Performance checking method based on basic law index center and related equipment

Abstract

The invention belongs to the technical field of data analysis, and relates to a performance examination method based on a basic law index center and related equipment, and the method comprises the steps: constructing basic index data according to agent commission data; processing the basic index data, calculating assessment period data of each agent in each assessment scene, and associating the assessment period data with the comprehensive index data; slicing the comprehensive data set according to the assessment period data; summarizing index values of each person and each team in each assessment period according to the comprehensive data set sliced by the multi-dimensional summarizing algorithm; and performing calculation conversion operation on the index value of the summarized result data according to an assessment standard and a rule engine to obtain assessment result data. Through the technical means of accurate data collection, comprehensive index construction, efficient calculation processing, flexible configuration adjustment and the like, accurate, comprehensive and efficient evaluation of the performance of the agent is realized, and powerful support is provided for performance assessment management of an enterprise.

Description

Technical Field

[0001] The present application relates to the field of data analysis technology, and in particular to a performance evaluation method and related equipment based on a basic law indicator center. Background Art

[0002] With the development of the times and the continuous progress of society, performance has become a key issue that enterprises and organizations attach great importance to. Performance usually refers to the effect and quality of an individual or team completing work tasks within a certain period of time. In enterprises and organizations, performance is usually used to measure employees' work performance in order to evaluate, motivate and manage them. By setting specific and measurable work goals, it helps employees clarify work requirements and expectations, thereby improving work efficiency.

[0003] The performance appraisal index system is a tool for evaluating and measuring employee work performance. Through clear performance indicators, employees can clearly understand their work goals and requirements, so as to better plan and execute their work. The performance appraisal results can be used as the basis for decisions such as promotion, salary increase, and renewal of employment, which helps the company to effectively manage talent.

[0004] In the existing performance appraisal methods, it is generally impossible to accurately evaluate employee characteristics, resulting in the fairness and objectivity of the existing performance appraisal methods being unsatisfactory, which greatly affects the effectiveness of the performance appraisal methods based on the performance appraisal indicator system. In addition, when iterating, the existing performance appraisal methods based on the performance appraisal indicator system only update the appraisal indicators, and do not analyze and adjust the appraisal time, resulting in the iterative update efficiency of the performance appraisal methods based on the performance appraisal indicator system being unsatisfactory. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to propose a performance appraisal method and related equipment based on the basic law indicator center to solve the problem that the existing performance appraisal method cannot accurately evaluate employee characteristics.

[0006] In order to solve the above technical problems, the embodiment of the present application provides a performance evaluation method based on the basic law indicator center, which adopts the following technical solutions:

[0007] receiving a verification request sent by a user terminal, wherein the verification request carries identification information of an agent to be verified;

[0008] Reading the insurance policy system and obtaining agent commission data corresponding to the agent identification information in the insurance policy system;

[0009] constructing basic indicator data based on the agent commission data;

[0010] Process the basic indicator data according to the pre-configured personnel structure information and hierarchical aggregation algorithm to obtain the indicators of the directly subordinate teams and the indicators of the teams in preparation;

[0011] Calculate the assessment period data of each agent in each assessment scenario according to the preset assessment scenario rules, the indicators of the direct subordinate team, the indicators of the team in preparation, and the time window algorithm, and associate the assessment period data with the comprehensive indicator data to obtain a comprehensive data set;

[0012] Slicing the comprehensive data set according to the assessment period data to obtain a sliced ​​comprehensive data set;

[0013] Calculate the indicator values ​​of each person and each team in each assessment period of the sliced ​​comprehensive data set according to a multi-dimensional summary algorithm to obtain summary result data;

[0014] The index values ​​of the summary result data are calculated and converted according to the assessment standards and the rule engine to obtain the assessment result data.

[0015] Furthermore, after the step of reading the insurance policy system and obtaining the agent commission data corresponding to the agent identification information in the insurance policy system, the following steps are also included:

[0016] Performing data cleaning and conversion operations on the agent commission data to obtain structured commission data;

[0017] The step of constructing basic indicator data based on the agent commission data specifically includes the following steps:

[0018] Basic indicator data is constructed based on the structured commission data.

[0019] Furthermore, the step of constructing basic indicator data based on the agent commission data specifically includes the following steps:

[0020] Calling the personnel system interface and obtaining monthly personnel basic data from the personnel system interface;

[0021] The agent commission data and the monthly personnel basic data are associated with each other according to a data association algorithm to obtain the basic indicator data.

[0022] Furthermore, after the step of calling the personnel system interface and obtaining monthly personnel basic data from the personnel system interface, the following steps are also included:

[0023] The monthly basic personnel data is verified and completed to obtain complete monthly basic personnel data.

[0024] Furthermore, after the step of performing calculation and conversion operations on the index values ​​of the summary result data according to the assessment standards and the rule engine to obtain the assessment result data, the following steps are also included:

[0025] Read the system database and obtain the assessment results of the previous month in the system database;

[0026] performing an abnormality identification operation on the assessment result data according to the assessment result of the previous month to obtain an abnormality identification result;

[0027] The assessment result data is marked according to the abnormality identification result.

[0028] Furthermore, after the step of performing calculation and conversion operations on the index values ​​of the summary result data according to the assessment standards and the rule engine to obtain the assessment result data, the following steps are also included:

[0029] The agent commission data and the monthly personnel basic data are synchronized to the indicator center in real time based on DTS synchronization technology.

[0030] In order to solve the above technical problems, the embodiment of the present application further provides a performance evaluation device based on the basic law indicator center, which adopts the following technical solution:

[0031] a request receiving module, configured to receive a verification request sent by a user terminal, wherein the verification request carries identification information of an agent to be verified;

[0032] a commission data acquisition module, configured to read the insurance policy system and acquire agent commission data corresponding to the agent identification information in the insurance policy system;

[0033] A basic indicator construction module, configured to construct basic indicator data based on the agent commission data;

[0034] An indicator processing module is used to process the basic indicator data according to pre-configured personnel structure information and hierarchical aggregation algorithm to obtain indicators of directly subordinate teams and indicators of teams in preparation;

[0035] A comprehensive data acquisition module is used to calculate the assessment period data of each agent in each assessment scenario based on the preset assessment scenario rules, the indicators of the direct subordinate team, the indicators of the team in preparation, and the time window algorithm, and associate the assessment period data with the comprehensive indicator data to obtain a comprehensive data set;

[0036] A data slicing module, configured to slice the comprehensive data set according to the assessment period data to obtain a sliced ​​comprehensive data set;

[0037] An indicator value calculation module is used to calculate the indicator value of each person and each team in the sliced ​​comprehensive data set during each assessment period according to a multi-dimensional summary algorithm to obtain summary result data;

[0038] The indicator value calculation and conversion module is used to perform calculation and conversion operations on the indicator values ​​of the summary result data according to the assessment standards and the rule engine to obtain the assessment result data.

[0039] Furthermore, the device includes: a data cleaning and conversion module, and the basic indicator construction module includes: a basic indicator construction submodule, wherein:

[0040] The data cleaning and conversion module is used to perform data cleaning and conversion operations on the agent commission data to obtain structured commission data;

[0041] The basic indicator construction submodule is used to construct basic indicator data based on the structured commission data.

[0042] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0043] It includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, it implements the steps of the performance appraisal method based on the basic law indicator center as described above.

[0044] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0045] The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the performance appraisal method based on the Basic Law indicator center as described above.

[0046] The present application provides a performance appraisal method based on a basic law indicator center, comprising: receiving an appraisal request sent by a user terminal, wherein the appraisal request carries identification information of an agent to be appraised; reading an insurance policy system and obtaining agent commission data corresponding to the agent identification information in the insurance policy system; constructing basic indicator data based on the agent commission data; processing the basic indicator data according to pre-configured personnel structure information and a hierarchical aggregation algorithm to obtain indicators of direct subordinate teams and indicators of teams in preparation; calculating the appraisal period data of each agent in each appraisal scenario according to preset appraisal scenario rules, the indicators of the direct subordinate teams, the indicators of the teams in preparation and a time window algorithm, and associating the appraisal period data with comprehensive indicator data to obtain a comprehensive data set; slicing the comprehensive data set according to the appraisal period data to obtain a sliced ​​comprehensive data set; calculating the indicator values ​​of each person and each team in the sliced ​​comprehensive data set in each appraisal period according to a multi-dimensional summary algorithm to obtain summary result data; performing calculation and conversion operations on the indicator values ​​of the summary result data according to the appraisal standards and a rule engine to obtain appraisal result data. Compared with existing technologies, this application achieves accurate, comprehensive and efficient evaluation of agent performance through technical means such as precise data collection, comprehensive indicator construction, efficient calculation and processing, and flexible configuration adjustment, providing strong support for the company's performance appraisal management. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0048] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0049] Figure 2 This is a flowchart of the implementation of the performance evaluation method based on the Basic Law indicator center provided in the embodiment of the present application;

[0050] Figure 3 This is a schematic diagram of the structure of a performance evaluation device based on the Basic Law indicator center provided in an embodiment of the present application;

[0051] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are for the purpose of describing specific embodiments only and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0053] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0054] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0055] like Figure 1 As shown, system architecture 100 may include a terminal device 101, a network 102, and a server 103. Terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. Network 102 is a medium for providing a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0056] The user can use the terminal device 101 to interact with the server 103 via the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0057] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop computer 1011, tablet computer 1012 or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer and a desktop computer, etc.

[0058] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0059] It should be noted that the performance evaluation method based on the Basic Law Index Center provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the performance evaluation device based on the Basic Law Index Center is generally set in the server / terminal device.

[0060] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0061] Continue to refer Figure 2 , which shows a flow chart of an embodiment of a performance evaluation method based on the Basic Law Indicator Center according to the present application. The performance evaluation method based on the Basic Law Indicator Center includes: step S201, step S202, step S203, step S204, step S205, step S206, step S207, and step S208.

[0062] In step S201, a verification request sent by a user terminal is received, wherein the verification request carries identification information of an agent to be verified.

[0063] In the embodiments of the present application, the user terminal refers to a terminal device used to execute the image processing method for preventing document abuse provided by the present application. The user terminal can be a mobile terminal such as a mobile phone, a smart phone, a laptop computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation device, etc., as well as a fixed terminal such as a digital TV, a desktop computer, etc. It should be understood that the examples of user terminals here are only for convenience of understanding and are not used to limit the present application.

[0064] In this embodiment of the application, the system first waits for and monitors for performance review requests from a user terminal (e.g., a computer or mobile phone). When a user (management or the performance review department) wishes to review the performance of a specific agent, they submit a performance review request through the user terminal. This request includes the agent's identification information, such as the agent's ID, name, or employee number, which is used to subsequently identify and locate the corresponding agent in the system.

[0065] In step S202, the insurance policy system is read, and agent commission data corresponding to the agent identification information is obtained in the insurance policy system.

[0066] In this embodiment of the present application, upon receiving a review request, the system accesses the policy system based on the agent identification information provided in the request. The policy system is a database that records all policy information (including policyholders, insureds, agent commissions, etc.). The system retrieves all policy records related to the agent being reviewed from the policy system and extracts the agent's commission data. This data reflects the agent's income from selling policies over a specific period of time.

[0067] In step S203, basic indicator data is constructed based on the agent commission data.

[0068] In this embodiment of the application, after obtaining agent commission data, the system will construct basic indicator data based on this data. Basic indicator data generally includes the agent's total commission, commission growth rate, commission composition ratio, etc. This data provides a direct quantitative basis for subsequent assessment.

[0069] In step S204, the basic indicator data is processed according to the pre-configured personnel structure information and the hierarchical aggregation algorithm to obtain the indicators of the directly subordinate teams and the indicators of the teams in preparation.

[0070] In this embodiment of the present application, the system further processes the basic indicator data based on pre-configured personnel structure information (such as the agent's superior-subordinate relationship, team affiliation, etc.) and a hierarchical aggregation algorithm. Through the algorithm, the system can calculate the indicators of each agent's direct subordinate team (such as the team's total commission, average commission, etc.) and the indicators of the team in preparation (such as the progress of new team formation, potential commission, etc.). These team indicators reflect the agent's performance in team management and business development.

[0071] In step S205, the assessment period data of each agent in each assessment scenario is calculated according to the preset assessment scenario rules, the indicators of the direct subordinate team, the indicators of the team in preparation and the time window algorithm, and the assessment period data is associated with the comprehensive indicator data to obtain a comprehensive data set.

[0072] In an embodiment of the present application, the system calculates the assessment period data of each agent in each assessment scenario based on the preset assessment scenario rules (such as monthly assessment, quarterly assessment, etc.), the indicators of the direct subordinate team, the indicators of the team in preparation, and the time window algorithm. The assessment period data includes the total commission, growth rate, team size change, etc. within each assessment cycle. Then, the system associates these assessment period data with comprehensive indicator data (such as historical performance, training participation, etc.) to form a comprehensive data set.

[0073] In step S206 , the comprehensive data set is sliced ​​according to the assessment period data to obtain a sliced ​​comprehensive data set.

[0074] In this embodiment of the application, to more deeply analyze agent performance, the system slices the comprehensive dataset. Slicing involves dividing the dataset into smaller subsets based on specific dimensions (such as time, region, product type, etc.). This allows the system to analyze and compare each subset individually, leading to a more accurate assessment of agent performance across different dimensions.

[0075] In step S207, the indicator values ​​of each person and each team in each assessment period of the sliced ​​comprehensive data set are calculated according to the multi-dimensional summary algorithm to obtain summary result data.

[0076] In this embodiment of the present application, the system uses a multi-dimensional aggregation algorithm to calculate the indicators of each individual and team during each assessment period. These indicators include total commission, average commission, commission growth rate, team size, customer satisfaction, etc. By calculating these indicators, the system can obtain comprehensive, multi-dimensional summary results data for subsequent assessment analysis and evaluation.

[0077] In step S208, the indicator values ​​of the summary result data are calculated and converted according to the assessment standards and the rule engine to obtain the assessment result data.

[0078] In this embodiment of the present application, the system calculates and converts the indicator values ​​of the summary result data based on preset assessment criteria and a rule engine. The rule engine is a system component used to execute preset rules. It can calculate the final assessment result data based on different conditions and logic. This assessment result data includes assessment grades, bonus distribution, promotion opportunities, etc., providing a basis for subsequent reward and punishment decisions.

[0079] In an embodiment of the present application, a performance appraisal method based on a basic law indicator center is provided, including: receiving an appraisal request sent by a user terminal, wherein the appraisal request carries identification information of an agent to be appraised; reading an insurance policy system, and obtaining agent commission data corresponding to the agent identification information in the insurance policy system; constructing basic indicator data based on the agent commission data; processing the basic indicator data according to pre-configured personnel structure information and a hierarchical aggregation algorithm to obtain indicators of direct subordinate teams and indicators of teams in preparation; calculating the appraisal period data of each agent in each appraisal scenario according to preset appraisal scenario rules, indicators of direct subordinate teams, indicators of teams in preparation and a time window algorithm, and associating the appraisal period data with comprehensive indicator data to obtain a comprehensive data set; slicing the comprehensive data set according to the appraisal period data to obtain a sliced ​​comprehensive data set; calculating the indicator values ​​of each person and each team in the sliced ​​comprehensive data set in each appraisal period according to a multi-dimensional summary algorithm to obtain summary result data; performing calculation and conversion operations on the indicator values ​​of the summary result data according to the appraisal standards and the rule engine to obtain appraisal result data. Compared with existing technologies, this application achieves accurate, comprehensive and efficient evaluation of agent performance through technical means such as precise data collection, comprehensive indicator construction, efficient calculation and processing, and flexible configuration adjustment, providing strong support for the company's performance appraisal management.

[0080] In some optional implementations of the embodiments of the present application, after the step of reading the insurance policy system and obtaining the agent commission data corresponding to the agent identification information in the insurance policy system, the following steps are also included:

[0081] Perform data cleansing and conversion operations on agent commission data to obtain structured commission data;

[0082] The steps for constructing basic indicator data based on agent commission data specifically include the following steps:

[0083] Build basic indicator data based on structured commission data.

[0084] In the embodiment of the present application, the specific operations of data cleaning include:

[0085] (1) Deduplication processing:

[0086] Remove duplicate data entries to ensure that each agent's commission record is unique, avoiding duplicate counting problems in subsequent calculations.

[0087] (2) Missing value processing:

[0088] Fill in or delete missing commission data. If the missing data has little impact on the analysis, you can choose to delete it directly. If the missing data is large and has a significant impact on the analysis, you need to fill it in through interpolation, regression, or other algorithms.

[0089] (3) Outlier processing:

[0090] Identify and address outliers in commission data, such as commission amounts outside a reasonable range, commission records that do not conform to business logic, etc. These outliers are caused by data entry errors or system anomalies and need to be corrected or deleted.

[0091] (4) Unified format:

[0092] Unify the format of commission data into a standard format that the system can recognize, such as date format, number format, etc. This will facilitate subsequent data processing and calculation.

[0093] In the embodiment of this application, after the above-mentioned data cleaning and conversion operations, the raw commission data is converted into structured commission data. Structured data has clear field definitions, data types, and data structures, which facilitates the system's subsequent data processing and analysis. This structured commission data will serve as the basis for the performance appraisal process, used to construct basic indicator data, calculate team indicators, and appraisal period data.

[0094] In some optional implementations of the embodiments of the present application, the step of constructing basic indicator data based on agent commission data specifically includes the following steps:

[0095] Call the human resources system interface and obtain monthly basic personnel data from the human resources system interface;

[0096] The agent commission data and monthly personnel basic data are associated with each other according to the data association algorithm to obtain basic indicator data.

[0097] In the embodiments of this application, before making an interface call, you must first clarify the specific address (URL) of the personnel system interface, the request method (such as GET or POST), the request parameters (such as time range, person ID, etc.), and the response format (such as JSON, XML, etc.). According to the interface documentation or communicate with the technical team, ensure that the call parameters and request format are correct.

[0098] In the embodiment of the present application, an HTTP request is constructed using an appropriate programming language and framework (such as Python's requests library, Java's HttpClient, etc.) and sent to the human resources system interface. The interface response is waited for and any exceptions or errors (such as network timeout, interface unavailable, etc.) are caught.

[0099] In an embodiment of the present application, the response data returned by the receiving interface is parsed according to the response format. Typically, the response data is returned in JSON or XML format and needs to be parsed into a data structure that the program can handle (such as a Python dictionary or a Java object). Extract monthly personnel basic data such as personnel ID, name, department, position, date of employment, etc.

[0100] In this embodiment of the present application, basic indicator data can be constructed by calling the personnel system interface to obtain monthly basic personnel data and correlating agent commission data using a data correlation algorithm. This basic indicator data provides an important basis and support for subsequent performance evaluation. Throughout this process, it is necessary to ensure the accuracy, completeness, and consistency of the data, while paying attention to the stability of the interface call and the efficiency of data processing.

[0101] In some optional implementations of the embodiments of the present application, after the above steps of calling the personnel system interface and obtaining monthly personnel basic data from the personnel system interface, the following steps are also included:

[0102] The monthly basic personnel data is verified and completed to obtain complete monthly basic personnel data.

[0103] In the embodiment of this application, data verification is an important step to ensure the accuracy and consistency of monthly personnel basic data. It mainly includes the following aspects:

[0104] (1) Integrity check:

[0105] Check whether the monthly personnel basic data contains all necessary fields, such as personnel ID, name, department, position, etc.

[0106] Ensure that there are no missing records or fields. Missing data needs to be marked or completed later.

[0107] (2) Format verification:

[0108] Verify whether the data format meets expectations, such as whether the date field meets the date format and whether the numeric field contains illegal characters.

[0109] Data that does not conform to the format needs to be converted or marked as erroneous data.

[0110] (3)Logical verification:

[0111] Check whether the logical relationship between the data is established, such as the relationship between the date of joining the company and the current date, the correspondence between departments and positions, etc.

[0112] Logically inconsistent data needs to be corrected or marked as abnormal data.

[0113] (4) Uniqueness check:

[0114] Ensure that unique identifiers in the data (such as person IDs) are unique within the dataset and have no duplicates.

[0115] Duplicate data needs to be deduplicated or marked as conflicting data.

[0116] In the embodiment of this application, data completion is the process of supplementing and improving missing or incomplete data in the monthly personnel basic data. It mainly includes the following aspects:

[0117] (1) Direct completion:

[0118] For missing data that is known and can be directly obtained, such as the default values ​​of certain fields or values ​​inferred from other fields, it can be directly completed.

[0119] For example, for a missing department field, the department can be inferred based on the position field and completed.

[0120] (2) Indirect completion:

[0121] Missing data that cannot be obtained directly can be supplemented through other channels or data sources.

[0122] For example, missing contact information fields can be queried and completed through interfaces with other systems or databases.

[0123] (3) Manual completion:

[0124] Data that cannot be completed through automated means can be supplemented through manual intervention.

[0125] For example, some special fields or complex situations require manual review and completion.

[0126] (4) Data interpolation:

[0127] For time series data or continuous data, interpolation methods can be used to estimate and fill in missing values ​​in the data.

[0128] For example, missing monthly sales data can be filled using linear interpolation or other interpolation methods.

[0129] In the embodiment of this application, verifying and completing the monthly personnel basic data is an important step to ensure data quality, improve data consistency and support decision-making. In actual operation, it is necessary to select appropriate verification and completion methods based on the specific data situation and business needs, and continuously optimize and improve the processing flow.

[0130] In some optional implementations of the embodiments of the present application, after the step of performing calculation and conversion operations on the indicator values ​​of the summary result data according to the assessment criteria and the rule engine to obtain the assessment result data, the following steps are also included:

[0131] Read the system database and obtain the assessment results of the previous month in the system database;

[0132] Perform anomaly recognition operations on the assessment result data based on the assessment results of the previous month to obtain anomaly recognition results;

[0133] The assessment result data is marked based on the abnormality identification results.

[0134] In the embodiments of this application, before identifying anomalies, it is necessary to clarify what constitutes an "abnormality." This typically involves setting rules or thresholds, such as the normal range of assessment results, or the signs or patterns of abnormal results. These criteria can be determined based on historical data, business logic, or industry standards.

[0135] In the embodiment of the present application, the assessment result data of the previous month is verified according to the defined abnormality criteria. Each assessment result is checked to see whether it meets the abnormality criteria, such as exceeding the normal range, not conforming to business logic, or having a specific abnormal pattern.

[0136] In the embodiment of the present application, data that meets the abnormality criteria is identified as an abnormal result, and specific information of the abnormal result, such as the assessment result, abnormality type, and abnormality cause, is recorded.

[0137] In the embodiment of the present application, all identified abnormal results are summarized for subsequent processing and analysis.

[0138] In the embodiments of this application, by reading the system database to obtain the previous month's assessment results, performing anomaly identification, and marking the assessment result data based on the anomaly identification results, comprehensive inspection and quality control of the assessment result data can be achieved. This process helps to identify potential problems and anomalies, providing strong support for subsequent analysis, processing, and decision-making. At the same time, it also ensures the consistency and accuracy of the data, improving the reliability and stability of the system.

[0139] In some optional implementations of the embodiments of the present application, after the step of performing calculation and conversion operations on the indicator values ​​of the summary result data according to the assessment criteria and the rule engine to obtain the assessment result data, the following steps are also included:

[0140] Based on DTS synchronization technology, agent commission data and monthly personnel basic data are synchronized to the indicator center in real time.

[0141] In the embodiments of this application, DTS (Data Transmission Service) synchronization technology is an efficient and reliable data transmission and synchronization service that can synchronize data from one data source to another in real time or on a scheduled basis. DTS technology is widely used in scenarios such as data backup, data migration, and data integration to ensure data integrity, consistency, and availability.

[0142] In this embodiment of the application, DTS synchronization technology enables real-time synchronization of agent commission data and monthly personnel baseline data to the indicator center. This process ensures data integrity, consistency, and real-time availability, providing strong support for subsequent data analysis and business decision-making. Furthermore, DTS synchronization technology provides synchronization monitoring and alarm functions, enabling timely detection and resolution of problems and anomalies during the synchronization process.

[0143] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0144] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0145] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware via computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above-described method embodiments. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0146] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0147] Further references Figure 3 , as a response to the above Figure 2 The present application provides an embodiment of a performance evaluation device based on the basic law indicator center. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0148] like Figure 3 As shown, the performance evaluation device 200 based on the basic law indicator center in the embodiment of the present application includes:

[0149] The request receiving module 210 is configured to receive a verification request sent by a user terminal, wherein the verification request carries identification information of the agent to be verified;

[0150] The commission data acquisition module 220 is used to read the insurance policy system and obtain the agent commission data corresponding to the agent identification information in the insurance policy system;

[0151] A basic indicator construction module 230 is used to construct basic indicator data based on agent commission data;

[0152] The indicator processing module 240 is used to process the basic indicator data according to the pre-configured personnel structure information and the hierarchical aggregation algorithm to obtain the indicators of the directly subordinate teams and the indicators of the teams in preparation;

[0153] Comprehensive data acquisition module 250, for calculating the assessment period data of each agent in each assessment scenario based on preset assessment scenario rules, indicators of direct subordinate teams, indicators of teams in preparation, and a time window algorithm, and associating the assessment period data with the comprehensive indicator data to obtain a comprehensive data set;

[0154] The data slicing module 260 is used to slice the comprehensive data set according to the assessment period data to obtain a sliced ​​comprehensive data set;

[0155] The indicator value calculation module 270 is used to calculate the indicator value of each person and each team in each assessment period of the sliced ​​comprehensive data set according to the multi-dimensional summary algorithm to obtain summary result data;

[0156] The indicator value calculation and conversion module 280 is used to perform calculation and conversion operations on the indicator values ​​of the summary result data according to the assessment standards and the rule engine to obtain assessment result data.

[0157] In an embodiment of the present application, a performance evaluation device 200 based on a basic law indicator center is provided, comprising: a request receiving module 210 for receiving an evaluation request sent by a user terminal, wherein the evaluation request carries identification information of an agent to be evaluated; a commission data acquisition module 220 for reading an insurance policy system and acquiring agent commission data corresponding to the agent identification information in the insurance policy system; a basic indicator construction module 230 for constructing basic indicator data based on the agent commission data; an indicator processing module 240 for processing the basic indicator data based on pre-configured personnel structure information and a hierarchical aggregation algorithm to obtain indicators of directly subordinate teams and indicators of teams in preparation; and a comprehensive data acquisition module 250 for It is used to calculate the assessment period data of each agent in each assessment scenario according to the preset assessment scenario rules, the indicators of the team of direct subordinates, the indicators of the team in preparation and the time window algorithm, and associate the assessment period data with the comprehensive indicator data to obtain a comprehensive data set; the data slicing module 260 is used to slice the comprehensive data set according to the assessment period data to obtain the sliced ​​comprehensive data set; the indicator value calculation module 270 is used to calculate the indicator value of each person and each team in the sliced ​​comprehensive data set in each assessment period according to the multi-dimensional summary algorithm to obtain the summary result data; the indicator value calculation conversion module 280 is used to perform calculation and conversion operations on the indicator value of the summary result data according to the assessment standards and the rule engine to obtain the assessment result data. Compared with the existing technology, this application realizes the accurate, comprehensive and efficient evaluation of agent performance through technical means such as accurate data collection, comprehensive indicator construction, efficient calculation processing and flexible configuration adjustment, providing strong support for the performance assessment management of the enterprise.

[0158] In some optional implementations of the embodiments of the present application, the performance evaluation device 200 based on the basic law indicator center further includes: a data cleaning and conversion module, and the basic indicator construction module includes: a basic indicator construction sub-module, wherein:

[0159] The data cleaning and conversion module is used to perform data cleaning and conversion operations on agent commission data to obtain structured commission data;

[0160] The basic indicator construction submodule is used to construct basic indicator data based on structured commission data.

[0161] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device according to an embodiment of the present application.

[0162] The computer device 300 includes a memory 310, a processor 320, and a network interface 330 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 300 having components 310-330, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0163] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0164] The memory 310 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disk, optical disk, etc. In some embodiments, the memory 310 may be an internal storage unit of the computer device 300, such as a hard disk or memory of the computer device 300. In other embodiments, the memory 310 may also be an external storage device of the computer device 300, such as a plug-in hard disk equipped on the computer device 300, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 310 may also include both the internal storage unit of the computer device 300 and its external storage device. In the embodiment of the present application, the memory 310 is typically used to store an operating system and various application software installed on the computer device 300, such as computer-readable instructions for a performance appraisal method based on the Basic Law Indicator Center. Furthermore, the memory 310 can also be used to temporarily store various data that has been output or is about to be output.

[0165] In some embodiments, the processor 320 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 320 is generally used to control the overall operation of the computer device 300. In the embodiment of the present application, the processor 320 is used to execute computer-readable instructions or process data stored in the memory 310, such as computer-readable instructions for executing the performance evaluation method based on the Basic Law Indicator Center.

[0166] The network interface 330 may include a wireless network interface or a wired network interface. The network interface 330 is generally used to establish a communication connection between the computer device 300 and other electronic devices.

[0167] The computer equipment provided in this application realizes accurate, comprehensive and efficient evaluation of agent performance through technical means such as precise data collection, comprehensive indicator construction, efficient calculation and processing, and flexible configuration adjustment, providing strong support for the company's performance appraisal management.

[0168] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the performance appraisal method based on the Basic Law indicator center as described above.

[0169] The computer-readable storage medium provided in this application realizes accurate, comprehensive and efficient evaluation of agent performance through technical means such as precise data collection, comprehensive indicator construction, efficient computing and processing, and flexible configuration adjustment, providing strong support for the performance appraisal management of enterprises.

[0170] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0171] Obviously, the embodiments described above are only some of the embodiments of the present application, rather than all of the embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned specific embodiments, or to make equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the present application specification and the accompanying drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present application.

Claims

1. A performance evaluation method based on the basic law indicator center, characterized by: The steps include: receiving a verification request sent by a user terminal, wherein the verification request carries identification information of an agent to be verified; Reading the insurance policy system and obtaining agent commission data corresponding to the agent identification information in the insurance policy system; constructing basic indicator data based on the agent commission data; Process the basic indicator data according to the pre-configured personnel structure information and hierarchical aggregation algorithm to obtain the indicators of the directly subordinate teams and the indicators of the teams in preparation; Calculate the assessment period data of each agent in each assessment scenario according to the preset assessment scenario rules, the indicators of the direct subordinate team, the indicators of the team in preparation, and the time window algorithm, and associate the assessment period data with the comprehensive indicator data to obtain a comprehensive data set; Slicing the comprehensive data set according to the assessment period data to obtain a sliced ​​comprehensive data set; Calculate the indicator values ​​of each person and each team in each assessment period of the sliced ​​comprehensive data set according to a multi-dimensional summary algorithm to obtain summary result data; The index values ​​of the summary result data are calculated and converted according to the assessment standards and the rule engine to obtain the assessment result data.

2. The performance evaluation method based on the basic law indicator center according to claim 1 is characterized in that: After the step of reading the insurance policy system and obtaining the agent commission data corresponding to the agent identification information in the insurance policy system, the following steps are also included: Performing data cleaning and conversion operations on the agent commission data to obtain structured commission data; The step of constructing basic indicator data based on the agent commission data specifically includes the following steps: Basic indicator data is constructed based on the structured commission data.

3. The performance evaluation method based on the basic law indicator center according to claim 1 is characterized in that: The step of constructing basic indicator data based on the agent commission data specifically includes the following steps: Calling the personnel system interface and obtaining monthly personnel basic data from the personnel system interface; The agent commission data and the monthly personnel basic data are associated with each other according to a data association algorithm to obtain the basic indicator data.

4. The performance evaluation method based on the basic law indicator center according to claim 3 is characterized in that: After the steps of calling the personnel system interface and obtaining monthly personnel basic data from the personnel system interface, the following steps are also included: The monthly basic personnel data is verified and completed to obtain complete monthly basic personnel data.

5. The performance evaluation method based on the basic law indicator center according to claim 1 is characterized in that: After the step of performing calculation and conversion operations on the index values ​​of the summary result data according to the assessment standards and the rule engine to obtain the assessment result data, the following steps are also included: Read the system database and obtain the assessment results of the previous month in the system database; performing an abnormality identification operation on the assessment result data according to the assessment result of the previous month to obtain an abnormality identification result; The assessment result data is marked according to the abnormality identification result.

6. The performance evaluation method based on the basic law indicator center according to claim 4 is characterized in that: After the step of performing calculation and conversion operations on the index values ​​of the summary result data according to the assessment standards and the rule engine to obtain the assessment result data, the following steps are also included: The agent commission data and the monthly personnel basic data are synchronized to the indicator center in real time based on DTS synchronization technology.

7. A performance evaluation device based on the basic law indicator center, characterized in that: include: a request receiving module, configured to receive a verification request sent by a user terminal, wherein the verification request carries identification information of an agent to be verified; a commission data acquisition module, configured to read the insurance policy system and acquire agent commission data corresponding to the agent identification information in the insurance policy system; A basic indicator construction module, configured to construct basic indicator data based on the agent commission data; An indicator processing module is used to process the basic indicator data according to pre-configured personnel structure information and hierarchical aggregation algorithm to obtain indicators of directly subordinate teams and indicators of teams in preparation; A comprehensive data acquisition module is used to calculate the assessment period data of each agent in each assessment scenario based on the preset assessment scenario rules, the indicators of the direct subordinate team, the indicators of the team in preparation, and the time window algorithm, and associate the assessment period data with the comprehensive indicator data to obtain a comprehensive data set; A data slicing module, configured to slice the comprehensive data set according to the assessment period data to obtain a sliced ​​comprehensive data set; An indicator value calculation module is used to calculate the indicator value of each person and each team in the sliced ​​comprehensive data set in each assessment period according to a multi-dimensional summary algorithm to obtain summary result data; The indicator value calculation and conversion module is used to perform calculation and conversion operations on the indicator values ​​of the summary result data according to the assessment standards and the rule engine to obtain the assessment result data.

8. The performance evaluation device based on the basic law indicator center according to claim 7 is characterized in that: The device includes: a data cleaning and conversion module, and the basic indicator construction module includes: a basic indicator construction submodule, wherein: The data cleaning and conversion module is used to perform data cleaning and conversion operations on the agent commission data to obtain structured commission data; The basic indicator construction submodule is used to construct basic indicator data based on the structured commission data.

9. A computer device comprising a memory and a processor, characterized in that: The memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, the steps of the performance appraisal method based on the Basic Law indicator center as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the performance appraisal method based on the Basic Law indicator center as described in any one of claims 1 to 6.

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