle. The system identifies the allocability of the asset, and determines whether the asset can be put into use within the time required by the task by the physical location of the asset, allocation restrictions, and cross-region allocation rules.

[0033] The system uses a preset rule set when performing conflict assertion, which at least includes permission conflict assertion rules, process state assertion rules, and information version assertion rules. The permission conflict assertion rules are used to identify whether the access permissions of different business systems to the same element are consistent, and to identify whether the element is displayed as accessible in one system but marked as limited access in another system. Such differences will be determined as permission conflicts. The process state assertion rules are used to check whether the flow state of the element in the business process is consistent, and to determine whether the human resource element is marked as approved or pending in the process system, while the cost status of the financial element or the allocation state of the asset element is compared for consistency. The information version assertion rules are used to identify whether the same data recorded in multiple systems has version differences, and to identify whether there is an update lag or island modification by comparing the record time, modification serial number, and data content changes.

[0034] After determining that there is a conflict according to the assertion rules, the system needs to use the responsibility chain decision mechanism to select which business system to make the final decision on the conflict. The responsibility chain decision mechanism is composed of multiple rules arranged according to the business domain priority, and is used to determine the decision order and power level of different business systems in the conflict handling process. Before executing the decision, the system will perform three comparisons of the business systems involved in the conflict, including business domain comparison, data authority level comparison, and timestamp credibility comparison. The business domain comparison is used to assess the business ownership relationship of the system in handling tasks of this type of element, to identify the business responsible system. The data authority level comparison is used to identify the authority degree of the system in the data production and confirmation process, to determine the data credibility level. The timestamp credibility comparison is used to identify whether the time information recorded by the system is accurate and synchronized, to avoid errors in the decision conclusion due to time deviation. The system selects the priority decision system according to the results of the three comparisons and executes the decision process. In the case where the decision can be completed, the final data state is generated by the priority decision system. In the case where the decision cannot be completed, the system enters the manual arbitration process.

[0035] When entering the artificial arbitration process, the system generates a conflict context description composed of identification information of the conflict elements, system records of the conflict source, content description of field differences, and recommended handling direction, so that the artificial approval node can accurately understand the reasons for conflict formation and solutions. The system then pushes the arbitration request to the configured artificial approval node, which can view conflict details and make a final decision through a unified approval interface after receiving the request. The decision result is written back to each business system to form a consistent data state.

[0036] After confirming the legality of the data state, the system enters the linkage sensitivity calculation phase, which aims to determine the execution order of the task in the final scheduling sequence according to the importance of the elements reflected by the participation parameter and the linkage requirements in the current business environment. The system processes the quantitative data of three dimensions of task dependency, resource scarcity, and processing timeliness to generate a sensitivity expression of the task in the entire time window. To achieve nonlinear fusion processing of the above multi-dimensional quantitative indicators, the system uses a dynamic weighted integral function to calculate the sensitivity, which can continuously accumulate the change trend of the three factors within the task execution window to form a sensitivity value with adaptability. The sensitivity calculation formula is as follows:

[0037] Wherein: is the comprehensive linkage sensitivity of the task, is the time window in which the task can be executed, is the time of the task dependency, is the resource scarcity coefficient, is the processing timeliness index, is the task dependency influence weight, is the exponential parameter for adjusting the growth trend of dependency, is the resource scarcity influence weight, is the timeliness influence weight, is the shape parameter for controlling the steepness of the timeliness curve, is the timeliness critical threshold.

[0038] The continuous evaluation of the task critical factors at different time points is realized by the above integral form, so that the sensitivity value can reflect the dynamic changes in the task execution process. After the sensitivity calculation is completed, the system generates the task execution sequence according to the sensitivity, and at the same time, the dynamic response suppression strategy is executed for the elements with high dependence, so as to reduce the conflict risk by adjusting the task triggering time and limiting the task concurrency degree. Subsequently, the system performs cross-system semantic consistency checking on each execution instruction in the task scheduling sequence generated thereby, and the checking process successively calls the action intention matching rule, the field meaning matching rule and the cross-system terminology consistency rule to ensure that the instruction maintains consistent business meaning between different business systems. When the system determines that the instruction has semantic inconsistency or encapsulation format exception, the instruction rollback or suspension processing will be triggered immediately to maintain the correctness and controllability of the business linkage process.

[0039] The function derivation process: The sensitivity is defined as a dynamic quantity that changes with the time window , and the local sensitivity of the task at any time is composed of three additive nonlinear components; first, the task dependence usually presents an exponential offset characteristic over time, that is, the deeper the dependence chain, the more cumulative the impact, so a power function form is introduced to reflect the accelerated impact of dependence, where is the dependence impact weight, is an exponential factor to adjust the growth curve shape of dependence; Secondly, the change of resource scarcity usually has a marginal decreasing characteristic, that is, a small increase in scarcity will cause a greater impact, and after a high degree of scarcity, the impact tends to be saturated, so a logarithmic transformation is adopted to smooth the increase of scarcity in the high interval, where is the scarcity impact weight; Thirdly, the processing timeliness of the task often presents a threshold response characteristic, that is, the sensitivity increases sharply after exceeding a timeliness critical point, so a logic function is adopted, where is the timeliness impact weight, is used to adjust the steepness of the curve, represents the timeliness trigger threshold; by integrating the above three items in the time dimension, the overall sensitivity of the task in the execution window can be obtained. Thus, the comprehensive sensitivity formula .

[0040] The instruction rollback control is used to reverse the business changes caused by the instruction when the instruction has been partially executed on the target system but not completed, so as to restore the business state of the system to the initial state before the execution of the instruction. To achieve this process, the system records the key fields and business state information before the execution of the instruction, and calls the rollback mechanism to reset the affected business records in reverse order when it is determined that there is semantic inconsistency or encapsulation exception in the current instruction. The system ensures the integrity of data dependency when executing the rollback, and ensures that the restored state does not cause new conflicts with other business logic.

[0041] The instruction suspension control is used to mark the instruction as a to-be-executed state when the instruction has not been executed or has only completed the preparation phase, and to suspend the calling process of the instruction in the target system. The system removes the instruction from the current scheduling queue or places it in the waiting area by setting the suspension identifier in the instruction management module, so as to avoid the misexecution of the instruction by the system in the case of incomplete semantic verification or unsatisfied resource conditions. The suspended instruction is only allowed to re-enter the scheduling queue after the semantic consistency verification passes or the related resource state returns to normal.

[0042] The business scenario event includes at least one of a project change event, a budget adjustment event, a post adjustment event, or an asset state change event. The project change event involves project plan changes, task decomposition adjustments, or personnel division updates; the budget adjustment event involves cost redistribution, budget freezing, or budget expansion; the post adjustment event involves personnel job transfer, post cancellation, or post addition; and the asset state change event involves equipment warehousing, allocation, maintenance, or scrapping. The system triggers the linkage logic when any of the above business scenario events is detected.

[0043] In combination with the accompanying Figure 3 Event type identification relies on three key dimensions of event trigger source system, event field, and event time window to perform category determination. The trigger source system is used to indicate the business domain corresponding to the event source. If the event comes from the project management system, it belongs to the project adjustment type, and if it comes from the budget system, it belongs to the budget change type. The event field is used to reflect the key business fields involved in the event content, such as post number, budget amount, or asset state. The system determines the business category of the event through the mapping relationship between the meaning of the field content and the business rules. The event time window is used to identify whether the event belongs to planned change, periodic update, or sudden exception according to the time range of the event occurrence, and further refines the category to which the event belongs.

[0044] After the event type is identified, the system needs to determine the business target corresponding to the event, which includes at least one of the cost control target, the human resource matching target, and the asset allocation target. The system determines the business direction currently concerned by the event according to the event type and the business intention content contained in the event field. When the event involves budget changes and is accompanied by an expenditure limit identifier, the system determines the business target as cost control. When the event involves personnel gaps or post adjustments, the business target is determined as human resource matching. When the event contains asset state changes or asset allocation requirements, the business target is determined as asset allocation. Accurate determination of the business target can provide a clear calculation direction for subsequent human, financial, and material element participation calculation.

[0045] The system identifies the direct impact objects of the event, personnel, expenses, or assets, by analyzing the event content and business domain rules, and determines the indirectly affected associated elements of the event in combination with the business topology relationship of the event trigger source system. Project adjustments will cause the redistribution of post personnel and also affect project budget and asset occupation. The system establishes an impact link to determine the scope of these direct and indirect elements, and forms a set of involved human resource data, financial data, and asset data according to the spread result, providing complete and accurate input basis for participation parameter calculation.

[0046] When the business domain indicated by the event trigger source system is different from the business action recorded in the event field, the system will take the business action embodied in the event field as the final basis for event category determination. The field priority judgment logic reads the key business fields in the event record and matches the corresponding business operation rules to avoid event category identification errors caused by trigger source system configuration errors or source system identification deviation in the cross-system event forwarding process.

[0047] Enterprise business processes usually set multiple time windows according to different task types, daily, weekly, or monthly processing periods. When the event occurrence time is located at the intersection of multiple cycle intervals, it will cause potential multiple interpretations of the event type. To ensure the definiteness of the response strategy, the system will determine the final category of the event according to the corresponding shortest response period in multiple time windows. The selection strategy of the shortest response period defines the event category by prioritizing the time window that can process the business in the shortest time, to ensure that the event can be processed within the time limit required by the business, and to avoid business response delay caused by using a longer cycle window. When making the judgment, the system compares the start and end times of each time window and the business processing requirements, and selects the smallest period as the final time category basis for the event.

[0048] To avoid the event type from being unable to be determined due to the missing field, the system enables the completion judgment logic based on the trigger source system. The logic infers the business category corresponding to the event by reading the business domain attribute of the event trigger source system, the default event type mapping relationship configured in the system and the recent business activity of the trigger source system. When the event comes from the budget management system and the key field is missing, the system takes the budget-related action type as the basis for event category inference, ensuring that the event has a clear category identifier when entering the subsequent linkage process. The completion judgment logic also selects the result that meets the business rules from multiple categories in combination with the time characteristics of the event occurrence and the business attributes of the event associated objects.

[0049] When the event trigger source system is inconsistent with the typical source of historical events of the same type, the system will perform abnormal source judgment logic. The logic compares the distribution of historical event sources, analyzes the business responsibility range, data authority range and recent operation and maintenance status of the current source system, and determines whether the current event source is reliable. If the system determines that the event source deviates significantly from the expected source, or the business authority of the source system does not have the business ability to trigger the event, the event will be marked as an abnormal event category. The system will pause the linkage processing process of the abnormal event after marking it, and transfer it to the abnormal event processing channel, ensuring that abnormal events do not affect normal business scheduling.

[0050] When the same event meets the trigger conditions of multiple business targets at the same time, the system will perform target conflict judgment to ensure that the business linkage process has a unique and clear processing direction. The system parses the business intent field in the event record when performing target conflict judgment. The business intent field usually contains the business purpose description when the event is triggered, such as cost compression demand, personnel supplement demand or asset allocation demand. The system matches the key semantic features in the business intent field, compares the field content with the preset business target semantic library, and determines the target that is most consistent with the business intent as the final business target from multiple candidate targets. In the case where the field contains multiple intent expressions, the system will make a comprehensive judgment on the field content according to the intent strong correlation, appearance order and business rule weight.

[0051] When the cost control target and the manpower matching target meet the trigger conditions at the same time, the system takes the cost control target as the priority business target. This priority selection strategy is based on the management requirement of enterprises to have higher priority for cost control in the resource tightening or budget limited scenario, so in the case where cost pressure and personnel gap exist at the same time, the system will prioritize the execution of cost control logic. After performing the priority judgment, the system writes the determined business target into the linkage context, which is used to guide the participation parameter calculation, sensitivity calculation and subsequent task scheduling process logic direction, ensuring that the processing path of the entire linkage process meets the enterprise business policy and operation constraints.

[0052] The system sets up target conflict judgment logic to make a unique selection among multiple potential business targets. The system parses the text content or structured tags in the business intent field, and judges the degree of association between the event and different business targets by identifying key semantic indicators appearing in the field. When the business intent field contains cost constraint indication information that can reflect the requirement of cost control, the system directly sets the business target of the event as the cost control target, to reflect the priority of the cost factor when the enterprise is under budget tightening or greater pressure of cost control.

[0053] The order determination logic infers the master-slave relationship of the business intent by reading the appearance position of the two types of indicators in the business intent field, and according to the writing order of the information in the field. If the cost constraint indication information appears before the manpower gap indicator in the field, the system sets the business target as the cost control target; if the manpower gap indicator appears first, the system sets the business target as the manpower matching target. The core of order determination is to reflect the intention priority when the event is triggered through the natural order of field content, avoiding the identification bias of business target caused by information clutter or redundant expression.

[0054] Embodiment 1: In combination with the accompanying Figure 4 In a certain enterprise resource coordination environment, the system identifies human resource data and reads the post information about the post involved in this expansion task in the post management system. The system identifies that the post types are equipment maintenance posts and operation posts, totaling 2 categories, and each category has a number of post instances. When checking the personnel qualification information, the system finds that the qualification level requirement of the maintenance post is level four, and the number of personnel in the system with this qualification level is three, and further reads the on-duty state field of the personnel, finds that one of the personnel is in a busy state, and the estimated completion time of the other task being executed is thirty-six units of time, and the other two personnel are in a deployable state. When calculating the resource occupation of the personnel, the system finds that one of the deployable personnel has a current load of 20%, and the other has a load of 50%, so the system marks the personnel with lower load as the preferred allocation object.

[0055] When identifying financial data, the system reads the budget state of the cost center to which the expansion task belongs from the budget system, detects that the budget balance of the budget subject corresponding to the task is 400,000 units of quota, and the budget frozen amount is 50,000 units of quota, and the system determines that the budget is in an executable condition. At the same time, the system identifies that the expense category is equipment purchase expense, and reads the approval chain state from the approval system, finds that the previous node of the current approval chain has completed the approval, the approval authority of the next node is complete and no suspension record appears, so the financial data is marked as compliant and available.

[0056] In identifying asset data, the system reads the records in the asset system, determines that there are five key devices available for expansion, of which three are in use, one is in maintenance, and one is idle. The system further calculates the occupancy information of each device and identifies that the three devices in use have been occupied for eighty, ninety, and one hundred and twenty units of time, respectively. The maintenance device is expected to have a remaining maintenance time of twelve units of time, and the idle device can be immediately deployed. The system then identifies the life cycle state of the device and finds that the idle device has been in use for forty percent of its life cycle and is still in a stable state, making it suitable for deployment. Therefore, the system determines the idle device as the preferred resource for this expansion plan.

[0057] After completing the identification of the three types of element data, the system begins to execute conflict assertion rules to determine whether there are inconsistencies in multi-source data. The system performs permission conflict assertion by comparing the permission configurations of the human resource system, the financial system, and the asset system. It finds that the configuration of a certain sub-permission of the budget adjustment function in the financial system is inconsistent with the permission mapping recorded in the human resource system. The system continues to verify the process records according to the process state assertion rule and finds no contradictions in the process state. Then it executes the information version assertion rule, and the system compares the data update timestamps recorded in the three systems. It finds that the latest record in the asset system is updated later than the reference version recorded in the human resource system, indicating a potential version lag risk.

[0058] To determine which system will resolve the conflict, the system starts the responsibility chain resolution mechanism by comparing the business domains, data authority levels, and timestamp credibility of the three systems to determine the appropriate resolution order. The human resource system is marked as the authoritative domain for personnel attribute data, the financial system is marked as the authoritative domain for budget data, and the asset system is marked as the authoritative domain for device data. The system determines that the budget permission conflict should be resolved by the financial system according to the priority rule, as the budget permission belongs to the core data of the financial domain. At the same time, the system checks the data authority level of the financial system, which is nine, the human resource system, which is six, and the asset system, which is seven, so the financial system also has an advantage in authority level. The system continues to check the timestamp credibility of the records, and the financial system record has a time deviation of zero point two units of time, which is within the highest credibility range. Therefore, the system determines the financial system as the preferred resolution system for this conflict. The financial system eliminates the permission mapping conflict according to the rules and writes the adjusted permissions back to the remaining systems. The system also records the resolution process for subsequent audit calls.

[0059] The asset system records that a certain device is idle, and can be immediately allocated, while the task referencing the device ID in the human system shows that it is in use. Since the time stamps of the records in the two systems are very close and the data authority levels are comparable, the system cannot complete the arbitration according to the current assertion rule, so the manual arbitration branch is triggered, the system generates a context description including the conflict field, the source system, the version number, the conflict description and the impact path, and pushes it to the arbitration request pool of the manual approval node for manual multi-factor judgment and decision-making.

[0060] During the waiting for manual arbitration, the system calculates the comprehensive linkage sensitivity of each human and material element in the current business scenario based on the previously confirmed task and resource relationship, to determine the subsequent task execution order and whether to perform dynamic response suppression. The system sets the executable time window of this expansion task to 10 time units, and dynamically generates the task dependency function , the resource scarcity function , and the processing timeliness function at each time according to the scheduling management module, and calculates the dynamic weighted integral function as follows:

[0061] The example values of each function input are as follows: , indicating that the task dependency increases slightly over time; , indicating that the resource scarcity gradually eases with allocation; , indicating that the timeliness gradually improves; The weights and adjustment parameters are set as follows: , , , , , .

[0062] Substituting the integral expression, we get:

[0063] The system uses numerical integration method to calculate, and performs trapezoidal integration in 10 intervals: Calculate the first term: , square it and multiply by 4; Take the logarithm of the second term: ) multiplied by 1.5; The third term is the adjusted form of the sigmoid activation function, representing the nonlinear sensitive rise of timeliness; After system integration calculation, the result is: ​

[0064] The system accordingly marks the comprehensive linkage sensitivity of this task as 84.27, which exceeds the 70-point suppression threshold in the current linkage task pool, and therefore judges that the task has high sensitivity and must be prioritized and cannot be delayed or suppressed. The sensitivity of a certain financial approval task among other tasks is only 48.91, and the system lists it in the delayed scheduling queue, releasing scheduling resources for the current high-priority task.

[0065] The system begins to issue cross-system instructions in the scheduling order, making system calls for deployment equipment, assigning personnel, and allocating budgets. In the instruction sequence, the equipment call instruction received by the asset system is intercepted by the system semantic comparison rule module. The system calls the semantic comparison rule set, including: Action intent matching rule: ensure that the allocation behavior is consistent with the system business action; Field meaning matching rule: ensure that the equipment number and usage state field are consistent in the meaning of each system; Terminology consistency rule: ensure that the terms idle and allocated do not produce ambiguity in each system; After matching, the system finds that the device state field in the asset system is defined as 0 indicating idle, while the state code IDLE identified in the task scheduling is not synchronized with the dictionary, resulting in a field semantic conflict. The system immediately suspends the scheduling call process of this instruction, marks it as suspended, and records the semantic conflict log, notifying the data management system to update the field mapping.

[0066] The system has completed resource sensitivity evaluation and generated a high-priority task scheduling sequence. A certain key task involves state adjustment and allocation call for a spare device numbered A1002, which is originally in an idle state. The system issues a transfer into the expansion project operation instruction, and has been preliminarily executed by the asset system to update the device state to in use, while switching its cost center from the general equipment pool to the expansion project cost center. After the operation is completed, the system enters the semantic consistency verification process.

[0067] However, in the cross-system semantic comparison process, the system finds that the device management subsystem uses an integer type identifier for the usage state, while the scheduling system uses a string identifier, and no semantic mapping has been established between the two, resulting in some fields being escaped incorrectly during data encapsulation. The state code received by the asset system is 2, which should represent under repair, not in use. Such misencapsulation causes device deployment conflicts after the operation is landed, and the A1002 device relied on by the expansion task is incorrectly marked as under repair and excluded from the current project resource pool by other scheduling logic, causing the task dependency chain to break.

[0068] To avoid the propagation of the expansion error to subsequent tasks, the system initiates an instruction rollback control mechanism, which identifies the partially executed operation records in the instruction sequence, extracts the initial state, and performs a reverse recovery process. The rollback process includes three steps: the first step is to restore the usage state field of device A1002 to idle, the second step is to restore the device home cost center field value to the general device pool, and the third step is to delete the erroneous task state dependency relationship in the scheduling engine and update the device index table. After the rollback operation is completed, the system records the exception operation number and field repair record and archives it.

[0069] After the device instruction rollback is completed, the system reloads the task sequence and continues to execute the next instruction, i.e., sets another device numbered A1005 as the replacement resource. Since this device is in maintenance in the asset system and has a version number inconsistency problem, the system identifies that the maintenance record version of A1005 in the asset system is lower than the snapshot of the version used by the scheduling system, which poses a potential encapsulation failure risk. At this time, the system initiates an instruction suspension control mechanism, which marks the allocation A1005 operation instruction as a pending state and suspends it from the current time window scheduling call process. The suspended instruction is transferred to the system suspension queue and triggers a version comparison task in the maintenance system, and after the data consistency is completed, it is awakened.

[0070] Embodiment 2: In combination with the attached Figure 5 Based on Embodiment 1, after the previous stage device allocation task has undergone instruction rollback and suspension processing, the system detects a new business trigger event. This event originates from the budget system, with event record number E202311. The trigger source system of this event record is the financial budget module, and the update field in the event field shows that the expansion special budget quota has been increased from 300,000 to 400,000. The system preliminarily identifies the event type according to the preset rules, reads the event trigger source system, confirms that it is the budget system, and classifies it as a financial event according to the defined relationship between systems. Analyzing the event field content, the field name is budget.amount.increment, and the semantic identifier is an amount adjustment operation. According to the field operation classification, it is further determined that the event is a budget adjustment event. The system judges whether the time window in which the event occurs covers the current task execution window. The current expansion task scheduling window is set to T1 to T10, and the event occurs at time point T3. According to the rule engine matching, this event falls into the budget event quick reaction interval, i.e., budget adjustment within five units of time will affect the current task allocation.

[0071] By the above three dimensions of joint judgment, the system finally classifies the event as a budget adjustment event and activates the corresponding business target judgment process. Since the event originates from budget adjustment, the system reads the business target bias table, and according to the budget adjustment description field recorded in the budget system, it parses the keywords cost reduction and fund rearrangement semantics, and accordingly sets the business target of this time as cost control priority. At the same time, the system also scans the task scheduling queue and finds that there are still some post personnel unassigned, which exists the risk of manpower vacancy, but since the event priority is fund change type, the system sets the manpower matching target as secondary, and does not enter the main scheduling logic.

[0072] After determining the business target, the system prepares for subsequent generation of participation parameters of three types of resource elements. The generation of participation parameters requires the spread judgment of the influence range of the event. The system adopts the following spread judgment logic: starting from the expansion special budget number bound by the event, it locates the associated business task pool, including equipment allocation, personnel allocation, and construction coordination. The system determines the influence of budget changes on personnel compensation, equipment procurement, and construction contracting three types of sub-items according to the human, financial and material data source tables they depend on. The system performs influence chain analysis on the data fields associated outside each affected sub-item, identifies that the post types affected by the compensation item are engineering management post and procurement post, the asset types affected by equipment procurement are A type of allocated equipment and temporary rental equipment, and the organization entities affected by construction coordination are project temporary personnel pool and material plan table.

[0073] The system constructs an event spread path graph through a graph-based influence chain evaluation method, and identifies a total of five human resource sub-items, four financial fields, and seven asset records involved in the event, marked as involving three types of resource elements. The system inputs these involved fields into the participation calculation module, generates a set of participation parameters as scheduling input in combination with the priority target of the event and the task binding depth.

[0074] The system detects another event record at time point T5, event number E202312. The trigger source system of the event is marked as the human resource management platform, but it records not personnel scheduling related content, but a field named equipment_reassign_flag, whose field value is switched from False to True. This field is intended to be a device reassignment start signal, which obviously belongs to the asset system defined field, but is sent by the human system.

[0075] The system triggers the event type identification mechanism, finds that the event source system is a human system, but the field is obviously unique to the asset system. According to the defined field priority judgment mechanism, the system does not take the source system as the event type determination basis, but identifies the business action semantics expressed by the field. Through the system search of the field mapping table, it is found that the field is defined as a device allocation behavior start item, corresponding to the asset allocation process, so the event type is determined as an asset state change event rather than a post adjustment event, successfully avoiding the event classification error caused by the source system misinvestment.

[0076] At the same time, the system identifies that this event and the previous budget adjustment event E202311 belong to the associated trigger events of task T4, and the time window of task T4 covers T2 to T7, the time point of event E202311 is T3, the time point of E202312 is T5, and another post adjustment request event E202313 has a time point of T6, its source system is human platform, the field is post_change_id, and the field label is post change behavior. At this time, the system identifies that the three events all fall into the scheduling window of task T4, forming a multi-event overlap.

[0077] The system queries the standard response time limit table corresponding to each event, the budget event response period is five units, the post adjustment event is three units, and the device reallocation event response period is the shortest, only two units. The system takes the current event E202312 as the leading event driving task scheduling adjustment according to this, and updates the task scheduling path priority accordingly.

[0078] Since the event involves budget changes, human post adjustments, and asset reallocations, the system generates multiple candidate targets when identifying business targets. The system executes the business target conflict judgment mechanism according to the preset process, reads the business intent field content bound to task T4: project expansion has started, and needs to control cost and fill the human post gap. The analysis of the field result finds that it contains two semantic keywords: cost control and human post matching. The system determines that there is a multi-target candidate scenario.

[0079] According to the priority rules, the system identifies that the cost control keyword appears first in the field, and is defined as a high-weight target keyword in the matching library. The system determines that the current business target is the cost control priority target, not the human post matching target.

[0080] Finally, the system successfully avoids event classification errors based on the identification mechanism that the event field and the source system are inconsistent; based on the fast calculation mechanism of the response period in the cross time window, it accurately selects the event driving scheduling adjustment with the most time efficiency impact; and combined with the semantic order and weight analysis of the business intent field, it realizes the unique determination of the business target in the multi-target scenario.

[0081] The scheduling system receives a new round of task update event from the collaborative management platform, and the event number is E202314. The business intent field contained in the event is: the project expansion needs to be completed quickly, the current post personnel is insufficient, and the budget has approached the upper limit, and the cost needs to be controlled carefully. This field is a business semantic expression input used to assist decision-making by the system, and the field content comes from the project manager or the process engine splicing.

[0082] After the system receives the field, it triggers the target conflict judgment mechanism and enters the multi-target conflict judgment process. The system uses a natural language parser to split the business intent field into several logical clauses and identifies the indicating information phrases therein, including the budget approaching the upper limit and the post personnel being insufficient. The system matches the former with the cost constraint indicating information library and the latter with the manpower gap identifier, and preliminarily confirms that there are two candidate business targets, namely the cost control target and the manpower matching target.

[0083] The system executes the instruction information weight priority evaluation logic. According to the order of the original text in the field, the budget approaching the upper limit is a phrase that appears earlier and is located in the second sentence after the beginning of the entire field, while the post personnel being insufficient is a descriptive clause and is located in the third sentence. Under the order priority mechanism, the system determines the priority of the target according to the order of the indicating information. If the cost constraint phrase appears before the manpower gap phrase, the priority target is determined to be the cost control target.

[0084] Based on the confirmation of the target, the system adjusts the original scheduling task plan. Since the current expansion task involves two adjustable post personnel and three equipment procurement operations, and the budget occupancy has reached 90% of the upper limit, the system generates an adjustment scheme accordingly: suspend one of the equipment procurement instructions in the allocation plan, and prioritize the execution of the manpower allocation task, while introducing a resource occupancy rate control condition to limit the execution cost.

[0085] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for linking enterprise human, financial, and material data with business scenarios, characterized in that: Includes the following steps: When a target business scenario event is detected in the operation of an enterprise, the three types of elements involved—human resources data, financial data, and asset data—are determined based on the event type and business objectives, and participation parameters reflecting the depth of participation and response priority of the elements are generated. For the multi-source human, financial and material data corresponding to the participation parameters, the system performs status conflict identification, determines whether there are permission conflicts, version conflicts or logical contradictions based on the preset conflict assertion rules, and specifies the priority adjudication system through the chain of responsibility adjudication mechanism. If the conflict cannot be eliminated, it enters the manual arbitration branch. Provided that the data status is legal, the linkage sensitivity of each person, financial and material element is calculated based on the participation parameter to determine the task execution order and implement dynamic response suppression for elements with high dependence to generate a task scheduling sequence; then the execution instructions in the task scheduling sequence are sequentially called to cross-system semantic comparison rules. If the semantics of the instructions are determined to be inconsistent or the encapsulation is abnormal, instruction rollback or suspension is triggered.

2. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 1, characterized in that... The process of determining the human resources data includes classifying and identifying job information, personnel qualifications, on-the-job status, and resource utilization; the process of determining the financial data includes determining budget status, expense categories, cost centers, and approval chain status; and the process of determining the asset data includes identifying asset usage status, occupancy information, lifecycle status, and availability.

3. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 1, characterized in that... The conflict assertion rules include at least one of permission conflict assertion rules, process status assertion rules, and information version assertion rules; the chain of responsibility adjudication mechanism includes a set of rules for adjudication based on the priority of the business domain to which the system belongs; the chain of responsibility adjudication mechanism compares the business domain, data authority level, and timestamp credibility of each system before executing the adjudication to determine the system to be adjudicated first.

4. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 1, characterized in that... The process of entering the manual arbitration branch includes generating a conflict context description and pushing an adjudication request to the manual approval node; the calculation of the linkage sensitivity includes a combination of sensitivity factors based on task dependency, resource scarcity and processing timeliness; the semantic comparison rule set includes at least one of action intent matching rules, field meaning matching rules and cross-system terminology consistency rules.

5. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 1, characterized in that... The instruction rollback control includes reversing and resetting the executed partial operations to restore the initial state; the instruction suspension control includes marking the instruction as pending execution and suspending its invocation process in the target system; the business scenario event includes at least one of the following: project change event, budget adjustment event, job adjustment event, or asset status change event.

6. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 1, characterized in that... The identification of the event type includes classifying the event based on the event triggering source system, event fields, and event time windows; the business objectives include at least one of cost control objectives, manpower matching objectives, and asset allocation objectives; before generating the participation parameters, the scope of the event's impact is assessed to determine the actual involvement of the three types of elements.

7. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 6, characterized in that... During the event type identification process, when the event triggering source system and the event field are inconsistent, field priority judgment is performed, and the business action recorded in the event field is used as the final basis for the event category; when the event belongs to the intersection of multiple time windows, the event category is determined according to the time window corresponding to the shortest response period.

8. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 6, characterized in that... In the event field that is missing, the system executes a completion judgment logic based on the triggering source system to infer the business category corresponding to the event; when the event triggering source system is inconsistent with the source of similar historical events, the system executes the abnormal source judgment logic and marks the event as an abnormal event category.

9. The method for linking enterprise personnel, financial, and material data with business scenarios according to claim 6, characterized in that... When there are multiple candidate business objectives, the system performs objective conflict judgment and selects a single business objective by identifying the business intent field; when the cost control objective and the manpower matching objective meet the trigger conditions at the same time, the cost control objective is taken as the priority business objective.

10. The method for linking enterprise human, financial, and material data with business scenarios according to claim 9, characterized in that... The execution target conflict judgment includes: parsing the content in the business intent field; if the business intent field contains cost constraint indication information, setting the business target as a cost control target; if the business intent field contains both cost constraint indication information and manpower shortage indicator, performing order judgment according to the order of appearance of cost constraint indication information and manpower shortage indicator in the business intent field to determine the final setting of the business target.

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