Virtual organization-based mining and selling business collaborative management method and system

Abstract

The invention discloses a virtual organization-based mining and selling business collaborative management method and system, and the method comprises the steps: constructing a virtual organization tree with financial categories, commodity categories or business lines as dimensions, and building the ternary relation data among virtual organization nodes, mining and selling personnel and a commodity management authority range; based on the ternary relation data, the system can respond to a downstream request, position a commodity principal through an authority reverse checking algorithm, or generate an approval link through a dynamic routing algorithm; meanwhile, according to the ternary relation data, the original performance data are aggregated into structured performance indicator data according to the personnel dimension, and when personnel responsibilities are changed, all algorithms can be linked to take effect by updating the node binding relation. According to the invention, automatic cooperation of authority verification, approval circulation and performance accounting is realized through a unified data model, the problems of tedious maintenance and system fragility caused by separation of an organization model and a business rule are solved, and the efficiency of acquisition and sales business management is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of enterprise information management technology, and in particular to a method and system for collaborative management of procurement and sales based on virtual organizations. Background Technology

[0002] In the field of enterprise management, procurement and sales are the core links connecting the supply chain and sales terminals, and their collaborative efficiency directly affects the company's operating costs and market responsiveness. Traditional management methods rely on the physical organizational structure defined by the enterprise's human resources system. This structure is centered on administrative boundaries and focuses on static management functions such as staffing and budget control, resulting in a relatively stable structure. As business processes become more sophisticated, the actual responsibilities of procurement and sales personnel often need to be divided according to dynamic business dimensions such as financial categories, product categories, and business lines. These dimensions naturally present a granularity mismatch with fixed physical departments. To address this challenge, existing technologies have introduced solutions that incorporate the concept of virtual organizations. These solutions allow for the creation of flexible management units outside the physical organizational structure, based on projects or temporary tasks, to facilitate personnel search and simple permission allocation.

[0003] However, existing solutions still have fundamental limitations when addressing the deep collaboration needs of vertical business chains like procurement and sales. The construction of virtual organizations is often independent of core business data flows and process rules, resulting in a disconnect between them and downstream critical business systems such as access control, approval processes, and performance evaluation. Granting and revoking permissions, determining approval nodes, and collecting performance data still rely heavily on manual configuration and data transfer across systems. When business scope changes or personnel responsibilities change, this fragmented, primarily manual maintenance model is not only inefficient but also prone to systemic risks such as inconsistent data definitions and process interruptions, making it difficult to support the needs of rapid business iteration and refined operations. How to build an integrated management framework that can deeply integrate into business scenarios and achieve automatic linkage between organizational models, business rules, and data, thereby systematically improving the agility and reliability of procurement and sales collaboration, has become a pressing technical problem in this field. Summary of the Invention

[0004] In view of this, the purpose of this invention is to propose a collaborative management method and system for procurement and sales business based on virtual organizations. By constructing a virtual organizational tree that is deeply bound to the business dimension and forming a three-element relationship data of nodes, personnel, and products, it realizes automatic linkage and unified management of core business scenarios such as permissions, approval, and performance, and solves the problems of inefficient maintenance and system fragility caused by the separation of organizational models and business rules in procurement and sales business collaboration.

[0005] To achieve the aforementioned technical objectives, in a first aspect, this application provides a collaborative management method for procurement and sales operations based on a virtual organization, comprising: Receive entity organizational structure data from the enterprise's human resources system, and construct a virtual organizational tree based on the procurement and sales business dimension. The virtual organizational tree contains virtual organizational nodes based on financial categories, product categories, or business lines, and assigns a unique identifier to each virtual organizational node. Bind virtual organization nodes to purchasing and sales personnel, and configure the virtual positions and product management permission scope corresponding to the virtual organization nodes to generate node-person-product ternary relationship data; In response to a permission verification request initiated by a downstream business system, which contains target product information, the system executes a reverse permission lookup algorithm based on ternary relation data to locate and return the purchasing and sales personnel responsible for the target product information. In response to the approver retrieval request initiated by the approval system, which includes business context information, the target node is located in the virtual organization tree based on the product or financial category parameters in the business context information. Based on the virtual job information configured on the target node, the approval link and specific approver are generated through a dynamic routing algorithm. Raw performance data related to product or financial categories is collected from business data sources. Based on the ternary relationship data, a data aggregation algorithm is executed to aggregate the raw performance data according to the personnel dimension and generate structured performance indicator data. When a change in the responsibilities of a purchasing and sales personnel is detected, the node binding relationship in the virtual organization tree is updated, and a synchronization mechanism is triggered, so that the permission reverse lookup algorithm, dynamic routing algorithm and data aggregation algorithm automatically take effect based on the updated ternary relationship data.

[0006] In some embodiments, receiving entity organizational structure data from an enterprise's human resources system and constructing a virtual organizational tree based on the procurement and sales business dimension includes: Receive entity organization change events from the enterprise human resources system. Entity organization change events include operations such as adding, updating, merging, splitting or transferring organizations and their associated data. According to the preset mapping rules, entity organization change events are converted into virtual organization tree maintenance instructions. The preset mapping rules define the correspondence between entity organization units and procurement and sales business dimensions. Execute virtual organization tree maintenance instructions to create or update virtual organization nodes in the virtual organization platform based on financial category, product category or business line, and generate a globally unique node identifier for each newly created virtual organization node; Establish and persist the mapping relationship records between virtual organization nodes and source entity organization units and business dimensions to form the metadata foundation of the virtual organization tree. The metadata foundation is used to support subsequent change traceability and data synchronization consistency verification.

[0007] In some embodiments, virtual organization nodes are bound to purchasing and sales personnel, and the virtual positions and product management permission scopes corresponding to the virtual organization nodes are configured to generate node-person-product ternary relationship data, including: Receive binding instructions and configuration parameters for the target virtual organization node. The configuration parameters include the identifier of the purchasing and sales personnel to be bound, the virtual job role assigned to the virtual organization node, and the definition of the range of products that the virtual organization node can manage. According to the binding instructions, establish the association between the target virtual organization node and the procurement and sales personnel identifier in the data model of the virtual organization tree; Based on the product range definition in the configuration parameters, a corresponding permission policy expression is generated for the target virtual organization node. The permission policy expression is used to describe the management boundaries of the virtual organization node in terms of product, financial category or store dimension. The relationships, virtual job role information, and permission policy expressions are logically linked and persistently stored to form a data unit for the node-person-product ternary relationship data.

[0008] In some embodiments, an access control algorithm is executed based on ternary relation data to locate and return the purchasing and sales personnel responsible for the target product information, including: Parse the target product information in the permission verification request and extract the key attributes used for matching. The key attributes include financial category code, product category code or store code. Using key attributes as input conditions, a multi-dimensional matching query is performed in the ternary relation data. The multi-dimensional matching query filters out candidate virtual organization nodes whose management scope covers the target product information by traversing the permission policy expressions of the nodes. From the selected candidate virtual organization nodes, the final target node is determined according to the preset conflict resolution rules, which include, but are not limited to, exact matching priority and the finest granular node priority. Based on the relationships stored in the ternary relation data, extract the procurement and sales personnel identifiers bound to the final target node, and return them as the permission verification result to the downstream business system that initiated the request.

[0009] In some embodiments, determining the final target node from the selected candidate virtual organization nodes according to a preset conflict resolution rule includes: Obtain candidate virtual organization nodes and read the permission policy expression corresponding to each candidate virtual organization node. The permission policy expression defines the management scope boundary of the node in terms of financial category, product category and store dimension. The matching degree of the permission policy expression of each candidate virtual organization node is calculated with the key attributes of the target product information to generate a matching degree score. The matching degree score is used to quantify the accuracy of the coverage between the node management scope and the target product information. The conflict resolution rules are applied according to the preset resolution priority order. The resolution priority order specifies that when the matching scores are the same, the exact matching rule is used first, followed by the finest granular node rule. Based on the results of applying the conflict resolution rules, a unique candidate virtual organization node is selected from the candidate virtual organization nodes as the final target node responsible for the target product information, and the identifier of the final target node is output.

[0010] In some embodiments, based on the product or financial category parameters in the business context information, a target node is located in the virtual organization tree, and based on the virtual job information configured on the target node, an approval link and specific approver are generated through a dynamic routing algorithm, including: Parse the business context information and extract the product identifier or financial category code used for node positioning as the query key; Using the query key as input, a node location query is performed in the virtual organization tree. The node location query determines the virtual organization node most relevant to the business context information by matching the business dimension attributes or permission policy expressions of the virtual organization node, and is recorded as the initial target node. Obtain the virtual job sequence pre-configured for the current approval scenario on the initial target node. The virtual job sequence defines the role order required for the approval process. For each virtual job in the virtual job sequence, query the ternary relation data for purchasing and sales personnel who are bound to the initial target node and whose roles match. If there is no matching personnel at the current node, the query will proceed step by step up the virtual organization tree according to the preset backtracking rules until a matching personnel is found for the current virtual position or the backtracking termination condition is met, and the backtracking query result will be obtained. The procurement and sales personnel determined by the virtual job sequence and retrospective query results will be arranged in an orderly manner, generating a complete approval chain and a list of specific approvers, and then returned to the approval system.

[0011] In some embodiments, if there is no matching personnel at the current node, the query proceeds upwards along the parent node path of the virtual organization tree according to preset backtracking rules until a bound personnel is found for the current virtual position or the backtracking termination condition is met, obtaining the backtracking query results, including: If no matching personnel for the current virtual position are found at the initial target node, a backtracking query process is triggered. Based on the node hierarchy stored in the virtual organization tree, the direct parent node of the initial target node is obtained as the current backtracking node; In the ternary relation data, query the purchasing and sales personnel who are bound to the current backtracking node and whose roles match the current virtual positions; If the query is successful, the procurement and sales personnel found will be designated as the approver for the current virtual position, and the backtracking query for the current virtual position will be terminated. If the query fails, the direct parent node of the current backtrack node will be updated to the new current backtrack node, and the personnel query steps will be repeated. When the backtracking query reaches the root node of the virtual organization tree and still fails to find a matching person, or reaches the preset maximum backtracking level, it is determined that the backtracking termination condition has been met, and the backtracking query result is generated according to the preset default processing strategy.

[0012] In some embodiments, raw performance data associated with product or financial categories is collected from business data sources. Based on ternary relationship data, a data aggregation algorithm is executed to aggregate the raw performance data by personnel dimension, generating structured performance indicator data, including: Raw performance data streams are collected from designated business data sources in a triggered manner. Each record in the raw performance data stream is associated with at least one product identifier or financial category code and at least one performance numerical indicator. Using the product identifier or financial category code in the original performance data stream as the association key, perform a reverse mapping query in the ternary relation data to determine one or more responsible virtual organization nodes to which each original performance record belongs, and further obtain the purchasing and sales personnel identifiers bound to these nodes; Based on the preset performance indicator calculation rules and aggregation logic, the numerical indicators in multiple original performance records belonging to the same procurement and sales personnel are aggregated. The aggregation operation includes summation, averaging, counting, or weighted calculation. The results of the aggregation operation are combined with the corresponding procurement and sales personnel identification, scope of responsibility description, and performance cycle information to generate structured performance indicator data records based on personnel, and then output to the performance appraisal system or data dashboard.

[0013] In some embodiments, using the product identifier or financial category code in the original performance data stream as the association key, a reverse mapping query is performed in the ternary relation data to determine one or more responsible virtual organization nodes to which each original performance record belongs, and further obtains the purchasing and sales personnel identifiers bound to these nodes, including: For each performance record in the original performance data stream, the association key contained in the performance record is used as the current query key for this query; The current query key is compared one by one with the permission policy expressions corresponding to each virtual organization node recorded in the ternary relation data to obtain the comparison results; Based on the comparison results, identify all virtual organization nodes whose management scope, as defined by their permission policy expressions, can cover the current query key, and mark these virtual organization nodes as the responsible virtual organization nodes for the current performance record; Additionally, based on the virtual organization nodes and personnel binding relationships stored in the ternary relationship data, the procurement and sales personnel identifier associated with each responsible virtual organization node is obtained.

[0014] In a second aspect, the present invention also provides a procurement and sales business collaborative management system based on virtual organizations, applicable to the method described in the first aspect. The system includes a virtual organization construction module, a relationship configuration and storage module, a permission service module, an approval routing service module, a performance data aggregation module, and a change synchronization and activation module. The virtual organization construction module receives entity organizational structure data from the enterprise's human resources system and constructs a virtual organization tree based on the procurement and sales business dimension. The virtual organization tree contains virtual organization nodes based on financial categories, product categories, or business lines, and assigns a unique identifier to each virtual organization node. The relationship configuration and storage module binds virtual organization nodes to procurement and sales personnel, configures the virtual positions and product management permission scope corresponding to the virtual organization nodes, and generates and stores ternary relationship data between nodes, personnel, and products. The permission service module responds to permission verification requests initiated by downstream business systems. The permission verification request includes target product information and executes the request based on the ternary relationship data. The system employs a reverse lookup algorithm to locate and return the purchasing and sales personnel responsible for the target product information. The approval routing service module responds to approver retrieval requests initiated by the approval system. These requests include business context information. Based on the product or financial category parameters in the business context information, it locates the target node in the virtual organizational tree and generates the approval chain and specific approvers based on the virtual job information configured on the target node using a dynamic routing algorithm. The performance data aggregation module collects raw performance data associated with product or financial categories from business data sources. Based on the ternary relationship data, it executes a data aggregation algorithm to aggregate the raw performance data by personnel dimension, generating structured performance indicator data. The change synchronization and activation module updates the node binding relationship in the virtual organizational tree when a change in the responsibilities of purchasing and sales personnel is detected, triggering a synchronization mechanism so that the permission service module, approval routing service module, and performance data aggregation module automatically take effect based on the updated ternary relationship data.

[0015] By adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art: The present invention provides a method and system for collaborative management of procurement and sales business based on virtual organizations. This method constructs a virtual organizational tree with dimensions such as financial category, commodity category, or business line, and establishes a ternary relationship data between virtual organizational nodes, procurement and sales personnel, and commodity management authority scope. Based on this ternary relationship data, the system can respond to downstream requests, locate the commodity responsible person through a reverse lookup algorithm, or generate an approval link through a dynamic routing algorithm. Simultaneously, based on the ternary relationship data, the original performance data is aggregated into structured performance indicator data according to the personnel dimension. When personnel responsibilities change, updating the node binding relationship enables all algorithms to take effect in tandem. The present invention achieves automatic collaboration of permission verification, approval flow, and performance calculation through a unified data model, solving the problems of cumbersome maintenance and system fragility caused by the separation of organizational models and business rules, and significantly improving the efficiency of procurement and sales business management. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of steps S101 to S106 of the procurement and sales business collaborative management method described in the specific implementation method; Figure 2 This is a flowchart illustrating the process of configuring virtual positions and product management permission scopes corresponding to virtual organization nodes as described in the specific implementation method. Figure 3 This is a flowchart illustrating the process of generating the approval chain and specific approvers as described in the specific implementation method. Detailed Implementation

[0018] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be particularly noted that the following embodiments are for illustrative purposes only and do not limit the scope of the invention. Similarly, the following embodiments are only some, not all, embodiments of the present invention, and all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 In a first aspect, this embodiment provides a collaborative management method for procurement and sales operations based on a virtual organization, including: S101. Receive entity organizational structure data from the enterprise human resources system and construct a virtual organizational tree based on the procurement and sales business dimension. The virtual organizational tree contains virtual organizational nodes based on financial category, product category or business line, and assigns a unique identifier to each virtual organizational node. S102. Bind the virtual organization node to the purchasing and sales personnel, and configure the virtual positions and product management permission scope corresponding to the virtual organization node to generate node-person-product ternary relationship data; S103. In response to the permission verification request initiated by the downstream business system, the permission verification request contains the target product information. Based on the ternary relation data, the permission reverse lookup algorithm is executed to locate and return the purchasing and sales personnel responsible for the target product information. S104. In response to the approver retrieval request initiated by the approval system, the approver retrieval request contains business context information. Based on the product or financial category parameters in the business context information, the target node is located in the virtual organization tree. Based on the virtual job information configured on the target node, the approval link and specific approver are generated through a dynamic routing algorithm. S105. Collect raw performance data related to product or financial categories from business data sources, and based on the ternary relationship data, execute the data aggregation algorithm to collect the raw performance data by personnel dimension and generate structured performance indicator data. S106. When a change in the responsibilities of a purchasing and sales personnel is detected, update their node binding relationship in the virtual organization tree and trigger the synchronization mechanism so that the permission reverse lookup algorithm, dynamic routing algorithm and data aggregation algorithm automatically take effect based on the updated ternary relationship data.

[0020] In step S101, the entity organizational structure data is obtained from the enterprise's human resources system through a preset interface, reflecting the company's administrative management levels. A virtual organizational tree is constructed based on the procurement and sales business dimension, using specific business attributes such as financial categories, product categories, or business lines as the basis for division, creating a new organizational model independent of entity departments. Each virtual organizational node in the virtual organizational tree represents a specific business management scope, such as a third-level financial category or a product category. A unique identifier is assigned to each node, generated using globally unique coding rules, to unambiguously identify the node within the system and in cross-system interactions. This step, by combining a stable entity organizational framework with flexible business management needs, establishes a unified and scalable organizational data foundation for subsequent collaborative management.

[0021] In step S102, the binding operation between the virtual organization node and the purchasing and sales personnel establishes the association between the business scope represented by the node and the specific person in charge. The virtual positions configured for the node define the logical role that the node plays in a specific business process (such as product approval), such as "reviewer" or "person in charge," and these roles are separate from the physical administrative positions. Simultaneously, the product management permission scope configured for the node clarifies the boundaries of the set of products that the node is authorized to manage through rules (such as a financial category list and product category range). The above binding relationships, virtual position information, and permission scope rules are logically linked and persistently stored, collectively constituting the node-person-product ternary relationship data. This step, through centralized configuration, solidifies personnel, business roles, and resource management scope into a unified data model, realizing the explicitness and structuring of management rules.

[0022] In step S103, when a downstream business system (such as a product management system) needs to verify permissions for a certain product operation, it initiates a request containing target product information (such as product ID and financial category). The permission reverse lookup algorithm takes this target product information as input, queries the product management permission scope of each node in the ternary relation data, identifies all virtual organization nodes whose management scope covers the product, and then determines the identifier of the purchasing and sales personnel responsible for the product based on the binding relationship between nodes and personnel. This identifier is then returned as the verification result. This step, through automated querying based on unified data relationships, replaces the traditional decentralized and static permission configuration checks, achieving accurate and efficient permission judgment.

[0023] In step S104, when the approval system needs to determine approvers for business processes involving specific product or financial categories (such as new product introduction), it initiates a request containing business context information. Based on the product or financial category parameters in the request, the virtual organization tree is queried to locate the virtual organization node whose management scope best matches the parameter as the target node. Based on the virtual job information pre-configured on the target node (e.g., configuring "preliminary review" and "final review" positions for the "contract approval" scenario), the dynamic routing algorithm searches for purchasing and sales personnel bound to and matching the position for each required position in the ternary relation data. If there is no matching personnel for a position at the current node, it is processed according to preset rules (e.g., searching to the superior node), ultimately generating an ordered list of approvers, i.e., the approval chain. This step dynamically associates approval rules (positions) with specific executors (personnel), enabling the approval process to adapt to changes in business structure and personnel responsibilities.

[0024] In step S105, raw performance data is collected from business data sources (such as transaction systems). Each record is associated with a specific product or financial category and performance indicators (such as sales revenue). The data aggregation algorithm, based on ternary relational data, first maps the product or financial category information in the records back to the responsible virtual organization node and the associated purchasing / sales personnel. Subsequently, the algorithm summarizes and calculates all performance indicators belonging to the same purchasing / sales personnel, generating structured data centered on the personnel, clearly listing their responsibilities and corresponding performance indicators. This step, through automated data mapping and aggregation, transforms scattered business details into a performance view centered on the responsible person, ensuring the consistency and accuracy of statistical standards.

[0025] In step S106, when the responsibilities of procurement and sales personnel change (e.g., triggered by a human resources system event or management operation), the binding relationship between the personnel and virtual organization nodes is updated in the virtual organization tree. This operation directly modifies the ternary relationship data. After the update is completed, a synchronization mechanism is triggered to notify or drive relevant services that depend on the ternary relationship data. Subsequently, the permission reverse lookup algorithm, dynamic routing algorithm, and data aggregation algorithm will automatically perform calculations based on the ternary relationship data containing the latest binding relationship during runtime, thereby enabling permission verification, approver determination, and performance statistics results to reflect the change in responsibilities in real time. This step, by establishing a change response closed loop centered on the core data model, achieves a one-time adjustment with global effect, significantly reducing the complexity and risk of multi-system collaborative maintenance.

[0026] This embodiment constructs and maintains a unified "node-person-product" ternary relationship data model, serving as a hub connecting organizations, personnel, and resources in procurement and sales operations. First, a virtual organizational tree tailored to the business is derived from the physical organization, generating core ternary relationship data. Based on this data model, a reverse lookup mechanism for permission verification, a dynamic routing mechanism for approval workflows, and an automatic aggregation mechanism for performance accounting are implemented. By establishing linkage and synchronization between responsibility changes and the data model, it ensures that all business logic can automatically and consistently adjust with changes. This embodiment, through data-driven approaches, deeply integrates previously fragmented management processes such as permissions, approvals, and performance into an organic whole, effectively solving the systemic problems of cumbersome maintenance, slow response, and error-proneness in traditional methods, thus improving the overall efficiency and robustness of procurement and sales management.

[0027] In some embodiments, receiving entity organizational structure data from an enterprise's human resources system and constructing a virtual organizational tree based on the procurement and sales business dimension includes: Receive entity organization change events from the enterprise human resources system. Entity organization change events include operations such as adding, updating, merging, splitting or transferring organizations and their associated data. According to the preset mapping rules, entity organization change events are converted into virtual organization tree maintenance instructions. The preset mapping rules define the correspondence between entity organization units and procurement and sales business dimensions. Execute virtual organization tree maintenance instructions to create or update virtual organization nodes in the virtual organization platform based on financial category, product category or business line, and generate a globally unique node identifier for each newly created virtual organization node; Establish and persist the mapping relationship records between virtual organization nodes and source entity organization units and business dimensions to form the metadata foundation of the virtual organization tree. The metadata foundation is used to support subsequent change traceability and data synchronization consistency verification.

[0028] In this embodiment, the process of constructing the virtual organizational tree is driven by change events in the enterprise's human resources system. Entity organizational change events can be obtained by subscribing to message notifications from the human resources system or by monitoring its data change logs. The events not only specify the operation type (such as adding a department or merging two stores), but also carry the specific identifier, attributes, and relationship data of the operation object, ensuring that the virtual organizational platform can promptly and accurately perceive any organizational structure changes in the source system.

[0029] Preset mapping rules are used to automatically convert entity organizations to business dimensions. Preferably, these preset mapping rules exist in the form of structured configuration files or logical statements stored in the rule engine. They explicitly specify which purchasing and sales business dimensions a particular entity organizational unit (e.g., a purchasing department with a specific functional code, or a group of stores located in a specific region) should be mapped to, such as a specific list of financial categories, a collection of product categories, or a business line identifier. When an entity organizational change event is received, these preset rules are queried based on the entity unit information in the event, thereby generating a corresponding virtual organization tree maintenance instruction. This instruction contains the operation to be performed (create, update, delete) and the specific parameters of the operation object in the business dimension.

[0030] Executing virtual organization tree maintenance commands involves completing the actual construction at the data layer of the virtual organization platform. The virtual organization platform parses the commands; if it's a creation operation, it inserts a new node record into the database based on the specified financial category, product category, or business line information, and generates a globally unique node identifier for that node. Generating a unique identifier can employ a distributed algorithm combining timestamps, machine identifiers, and serial numbers, or it can use a pre-allocated unique code segment to ensure its uniqueness across all virtual nodes. If it's an update operation, it modifies the dimensional attributes or status of an existing node.

[0031] After a node is created or updated, a mapping record is established and persistently stored. This mapping record contains at least the unique identifier of the virtual organization node, the identifier of the source entity organizational unit that triggered the operation, and the specific business dimension value mapped to that node. All such records constitute the metadata foundation of the virtual organization tree. The metadata is used to record the data source and evolution chain of the organizational model. When it is necessary to investigate data inconsistencies or conduct audits, this metadata can be used to fully trace the source and basis of each change of any virtual node, and provide a solid data comparison benchmark for verifying the synchronization status between the virtual organization tree and the entity organizational structure.

[0032] This embodiment achieves automated and rule-based synchronization between the virtual organizational tree and the physical organizational structure. Through a set of predefined and clear mapping rules, it automatically translates physical organizational change events occurring in the enterprise's human resources system into specific maintenance actions for the virtual organizational tree oriented towards procurement and sales operations, and solidifies complete mapping traceability information in the process. This embodiment upgrades the construction of the virtual organizational tree from a manual, batch maintenance mode to an event-driven, real-time automated process, significantly improving maintenance efficiency and accuracy. At the same time, the established metadata foundation provides indispensable data support for the reliability, auditability, and consistency verification of the entire collaborative management system, making the virtual organizational tree a dynamic, reliable, and traceable cornerstone of business management.

[0033] Please see Figure 2 In some embodiments, virtual organization nodes are bound to purchasing and sales personnel, and the virtual positions and product management permission scopes corresponding to the virtual organization nodes are configured to generate node-person-product ternary relationship data, including: Receive binding instructions and configuration parameters for the target virtual organization node. The configuration parameters include the identifier of the purchasing and sales personnel to be bound, the virtual job role assigned to the virtual organization node, and the definition of the range of products that the virtual organization node can manage. According to the binding instructions, establish the association between the target virtual organization node and the procurement and sales personnel identifier in the data model of the virtual organization tree; Based on the product range definition in the configuration parameters, a corresponding permission policy expression is generated for the target virtual organization node. The permission policy expression is used to describe the management boundaries of the virtual organization node in terms of product, financial category or store dimension. The relationships, virtual job role information, and permission policy expressions are logically linked and persistently stored to form a data unit for the node-person-product ternary relationship data.

[0034] In this embodiment, a specific data unit for generating node-person-product ternary relationship data begins with receiving a configuration operation for the target virtual organization node. This configuration operation can be initiated through the management interface or configuration interface provided by the virtual organization platform. The configuration parameters passed in explicitly include the identifier of the purchasing and sales personnel to be bound, the name of the virtual job role assigned to the node, and the definition of the product management scope described by rules. For example, the definition can be expressed as all products belonging to certain financial categories, or a set of products that simultaneously meet the conditions of a specific product category and store type.

[0035] Upon receiving the binding command and configuration parameters, the system immediately performs an operation in the data model used by the virtual organization tree to establish the association between the target virtual organization node and the specified procurement and sales personnel identifier. This is typically reflected in the underlying database as inserting a new record into the table storing the node-personnel mapping relationship, or updating an existing record, thereby establishing the responsibility relationship between personnel and business nodes at the data level.

[0036] Furthermore, the product range definition in the configuration parameters is used to generate the corresponding permission policy expression. The specific processing involves parsing the rule conditions in the definition and converting them into a structured expression that connects multiple dimension conditional clauses using logical operators. This permission policy expression precisely characterizes the management boundaries of virtual organization nodes in one or more dimensions such as product identification, financial category coding, and store type, becoming a standardized policy representation that can be directly parsed and executed by computer programs for matching judgments.

[0037] The node-person association records, virtual job role name information, and generated permission policy expressions generated in the preceding steps are logically bound together. Preferably, the binding is achieved by assigning the same transaction identifier or association key to these data elements generated in the same configuration operation. The bound whole is a complete data unit and is persistently stored in a database or other storage system. This data unit, which includes personnel associations, role definitions, and permission boundaries, constitutes a basic and independently usable data record in the node-person-product ternary relationship data.

[0038] This embodiment receives structured configuration input, sequentially establishes relationships between personnel and nodes, formalizes the strategy expression of product management scope, and stores these elements as a whole. This transforms business management intentions into structured, computable data entities, providing a unified, accurate, and directly operable data foundation for all collaborative management algorithms executed based on this ternary relationship data. This standardized data generation process ensures the consistency and reliability of the core data model.

[0039] In some embodiments, an access control algorithm is executed based on ternary relation data to locate and return the purchasing and sales personnel responsible for the target product information, including: Parse the target product information in the permission verification request and extract the key attributes used for matching. The key attributes include financial category code, product category code or store code. Using key attributes as input conditions, a multi-dimensional matching query is performed in the ternary relation data. The multi-dimensional matching query filters out candidate virtual organization nodes whose management scope covers the target product information by traversing the permission policy expressions of the nodes. From the selected candidate virtual organization nodes, the final target node is determined according to the preset conflict resolution rules, which include, but are not limited to, exact matching priority and the finest granular node priority. Based on the relationships stored in the ternary relation data, extract the procurement and sales personnel identifiers bound to the final target node, and return them as the permission verification result to the downstream business system that initiated the request.

[0040] In this embodiment, the execution of the permission reverse lookup algorithm begins with parsing the permission verification request. Upon receiving the request, key attributes for subsequent matching are extracted from the target product information contained therein. These attributes are identification information that can be associated with the virtual organization node management dimension, such as the financial category code to which the product belongs, its product category code, or the corresponding store code. The parsing process typically involves reading and identifying the fields of the request message or data object to obtain this standardized coded information.

[0041] After extracting the key attributes, they are used as input conditions to perform a multi-dimensional matching query in the ternary relation data. This query is achieved by traversing the permission policy expressions stored in each data unit of the ternary relation data. For each data unit, the key attribute is matched against the management scope defined by the permission policy expression to determine whether the attribute falls within the boundary described by the expression. After the traversal is complete, all virtual organization nodes whose permission policy expressions can cover the target product information are filtered out to form a candidate virtual organization node set.

[0042] Since a product may fall under the management scope of multiple different virtual organization nodes simultaneously, it is necessary to determine a single, responsible final target node from the candidate node set according to predefined conflict resolution rules. These conflict resolution rules are predefined and used to arbitrate among multiple candidate nodes; they include, but are not limited to, rules prioritizing exact matches and prioritizing the finest-grained node. These rules are applied to compare and rank the candidate nodes, thereby selecting the final target node.

[0043] After determining the final target node, the purchasing and sales personnel identifiers bound to that node identifier are queried based on the persistently stored associations in the ternary relation data. This query is typically performed in the database table storing the node-personnel association relationships. The corresponding purchasing and sales personnel identifier is retrieved through the node identifier, and the retrieved purchasing and sales personnel identifier is encapsulated as an authorization verification result and returned to the downstream business system that initiated the request, allowing it to complete the subsequent authorization decision-making process.

[0044] In this embodiment, the permission reverse lookup algorithm extracts key attributes by parsing the request, uses structured permission policy expressions in ternary relation data for traversal matching to initially screen candidate nodes, then applies preset conflict resolution rules to arbitrate and determine the unique responsible node, and finally locates and returns the specific person in charge based on the fixed association relationship. This process transforms product-based permission judgment into a series of automated query and decision-making steps based on clear rules and structured data, realizing accurate and efficient mapping from product information to responsible persons, and providing a reliable basis for permission decision-making for downstream business systems.

[0045] In some embodiments, determining the final target node from the selected candidate virtual organization nodes according to a preset conflict resolution rule includes: Obtain candidate virtual organization nodes and read the permission policy expression corresponding to each candidate virtual organization node. The permission policy expression defines the management scope boundary of the node in terms of financial category, product category and store dimension. The matching degree of the permission policy expression of each candidate virtual organization node is calculated with the key attributes of the target product information to generate a matching degree score. The matching degree score is used to quantify the accuracy of the coverage between the node management scope and the target product information. The conflict resolution rules are applied according to the preset resolution priority order. The resolution priority order specifies that when the matching scores are the same, the exact matching rule is used first, followed by the finest granular node rule. Based on the results of applying the conflict resolution rules, a unique candidate virtual organization node is selected from the candidate virtual organization nodes as the final target node responsible for the target product information, and the identifier of the final target node is output.

[0046] In this embodiment, the process of determining the final target node from candidate virtual organization nodes involves quantitative matching evaluation and rule-based priority adjudication. First, all candidate virtual organization nodes selected in the previous stage are obtained, and the permission policy expression corresponding to each node is read. These expressions, in the form of structured logical conditions, define the specific management scope boundaries of the node in dimensions such as financial category, product category, and store.

[0047] The matching degree of each candidate node's permission policy expression with the key attributes of the target product information is calculated. This calculation is achieved by analyzing the degree to which the key attributes satisfy the conditions of each dimension in the permission policy expression. For example, if the key attributes and the expression match perfectly in both the financial category and product category dimensions, the matching degree score is high; if they match only in one dimension, or if the match is a range inclusion relationship, the score is relatively low. This method generates a quantitative matching degree score, which is used to objectively measure the accuracy of the node's management scope in covering the target product information.

[0048] After obtaining the matching scores for each candidate node, conflict resolution rules are applied according to a preset priority order. The priority order is pre-defined; for example, it might stipulate that matching scores are compared first, with higher scores taking precedence. If scores are the same, the exact matching rule is prioritized, meaning nodes whose management scope and key attributes are completely consistent with their permission policy expressions are selected first. If a distinction still cannot be made, the finest-grained node rule is then applied, prioritizing nodes with more detailed business dimensions and more specific management scopes (e.g., managing fourth-level financial categories instead of third-level). These rules are applied sequentially to filter and rank the candidate nodes.

[0049] Based on the results of applying the aforementioned conflict resolution rules, a single node is selected from the candidate virtual organization nodes as the final target node responsible for the target product information. Once selected, the unique identifier of this final target node is output for use in subsequent steps.

[0050] This embodiment provides a specific application mechanism for conflict resolution rules. It introduces a matching score to initially quantify and rank candidate nodes, and when scores are the same, it applies more specific rules sequentially according to a clear priority order (precise matching first, finest granularity first) for resolution. This mechanism transforms potentially overlapping or ambiguous responsibility division issues into a repeatable and objective decision-making process based on quantified scoring and hierarchical rules. This ensures the accuracy, consistency, and automation of permission responsibility determination in complex business scenarios, effectively supporting the robustness of the permission reverse lookup algorithm.

[0051] Please see Figure 3 In some embodiments, based on the product or financial category parameters in the business context information, a target node is located in the virtual organization tree, and based on the virtual job information configured on the target node, an approval link and specific approver are generated through a dynamic routing algorithm, including: Parse the business context information and extract the product identifier or financial category code used for node positioning as the query key; Using the query key as input, a node location query is performed in the virtual organization tree. The node location query determines the virtual organization node most relevant to the business context information by matching the business dimension attributes or permission policy expressions of the virtual organization node, and is recorded as the initial target node. Obtain the virtual job sequence pre-configured for the current approval scenario on the initial target node. The virtual job sequence defines the role order required for the approval process. For each virtual job in the virtual job sequence, query the ternary relation data for purchasing and sales personnel who are bound to the initial target node and whose roles match. If there is no matching personnel at the current node, the query will proceed step by step up the virtual organization tree according to the preset backtracking rules until a matching personnel is found for the current virtual position or the backtracking termination condition is met, and the backtracking query result will be obtained. The procurement and sales personnel determined by the virtual job sequence and retrospective query results will be arranged in an orderly manner, generating a complete approval chain and a list of specific approvers, and then returned to the approval system.

[0052] In this embodiment, the product identifier or financial category code parsed from the business context information serves as the query key for locating the approval responsibility node in the virtual organization tree. The node location query traverses the nodes in the virtual organization tree, directly comparing the query key with the business dimension attributes (e.g., the financial category code represented by the node) directly recorded by each node, or substituting the query key into the permission policy expression associated with each node for logical calculation. Through this method, virtual organization nodes whose management scope covers the query key are selected. Preferably, this process can reuse the node matching logic in the permission reverse lookup algorithm, and the successfully matched nodes are determined as the initial target nodes for the current approval item.

[0053] After obtaining the initial target node, the system reads the pre-configured virtual job sequence for the current approval type (e.g., "Product Price Change Approval") on that node. The virtual job sequence is stored as a list, clearly defining the roles that must be passed sequentially to complete this type of approval, such as "Initial Business Reviewer," "Financial Reviewer," and "Responsible Person Approvaler." Optionally, to improve configuration efficiency and maintenance consistency, the virtual job sequence can be managed using a template-based approach. Specifically, the system can predefine a series of approval process templates corresponding to different approval scenarios (e.g., "New Product Introduction Approval" and "Price Adjustment Approval"), each template encapsulating a fixed virtual job sequence. When configuring approval rules for a virtual organization node, simply associating it with one or more approval process templates completes the configuration of the job sequence for the corresponding approval scenario on that node.

[0054] For each virtual position in the sequence, query the ternary relation data for purchasing and sales personnel who are bound to the initial target node and whose virtual position role information matches the current position. If the query is successful, list that personnel as the approver for the current position.

[0055] If no matching personnel are found at the initial target node for a specific virtual position, processing is initiated according to preset backtracking rules. These backtracking rules aim to find personnel capable of fulfilling the responsibilities of the position by querying upwards along the parent node path of the virtual organization tree. Specifically, it first attempts to query the direct parent node of the initial target node for a matching personnel; if no such personnel are found, it continues querying the next higher parent node, and so on. This process continues until a matching personnel is found for the current virtual position, or the backtracking termination condition is met (e.g., backtracking has reached the root node of the virtual organization tree).

[0056] After traversing all positions in the virtual job sequence, the approvers for each position (from the initial node binding or backtracking query results) are arranged strictly according to the job order defined in the sequence, generating an ordered list of approvers, i.e., the complete approval chain. Finally, this approval chain is returned to the approval system to instantiate the specific approval process.

[0057] This embodiment dynamically constructs the approval process by combining node location query, pre-configured job sequence binding, and a hierarchical backtracking mechanism. Node location query accurately locates business responsibility points using existing permission policy data; job sequences provide a standardized framework for the approval process; when the framework cannot be implemented at a specific node, the backtracking mechanism automatically searches for solutions up the organizational hierarchy, ensuring the inevitable generation of the approval process. This method transforms the generation of the approval process from static configuration to calculation results based on real-time organizational relationships and rules, achieving both flexibility and reliability in the approval process.

[0058] In some embodiments, if there is no matching personnel at the current node, the query proceeds upwards along the parent node path of the virtual organization tree according to preset backtracking rules until a bound personnel is found for the current virtual position or the backtracking termination condition is met, obtaining the backtracking query results, including: If no matching personnel for the current virtual position are found at the initial target node, a backtracking query process is triggered. Based on the node hierarchy stored in the virtual organization tree, the direct parent node of the initial target node is obtained as the current backtracking node; In the ternary relation data, query the purchasing and sales personnel who are bound to the current backtracking node and whose roles match the current virtual positions; If the query is successful, the procurement and sales personnel found will be designated as the approver for the current virtual position, and the backtracking query for the current virtual position will be terminated. If the query fails, the direct parent node of the current backtrack node will be updated to the new current backtrack node, and the personnel query steps will be repeated. When the backtracking query reaches the root node of the virtual organization tree and still fails to find a matching person, or reaches the preset maximum backtracking level, it is determined that the backtracking termination condition has been met, and the backtracking query result is generated according to the preset default processing strategy.

[0059] In this embodiment, when the query to bind personnel for a virtual position on the initial target node fails, a backtracking query process is triggered. After triggering, the node hierarchy relationship stored in the virtual organization tree data model is first used to retrieve the identifier of the direct parent node of the initial target node by querying the node relationship table, using the identifier of the initial target node as the key, and then setting the parent node as the current backtracking node.

[0060] Subsequently, using the identifier of the current backtracking node and the current virtual job title as conditions, a query is executed in the ternary relation data to find purchasing and sales personnel bound to this node whose virtual job title information matches the current job title. This query operation is consistent with the query logic on the initial target node, but the target node has now become its parent node.

[0061] If the query is successful, meaning a matching procurement and sales personnel is found, that person will be designated as the approver for the current virtual position, and the entire backtracking query process for this position will be terminated immediately, without tracing back to higher-level nodes.

[0062] If the query fails, meaning there are no matching individuals at the current backtracking node, it's necessary to continue backtracking upwards. In this case, the direct parent node of the current backtracking node is updated to the new current backtracking node. This update operation is also performed by querying the node relationship table to obtain the parent node identifier of the current backtracking node. After the update, the personnel query steps described above are repeated, meaning a new query for matching individuals is performed at the newly determined current backtracking node.

[0063] This "query-failure-update node-query again" cycle continues. The cycle terminates under a backtracking termination condition. The backtracking termination condition is met when the backtracking query reaches the root node of the virtual organization tree (i.e., the top-level node without a parent node), or when the number of backtracking levels reaches a preset maximum value (e.g., a maximum of 3 levels backtracked). Upon reaching the termination condition, the backtracking query result is generated according to a pre-configured default processing strategy. The default processing strategy may include: returning a null value and marking the approval chain as interrupted, specifying a fixed default approver role (such as a system administrator), or triggering an exception handling process to notify the administrator for manual intervention.

[0064] This embodiment provides a complete and operable implementation scheme for the backtracking query process. It is initiated through a clear trigger mechanism, using the hierarchical relationship data of the virtual organizational tree to drive iterative queries. Standard personnel matching checks are performed at each level of the node, and query boundaries are managed through loop control and termination conditions. This embodiment transforms the business rule of "finding the approver from the superior" into an automated algorithm driven by data relationships and with a clear exit mechanism. This ensures the reliability and controllability of dynamically locating approval responsibilities within the organizational structure, effectively solving the problem of approval process blockage caused by personnel vacancies at local nodes, and is a key guarantee for the robustness of the dynamic routing algorithm.

[0065] In some embodiments, raw performance data associated with product or financial categories is collected from business data sources. Based on ternary relationship data, a data aggregation algorithm is executed to aggregate the raw performance data by personnel dimension, generating structured performance indicator data, including: Raw performance data streams are collected from designated business data sources in a triggered manner. Each record in the raw performance data stream is associated with at least one product identifier or financial category code and at least one performance numerical indicator. Using the product identifier or financial category code in the original performance data stream as the association key, perform a reverse mapping query in the ternary relation data to determine one or more responsible virtual organization nodes to which each original performance record belongs, and further obtain the purchasing and sales personnel identifiers bound to these nodes; Based on the preset performance indicator calculation rules and aggregation logic, the numerical indicators in multiple original performance records belonging to the same procurement and sales personnel are aggregated. The aggregation operation includes summation, averaging, counting, or weighted calculation. The results of the aggregation operation are combined with the corresponding procurement and sales personnel identification, scope of responsibility description, and performance cycle information to generate structured performance indicator data records based on personnel, and then output to the performance appraisal system or data dashboard.

[0066] In this embodiment, triggered data collection can be accomplished by configuring a timed task to actively query detailed tables such as transaction and inventory in the business database at a specific time (e.g., early morning every day), or by listening to data change message streams issued by the business system. Each collected original performance record contains at least one identifier that can be associated with a specific business dimension (e.g., a unique product code or financial category code), and one or more performance numerical indicators to be statistically analyzed, such as product sales, gross profit, or the number of tasks completed.

[0067] After obtaining the raw performance data stream, it is mapped to specific responsible persons. This process uses the product identifier or financial category code in the record as the association key and performs a reverse mapping query in the ternary relation data. The reverse mapping query traverses each data unit in the ternary relation data to determine whether the association key falls within the management scope defined by the permission policy expression in that data unit. For each performance record, all virtual organization nodes whose association keys fall within its management scope are identified as the responsible virtual organization nodes for that record. Then, by querying the binding relationship between these responsible nodes and personnel, the responsible purchasing and sales personnel identifier is obtained. A performance record may be mapped to multiple personnel due to overlapping management scopes.

[0068] After identifying the responsible party for each performance record, the data is aggregated according to pre-defined calculation rules and aggregation logic for different performance indicators. For example, for the "sales revenue" indicator, the rule might specify summing the values ​​by personnel; for the "average gross profit margin" indicator, the rule might specify first calculating the ratio of gross profit to sales revenue for each record, and then averaging these ratios by personnel. Aggregation operations are performed in memory or the data processing engine, performing operations such as summing, averaging, counting, or weighting on the numerical indicators of multiple records belonging to the same purchasing / sales personnel identifier according to the rules.

[0069] After completing the aggregation operation, the aggregation results (such as total sales and average gross profit) for each purchasing and sales personnel are combined with the personnel's identifier, a description of their responsibilities (which can be obtained from the associated virtual organization node information), and the period information (such as year, month, and day) of the performance data to generate a complete, personnel-centric structured performance indicator data record. Finally, these records are batch-output to the performance appraisal system for further analysis or pushed to a data dashboard for visualization. The content of the responsibility scope description can be flexibly generated according to actual needs. For example, the name of the virtual organization node to which the responsibility belongs can be directly extracted as the description; or, based on the key business dimensions (such as financial category and product category) covered by the node's permission policy expression, a more business-semantic descriptive text can be automatically generated.

[0070] This embodiment constructs an automated aggregation pipeline from raw business data to performance results at the personnel level. Triggered data collection ensures data timeliness, and ternary relational data enables precise reverse mapping from products to responsible individuals. Flexible indicator calculation and aggregation are performed according to preset rules, ultimately generating structured performance data records. This embodiment automatically transforms scattered and detailed business data into structured performance information directly usable for assessment and analysis, based on a unified organizational and responsibility model. It completely eliminates common problems in manual statistics, such as inconsistent definitions, aggregation errors, and inefficiency, providing an efficient, accurate, and traceable data foundation for performance evaluation.

[0071] In some embodiments, using the product identifier or financial category code in the original performance data stream as the association key, a reverse mapping query is performed in the ternary relation data to determine one or more responsible virtual organization nodes to which each original performance record belongs, and further obtains the purchasing and sales personnel identifiers bound to these nodes, including: For each performance record in the original performance data stream, the association key contained in the performance record is used as the current query key for this query; The current query key is compared one by one with the permission policy expressions corresponding to each virtual organization node recorded in the ternary relation data to obtain the comparison results; Based on the comparison results, identify all virtual organization nodes whose management scope, as defined by their permission policy expressions, can cover the current query key, and mark these virtual organization nodes as the responsible virtual organization nodes for the current performance record; Additionally, based on the virtual organization nodes and personnel binding relationships stored in the ternary relationship data, the procurement and sales personnel identifier associated with each responsible virtual organization node is obtained.

[0072] In this embodiment, the reverse mapping query is executed independently for each original performance record. First, the associated product identifier or financial category code is extracted from the performance record and used as the current query key for this query.

[0073] The comparison phase then proceeds, traversing each data unit (i.e., node-person-product relationship record) stored in the ternary relation data. For each data unit, its contained permission policy expression is read. The permission policy expression is a structured string or object that connects multiple dimension conditional clauses using logical operators, for example, used to determine if "financial category belongs to a certain set" and "product category is a certain value." The comparison operation takes the current query key as input and substitutes it into the permission policy expression for logical calculation. Specifically, the dimension value represented by the query key (such as the specific financial category code "FC1001") is matched against the conditions in the expression (such as "financial category IN('FC1001', 'FC1002')"). If all conditional clauses in the expression are true based on the query key, the management scope defined by the expression is considered to cover the current query key, and the comparison result is successful; otherwise, it fails.

[0074] Based on the comparison results obtained after traversing all data units, all virtual organization nodes that successfully matched the permission policy expressions were identified. These nodes were then marked as the responsible virtual organization nodes for the performance record currently being processed, meaning that the business outcome represented by the record falls under the management scope of these nodes.

[0075] After identifying the responsible virtual organization nodes, based on the binding relationship records between the virtual organization nodes and purchasing and sales personnel that are persistently stored in the ternary relationship data, the identifiers of these responsible nodes are queried to obtain the identifiers of one or more purchasing and sales personnel bound to them, thus completing the precise mapping from a performance record to one or more responsible persons.

[0076] This embodiment uses the business identifier of performance records as input to perform a logical calculation traversal on all permission policy expressions in the ternary relation data. This accurately locates all responsibility nodes whose management scope covers the record and further associates them with specific responsible persons. This process transforms the business requirement of "finding the responsible person based on the product" into an automated query algorithm that can be executed in batches and yields definitive results, based on a rule engine or expression calculation. This ensures the accuracy and completeness of responsibility allocation during performance data collection and is a key technical step in achieving accurate data-person association in the automated performance data aggregation process.

[0077] In a second aspect, this embodiment also provides a procurement and sales business collaborative management system based on virtual organizations, applicable to the method described in the first aspect. The system includes a virtual organization construction module, a relationship configuration and storage module, a permission service module, an approval routing service module, a performance data aggregation module, and a change synchronization and activation module. The virtual organization construction module receives entity organizational structure data from the enterprise's human resources system and constructs a virtual organization tree based on the procurement and sales business dimension. The virtual organization tree contains virtual organization nodes based on financial categories, product categories, or business lines, and assigns a unique identifier to each virtual organization node. The relationship configuration and storage module binds virtual organization nodes to procurement and sales personnel, configures the virtual positions and product management permission scope corresponding to the virtual organization nodes, and generates and stores ternary relationship data between nodes, personnel, and products. The permission service module responds to permission verification requests initiated by downstream business systems. The permission verification request includes target product information and executes the request based on the ternary relationship data. The system employs a reverse lookup algorithm to locate and return the purchasing and sales personnel responsible for the target product information. The approval routing service module responds to approver retrieval requests initiated by the approval system. These requests include business context information. Based on the product or financial category parameters in the business context information, it locates the target node in the virtual organizational tree and generates the approval chain and specific approvers based on the virtual job information configured on the target node using a dynamic routing algorithm. The performance data aggregation module collects raw performance data associated with product or financial categories from business data sources. Based on the ternary relationship data, it executes a data aggregation algorithm to aggregate the raw performance data by personnel dimension, generating structured performance indicator data. The change synchronization and activation module updates the node binding relationship in the virtual organizational tree when a change in the responsibilities of purchasing and sales personnel is detected, triggering a synchronization mechanism so that the permission service module, approval routing service module, and performance data aggregation module automatically take effect based on the updated ternary relationship data.

[0078] In this embodiment, The system establishes and maintains a node-personnel-product ternary relationship data model through a virtual organization construction module and a relationship configuration and storage module. Based on this unified model, the permission service module, approval routing service module, and performance data aggregation module respectively implement three major business functions: permission reverse lookup, dynamic approval routing, and automatic performance data aggregation. The change synchronization and activation module ensures that when personnel responsibilities change, each business module can take effect in conjunction with the updated model data. This system deeply integrates the fragmented permission, approval, and performance management processes in procurement and sales operations through a unified data model and modular services, forming a data-driven, automatically collaborative management loop. This fundamentally solves the problems of cumbersome maintenance, delayed response, and inconsistent standards inherent in traditional methods, significantly improving the overall efficiency of business management and the system's robustness.

[0079] By adopting the above technical solutions, this invention differs from existing technologies and possesses the following beneficial effects: By constructing a virtual organizational tree based on financial categories, product categories, or business lines, and generating unified node-personnel-product ternary relationship data, it deeply associates and structurally models the organization, personnel, and product resources in procurement and sales operations. Based on this data model, this invention achieves automated collaboration in three key business scenarios: permission verification, approval workflow, and performance accounting. The permission reverse lookup algorithm, based on the ternary relationship data, accurately locates the product manager by matching permission policy expressions and conflict resolution. The dynamic routing algorithm, combined with virtual job sequences and hierarchical backtracking mechanisms, dynamically generates a complete approval chain. The data aggregation algorithm, using reverse mapping queries, automatically aggregates original performance data to the responsible person. When personnel responsibilities change, only their binding relationship in the ternary relationship data needs to be updated to trigger a synchronization mechanism, enabling all business logic to automatically take effect. The above technical solution integrates the originally scattered, static, and manually maintained permission configuration, approval process, and performance statistics into an organic whole driven by a data model and with automatic linkage between each link. It effectively solves the systemic problems in traditional procurement and sales business collaborative management caused by the separation of organizational model and business rules, such as low maintenance efficiency, fragile approval process, inconsistent performance statistics and system response lag. It significantly improves the level of refinement, automation and overall robustness of business management.

[0080] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0081] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] The above description is only a part of the embodiments of the present invention and does not limit the scope of protection of the present invention. Any equivalent device or equivalent process transformation made based on the content of the present invention specification and drawings, or direct or indirect application in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A collaborative management method for procurement and sales operations based on virtual organizations, characterized in that, include: Receive entity organizational structure data from the enterprise human resources system, and construct a virtual organizational tree based on the procurement and sales business dimension. The virtual organizational tree contains virtual organizational nodes based on financial category, product category or business line, and assigns a unique identifier to each virtual organizational node. The virtual organization nodes are bound to the purchasing and sales personnel, and the virtual positions and product management permission scope corresponding to the virtual organization nodes are configured to generate node-person-product ternary relationship data; In response to a permission verification request initiated by a downstream business system, the permission verification request includes target product information. Based on the ternary relationship data, a permission reverse lookup algorithm is executed to locate and return the purchasing and sales personnel responsible for the target product information. In response to an approver retrieval request initiated by the approval system, the approver retrieval request includes business context information. Based on the product or financial category parameters in the business context information, the target node is located in the virtual organization tree. Based on the virtual job information configured on the target node, an approval link and specific approver are generated through a dynamic routing algorithm. Raw performance data associated with product or financial categories is collected from business data sources. Based on the ternary relationship data, a data aggregation algorithm is executed to aggregate the raw performance data according to the personnel dimension and generate structured performance indicator data. When a change in the responsibilities of a purchasing and sales personnel is detected, the node binding relationship in the virtual organization tree is updated, and a synchronization mechanism is triggered, so that the permission reverse lookup algorithm, dynamic routing algorithm and data aggregation algorithm automatically take effect based on the updated ternary relationship data.

2. The collaborative management method for procurement and sales operations based on virtual organizations according to claim 1, characterized in that, Receive entity organizational structure data from the enterprise's human resources system and construct a virtual organizational tree based on the procurement and sales business dimension, including: Receive entity organization change events from the enterprise human resources system, the entity organization change events include organization addition, update, merger, split or transfer operations and their associated data; According to the preset mapping rules, the entity organization change event is converted into a virtual organization tree maintenance instruction. The preset mapping rules define the correspondence between entity organization units and procurement and sales business dimensions. Execute the virtual organization tree maintenance command to create or update virtual organization nodes in the virtual organization platform based on financial category, product category or business line as the main dimension, and generate a globally unique node identifier for each newly created virtual organization node; Establish and persist the mapping relationship records between the virtual organization nodes and the source entity organization units and business dimensions to form the metadata foundation of the virtual organization tree. The metadata foundation is used to support subsequent change traceability and data synchronization consistency verification.

3. The collaborative management method for procurement and sales operations based on virtual organizations according to claim 1, characterized in that, The virtual organization nodes are bound to purchasing and sales personnel, and the virtual positions and product management permission scopes corresponding to the virtual organization nodes are configured to generate node-person-product ternary relationship data, including: Receive binding instructions and configuration parameters for the target virtual organization node. The configuration parameters include the identifier of the purchasing and sales personnel to be bound, the virtual job role assigned to the virtual organization node, and the definition of the range of products that the virtual organization node can manage. According to the binding instruction, an association relationship between the target virtual organization node and the procurement and sales personnel identifier is established in the data model of the virtual organization tree; Based on the product range definition in the configuration parameters, a corresponding permission policy expression is generated for the target virtual organization node. The permission policy expression is used to describe the management boundaries of the virtual organization node in terms of product, financial category or store dimension. The relationships, virtual job role information, and permission policy expressions are logically linked and persistently stored to form the data units of the node-person-product ternary relationship data.

4. The collaborative management method for procurement and sales operations based on virtual organizations according to claim 1, characterized in that, Based on the aforementioned ternary relation data, an access control algorithm is executed to locate and return the purchasing and sales personnel responsible for the target product information, including: Parse the target product information in the permission verification request and extract the key attributes used for matching. The key attributes include financial category code, product category code or store code. Using the key attributes as input conditions, a multi-dimensional matching query is performed in the ternary relation data. The multi-dimensional matching query filters out candidate virtual organization nodes whose management scope covers the target product information by traversing the permission policy expressions of the nodes. From the selected candidate virtual organization nodes, the final target node is determined according to the preset conflict resolution rules, which include, but are not limited to, exact matching priority and finest granular node priority. Based on the association relationships stored in the ternary relationship data, the procurement and sales personnel identifier bound to the final target node is extracted and returned as the permission verification result to the downstream business system that initiated the request.

5. The collaborative management method for procurement and sales operations based on a virtual organization according to claim 4, characterized in that, From the selected candidate virtual organization nodes, the final target node is determined according to a preset conflict resolution rule, including: Obtain the candidate virtual organization nodes and read the permission policy expression corresponding to each candidate virtual organization node. The permission policy expression defines the management scope boundary of the node in terms of financial category, product category and store dimension. The matching degree of the permission policy expression of each candidate virtual organization node is calculated with the key attributes of the target product information to generate a matching degree score. The matching degree score is used to quantify the accuracy of the coverage between the node management scope and the target product information. The conflict resolution rules are applied according to a preset resolution priority order. The resolution priority order specifies that when the matching scores are the same, the exact matching rule is used first, followed by the finest granular node rule. Based on the result of applying the conflict resolution rules, a unique candidate virtual organization node is selected from the candidate virtual organization nodes as the final target node responsible for the target product information, and the identifier of the final target node is output.

6. The collaborative management method for procurement and sales operations based on virtual organizations according to claim 1, characterized in that, Based on the product or financial category parameters in the business context information, the target node is located in the virtual organization tree, and based on the virtual job information configured on the target node, an approval link and specific approver are generated through a dynamic routing algorithm, including: Parse the business context information and extract the product identifier or financial category code used for node positioning as the query key; Using the query key as input, a node location query is performed in the virtual organization tree. The node location query determines the virtual organization node most relevant to the business context information by matching the business dimension attributes or permission policy expressions of the virtual organization node, and is recorded as the initial target node. Obtain the virtual job sequence pre-configured for the current approval scenario on the initial target node, wherein the virtual job sequence defines the role order required for the approval process; For each virtual job in the virtual job sequence, query the ternary relation data for purchasing and sales personnel who are bound to the initial target node and whose roles match; If there is no matching personnel at the current node, the query will proceed step by step up the virtual organization tree according to the preset backtracking rules until a matching personnel is found for the current virtual position or the backtracking termination condition is met, and the backtracking query result will be obtained. The procurement and sales personnel determined according to the virtual job sequence and the retrospective query results are arranged in an orderly manner, generating a complete approval chain and a list of specific approvers, and then returned to the approval system.

7. The collaborative management method for procurement and sales operations based on a virtual organization according to claim 6, characterized in that, If no matching personnel are found at the current node, the query proceeds upwards along the parent node path of the virtual organization tree according to the preset backtracking rules, until a bound personnel is found for the current virtual position or the backtracking termination condition is met, yielding the backtracking query results, including: If no matching personnel for the current virtual position are found on the initial target node, a backtracking query process is triggered. Based on the node hierarchy stored in the virtual organization tree, the direct parent node of the initial target node is obtained as the current backtracking node; In the ternary relation data, query the purchasing and sales personnel who are bound to the current backtracking node and whose roles match the current virtual job positions; If the query is successful, the procurement and sales personnel found will be designated as the approver for the current virtual position, and the backtracking query for the current virtual position will be terminated. If the query fails, the direct parent node of the current backtracking node is updated to the new current backtracking node, and the personnel query steps are repeated. When the backtracking query reaches the root node of the virtual organization tree and still fails to find a matching person, or reaches the preset maximum backtracking level, it is determined that the backtracking termination condition has been met, and the backtracking query result is generated according to the preset default processing strategy.

8. The collaborative management method for procurement and sales operations based on virtual organizations according to claim 1, characterized in that, Raw performance data associated with product or financial categories is collected from business data sources. Based on the aforementioned ternary relationship data, a data aggregation algorithm is executed to aggregate the raw performance data according to the personnel dimension, generating structured performance indicator data, including: Raw performance data streams are collected from a specified business data source in a triggered manner. Each record in the raw performance data stream is associated with at least one product identifier or financial category code and at least one performance numerical indicator. Using the product identifier or financial category code in the original performance data stream as the association key, perform a reverse mapping query in the ternary relation data to determine one or more responsible virtual organization nodes to which each original performance record belongs, and further obtain the purchasing and sales personnel identifiers bound to these nodes. According to the preset performance indicator calculation rules and aggregation logic, the numerical indicators in multiple original performance records belonging to the same procurement and sales personnel are aggregated. The aggregation operation includes summation, averaging, counting or weighted calculation. The results of the aggregation operation are combined with the corresponding procurement and sales personnel identification, scope of responsibility description, and performance cycle information to generate structured performance indicator data records based on personnel, and then output to the performance appraisal system or data dashboard.

9. The collaborative management method for procurement and sales operations based on a virtual organization according to claim 8, characterized in that, Using the product identifier or financial category code in the original performance data stream as the association key, a reverse mapping query is performed in the ternary relation data to determine one or more responsible virtual organization nodes to which each original performance record belongs, and further obtains the purchasing and sales personnel identifiers bound to these nodes, including: For each performance record in the original performance data stream, the association key contained in the performance record is used as the current query key for this query; The current query key is compared one by one with the permission policy expressions corresponding to each virtual organization node recorded in the ternary relation data to obtain the comparison results; Based on the comparison results, identify all virtual organization nodes whose management scope, as defined by their permission policy expressions, can cover the current query key, and mark these virtual organization nodes as the responsible virtual organization nodes for the current performance record; Furthermore, based on the virtual organization node and personnel binding relationship stored in the ternary relationship data, the procurement and sales personnel identifier associated with each of the responsible virtual organization nodes is obtained.

10. A collaborative management system for procurement and sales operations based on a virtual organization, characterized in that, The system applicable to the method of any one of claims 1 to 9 comprises: The virtual organization building module is used to receive entity organizational structure data from the enterprise human resources system and build a virtual organization tree based on the procurement and sales business dimension. The virtual organization tree contains virtual organization nodes based on financial category, product category or business line, and assigns a unique identifier to each virtual organization node. The relationship configuration and storage module is used to bind the virtual organization nodes with purchasing and sales personnel, configure the virtual positions and product management permission scope corresponding to the virtual organization nodes, and generate and store the ternary relationship data of node-personnel-product. The permission service module is used to respond to permission verification requests initiated by downstream business systems. The permission verification request contains target product information. Based on the ternary relationship data, the permission reverse lookup algorithm is executed to locate and return the purchasing and sales personnel responsible for the target product information. The approval routing service module is used to respond to the approver acquisition request initiated by the approval system. The approver acquisition request includes business context information. Based on the product or financial category parameters in the business context information, the module locates the target node in the virtual organization tree and generates the approval link and specific approver based on the virtual job information configured on the target node through a dynamic routing algorithm. The performance data aggregation module is used to collect raw performance data associated with product or financial categories from business data sources, and execute data aggregation algorithms based on the ternary relationship data to aggregate the raw performance data according to the personnel dimension and generate structured performance indicator data. The change synchronization and activation module is used to update the node binding relationship of the purchasing and sales personnel in the virtual organization tree when a change in the responsibilities of the purchasing and sales personnel is detected, and to trigger the synchronization mechanism so that the permission service module, approval routing service module and performance data aggregation module automatically take effect based on the updated ternary relationship data.

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