Business personnel assessment method and device, equipment and medium

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a business personnel assessment method, which comprises the steps of decomposing assessment logic, salary calculation logic and level management logic, generating basic factors, and forming a factor library and a strategy library; generating a strategy set version according to the strategy condition, and distributing a strategy set version ID and a calculation batch ID for the strategy set version; an assessment strategy set is called through the strategy set version ID and the calculation batch ID, and based on the assessment strategy set, an assessment result and assessment early warning information are calculated according to the business data and the basic data; a salary accounting strategy set is extracted according to the strategy set version ID, and a salary detail and a salary prediction result are generated in combination with the assessment result, the service data and the basic factors; and performing level adjustment on the business personnel according to the assessment result, the salary details, the assessment early warning information and the salary prediction result. The method can be applied to the scene of salary assessment of business personnel of medical health and financial science and technology, and the accuracy of business personnel assessment is improved.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to a method, apparatus, equipment, and storage medium for evaluating business personnel. Background Technology

[0002] The dynamic performance evaluation system for insurance agents is a core support system for business operations, spanning the entire lifecycle management process of the agent team, including "selection, training, utilization, retention, evaluation, motivation, adjustment, and retirement." Its evaluation results directly impact agent salary calculation, performance appraisal, and job level adjustments, playing a crucial role in the effectiveness of team management. However, the current traditional dynamic performance evaluation system for agents has revealed many pain points in actual operation, making it difficult to adapt to the actual needs of industry development and team management. First, the efficiency of rule updates is low. Assessment rules need to be iterated rapidly according to business development, but in the traditional model, rule updates rely on manual modification of code or complex configuration files, a cumbersome and time-consuming process that severely slows down the update pace. Second, operational risks are high. Core business processes such as salary calculation, performance evaluation, and job level adjustment rely heavily on manual operation, which is prone to calculation errors and assessment mistakes due to human error, thus affecting agents' business development motivation and overall team productivity. Third, the assessment process lacks transparency. A standardized and open assessment mechanism has not yet been established, making agents prone to questioning the fairness and accuracy of assessment results, reducing their acceptance of the assessment system. Fourth, salary payment timeliness is insufficient. Salary calculation and payment also rely on manual operation, and low process efficiency leads to salary delays, directly affecting agents' work enthusiasm. Fifth, there is a lack of professional prediction and early warning functions. It is impossible to predict agents' assessment results and salary payment status in advance, making it difficult for management to adjust team management strategies in a timely manner based on potential situations, and also preventing targeted intervention for agents who fail to meet assessment standards, thus missing opportunities for management optimization.

[0003] In the fintech business, the technical system adapted to the dynamic assessment of agents has significant architectural and functional shortcomings, becoming a core obstacle to efficient business operations. Technically, there is a lack of a flexible rule configuration engine; assessment rule iterations lack standardized technical support, requiring manual code modification or complex configuration files for updates, resulting in low technical adaptation efficiency and an inability to meet the needs of rapid business rule adjustments. Core business processes have not achieved end-to-end technical automation; salary calculation, performance evaluation, and other aspects still rely on manual intervention with the technical system, increasing the probability of operational errors and reducing process efficiency due to human intervention. The collection, calculation, and display of assessment data lack an integrated technical platform; data flow is opaque and lacks real-time traceability, making the assessment process unvisual and untraceable. Furthermore, the existing technical system lacks data modeling and predictive analysis capabilities, and has not built early warning models for assessment and salary data, making it impossible to predict data trends through technical means and support timely strategy adjustments by management based on data, resulting in a disconnect between technical capabilities and business management needs.

[0004] In the healthcare sector, the dynamic management technology system for practitioners, which is analogous to the assessment system for insurance agents, suffers from multiple problems, including insufficient technical adaptability and missing functional modules. First, the assessment rules for medical staff, health managers, and other practitioners require continuous optimization due to the ever-changing nature of medical business scenarios. However, the existing technical system lacks a flexible rule editing and updating module. Rule adjustments require manual modification of the underlying code by technical personnel, resulting in slow technical response and an inability to adapt to the dynamic management needs of medical business. Second, the technical systems for practitioner performance calculation, professional title adjustment, and salary payment are fragmented, with data unable to be shared. Manual cross-system data retrieval is required, which is prone to calculation errors due to data transmission mistakes, and the low degree of technical integration leads to low process efficiency. Third, there is a lack of a unified assessment data visualization technology platform. Practitioners cannot query the assessment basis and results through technical channels, and the technical aspect does not achieve open and traceable assessment processes. Fourth, the existing technology lacks data mining and predictive early warning functions, making it impossible to pre-judge practitioner assessment results and salary calculations, and there are no technical means to achieve timely early warning of assessment risks, making it difficult to support medical and health institutions in the refined and forward-looking management of their workforce. Summary of the Invention

[0005] The main objective of this invention is to provide a method, apparatus, equipment, and storage medium for evaluating business personnel, aiming to solve the problems of long business response cycles, high manpower costs, and lack of standardization in the existing technology for evaluating business personnel.

[0006] To achieve the above objectives, the present invention provides a method for evaluating business personnel, comprising: The assessment logic, salary calculation logic, and job level management logic are decomposed to generate several basic factors, which then form a factor library and a strategy library. Generate a policy set version based on the policy conditions uploaded by the user, and assign a policy set version ID and a calculation batch ID to the policy set version; The assessment strategy set is retrieved from the strategy library using the strategy set version ID and calculation batch ID. Based on the assessment strategy set, the assessment results and assessment warning information of business personnel are calculated according to business data and basic data. Based on the strategy set version ID, extract the salary calculation strategy set from the strategy library, and combine it with the assessment results, business data and basic factors in the factor library to generate salary details and salary prediction results; The job levels of the business personnel will be adjusted based on the assessment results, salary details, assessment warning information, and salary forecast results.

[0007] Furthermore, to achieve the above objectives, the present invention provides a business personnel assessment device based on a rules engine, comprising: The basic library construction module is used to decompose the assessment logic, salary calculation logic, and job level management logic, generate several basic factors, and form a factor library and a strategy library from the basic factors. The strategy management module is used to generate a strategy set version based on the strategy conditions uploaded by the user, and to assign a strategy set version ID and a calculation batch ID to the strategy set version. The assessment module is used to retrieve the assessment strategy set from the strategy library using the strategy set version ID and calculation batch ID, and calculate the assessment results and assessment warning information of business personnel based on the assessment strategy set, business data and basic data. The salary calculation module is used to extract the salary calculation strategy set from the strategy library according to the strategy set version ID, and generate salary details and salary prediction results by combining the assessment results, business data and basic factors in the factor library. The job level management module is used to adjust the job levels of the business personnel based on the assessment results, salary details, assessment warning information, and salary forecast results.

[0008] Furthermore, to achieve the above objectives, the present invention also provides a computer device, the computer device including a memory, a processor, and a rule engine-based business personnel assessment program stored in the memory and executable on the processor, wherein the rule engine-based business personnel assessment program, when executed by the processor, implements the steps of the business personnel assessment method as described above.

[0009] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a rule-engine-based business personnel assessment program, which, when executed by a processor, implements the steps of the business personnel assessment method described above.

[0010] Beneficial Effects: This invention relates to the field of artificial intelligence technology and can be applied to business system platforms such as healthcare and fintech. It discloses a method for performance evaluation of business personnel, including: decomposing the evaluation logic, salary calculation logic, and job level management logic to generate several basic factors, which form a factor library and a strategy library; generating a strategy set version based on strategy conditions, and assigning a strategy set version ID and a calculation batch ID to the strategy set version; retrieving the evaluation strategy set through the strategy set version ID and calculation batch ID, and calculating the evaluation results and evaluation warning information based on the evaluation strategy set, business data, and basic data; extracting the salary calculation strategy set based on the strategy set version ID, and generating salary details and salary prediction results by combining the evaluation results, business data, and basic factors; and adjusting the job level of business personnel based on the evaluation results, salary details, evaluation warning information, and salary prediction results. This invention can be applied to salary assessment scenarios for business personnel in the healthcare and fintech sectors. It first decomposes three core logic categories to generate basic factors, constructing a factor library and a strategy library. Then, it generates a set of strategies with unique IDs based on user strategies. The corresponding strategies are retrieved via these IDs, and combined with data, assessment, salary-related results, and early warning information are calculated, ultimately completing job level adjustments. This invention automates the process, reduces manpower and errors, and improves assessment transparency and business response speed. Attached Figure Description

[0011] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a schematic diagram of an application environment for a business personnel assessment method according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating an embodiment of the personnel assessment method of the present invention; Figure 3 This is a schematic diagram of the functional modules of a preferred embodiment of the business personnel assessment device based on a rule engine of the present invention; Figure 4 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention; Figure 5 This is another structural schematic diagram of a computer device according to one embodiment of the present invention. Detailed Implementation

[0012] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0013] The personnel assessment method provided in this invention can be applied to, for example... Figure 1In this application environment, the user terminal communicates with the server via a network. The server can obtain the strategy conditions uploaded by the user terminal, generate a strategy set version based on the strategy conditions, and assign a strategy set version ID and a calculation batch ID to the strategy set version. It decomposes the assessment logic, salary calculation logic, and job level management logic to generate several basic factors, which form a factor library and a strategy library. The server retrieves the assessment strategy set using the strategy set version ID and calculation batch ID, and calculates the assessment results and assessment warning information based on the assessment strategy set, business data, and basic data. It extracts the salary calculation strategy set based on the strategy set version ID, and generates salary details and salary prediction results by combining the assessment results, business data, and basic factors. Finally, it adjusts the job levels of business personnel based on the assessment results, salary details, assessment warning information, and salary prediction results. This invention first decomposes three types of core logic to generate basic factors, constructs a factor library and a strategy library, then generates a strategy set version with a unique ID based on the user's strategy, retrieves the corresponding strategy through the ID, calculates assessment and salary-related results and warning information based on data, and finally completes the job level adjustment. This invention can be applied to salary assessment scenarios for business personnel in the healthcare and fintech sectors, automating the process, reducing manpower and errors, and improving assessment transparency and business response speed. The user end can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server end can be implemented using a dedicated server or a server cluster consisting of multiple servers. The invention will be described in detail below through specific embodiments.

[0014] Please see Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of the personnel assessment method provided by the present invention. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0015] like Figure 2 As shown, the performance evaluation method for business personnel proposed in this invention includes the following steps: S100. Decompose the assessment logic, salary calculation logic, and job level management logic to generate several basic factors, and form a factor library and strategy library from the basic factors. S200. Generate a strategy set version based on the strategy conditions uploaded by the user, and assign a strategy set version ID and a calculation batch ID to the strategy set version; S300. Retrieve the assessment strategy set from the strategy library using the strategy set version ID and calculation batch ID, and calculate the assessment results and assessment warning information of business personnel based on the assessment strategy set, according to business data and basic data. S400: Extract the salary calculation strategy set from the strategy library according to the strategy set version ID, and generate salary details and salary prediction results by combining the assessment results, business data and basic factors in the factor library. S500. Adjust the job level of the business personnel based on the assessment results, salary details, assessment warning information and salary forecast results.

[0016] In this embodiment, firstly, a deep logical decomposition is performed on the three core aspects of performance evaluation, salary calculation, and job level management, extracting several basic factors. The performance evaluation logic is decomposed around dimensions such as business achievement rate, performance growth rate, compliance compliance, and customer satisfaction. The salary calculation logic focuses on elements such as base salary, performance-based commission rate, bonus coefficient, and deduction standards. The job level management logic is decomposed into core content such as job level promotion thresholds, demotion rules, and job level corresponding permissions. These basic factors together constitute a factor library covering the entire business process. The specific execution guidelines formed by combining basic factors based on different business scenarios and management objectives constitute a flexible and adaptable strategy library.

[0017] When specific business needs arise, a corresponding strategy set version is generated based on the user-defined strategy conditions. Each version is assigned a unique strategy set version ID and calculation batch ID. These two identifiers act like precise coordinates, ensuring the accuracy and uniqueness of strategy invocation and data calculation. Using these IDs, the system can quickly retrieve the corresponding performance evaluation strategy set from the strategy library. Combined with real-time business data (such as transaction amount, number of transactions, service duration, etc.) and basic data (such as years of service, job type, basic qualifications, etc.), the system automatically calculates objective performance results through a rules engine. Simultaneously, the system monitors performance progress in real time and generates performance warnings for key milestones where targets are not met, providing timely feedback to business personnel and managers.

[0018] In the payroll calculation process, the system extracts the corresponding payroll calculation strategy set from the strategy library based on the strategy set version ID. It then performs multi-dimensional fusion calculations by integrating previously generated assessment results, business data, and basic factors (such as commission rates and bonus coefficients) in the factor library. This not only generates detailed payroll details, clarifying the specific amounts and calculation basis of each income and deduction item, but also generates salary prediction results in advance based on historical data and current business trends, allowing business personnel to have a clear expectation of their income.

[0019] Ultimately, based on the comprehensive assessment results, salary details, assessment warning information, and salary forecast results, the system automatically initiates the job level adjustment process according to the job level management strategy. For business personnel with excellent performance and outstanding results, the job level is automatically promoted and corresponding permissions and benefits are matched according to the rules. For personnel who do not meet the assessment standards, adjustments such as demotion or probation are triggered according to the specific circumstances to ensure the fairness and efficiency of job level management.

[0020] In the fintech business sector, taking the management of business teams in industries such as insurance and securities as examples, the performance evaluation process can incorporate basic factors such as premium income, policy renewal rate, customer asset appreciation rate, and compliance compliance. The strategy library can quickly update the evaluation strategies based on market product iterations and regulatory policy changes, accurately implementing new strategies through strategy set version IDs and calculation batch IDs. Regarding salary calculation, factors such as financial product commission rules and team collaboration reward mechanisms are combined to achieve automated calculation and real-time payment of commissions and bonuses. The salary prediction function helps financial advisors and insurance agents plan their business goals in advance, improving their work enthusiasm. Job level adjustments are automatically executed based on multi-dimensional data such as business personnel performance, customer maintenance quality, and compliance records, ensuring fairness and transparency in promotions and demotions. Simultaneously, performance warnings can promptly alert business personnel to compliance risks or performance gaps, helping financial institutions improve team management efficiency, reduce operational risks, and respond quickly to market changes.

[0021] In the healthcare sector, performance evaluation for marketing teams and health management consultants at healthcare service providers can be broken down into fundamental factors such as patient conversion rates, health management service satisfaction, expansion of partnerships with medical institutions, and compliance with medical information confidentiality. The strategy library can flexibly update evaluation strategies based on changes in healthcare policies and shifts in institutional business priorities (e.g., focusing on chronic disease management and health checkups), ensuring accurate strategy implementation through dedicated strategy set version IDs and calculation batch IDs. In the salary calculation phase, factors such as service visit commissions, long-term service rewards, and compliance service bonuses are incorporated, taking into account the specific characteristics of healthcare services, enabling accurate salary calculation and timely disbursement. Salary forecasting helps staff clarify service goals. Performance alerts can promptly address issues such as excessive patient complaint rates and non-standard service processes, helping to improve service quality. Job level adjustments are automatically made based on performance evaluation results, service reputation, and business contribution, incentivizing staff to improve professional service capabilities while ensuring standardized and fair management, driving healthcare institutions to optimize service processes, enhance customer experience, and achieve sustainable business development.

[0022] In one embodiment, S100 includes: S101. Obtain the performance evaluation logic, salary calculation logic, and job level management logic of business personnel; S102. Decompose the assessment logic, salary calculation logic, and job level management logic to obtain basic factors, basic logic, and basic strategies. S103. Perform correlation analysis on the basic factors, basic logic and basic strategies to determine the factor dependencies, data types and function definitions of each basic factor; S104. The factor library and strategy library are composed of the basic factors, factor dependencies, data types and function definitions.

[0023] In this embodiment, the construction of a dynamic assessment and management system first requires a comprehensive understanding of the core logic of performance evaluation, salary calculation, and job level management within the business scenario. This forms the basis for subsequent factor decomposition and database construction. The performance evaluation logic needs to cover core orientations such as performance measurement standards, compliance requirements, and service quality. The salary calculation logic needs to clarify key elements such as income composition, accounting rules, and reward and punishment mechanisms. The job level management logic needs to clarify the core basis for job level promotion and demotion, and the standards for matching permissions.

[0024] Based on the three core logics of acquisition, a deep decomposition is conducted to extract fundamental factors, fundamental logic, and fundamental strategies. Taking the performance evaluation logic as an example, it can be decomposed into fundamental factors such as performance completion rate, customer complaint rate, and number of compliance compliance instances, as well as fundamental logic such as passing the assessment if the performance completion rate is met and there are no compliance irregularities, and fundamental strategies such as differentiated assessment standards for different business positions. The salary calculation logic can be decomposed into fundamental factors such as base salary, performance commission rate, and full attendance bonus amount, the fundamental logic of "salary = base salary + performance commission - violation deduction", and the fundamental strategy of "different commission rates corresponding to different performance ranges". The job level management logic can be decomposed into fundamental factors such as the performance threshold required for job level promotion and the required years of service, the fundamental logic of promotion if the performance threshold for promotion is met and the required years of service are met, and the fundamental strategy of one-to-one correspondence between job levels and business authority.

[0025] Subsequently, a correlation analysis was conducted on the decomposed basic factors, basic logic, and basic strategies to clarify the dependencies between the basic factors. For example, the performance commission amount depends on the two basic factors of performance completion amount and commission rate. The data type of each basic factor was determined, such as performance completion amount as numerical, compliance status as Boolean, and customer evaluation as text. At the same time, the functions required for the operation of each factor were defined, such as the function for calculating performance completion rate and the function for calculating commission amount.

[0026] Finally, these fundamental factors, along with the identified factor dependencies, clearly defined data types, and predefined functions, are integrated to construct a well-structured and logically coherent factor library and strategy library. The factor library centrally stores various fundamental factors and their attribute information for easy retrieval and reuse; the strategy library contains basic strategies and related logic, providing support for the configuration of subsequent business rules.

[0027] This embodiment streamlines and integrates the core logic of personnel performance evaluation, salary calculation, and job level management. It breaks down these into basic factors, logic, and strategies, establishing connections between them. It clarifies factor dependencies, data types, and function definitions, constructing a comprehensive factor and strategy library. Its technical effects are significant: it enables dynamic rule configuration and rapid iteration, greatly shortening the business response cycle; it automates the entire process of performance evaluation, salary calculation, and job level adjustment, reducing manual intervention and errors, and improving calculation accuracy and timeliness; through clear factor associations and transparent strategies, it enhances the fairness and transparency of performance evaluation and job level adjustments, increasing personnel trust and work motivation; the modular design of the factor and strategy libraries improves system maintainability and scalability, helping enterprises quickly adapt to market changes, optimize team management, and ultimately promote increased productivity and sustained business growth.

[0028] In the fintech business, after acquiring the performance evaluation logic of business personnel (such as premium income assessment for insurance agents and client asset growth assessment for financial advisors), salary calculation logic (premium commission rules and asset custody fee sharing methods), and job level management logic (performance-based job level promotion paths), we decompose the basic factors such as premium income, client asset size, commission rate, and promotion performance thresholds, and sort out the basic logic and strategies such as "salary = premium commission + asset custody fee sharing" and "promotion requires meeting consecutive quarterly premium targets." Through correlation analysis, we clarify that "premium commission" depends on "premium income" and "commission rate," determine that the data type of relevant factors is numerical, define commission calculation functions, and then build a dedicated factor library and strategy library. With the help of this library, financial institutions can quickly adapt to market changes, such as adjusting the commission rate of different insurance products, without modifying the core code. This can be achieved simply by configuring the relevant factors and rules in the strategy library, greatly improving business response efficiency while ensuring the accuracy of performance evaluation and salary calculation.

[0029] In the healthcare business, after acquiring the assessment logic (number of patients served, patient satisfaction, and effectiveness of health plans), salary calculation logic (base salary, commission per service visit, and satisfaction bonus) and job level management logic (job level adjustments based on service quality and professional qualifications) of health management consultants, we decomposed these into basic factors such as the number of patients served, patient satisfaction scores, service commission standards, and professional qualification requirements corresponding to job levels. We then outlined basic logic and strategies such as "Salary = Base Salary + Commission per Service Visit + Satisfaction Bonus" and "Job level promotion requires meeting patient satisfaction standards and possessing corresponding professional certifications." Through correlation analysis, we clarified that "satisfaction bonus" depends on "patient satisfaction scores" and "reward coefficients," determined the data types of factors (e.g., satisfaction scores are numerical, professional qualifications are enumerated), defined the reward amount calculation function, and constructed a dedicated factor library and strategy library. When an organization adjusts its service assessment priorities, such as increasing the assessment weight of chronic disease management services, it can directly add a basic factor of "number of chronic disease management services" to the factor library, and configure the association rules between this factor and assessment results and salary calculation in the strategy library. This allows for the rapid implementation of new management requirements, helping medical and health institutions to standardize the management of business personnel and improve service quality and business efficiency.

[0030] In one embodiment, S200 includes: S2011. Obtain the policy conditions configured by the user through the operation page of the rules engine; S2012. Generate a strategy set version corresponding to the business scenario based on the strategy conditions; S2013. Assign a unique strategy set version ID and a calculation batch ID to the strategy set version.

[0031] In this embodiment, users' business management needs are transformed into standardized, executable strategy units, and the accuracy and traceability of execution are ensured through unique identifiers. First, users can easily upload specific strategy conditions through the rule engine's visual operation page by dragging and dropping components and configuring parameters, eliminating the need for complex code writing and lowering the operational threshold. These strategy conditions can be the setting of performance indicators (such as performance targets and compliance requirements), salary calculation rules (such as commission rates and reward standards), or the basis for job level adjustments (such as performance thresholds for promotion and demotion trigger conditions), comprehensively covering the core needs of business management.

[0032] Based on the strategy conditions uploaded by users, the system automatically matches the corresponding business scenarios, integrates relevant rules and factors, and generates a customized strategy set version. This version is a structured presentation of user needs, containing all the rule logic and execution standards required to achieve specific business management goals, ensuring the completeness and relevance of the strategy. Subsequently, the system assigns a unique strategy set version ID and calculation batch ID to each generated strategy set version. The strategy set version ID is used to distinguish different strategy schemes, facilitating subsequent querying, invocation, and iterative management. The calculation batch ID corresponds to a specific execution cycle or business batch, ensuring that all calculations within the same batch are based on a unified strategy standard, avoiding confusion, and providing a clear identification basis for subsequent result traceability and log querying.

[0033] In the fintech sector, when a new insurance product is launched and agent performance evaluation and compensation strategies need to be adjusted, managers can quickly upload new strategy conditions through an interface. These conditions include setting premium commission rates, sales performance indicators, and corresponding promotion point rules for the product. The system then generates a set of strategies tailored to the product's promotional scenario, assigning a unique version ID and calculation batch ID. In subsequent monthly and quarterly evaluations, the system can accurately retrieve this strategy version using these two IDs to uniformly calculate and adjust the performance, salary, and job level of relevant agents. This ensures rapid implementation of new strategies while clearly tracing the calculation basis for each batch, adapting to the rapid product iteration and frequent strategy adjustments characteristic of the financial industry. Similarly, in the securities and wealth management sectors, this process allows for the rapid configuration of sales evaluation strategies and commission calculation rules for different wealth management products, helping financial institutions respond quickly to market changes and regulatory requirements.

[0034] In the healthcare sector, taking health management institutions as an example, when an institution launches a new health management package and needs to adjust the assessment and incentive strategies for its marketing team, managers can upload strategy conditions through an operation page. These conditions include setting sales targets for the package, customer satisfaction assessment standards, corresponding commission rates, and promotion rules. The system will then generate a strategy set specifically for promoting that package and assign a unique identifier. In subsequent business cycles, the system can accurately invoke this strategy based on these two IDs to assess the sales performance and service quality of the promotion personnel, automatically calculate salaries, and adjust job levels accordingly, ensuring the precise implementation of incentive policies. For the management of partner doctors on medical service platforms, this process can also be used to configure strategy conditions such as assessment of treatment service volume, patient evaluation standards, and salary calculation rules, generating a dedicated strategy set and assigning an identifier. This enables standardized and efficient management of the doctor team, while the unique identifier ensures the traceability of assessments and salary calculations, guaranteeing fairness and impartiality in management.

[0035] This embodiment generates a policy set version corresponding to the business scenario and assigns a unique identifier by obtaining the policy conditions configured by the user on the rule engine operation page. The technical effect is significant. Users can complete policy configuration through visual operation without modifying code, greatly reducing the operational threshold and improving policy creation efficiency. The unique policy set version ID and calculation batch ID ensure the uniqueness and traceability of each policy version, facilitating version management and historical backtracking. Customized policy sets can be quickly generated for different business scenarios, achieving precise matching between business needs and policy configurations, enhancing system adaptability. At the same time, standardized identifier allocation provides a clear basis for subsequent rule calculation, result verification, and other processes, reducing process confusion and operational errors, ensuring the accuracy and stability of policy execution, helping to promote efficient business development, and quickly responding to dynamic changes in the market and business.

[0036] In one embodiment, S300 includes: S301. According to the preset cycle, retrieve the assessment and evaluation strategy set corresponding to the assessment cycle from the strategy library based on the strategy set version ID and calculation batch ID. S302. Obtain real-time business data and basic data from business personnel; S303. The real-time business data and basic data are assessed and calculated using a set of assessment strategies to generate an assessment score. S304. Generate assessment results based on factor dependencies and assessment scores; S305. Based on the comparison between the assessment results and the preset assessment threshold, generate assessment early warning information; S306. The assessment results, assessment warning information, corresponding calculation batch ID, and strategy set version ID are associated and stored.

[0037] In this embodiment, a visual operation interface built on a rules engine allows users to upload various business management policy conditions without needing complex coding skills. Users can easily upload these conditions simply by dragging and dropping functional components, filling in key parameters, and selecting logical conditions. These policy conditions cover all dimensions of business management, including performance quantification standards, compliance guidelines, and service quality requirements at the assessment level; basic salary base, performance-based commission tiers, special reward rules, and violation deduction standards at the salary level; and promotion performance thresholds, demotion trigger conditions, and corresponding permission lists at the job level, comprehensively responding to the core needs of business management.

[0038] After a user uploads strategy conditions, the system automatically integrates relevant basic factors, calculation logic, and execution rules based on built-in scenario matching logic, combined with dimensions such as business domain, job type, and management objectives, to generate a customized strategy set version. This version is a structured and systematic presentation of the user's needs, fully encompassing all the rule system and execution standards required to achieve specific management goals, ensuring the completeness, relevance, and executability of the strategy. To ensure accurate strategy invocation, iterative management, and result traceability, the system assigns a unique strategy set version ID and calculation batch ID to each strategy set version: the strategy set version ID serves as the core identifier to distinguish different strategy solutions, facilitating users to subsequently query, modify, and reuse strategies from different periods, supporting iterative optimization of strategies; the calculation batch ID is bound to a specific business cycle (such as monthly or quarterly) or special business batch, ensuring that all assessments, salary calculations, and job level adjustments within the same batch are executed based on a unified strategy standard, avoiding confusion between multiple version strategies, and providing a clear basis for subsequent calculation result verification, log querying, and problem tracing.

[0039] This embodiment retrieves the strategy set corresponding to the assessment period according to a preset cycle, combines real-time business data and basic data from business personnel to complete the assessment calculation, generate scores and results, and trigger warnings. Simultaneously, it stores relevant information, resulting in outstanding technical effectiveness. By accurately retrieving the corresponding strategy set, the accuracy and timeliness of the assessment basis are ensured, adapting to the assessment needs of different cycles. Relying on real-time data calculation and factor dependency analysis, the accuracy of assessment results is significantly improved, reducing errors caused by human intervention. The assessment warning function can promptly provide feedback on the gap between performance targets and actual results, helping business personnel quickly adjust their work direction and improve the pass rate. The associated storage of relevant information and unique identifiers enables full traceability of the assessment process, facilitating subsequent verification and version rollback, enhancing the transparency and credibility of the assessment. The overall automated process not only simplifies assessment operations and improves assessment efficiency but also provides reliable data support for business management, helping to optimize team management and promote high-quality business development.

[0040] In the fintech sector, when new insurance products are launched or regulatory policies are updated, managers can quickly upload new strategy conditions through a visual interface. These conditions can include setting specific premium commission rates, sales performance indicators, compliance requirements, and corresponding promotion point rules for new products. The system immediately generates a strategy set version adapted to the product's promotion scenario and assigns a unique version ID and calculation batch ID. In subsequent monthly or quarterly assessments, the system uses these two identifiers to accurately retrieve the corresponding strategies, automatically completing agent performance statistics, compliance reviews, salary calculations, and job level adjustments. This not only allows new strategies to be implemented within hours, significantly improving business response speed, but also allows for tracing the basis of each batch's calculations, ensuring compliance and accuracy in management. Similarly, in the securities and wealth management sectors, this process can be used to quickly configure sales performance standards, commission settlement rules, and promotion conditions for different wealth management products, helping financial institutions respond quickly to market changes and optimize team management efficiency.

[0041] In the healthcare business, when launching new health management packages or adjusting service priorities, managers can upload targeted strategy conditions through the interface. These conditions include setting sales performance targets for the new packages, customer service satisfaction thresholds, service process compliance requirements, and corresponding sales commission rates, service reward rules, and promotion standards. The system will then generate a unique strategy set version and assign a unique identifier. In subsequent business cycles, the system will accurately apply these strategies based on the identifier, automatically performing performance evaluations, service quality assessments, and salary calculations for promotion personnel. Based on the results, it will automatically adjust job levels, ensuring precise implementation of incentive policies and motivating the team. For managing partner doctors on the healthcare service platform, this process allows configuration of assessment conditions such as treatment volume, patient satisfaction ratings, medical document compliance, and referral success rates, along with corresponding salary calculation rules and promotion / demotion standards, generating a unique strategy set version and assigning an identifier. Based on these identifiers, the system automatically executes assessment and management processes, which not only standardizes and improves the efficiency of physician team management, but also ensures the traceability of assessment results and salary calculations through unique identifiers, thus ensuring fair and just management and helping medical and health institutions improve service quality and business sustainability.

[0042] In one embodiment, S400 includes: S401. Extract the salary calculation strategy set from the strategy library according to the strategy set version ID, and associate the salary calculation strategy set with the assessment results by calculating the batch ID; S402. Obtain the performance evaluation level of business personnel, real-time business data, and basic factors in the factor library; S403. Calculate salary components according to the salary calculation strategy set, combined with the basic factors, factor dependencies, assessment levels and business data of the factor library, and generate salary details; S404. Based on a set of preset business data prediction models and salary calculation strategies for a specified date, generate salary prediction results; S405. The salary details, salary prediction results, strategy set version ID, calculation batch ID, and assessment results are associated and stored.

[0043] In this embodiment, the system accurately extracts the corresponding salary calculation strategy set from the strategy library according to the pre-allocated strategy set version ID. This set contains core content such as salary composition rules, calculation logic, and factor association methods. Then, by calculating the batch ID, the extracted salary calculation strategy set is bound to the assessment results generated within the same business cycle to ensure the consistency between salary calculation and assessment results and avoid confusion across batches and strategies.

[0044] Subsequently, the system automatically obtains the performance evaluation level of business personnel (such as excellent, qualified, need improvement, etc.), real-time business data (including performance completion amount, number of business orders, service hours, compliance status, etc.), and retrieves the necessary basic factors from the factor library. These basic factors cover key elements such as base salary, performance commission rate, bonus coefficient, and deduction standards. Based on the logic set in the salary calculation strategy set, the system combines the basic factors and their inherent dependencies (such as commission amount depending on performance completion amount and commission rate), links the performance evaluation level (different levels correspond to different reward coefficients or commission rates), and real-time business data to calculate each salary component, including base salary, performance commission, special bonus, and violation deductions. Finally, it integrates and generates a detailed salary statement, clearly specifying the specific amount and calculation basis of each income and deduction item.

[0045] Based on the generated salary details, the system also uses a preset business data prediction model (built by combining historical business data, market trends, business objectives, etc.) for a specified date, combined with the current set of salary calculation strategies, to predict business data for a specific future period. This predictive model then calculates the corresponding salary amount, providing forward-looking references for business personnel and managers. Finally, the system associates and stores the generated salary details and prediction results with the corresponding strategy set version ID, calculation batch ID, and performance evaluation results. This ensures that every piece of salary data can be traced back to the strategy, business cycle, and performance evaluation criteria upon which it was calculated, providing complete support for subsequent data queries, verification, and auditing.

[0046] This embodiment integrates salary calculation strategies and performance evaluation results, combining employee performance ratings, real-time business data, and basic factors to complete salary calculation and prediction, and stores relevant information accordingly, resulting in significant technical improvements. Relying on the precise correlation between strategies and performance evaluation results, coupled with standardized data support from a factor library, it automates and accurately calculates salary components, significantly reducing human error and improving the accuracy and efficiency of salary calculation. The salary prediction function, based on preset models and calculation strategies, helps employees know their expected salaries in advance, enhancing their work planning and motivation. The associated storage of relevant data and unique identifiers ensures that the salary calculation and prediction process is traceable and verifiable, improving the transparency and standardization of salary management. The overall process simplifies the salary calculation process, shortens the payroll cycle, and optimizes the employee experience through accurate prediction and transparent management, strengthening team cohesion and providing strong support for efficient business operations and sustainable development.

[0047] In the fintech business, when calculating agents' monthly salaries, the system extracts the corresponding salary calculation strategy for that month (such as commission rates for different insurance products, team collaboration reward rules, compliance deduction standards, etc.) through the strategy set version ID, and associates it with the agent's monthly performance evaluation level (based on premium income, policy renewal rate, compliance compliance, etc.) through the batch ID calculation. Then, it retrieves the agent's real-time business data (such as premium sales for each product, number of customers served, etc.) and basic factors from the factor library (such as commission rates for each product, basic salary standards, etc.), and calculates the basic salary, product commissions, team rewards, compliance deductions, and other salary components according to the strategy rules, generating detailed salary information. Simultaneously, based on a preset quarterly business growth forecast model and the current salary strategy, the system can predict the agent's salary for the next quarter, helping them plan their business goals. All data is stored in association with the corresponding version ID, batch ID, and performance evaluation results, facilitating insurance companies to verify salary payments and allowing agents to easily access the basis for their salary calculations, significantly improving salary settlement efficiency and transparency. In the securities and wealth management sectors, this process can quickly calculate commissions and bonuses for financial advisors. By combining assessment results such as client asset appreciation rate and product sales performance with business data, it can generate accurate salary details and predict future salaries, helping financial institutions optimize incentive mechanisms and enhance team motivation.

[0048] In the healthcare business sector, taking the marketing team of a health management organization as an example, the system extracts salary calculation strategies for health management package sales (such as package sales commission rates, new customer development rewards, customer satisfaction rewards, etc.) through strategy set version IDs. It then calculates the monthly performance evaluation level of the marketing personnel (based on sales performance, customer satisfaction scores, compliance service status, etc.) associated with the batch ID. Subsequently, it acquires the personnel's real-time business data (such as the number of packages sold, the number of new customer contracts signed, customer satisfaction scores, etc.) and basic factors from the factor library (such as package commission standards, base salary, satisfaction reward coefficient, etc.), calculates various salary components according to the strategy rules, and generates detailed salary details. Based on the organization's annual business expansion target prediction model and current salary strategies, it can also predict the personnel's salary level for the next year, providing a reference for their work plan development. All data is stored in a linked manner, facilitating the organization's traceability of salary calculation basis and ensuring fairness in calculation. For doctors collaborating with the medical service platform, this process can extract salary calculation strategies for medical services (such as outpatient service unit price, surgical service fee, patient evaluation rewards, etc.), link them to the doctor's performance evaluation level (derived from medical service volume, patient satisfaction, medical document compliance, etc.), combine real-time medical data (such as outpatient visits, surgical procedures, patient evaluation scores, etc.) and basic factors (such as unit price of various services, reward coefficients, etc.) to generate detailed salary information for doctors and predict future salaries. This achieves both accurate and automated salary calculation and ensures the traceability of salary disbursement through data association and storage, helping medical and health institutions attract and retain outstanding talent and improve service quality.

[0049] In one embodiment, S500 includes: S501. Extract the job level adjustment strategy set from the strategy library according to the strategy set version ID, and associate the job level adjustment strategy set with the assessment results and salary details by calculating the batch ID; S502. Obtain basic data of business personnel; S503. Based on the set of job level adjustment strategies, combined with the assessment results, salary details and basic data, generate the job level adjustment results for the business personnel. S504. Synchronize the job level adjustment results to the strategy library to update the corresponding basic factors, and associate the strategy set version ID and calculation batch ID.

[0050] In this embodiment, the system accurately extracts the corresponding job level adjustment strategy set from the strategy library based on the strategy set version ID. This set contains core content such as the judgment rules, threshold standards, and factor association logic for job level promotion, demotion, and maintaining the original job level. Then, by calculating the batch ID, the extracted job level adjustment strategy set is bound to the assessment results and salary details within the same business cycle to ensure a logical closed loop between job level adjustment and assessment performance and salary level, and to avoid data misalignment across batches.

[0051] Subsequently, the system automatically acquires basic data of business personnel, including key information such as years of service, current job level, cumulative service hours, professional qualification certifications, and historical performance records, providing a comprehensive reference for job level adjustments. Based on the extracted set of job level adjustment strategies, the system performs multi-dimensional fusion calculations with performance results (such as performance level and key indicator achievement status), salary details (such as total salary, performance-based commission percentage, and other core data reflecting business contributions), and basic data of business personnel. According to the judgment logic set in the strategy (such as "two consecutive performance cycles of excellent and performance-based commission percentage reaching a preset threshold, promotion to one level is possible" and "performance level of needing improvement and salary below the baseline for two consecutive cycles triggers demotion"), the system generates job level adjustment results for each business personnel, clarifying their final job level status.

[0052] Finally, the system will synchronize the generated job level adjustment results to the strategy library, update the basic factors related to the job level (such as the base salary, commission rate cap, and permission configuration for the corresponding job level), and ensure that subsequent salary calculation and performance evaluation can be carried out based on the latest job level information. At the same time, the job level adjustment results will be associated with the corresponding strategy set version ID and calculation batch ID for storage, and the adjustment basis, process and results will be fully preserved to provide data support for subsequent traceability and rule optimization.

[0053] This embodiment achieves significant technical results by linking job level adjustment strategies with performance evaluation results and salary details, combined with basic data of business personnel to generate job level adjustment results and simultaneously update the factor library. Relying on the precise linkage between strategies and core business data, the entire job level adjustment process is automated, eliminating manual intervention, significantly improving adjustment efficiency, and avoiding human error to ensure the objectivity of the adjustment results. Job level adjustments are based on quantified performance evaluation and salary data, coupled with clear strategic logic, enhancing the transparency and fairness of the adjustment process, effectively improving the acceptance and trust of business personnel. The adjustment results are simultaneously updated to the strategy library, ensuring the real-time accuracy of basic factors and providing reliable data support for subsequent performance evaluations, salary calculations, and other business operations. The overall process simplifies job level management, optimizes team management mechanisms, helps enterprises build a scientific and standardized talent development system, further stimulates the work motivation of business personnel, and promotes the simultaneous improvement of team productivity and business quality.

[0054] In the fintech business, the system extracts the corresponding job level adjustment strategy through the strategy set version ID (e.g., "If quarterly premium income meets the target and there are no compliance issues, the job level can be promoted; if premium income fails to meet the target for two consecutive quarters, the job level will be downgraded"). It then calculates the batch ID and links it to the quarterly performance results (e.g., premium completion rate, compliance score) and salary details (e.g., total premium commission, team bonus amount). Subsequently, it retrieves the agent's basic data (e.g., current job level, years of service, past performance records) and makes a comprehensive judgment according to the strategy rules: if the agent's quarterly performance is excellent, premium commission reaches the high-level standard, and the agent has been with the company for at least one year, a promotion result is automatically generated; if the agent's performance is unsatisfactory for two consecutive quarters and the salary does not reach the corresponding job level benchmark, a downgrade is triggered. After the adjustment result is synchronized to the strategy library, the basic salary, commission rate, and other factors for the corresponding job level are updated. Subsequent salary calculations directly use the latest configuration, while also storing relevant identifiers to facilitate insurance companies in tracing the adjustment logic and to allow agents to clearly understand the basis for job level changes, ensuring management fairness. For investment advisors in the securities and wealth management fields, this process can automatically adjust job levels based on performance evaluations such as client asset appreciation rate, product sales performance, and client satisfaction, combined with basic data such as salary details, years of service, and professional qualifications. This helps financial institutions quickly optimize their team structure and motivate their staff.

[0055] In the healthcare business, the system extracts job level adjustment strategies (e.g., "Promotion is possible if the annual number of patients served meets the target, customer satisfaction score is excellent, and specialized qualification certification is completed; job level is downgraded if the service complaint rate exceeds the target or the assessment is unsatisfactory for two consecutive quarters") by calculating the batch ID and linking annual assessment results (e.g., number of patients served, satisfaction score, number of complaints) with salary details (e.g., total service commission, satisfaction bonus amount)). Then, it retrieves the basic data of health consultants (e.g., current job level, years of experience, qualification certification status) and determines the level according to the strategy rules: if a health consultant ranks among the top in the number of patients served annually, achieves a perfect satisfaction score, and adds senior health manager certification, a promotion result is automatically generated; if there are multiple service complaints and the assessment is unsatisfactory, a downgrade is triggered. After the adjustment results are synchronized to the strategy library, the corresponding job level's salary base, service permissions, and other factors are updated. Subsequent business operations and salary calculations are all based on the new job level, and relevant identifiers are stored to ensure the traceability of the adjustment process. For doctors collaborating with the medical service platform, this process can automatically adjust their professional titles based on assessment results such as the volume of medical services, patient cure rate, and compliance of medical documents, combined with basic data such as salary details, professional titles, and years of service. This not only automates and ensures fairness in the management of doctor teams, but also ensures the continuity of subsequent management processes by dynamically updating relevant factors related to job titles, thereby helping medical and health institutions improve service quality and the professional level of their teams.

[0056] In one embodiment, S200 further includes: S2021. When business requirements change, users can dynamically adjust strategy conditions by dragging and dropping components and configuring parameters. S2022. Update the strategy set version according to the adjusted strategy conditions; S2023, Update performance evaluation results, salary details, performance evaluation warning information, and salary prediction results by using the strategy set version ID.

[0057] In this embodiment, when business requirements change, relying on the rule engine's visual configuration capabilities, users can dynamically adjust the original strategy conditions without making complex code modifications. They can do so simply by dragging and dropping components, adjusting parameters, and selecting logical relationships on the user interface. These adjustments can include changes to performance indicator thresholds, modifications to salary calculation rules (such as adjustments to commission rates or updates to bonus rules), and optimizations to job level adjustment logic (such as adjustments to promotion thresholds or changes to demotion trigger conditions), fully adapting to flexible changes in business requirements.

[0058] After the user completes the policy condition adjustment, the system automatically generates an updated policy set version based on the new conditions and assigns it a new policy set version ID (or iterates and marks it based on the original version), ensuring that the new policy is clearly distinguishable from historical policies. At the same time, the system will synchronize the updated policy set version to the policy library, completing the rapid iteration and implementation of policies. The entire process does not require technical personnel intervention, significantly shortening the policy update cycle and improving business response efficiency.

[0059] Subsequently, the system uses the updated strategy set version ID as the core index to extract the new strategy set from the strategy library, re-associate and calculate the batch ID, retrieve the latest business data, basic information, and relevant basic factors from the factor library of business personnel, recalculate the assessment results according to the new strategy rules, generate adjusted salary details, update the threshold and trigger logic of assessment warnings, and simultaneously regenerate salary prediction results based on the new strategy and the preset business data prediction model. The entire update process is fully automated, ensuring that all relevant data, including assessment, salary, warnings, and predictions, are consistent with the latest business strategy, guaranteeing the accuracy and timeliness of business management.

[0060] This embodiment supports dynamic adjustment of strategy conditions by users through drag-and-drop component and parameter configuration when business needs change. It synchronously updates the strategy set version and related assessment and salary results, resulting in significant technical improvements. The visual adjustment method, requiring no code modification, greatly lowers the barrier to strategy iteration, shortens the business response cycle, and allows the system to quickly adapt to dynamic market and business changes. Real-time updates of the strategy set version ensure that all subsequent related calculations are based on the latest rules, guaranteeing the consistency and accuracy of business logic. Related data such as assessment results and salary details are updated synchronously with the strategy, avoiding information lag or inconsistency and improving data reliability. This flexible and efficient iteration mechanism not only reduces the manpower and time costs of strategy adjustments but also ensures that business management always aligns with actual needs, enhancing the system's adaptability and flexibility. It provides accurate and timely rule support for team management, helping enterprises continuously optimize operational efficiency and enhance core competitiveness.

[0061] In the fintech sector, such as the insurance industry, when regulators adjust compliance requirements or insurance companies launch new products and adjust corresponding sales commission rates, managers can quickly adjust compliance weights in performance indicators and modify commission rate parameters in salary calculation strategies by dragging and dropping components. The system automatically generates an updated strategy set version and triggers a recalculation of performance results and salary details updates for all or a specified range of agents using the new version ID. Simultaneously, it updates the monitoring thresholds for compliance indicators in performance alerts and the commission factors in salary prediction models. This allows new compliance requirements and incentive policies to be implemented quickly, helping insurance companies respond rapidly to regulatory requirements and market changes, avoiding management loopholes or incentive failures due to delayed strategy adjustments. In the securities and wealth management sectors, when commission settlement rules for wealth management products are adjusted or customer asset assessment standards change, this method can also be used to quickly update strategies and simultaneously adjust relevant data such as performance and salaries, ensuring real-time matching of business management with market dynamics.

[0062] In the healthcare sector, for example, when health management organizations shift their focus from basic physical examinations to chronic disease management services, they can add performance evaluation factors such as chronic disease management service volume and chronic disease customer retention rate by dragging and dropping components. They can also adjust the commission rate for chronic disease management services in salary calculations. The system automatically generates a new strategy set version, recalculates the performance evaluation results of relevant personnel based on the new ID, updates the commission amount for chronic disease services in salary details, adjusts the threshold for chronic disease service indicators in performance warnings, and recalculates salary forecasts. This allows the organization's management strategy to quickly keep pace with business transformation, incentivizing personnel to focus on new business priorities. For medical service platforms, when adjustments to medical insurance policies lead to changes in the salary calculation rules for medical services, or when the platform adds remote medical services and sets specific performance evaluation and incentive rules, managers can quickly adjust relevant strategies through parameter configuration. The system automatically completes subsequent data updates, ensuring that platform management remains synchronized with policy requirements and business expansion, improving operational efficiency and service quality.

[0063] In one embodiment, a rule-engine-based business personnel assessment device is provided, which corresponds one-to-one with the business personnel assessment methods described in the above embodiments. (Refer to...) Figure 3 , Figure 3 This is a schematic diagram of the functional modules of a preferred embodiment of the business personnel assessment device based on a rule engine of the present invention. The modules include a basic library construction module 10, a strategy management module 20, an assessment module 30, a salary calculation module 40, and a job level management module 50. Detailed descriptions of each functional module are as follows: The basic library construction module 10 is used to decompose the assessment logic, salary calculation logic and job level management logic, generate several basic factors, and form a factor library and a strategy library from the basic factors. The strategy management module 20 is used to generate a strategy set version based on the strategy conditions uploaded by the user, and to assign a strategy set version ID and a calculation batch ID to the strategy set version. The assessment module 30 is used to retrieve the assessment strategy set from the strategy library through the strategy set version ID and calculation batch ID, and calculate the assessment results and assessment warning information of business personnel based on the assessment strategy set, according to business data and basic data. The salary calculation module 40 is used to extract the salary calculation strategy set from the strategy library according to the strategy set version ID, and generate salary details and salary prediction results by combining the assessment results, business data and basic factors in the factor library. The job level management module 50 is used to adjust the job levels of the business personnel based on the assessment results, salary details, assessment warning information, and salary forecast results.

[0064] In one embodiment, the basic library construction module 10 includes: Acquire the performance evaluation logic, salary calculation logic, and job level management logic of business personnel; The assessment logic, salary calculation logic, and job level management logic are decomposed to obtain basic factors, basic logic, and basic strategies; A correlation analysis is performed on the aforementioned basic factors, basic logic, and basic strategies to determine the factor dependencies, data types, and function definitions of each basic factor; The factor library and strategy library are composed of the aforementioned basic factors, factor dependencies, data types, and function definitions.

[0065] In one embodiment, the policy management module 20 includes: Obtain the policy conditions configured by the user through the rules engine's operation page; Generate a set of strategies for the corresponding business scenario based on the aforementioned strategy conditions; Assign a unique strategy set version ID and a computation batch ID to the strategy set version.

[0066] In one embodiment, the assessment module 30 includes: According to the preset cycle, the assessment and evaluation strategy set corresponding to the assessment cycle is retrieved from the strategy library based on the strategy set version ID and calculation batch ID. Obtain real-time business data and basic data from business personnel; The real-time business data and basic data are assessed and calculated using a set of assessment strategies to generate an assessment score. The assessment results are generated based on factor dependencies and assessment scores. Based on the comparison between the assessment results and the preset assessment thresholds, assessment early warning information is generated. The assessment results, assessment warning information, corresponding calculation batch ID, and strategy set version ID are stored together.

[0067] In one embodiment, the salary calculation module 40 includes: The salary calculation strategy set is extracted from the strategy library according to the strategy set version ID, and the salary calculation strategy set is associated with the assessment results by calculating the batch ID; Obtain performance evaluation levels of business personnel, real-time business data, and basic factors from the factor library; Based on the set of salary calculation strategies, and combined with the basic factors, factor dependencies, assessment levels, and business data in the factor library, the salary components are calculated, and salary details are generated. Based on a preset business data prediction model and a set of salary calculation strategies for a specified date, generate salary prediction results; The salary details, salary prediction results, strategy set version ID, calculation batch ID, and assessment results are stored together in a linked manner.

[0068] In one embodiment, the job level management module 50 includes: The job level adjustment strategy set is extracted from the strategy library based on the strategy set version ID, and the job level adjustment strategy set is associated with the assessment results and salary details by calculating the batch ID; Obtain basic data of business personnel; Based on the set of job level adjustment strategies, combined with performance evaluation results, salary details, and basic data, the job level adjustment results for the aforementioned business personnel are generated; The job level adjustment results will be synchronized to the strategy library to update the corresponding basic factors, and the strategy set version ID and calculation batch ID will be associated.

[0069] In one embodiment, the policy management module 20 further includes: When business requirements change, users can dynamically adjust strategy conditions by dragging and dropping components and configuring parameters. Update the strategy set version according to the adjusted strategy conditions; Update performance evaluation results, salary details, performance evaluation warning information, and salary prediction results using the strategy set version ID.

[0070] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used for communication with external user terminals via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a business personnel assessment method on the server side.

[0071] In one embodiment, a computer device is provided, which may be a user terminal, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements the functions or steps of a business personnel assessment method on the user side. In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: The assessment logic, salary calculation logic, and job level management logic are decomposed to generate several basic factors, which then form a factor library and a strategy library. Generate a policy set version based on the policy conditions uploaded by the user, and assign a policy set version ID and a calculation batch ID to the policy set version; The assessment strategy set is retrieved from the strategy library using the strategy set version ID and calculation batch ID. Based on the assessment strategy set, the assessment results and assessment warning information of business personnel are calculated according to business data and basic data. Based on the strategy set version ID, extract the salary calculation strategy set from the strategy library, and combine it with the assessment results, business data and basic factors in the factor library to generate salary details and salary prediction results; The job levels of the business personnel will be adjusted based on the assessment results, salary details, assessment warning information, and salary forecast results.

[0072] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: The assessment logic, salary calculation logic, and job level management logic are decomposed to generate several basic factors, which then form a factor library and a strategy library. Generate a policy set version based on the policy conditions uploaded by the user, and assign a policy set version ID and a calculation batch ID to the policy set version; The assessment strategy set is retrieved from the strategy library using the strategy set version ID and calculation batch ID. Based on the assessment strategy set, the assessment results and assessment warning information of business personnel are calculated according to business data and basic data. Based on the strategy set version ID, extract the salary calculation strategy set from the strategy library, and combine it with the assessment results, business data and basic factors in the factor library to generate salary details and salary prediction results; The job levels of the business personnel will be adjusted based on the assessment results, salary details, assessment warning information, and salary forecast results.

[0073] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and user side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0074] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0075] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0076] It should be noted that any AI models, software tools, or components not belonging to this company appearing in the embodiments of this application are merely illustrative examples and do not represent actual use. All user personal information involved in the embodiments of this application has been authorized (with the knowledge and consent) by the relevant parties or has been fully authorized by all parties, and the executing entity may obtain it through various legal and compliant means. The collection, storage, use, processing, transmission, provision, and disclosure of the information, data, and signals involved all comply with relevant laws and regulations and do not violate public order and good morals.

[0077] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for evaluating sales personnel, characterized in that, Includes the following steps: The assessment logic, salary calculation logic, and job level management logic are decomposed to generate several basic factors, and a factor library and strategy library are constructed based on these basic factors. Generate a policy set version based on the policy conditions configured by the user, and assign a policy set version ID and a calculation batch ID to the policy set version; The assessment strategy set is retrieved from the strategy library using the strategy set version ID and calculation batch ID. Based on the assessment strategy set, the assessment results and assessment warning information of business personnel are calculated according to business data and basic data. Based on the strategy set version ID, extract the salary calculation strategy set from the strategy library, and combine it with the assessment results, business data and basic factors in the factor library to generate salary details and salary prediction results; The job levels of the business personnel will be adjusted based on the assessment results, salary details, assessment warning information, and salary forecast results.

2. The performance evaluation method for business personnel as described in claim 1, characterized in that, The process involves decomposing the performance evaluation logic, salary calculation logic, and job level management logic to generate several basic factors. These basic factors then form a factor library and a strategy library, including: Acquire the performance evaluation logic, salary calculation logic, and job level management logic of business personnel; The assessment logic, salary calculation logic, and job level management logic are decomposed to obtain basic factors, basic logic, and basic strategies; A correlation analysis is performed on the aforementioned basic factors, basic logic, and basic strategies to determine the factor dependencies, data types, and function definitions of each basic factor; The factor library and strategy library are composed of the aforementioned basic factors, factor dependencies, data types, and function definitions.

3. The performance evaluation method for business personnel as described in claim 1, characterized in that, The step of generating a policy set version based on the policy conditions uploaded by the user, and assigning a policy set version ID and a calculation batch ID to the policy set version, includes: Obtain the policy conditions configured by the user through the rules engine's operation page; Generate a set of strategies for the corresponding business scenario based on the aforementioned strategy conditions; Assign a unique strategy set version ID and a computation batch ID to the strategy set version.

4. The performance evaluation method for business personnel as described in claim 1, characterized in that, The process of retrieving the assessment strategy set from the strategy library using the strategy set version ID and calculation batch ID, and calculating the assessment results and assessment warning information for business personnel based on the assessment strategy set, according to business data and basic data, includes: According to the preset cycle, the assessment and evaluation strategy set corresponding to the assessment cycle is retrieved from the strategy library based on the strategy set version ID and calculation batch ID. Obtain real-time business data and basic data from business personnel; The real-time business data and basic data are assessed and calculated using a set of assessment strategies to generate an assessment score. The assessment results are generated based on factor dependencies and assessment scores. The assessment results are compared with the preset assessment thresholds, and assessment warning information is generated based on the comparison results. The assessment results, assessment warning information, corresponding calculation batch ID, and strategy set version ID are stored together.

5. The performance evaluation method for business personnel as described in claim 1, characterized in that, The process involves extracting a salary calculation strategy set from the strategy library based on the strategy set version ID, combining it with performance evaluation results, business data, and basic factors from the factor library to generate salary details and salary prediction results, including: The salary calculation strategy set is extracted from the strategy library according to the strategy set version ID, and the salary calculation strategy set is associated with the assessment results by calculating the batch ID; Obtain performance evaluation levels of business personnel, real-time business data, and basic factors from the factor library; Based on the set of salary calculation strategies, and combined with the basic factors, factor dependencies, assessment levels, and business data in the factor library, the salary components are calculated, and salary details are generated. Based on a preset business data prediction model and a set of salary calculation strategies for a specified date, generate salary prediction results; The salary details, salary prediction results, strategy set version ID, calculation batch ID, and assessment results are stored together in a linked manner.

6. The performance evaluation method for business personnel as described in claim 1, characterized in that, The adjustment of job levels for the business personnel based on the assessment results, salary details, assessment early warning information, and salary forecast results includes: The job level adjustment strategy set is extracted from the strategy library based on the strategy set version ID, and the job level adjustment strategy set is associated with the assessment results and salary details by calculating the batch ID; Obtain basic data of business personnel; Based on the set of job level adjustment strategies, combined with performance evaluation results, salary details, and basic data, the job level adjustment results for the aforementioned business personnel are generated; The job level adjustment results will be synchronized to the strategy library to update the corresponding basic factors, and the strategy set version ID and calculation batch ID will be associated.

7. The performance evaluation method for business personnel as described in any one of claims 1-6, characterized in that, Generate a policy set version based on the policy conditions uploaded by the user, and assign a policy set version ID and a calculation batch ID to the policy set version, and also include: When business requirements change, users can dynamically adjust strategy conditions by dragging and dropping components and configuring parameters. Update the strategy set version according to the adjusted strategy conditions; Update performance evaluation results, salary details, performance evaluation warning information, and salary prediction results using the strategy set version ID.

8. A business personnel assessment device based on a rules engine, characterized in that, The rule engine-based business personnel assessment device includes: The basic library construction module is used to decompose the assessment logic, salary calculation logic, and job level management logic, generate several basic factors, and form a factor library and a strategy library from the basic factors. The strategy management module is used to generate a strategy set version based on the strategy conditions uploaded by the user, and to assign a strategy set version ID and a calculation batch ID to the strategy set version. The assessment module is used to retrieve the assessment strategy set from the strategy library using the strategy set version ID and calculation batch ID, and calculate the assessment results and assessment warning information of business personnel based on the assessment strategy set, business data and basic data. The salary calculation module is used to extract the salary calculation strategy set from the strategy library according to the strategy set version ID, and generate salary details and salary prediction results by combining the assessment results, business data and basic factors in the factor library. The job level management module is used to adjust the job levels of the business personnel based on the assessment results, salary details, assessment warning information, and salary forecast results.

9. A computer device, characterized in that, The computer device includes a memory, a processor, and a rule-engine-based business personnel assessment program stored in the memory and executable on the processor. When the rule-engine-based business personnel assessment program is executed by the processor, it implements the steps of the business personnel assessment method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a business personnel assessment program based on a rule engine, which, when executed by a processor, implements the steps of the business personnel assessment method as described in any one of claims 1-7.

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