Comprehensive assessment and evaluation system supporting complex index calculation

Abstract

The invention discloses a comprehensive assessment and evaluation system supporting complex index calculation, and relates to the technical field of assessment and evaluation systems.The comprehensive assessment and evaluation system is characterized in that an index calculation module obtains multiple related data from a system database, the multiple related data are substituted into an index analysis model for comprehensive analysis, and an index assignment is output for a user; the evaluation module performs performance evaluation on the users according to a comparison result of the index assignment and the range critical value, the grading module performs grading processing on all the users according to the evaluation result, and generates a plurality of grading lists in each grade according to the index assignment of the users, and the reporting module obtains the grading lists and reports the grading lists to the evaluation module. A personalized feedback report is automatically generated, and a decision making module automatically generates decisions for users in each grading list, including a reward mechanism, a training plan and a promotion opportunity. The evaluation system can automatically obtain multiple indexes of the user, automatically analyze and evaluate the user performance based on the index analysis model, and improve the accuracy of user assessment and evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of assessment systems, and particularly relates to a comprehensive assessment system that supports complex index calculations. Background Art

[0002] An assessment system is a tool used to evaluate and review the performance of individuals, organizations, or projects. The system aims to comprehensively and objectively measure the performance of the object being evaluated on specific tasks or goals, in order to provide detailed information about their work performance. Such systems are commonly widely used in organizations, educational institutions, government departments, and other fields to ensure that the work of individuals or teams meets the expected goals and provides a basis for further improvement.

[0003] The prior art has the following defects:

[0004] Existing evaluation systems only assess users manually through a single indicator. The analysis of single-indicator assessment is not comprehensive, and manual assessment is highly subjective, thus reducing the accuracy of user assessment. Summary of the Invention

[0005] The purpose of the present invention is to provide a comprehensive assessment system that supports complex index calculations to address the deficiencies in the background art.

[0006] To achieve the above purpose, the present invention provides the following technical solution: A comprehensive assessment system that supports complex index calculations, including a goal-setting module, a data collection module, an index calculation module, an evaluation module, a grading module, a reporting module, a decision-making module, and an early warning module;

[0007] Goal-setting module: Used to set the goals and tasks of users within a specified time range. Users include individuals, teams, or organizations;

[0008] Data collection module: According to the set user goals and tasks, collect relevant data from multiple data sources, including performance data, project progress, and quality indicators, and automatically store the data in the system database;

[0009] Index calculation module: Obtain multiple relevant data from the system database, substitute the multiple relevant data into the index analysis model for comprehensive analysis, and output an index value for the user;

[0010] Evaluation module: Conduct performance evaluation on users based on the comparison result between the index value and the range threshold;

[0011] Grading module: Classify all users according to the evaluation results, and within each level, sort the users according to their index values to generate multiple grading lists;

[0012] Reporting module: After obtaining multiple graded lists, it automatically generates personalized feedback reports to provide performance information;

[0013] Decision-making module: automatically generates decisions for each user in the hierarchical list, including reward mechanisms, training plans, and promotion opportunities;

[0014] Early warning module: When user performance is found to have obvious fluctuations, an early warning will be issued in time to remind relevant personnel to pay attention and take measures.

[0015] Preferably, the data acquisition module establishes connections with various data sources according to the goals and tasks set by the user, extracts data that meets the set conditions from the data source, executes data extraction operations according to the set plan and conditions, obtains data that meets the requirements, cleans, converts the format, and deduplicates the collected data, runs verification algorithms, checks whether the collected data meets the predetermined accuracy and completeness standards, and securely stores the collected data in the system database.

[0016] Preferably, the indicator calculation module obtains a plurality of relevant data from a system database, the plurality of relevant data including performance index, project progress and quality amplitude;

[0017] The performance index, project progress and quality amplitude are substituted into the indicator analysis model for analysis, and the indicator analysis model outputs the indicator assignment after analysis.

[0018] Preferably, the function expression of the indicator analysis model is:

[0019] ,

[0020] In the formula, zf b Assign values ​​to indicators, yjz, xmd, are the performance index, project progress and quality amplitude respectively, α, β and γ are the proportional coefficients of performance index, project progress and quality amplitude respectively, X n represents the stable running time produced by the nth user, Y n represents the total running time of the nth user, m represents the number of users, and α, β, and γ are all greater than 0.

[0021] Preferably, the calculation expression of the performance index is: yjz=wrs / zrs, where wrs is the number of tasks completed by the user, and zrs is the total number of tasks;

[0022] The calculation expression for project progress is: xmd=wcj / zjd, where wcj is the number of completed stages of the user project and zjd is the total number of stages.

[0023] Preferably, after the evaluation module obtains the index assignment, it compares the index assignment with preset range critical values, where the range critical values include a first threshold and a second threshold. The first threshold is used to distinguish whether the user's assessment is up to standard, and the second threshold is used to distinguish the degree of the user's assessment being up to standard;

[0024] If the index assignment is less than the first threshold, it is analyzed that the user's assessment is not up to standard;

[0025] If the index assignment is greater than or equal to the first threshold, it is analyzed that the user's assessment is up to standard;

[0026] If the index assignment is greater than or equal to the first threshold and less than the second threshold, it is analyzed that the user's assessment is of medium level;

[0027] If the index assignment is greater than or equal to the second threshold, it is analyzed that the user's assessment is excellent.

[0028] Preferably, the grading module analyzes the evaluation results of multiple users;

[0029] If the evaluation result of a user is that the assessment is not up to standard, the user is classified into the poor set. If the evaluation result of a user is that the assessment is of medium level, the user is classified into the medium set. If the evaluation result of a user is that the assessment is excellent, the user is classified into the excellent set;

[0030] In the poor set, all users are sorted in descending order according to the index assignment to generate a poor set list. In the medium set, all users are sorted in descending order according to the index assignment to generate a medium set list. In the excellent set, all users are sorted in descending order according to the index assignment to generate an excellent set list.

[0031] Preferably, the warning module obtains the index assignments of users in the poor set list, the medium set list, and the excellent set list, compares the user's current period index assignment with the previous period index assignment, obtains the fluctuation value by subtracting the current period index assignment from the previous period index assignment. If the fluctuation value is greater than the preset fluctuation threshold, it is analyzed that the user's performance fluctuates significantly and a warning signal is issued.

[0032] In the above technical solution, the technical effects and advantages provided by the present invention:

[0033] 1. The present invention collects relevant data from multiple data sources by means of a data collection module according to the set user goals and tasks. The index calculation module obtains multiple relevant data from the system database, substitutes the multiple relevant data into an index analysis model for comprehensive analysis, and outputs an index assignment for the user. The evaluation module conducts a performance evaluation of the user based on the comparison result between the index assignment and the range threshold value. The grading module classifies all users according to the evaluation results, and within each level, sorts the users according to their index assignments to generate multiple grading lists. After obtaining the multiple grading lists, the report module automatically generates a personalized feedback report to provide performance information. The decision-making module automatically generates decisions for the users in each grading list, including reward mechanisms, training plans, and promotion opportunities. This evaluation system can automatically obtain multiple indicators of users and automatically analyze and evaluate user performance based on the index analysis model, improving the accuracy of user assessment and evaluation;

[0034] 2. The present invention obtains multiple relevant data from the system database. The multiple relevant data includes performance indexes, project progress, and quality amplitudes. The performance indexes, project progress, and quality amplitudes are substituted into the index analysis model for analysis. After analysis by the index analysis model, an index assignment is output, so as to comprehensively analyze whether the comprehensive indexes of the user meet the requirements, with high analysis accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0036] Figure 1 It is a system module diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0038] Embodiment: Please refer to Figure 1 As shown, the comprehensive assessment and evaluation system for supporting complex index calculations in this embodiment includes a target setting module, a data collection module, an index calculation module, an evaluation module, a grading module, a report module, a decision-making module, and an early warning module;

[0039] Goal Setting Module: Used to set goals and tasks for users within a specified time range. Users include individuals, teams, or organizations to ensure that the set goals can be accurately measured and tracked.

[0040] User Authentication:

[0041] Purpose: To confirm the user's identity and ensure that only authorized personnel can set goals.

[0042] Steps: The user logs in to the system and undergoes authentication, possibly through methods such as username, password, two-factor authentication, etc.

[0043] Select Goal Type:

[0044] Purpose: To define the types of goals, which may involve individual career development, team performance, organizational strategic goals, etc.

[0045] Steps: The user selects a goal category that suits their needs from the predefined goal types.

[0046] Set Specific Goals:

[0047] Purpose: The user clarifies the specific goals to be achieved within the specified time range.

[0048] Steps: Provide the user with an interface to input or select specific goals, which may include quantitative metrics, key performance indicators (KPIs), deadlines, etc.

[0049] Formulate Tasks and Steps:

[0050] Purpose: To break down the overall goal into more specific tasks and steps for better execution and tracking.

[0051] Steps: The user breaks down the goal into actionable tasks and steps and sets corresponding sub-goals, responsible persons, deadlines, etc. for each task.

[0052] Set Goal Weights and Priorities:

[0053] Purpose: To ensure that the system can more comprehensively evaluate the importance of goals for more accurate weighing.

[0054] Steps: The user assigns weights and priorities to each goal or task to guide the weighted calculation in the system's evaluation process.

[0055] Associate Goals with Key Performance Indicators:

[0056] Purpose: To ensure that goals are associated with key performance indicators (KPIs) for using relevant data in subsequent evaluations.

[0057] Steps: The user associates the set goals with relevant key performance indicators so that the system can use this information in the data collection and evaluation process.

[0058] Set monitoring frequency:

[0059] Purpose: To ensure that goals are continuously monitored and tracked within the set timeframe.

[0060] Steps: Users set the frequency of monitoring goals, which can be daily, weekly, monthly, etc. to ensure real-time understanding of progress.

[0061] Set up feedback mechanism:

[0062] Purpose: To provide users with timely feedback so that they can adjust goals or take action when necessary.

[0063] Steps: Users set the conditions under which the system will provide feedback to them, such as reaching a critical stage, failing to achieve the expected progress, etc.

[0064] Confirm goal setting:

[0065] Purpose: The user confirms all set objectives and related information to ensure accuracy and completeness.

[0066] Step 1: Provide users with a final confirmation interface to allow them to carefully review and confirm all the details of the goal setting.

[0067] To save and submit your goal settings:

[0068] Purpose: To save the goals set by the user into the system for subsequent evaluation and tracking.

[0069] Steps: Once the user saves or submits the goal setting, the system will save the information and monitor and evaluate it within the set time frame.

[0070] Data collection module: collects relevant data from multiple data sources, including performance data, project progress, quality indicators, etc., based on the set user goals and tasks, ensures that the collected data corresponds to the set goals, and automatically stores the data in the system database;

[0071] Determine the data source:

[0072] Purpose: Determine which data sources to obtain the necessary information from, which may include internal databases, external APIs, third-party services, etc.

[0073] Steps: Based on the goals and tasks set by the user, clarify which data sources need to be collected from.

[0074] To establish a data connection:

[0075] Objective: Establish connections with various data sources to effectively extract the required data.

[0076] Steps: Set the interfaces and connections between the data acquisition system and each data source to ensure the secure and efficient acquisition of data.

[0077] Formulate a data acquisition plan:

[0078] Objective: Formulate a clear plan, including acquisition frequency, time points, data formats, etc., to ensure the timely and accurate acquisition of data.

[0079] Steps: Set the data acquisition plan to determine when and how to acquire the required data.

[0080] Data extraction:

[0081] Objective: Extract data that meets the set conditions from the data source.

[0082] Steps: Execute the data extraction operation according to the set plan and conditions to obtain the required data.

[0083] Data transformation and cleaning:

[0084] Objective: Ensure that the acquired data meets the system requirements, and clean and transform the data to ensure consistency and accuracy.

[0085] Steps: Perform operations such as cleaning, format conversion, and duplicate removal on the acquired data to ensure the data quality.

[0086] Data verification:

[0087] Objective: Verify whether the acquired data is accurate, complete, and meets the expected data quality standards.

[0088] Steps: Run verification algorithms or rules to check whether the acquired data meets the predefined accuracy and integrity standards.

[0089] Data storage:

[0090] Objective: Securely store the acquired data in the system database for subsequent evaluation and analysis.

[0091] Steps: Store the cleaned and verified data in the system database to ensure data security and accessibility.

[0092] Set up an automated reminder and reporting mechanism:

[0093] Objective: Set up a reminder mechanism during the data acquisition process to ensure the timeliness of data acquisition, and generate reports to notify relevant personnel.

[0094] Steps: Set up automatic reminders during data collection, such as sending notifications to relevant personnel in case of anomalies or reaching critical stages.

[0095] Log recording:

[0096] Purpose: Record each step in the data collection process for future auditing and traceability.

[0097] Steps: Record detailed information for each data collection, including time, data source, collection status, etc.

[0098] Monitor data source changes:

[0099] Purpose: Detect and adapt to changes in the data source in a timely manner to ensure that the system continuously and accurately obtains data.

[0100] Steps: Implement a monitoring mechanism to regularly check whether the data source has changed and update the collection strategy when there are changes.

[0101] The indicator calculation module: Obtain multiple relevant data from the system database, substitute the multiple relevant data into the indicator analysis model for comprehensive analysis, and output an indicator assignment for the user. The indicator assignment is sent to the evaluation module, classification module, and warning module;

[0102] Obtain multiple relevant data from the system database. The multiple relevant data include performance index, project progress, and quality amplitude;

[0103] Substitute the performance index, project progress, and quality amplitude into the indicator analysis model for analysis, and the indicator analysis model outputs an indicator assignment after analysis.

[0104] The functional expression of the said indicator analysis model is:

[0105] ,

[0106] In the formula, zf b is the indicator assignment, yjz, xmd, are the performance index, project progress, and quality amplitude respectively, α, β, γ are the proportionality coefficients of the performance index, project progress, and quality amplitude respectively, X n represents the stable operation duration of the nth user's production, Y n represents the total operation duration of the nth user, m represents the number of users, and α, β, γ are all greater than 0.

[0107] This application obtains multiple relevant data from the system database. The multiple relevant data includes performance indices, project progress, and quality amplitudes. The performance indices, project progress, and quality amplitudes are substituted into the index analysis model for analysis. After the index analysis model analyzes, it outputs index assignments, thereby comprehensively analyzing whether the user's comprehensive index meets the requirements, with high analysis accuracy.

[0108] The calculation expression for the performance index is: yjz = wrs / zrs, where wrs is the number of tasks completed by the user and zrs is the total number of tasks.

[0109] The larger the user's performance index, the better the user's performance, that is, the higher the assessment and evaluation of the user. Specifically:

[0110] Achieving business goals: Excellent performance usually means that the user can successfully achieve the set business goals. This may include sales growth, market share increase, profit maximization, etc. The user's outstanding performance in achieving these goals will receive positive evaluations.

[0111] Improving customer satisfaction: The improvement of performance is usually positively correlated with customer satisfaction. The products or services provided by the user can meet customer needs and improve customer satisfaction, thus having a positive impact on the assessment and evaluation of the user.

[0112] Innovation and competitiveness: Excellent performance may reflect the user's innovation ability and competitiveness in the market. By introducing new products, services, or business models, the user can better respond to market changes, enhance the enterprise's competitive position, which has a positive impact on the assessment and evaluation of the user.

[0113] Financial health: Good performance is usually accompanied by an improvement in financial health. The user can effectively manage financial resources, achieve profitability, and maintain a sound financial position, which is an important consideration for the user's performance.

[0114] Team collaboration and leadership: The improvement of performance often requires team collaboration and effective leadership. The user can stimulate the potential of the team, coordinate the work of various departments, and demonstrate excellent leadership skills, which will help improve the assessment and evaluation of the user.

[0115] Social responsibility and sustainable development: Excellent performance may also be related to the user's efforts in social responsibility and sustainable development. Actively fulfilling social responsibilities and paying attention to environmental and social issues can enhance the enterprise's reputation and have a positive impact on the assessment and evaluation of the user.

[0116] The calculation expression for the project progress is: xmd = wcj / zjd, where wcj is the number of project completion stages of the user and zjd is the total number of stages.

[0117] The greater the project progress of the user, the faster the project progress of the user, that is, the higher the assessment and evaluation of the user. Specifically:

[0118] Goal achievement and delivery: Rapid project progress means that the user is more likely to achieve project goals and deliver results on time. This is crucial for business success and customer satisfaction, thus having a positive impact on the assessment and evaluation of the user.

[0119] Improved productivity: Rapid project progress usually indicates that the user's team and processes are efficient. The user can quickly respond to challenges, solve problems, and drive the project forward, which helps improve overall productivity and has a positive impact on the assessment and evaluation of the user.

[0120] Customer satisfaction: If the project involves customers, rapid project progress usually improves customer satisfaction. Timely delivery of products or services can meet customer needs and enhance customer trust, having a positive impact on the assessment and evaluation of the user.

[0121] Competitive advantage: Rapidly advancing projects in the market can provide a competitive advantage. The user can bring new products, services, or features to the market faster, taking the lead, thus having a positive impact on the assessment and evaluation of the user.

[0122] Team collaboration and leadership: Rapid project progress usually requires efficient team collaboration and leadership. The user can successfully inspire the team's cooperation spirit and effectively lead the project, which will help improve the assessment and evaluation of the user.

[0123] Responding to market changes: Rapid project progress enables the user to be more flexible in responding to market changes. The user can timely adjust strategies, products, or services to adapt to changing market demands, having a positive impact on the assessment and evaluation of the user.

[0124] Enhancing corporate reputation: Efficient project management and rapid project progress contribute to enhancing the corporate reputation. The user is regarded as an organization that can execute efficiently and deliver results, having a positive impact on the assessment and evaluation of the user.

[0125] The greater the quality amplitude of the user, the higher the product qualification rate of the user, that is, the higher the assessment and evaluation of the user. Specifically:

[0126] Compliance with quality standards: Achieving a high qualification rate usually means that the product meets quality standards and meets customer expectations. This indicates that the user can maintain a consistent quality level during production and delivery, which is very important for the assessment and evaluation of the user.

[0127] Customer satisfaction improvement: High product qualification rates are usually directly related to customer satisfaction. Products provided to users that meet or exceed the expected quality level will help establish and maintain good customer relationships and improve the user's performance evaluation.

[0128] Production efficiency and cost control: Achieving a high qualification rate may indicate the stability and efficiency of the production process. Reducing the rate of defective and waste products helps control costs and improve production efficiency, which has a positive impact on the user's performance evaluation.

[0129] Brand reputation enhancement: A high product qualification rate helps enhance the enterprise's brand reputation. Establishing a good quality image in the market can attract more customers and promote business growth, which is also a positive factor for the user's performance evaluation.

[0130] Compliance with regulations and standards: Achieving a high qualification rate may mean that the enterprise can comply with relevant regulations and industry standards. This is crucial for establishing a sustainable corporate image and competitiveness in the market, and also provides strong support for the user's performance evaluation.

[0131] Evaluation module: Perform a performance evaluation of users based on the comparison result between the indicator assignment and the range threshold value, and send the evaluation result to the grading module;

[0132] After obtaining the indicator assignment, compare the indicator assignment with the preset range threshold value. The range threshold value includes a first threshold and a second threshold. The first threshold is used to distinguish whether the user's performance evaluation meets the standard, and the second threshold is used to distinguish the degree of the user's performance meeting the standard;

[0133] If the indicator assignment is less than the first threshold, analyze that the user's performance evaluation does not meet the standard;

[0134] If the indicator assignment is greater than or equal to the first threshold, analyze that the user's performance evaluation meets the standard;

[0135] If the indicator assignment is greater than or equal to the first threshold and less than the second threshold, analyze that the user's performance evaluation meets the standard to a medium degree;

[0136] If the indicator assignment is greater than or equal to the second threshold, analyze that the user's performance evaluation meets the standard to an excellent degree.

[0137] Grading module: Classify all users according to the evaluation result, and within each level, sort the users according to their indicator assignments to generate multiple grading lists, and send the grading lists to the report module and the decision-making module;

[0138] If the evaluation result of the user is that the performance evaluation does not meet the standard, classify the user into the poor set. If the evaluation result of the user is that the performance evaluation meets the standard to a medium degree, classify the user into the medium set. If the evaluation result of the user is that the performance evaluation meets the standard to an excellent degree, classify the user into the excellent set;

[0139] In the difference set, all users are sorted in descending order according to the metric assignment to generate a difference set list. In the medium set, all users are sorted in descending order according to the metric assignment to generate a medium set list. In the excellent set, all users are sorted in descending order according to the metric assignment to generate an excellent set list.

[0140] Report module: After obtaining multiple grading lists, it automatically generates a personalized feedback report, provides detailed information about performance, and possible improvement suggestions, ensuring that the generated feedback and report are based on actual data and evaluation results;

[0141] Data summarization and classification:

[0142] Steps: Summarize the performance data of users from multiple grading lists and classify them according to the difference set list, medium set list, excellent set list, etc. Ensure the accuracy and integrity of the data.

[0143] Report template design:

[0144] Steps: Design the template of the feedback report, including the report structure, layout, style, etc. Determine the key information included in the report, such as metrics, achievements, improvement suggestions, etc.

[0145] Extraction of detailed performance information:

[0146] Steps: Extract detailed information from the summarized performance data, including specific metrics, achievements, task completion status, etc. Ensure that this information can reflect the true performance level of users.

[0147] Difference analysis and evaluation:

[0148] Steps: Conduct a difference analysis of the performance of users in different set lists, identify the highlights and problems in performance. Make a comprehensive evaluation based on the analysis results.

[0149] Generation of improvement suggestions:

[0150] Steps: Automatically generate possible improvement suggestions based on the results of the difference analysis. These suggestions can cover aspects such as skills training, goal adjustment, team collaboration, etc., to help users improve their performance levels.

[0151] Generation of personalized feedback report:

[0152] Steps: Integrate the performance information, difference analysis results, and improvement suggestions into a personalized feedback report. Ensure that the report content is presented in a personalized manner according to the performance characteristics and needs of users.

[0153] Visualization display:

[0154] Steps: Use visualization tools such as charts and graphs to present performance data in the report. Visualization helps users understand their performance more intuitively.

[0155] Report review and verification:

[0156] Steps: Before generating the report, conduct review and verification to ensure the content of the report is accurate, clear, and complete. It can be reviewed by the system administrator or relevant evaluators.

[0157] Report sending and access:

[0158] Steps: Send the generated personalized feedback report to users to ensure that users can conveniently access and view their performance reports. This can be done through internal system messages, emails, etc.

[0159] Feedback and improvement suggestion tracking:

[0160] Steps: Track users' feedback on the report and the adoption of improvement suggestions. This helps evaluate the effectiveness of the report and make adjustments and improvements when necessary.

[0161] Decision-making module: Automatically generate decisions for users in each grading list, including reward mechanisms, training plans, promotion opportunities, etc., to ensure that decisions are based on actual data and evaluation results. Continuously optimize the decision-making strategy according to user feedback to improve the accuracy and efficiency of decisions;

[0162] Data preparation and analysis:

[0163] Steps: Obtain the performance data of users in each grading list and conduct in-depth data analysis. Understand the performance of each user in the poor, medium, and excellent groups, and identify the highlights and problems of performance.

[0164] Formulate decision-making criteria:

[0165] Steps: Based on performance data and business goals, formulate decision-making criteria for rewards, training, and promotions. Clearly define what constitutes excellent performance, medium performance, and poor performance, as well as the corresponding rewards and development opportunities for each performance level.

[0166] Reward mechanism design:

[0167] Steps: Design a reward mechanism according to the performance level and decision-making criteria. This may include salary adjustments, bonus payments, welfare benefits, etc. Ensure that the rewards match the actual performance.

[0168] Training plan formulation:

[0169] Steps: Identify the training and development opportunities required by employees with poor and medium performance. Develop personalized training plans to improve employees' abilities and skills.

[0170] Promotion Opportunity Planning:

[0171] Steps: For employees with excellent performance, plan promotion opportunities. Determine the promotion conditions and paths to motivate employees to pursue outstanding performance.

[0172] Decision Generation:

[0173] Steps: According to the established decision-making criteria and designed reward, training, and promotion mechanisms, automatically generate personalized decisions for each user. Ensure that the decisions are based on actual data and evaluation results.

[0174] Feedback and Optimization:

[0175] Steps: Collect employees' feedback on the generated decisions. According to the feedback information, continuously optimize the decision-making strategy to improve the accuracy of decisions and user satisfaction.

[0176] Implementation of Decisions:

[0177] Steps: Implement the generated decisions into actual human resource management. Ensure that the reward, training, and promotion mechanisms are effectively implemented.

[0178] Effect Monitoring:

[0179] Steps: Monitor the implementation effects of decisions, including the improvement of employees' performance, training results, promotion rates, etc. Adjust the decision-making strategy according to the monitoring results.

[0180] Cyclic Iteration:

[0181] Steps: Based on the actual effects and continuously collected data, continuously iterate and optimize the decision-making module. Ensure that the decision-making strategy is consistent with the development of the organization and the needs of employees.

[0182] Early Warning Module: When significant fluctuations in user performance are detected, it will promptly issue an early warning to alert relevant personnel to pay attention and take measures

[0183] Obtain the index assignments of users in the list of difference sets, medium sets, and excellent sets, compare the user's current period index assignment with the previous period index assignment, obtain the fluctuation value by subtracting the current period index assignment from the previous period index assignment. If the fluctuation value is greater than the preset fluctuation threshold, analyze that the user's performance has significantly fluctuated and issue an early warning signal.

[0184] This application uses a data collection module to collect relevant data from multiple data sources according to the set user goals and tasks. The index calculation module obtains multiple relevant data from the system database, substitutes the multiple relevant data into the index analysis model for comprehensive analysis, and outputs an index assignment for the user. The evaluation module conducts a performance evaluation of the user based on the comparison result between the index assignment and the range threshold value. The grading module classifies all users according to the evaluation results and sorts the users according to their index assignments within each level, generating multiple grading lists. After obtaining the multiple grading lists, the report module automatically generates a personalized feedback report to provide performance information. The decision-making module automatically generates decisions for the users in each grading list, including reward mechanisms, training plans, and promotion opportunities. This evaluation system can automatically obtain multiple indicators of users and automatically analyze and evaluate user performance based on the index analysis model, improving the accuracy of user assessment and evaluation.

[0185] The above formulas are all dimensionless and take their numerical calculations. The formulas are obtained by collecting a large amount of data for software simulation to obtain a formula that is closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0186] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0187] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not elaborate on all the details and do not limit the present invention to only the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the present invention, so that those skilled in the art in the relevant technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A comprehensive assessment and evaluation system supporting the calculation of complex indicators, characterized by: It includes target setting module, data collection module, indicator calculation module, evaluation module, grading module, reporting module, decision-making module and early warning module; Goal Setting Module: used to set goals and tasks for users within a specified time frame. Users include individuals, teams or organizations; Data collection module: collects relevant data from multiple data sources, including performance data, project progress, and quality indicators, based on the set user goals and tasks, and automatically stores the data in the system database; Index calculation module: obtains multiple related data from the system database, substitutes multiple related data into the index analysis model for comprehensive analysis, and outputs an index value for the user; Evaluation module: evaluate the user's performance based on the comparison between the indicator value and the range critical value; Grading module: All users are graded according to the evaluation results, and in each level, users are sorted according to their indicator values ​​to generate multiple graded lists; Reporting module: After obtaining multiple graded lists, it automatically generates personalized feedback reports to provide performance information; Decision-making module: automatically generates decisions for each user in the hierarchical list, including reward mechanisms, training plans, and promotion opportunities; Early warning module: When user performance is found to have obvious fluctuations, an early warning will be issued in time to remind relevant personnel to pay attention and take measures.

2. A comprehensive assessment and evaluation system supporting complex indicator calculation according to claim 1, characterized in that: The data acquisition module establishes connections with various data sources according to the goals and tasks set by the user, extracts data that meets the set conditions from the data source, executes data extraction operations according to the set plan and conditions, obtains data that meets the requirements, cleans, converts the format, and deduplicates the collected data, runs verification algorithms, checks whether the collected data meets the predetermined accuracy and completeness standards, and securely stores the collected data in the system database.

3. A comprehensive assessment and evaluation system supporting complex index calculation according to claim 2, characterized in that: The indicator calculation module obtains a plurality of relevant data from the system database, wherein the plurality of relevant data includes performance index, project progress and quality amplitude; The performance index, project progress and quality amplitude are substituted into the indicator analysis model for analysis, and the indicator analysis model outputs the indicator assignment after analysis.

4. A comprehensive assessment and evaluation system supporting complex index calculation according to claim 3, characterized in that: The functional expression of the indicator analysis model is: ， In the formula, zf b Assign values ​​to indicators, yjz, xmd, are the performance index, project progress and quality amplitude respectively, α, β and γ are the proportional coefficients of performance index, project progress and quality amplitude respectively, X n represents the stable running time produced by the nth user, Y n represents the total running time of the nth user, m represents the number of users, and α, β, and γ are all greater than 0.

5. A comprehensive assessment and evaluation system supporting complex index calculation according to claim 4, characterized in that: The calculation expression of the performance index is: yjz = wrs / zrs, where wrs is the number of tasks completed by the user and zrs is the total number of tasks; The calculation expression for project progress is: xmd=wcj / zjd, where wcj is the number of completed stages of the user project and zjd is the total number of stages.

6. A comprehensive assessment and evaluation system supporting complex index calculation according to claim 5, characterized in that: After obtaining the indicator value, the evaluation module compares the indicator value with a preset range critical value, where the range critical value includes a first threshold value and a second threshold value, the first threshold value is used to distinguish whether the user's assessment evaluation meets the standard, and the second threshold value is used to distinguish the degree to which the user's assessment meets the standard; If the indicator value is less than the first threshold, the user's assessment evaluation is not up to standard; If the indicator value is greater than or equal to the first threshold, the user's assessment evaluation is analyzed to be up to standard; If the indicator value is greater than or equal to the first threshold, and the indicator value is less than the second threshold, the user's assessment and evaluation level is medium; If the indicator value is greater than or equal to the second threshold, the user's assessment and evaluation standard compliance is analyzed to be excellent.

7. A comprehensive assessment and evaluation system supporting complex index calculation according to claim 6, characterized in that: Analyzing the evaluation results of multiple users of the grading module; If the user's evaluation result is that the assessment evaluation is not up to standard, the user is divided into the poor set; if the user's evaluation result is that the assessment evaluation is of medium standard, the user is divided into the medium set; if the user's evaluation result is that the assessment evaluation is of excellent standard, the user is divided into the excellent set; In the poor set, all users are sorted from large to small according to the indicator assignment to generate a poor set list. In the medium set, all users are sorted from large to small according to the indicator assignment to generate a medium set list. In the excellent set, all users are sorted from large to small according to the indicator assignment to generate an excellent set list.

8. A comprehensive assessment and evaluation system supporting complex index calculation according to claim 7, characterized in that: The early warning module obtains the indicator values ​​of users in the poor set list, the medium set list, and the excellent set list, compares the user's current indicator value with the previous indicator value, and obtains the fluctuation value by subtracting the current indicator value from the previous indicator value. If the fluctuation value is greater than a preset fluctuation threshold, it is analyzed that the user's performance fluctuates significantly and a warning signal is issued.

Images