Employee work performance level determination method and device, electronic equipment and storage medium

Abstract

The invention provides a method and device for determining the work performance level of an employee, electronic equipment and a storage medium, and the method comprises the steps: carrying out the data processing of the core business work data of each month of the employee, and determining the core task performance index value of each month of the employee; performing core business score calculation based on a predetermined target performance score proportion of a department where the employee is located and the core task performance index value, and determining a core business score of the employee in each month; performing score calculation on the basic work business data of the employees in each month, determining basic business scores of the employees in each month, adding the basic business scores and the core business scores in the same month, and determining monthly performance scores of the employees; and performing performance grade evaluation on the performance scores of the employees in multiple months based on a normal distribution function, and determining the work performance grades of the employees. The influence of subjective judgment on the evaluation result is reduced, the fairness and accuracy of performance evaluation are ensured, and the evaluation efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of human resource management, and in particular to a method, device, electronic device and storage medium for determining an employee's work performance level. Background Art

[0002] The point-based performance management method is a performance management method that quantifies employees' work contributions and work performance in the form of points. This method converts employees' work results into specific point values ​​by setting a series of quantifiable performance indicators, thereby achieving quantitative evaluation and management of employee performance. Point-based performance management also relies on a sound performance management system and process. Enterprises need to establish a complete performance management system, clarify the standards, methods and processes of performance evaluation, and ensure the standardization and fairness of performance management. At the same time, enterprises also need to establish corresponding incentive mechanisms to link performance points with employee benefits such as salary, promotion, and training to stimulate employees' work enthusiasm and creativity. However, the point-based performance has the following problems: the performance level cannot be determined in advance within the performance appraisal cycle. This feature results in the inability to directly map the current accumulated points to specific levels for colleagues whose performance does not meet expectations, thereby hindering the possibility of timely identification and taking remedial measures. Therefore, how to accurately evaluate the performance level has become a technical issue that cannot be underestimated. Summary of the invention

[0003] In view of this, the purpose of this application is to provide a method, device, electronic device and storage medium for determining an employee's work performance level, which reduces the impact of subjective judgment on the evaluation results through clear evaluation standards and quantitative indicators, ensures the fairness and accuracy of performance evaluation, reduces tedious manual operations, and improves evaluation efficiency.

[0004] The present invention provides a method for determining an employee's work performance level, and the method for determining an employee's work performance level includes:

[0005] Process the core business work data of employees each month to determine the core task performance index value of the employees each month; wherein the core task performance index includes work timeliness rate, work task volume, work speed and work quality;

[0006] Calculate the core business score based on the predetermined target performance score ratio of the employee's department and the core task performance index value to determine the employee's core business score for each month;

[0007] Calculate the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, and add the basic business score and the core business score in the same month to determine the monthly performance score of the employee;

[0008] The performance level of the employee's multiple monthly performance scores is evaluated based on a normal distribution function to determine the employee's work performance level.

[0009] In a possible implementation manner, the target performance score ratio of the department to which the employee belongs is determined by the following steps:

[0010] Obtain the historical core task performance indicator values ​​and historical core business scores of the department;

[0011] Inputting the historical core task performance index value into an initial multiple regression linear model, taking different performance score ratios of the historical core task performance index value as independent variables, and taking the historical core business score as a dependent variable to train the initial multiple regression linear model, so that the initial multiple regression linear model predicts the predicted performance score ratio corresponding to the historical core task performance index value;

[0012] Iteratively adjusting the parameters of the initial multiple regression linear model based on the loss value between the sample core business score corresponding to the predicted performance score ratio and the historical core business score to determine the multiple regression linear model;

[0013] The core task performance index value of the employee's department is input into the multivariate regression linear model, and the target performance score ratio is output.

[0014] In a possible implementation manner, the core business score is calculated based on the predetermined target performance score ratio of the employee's department and the core task performance indicator value to determine the employee's core business score for each month, including:

[0015] If the work timeliness rate is 100%, the score corresponding to the work timeliness rate is the first performance score in the performance score ratio; if the work timeliness rate is less than 100%, the score corresponding to the work timeliness rate is 0;

[0016] Detecting whether the workload reaches the standard workload, and if so, the score corresponding to the workload is the second performance score in the performance score ratio;

[0017] Detecting whether the work speed reaches a preset ratio of the average work speed of the department in that month, and if so, the score corresponding to the work speed is the third performance score in the performance score ratio;

[0018] If the work quality is 100%, the score corresponding to the work quality is the fourth performance score in the performance score ratio;

[0019] The score corresponding to the work timeliness rate, the score corresponding to the workload, the score corresponding to the work speed, and the score corresponding to the work quality are added together to determine the core business score value of the employee.

[0020] In a possible implementation manner, after detecting whether the workload has reached the standard workload, the work performance level determination method further includes:

[0021] If not, the score corresponding to the workload is determined based on the product of the ratio of the workload to the standard workload and the second performance score.

[0022] In a possible implementation manner, the step of calculating a score of the basic work business data of the employee each month to determine the basic business score of the employee each month includes:

[0023] Performing ratio processing on the time consumption and the daily working hours in the basic work business data to determine a first ratio;

[0024] Performing ratio processing on the second performance score in the performance score ratio and the number of working days in the basic work business data to determine a second ratio;

[0025] The basic business score is determined based on the product of the first ratio and the second ratio.

[0026] In a possible implementation manner, the quarterly performance rating of the employee's multiple performance scores is performed based on a normal distribution function to determine the employee's work performance level, including:

[0027] Calculate the mean and standard deviation of each employee's multiple monthly performance scores to determine the average score and standard deviation;

[0028] Performing performance level classification based on the normal distribution function, the average score and the standard deviation;

[0029] The work performance level of the employee is determined by performing matching processing based on the score intervals corresponding to the divided performance levels and the multiple monthly performance scores of the employee.

[0030] The embodiment of the present application also provides a device for determining an employee's work performance level, the device comprising:

[0031] The performance indicator value determination module is used to process the core business work data of employees every month to determine the core task performance indicator value of the employees every month; wherein the core task performance indicators include work timeliness rate, work task volume, work speed and work quality;

[0032] A core business score calculation module, used to calculate the core business score based on the predetermined target performance score ratio of the employee's department and the core task performance index value, and determine the employee's core business score for each month;

[0033] A basic business score calculation module is used to calculate the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, and to add the basic business score and the core business score in the same month to determine the monthly performance score of the employee;

[0034] The performance evaluation module is used to evaluate the performance level of the employee's multiple monthly performance scores based on a normal distribution function to determine the employee's work performance level.

[0035] In a possible implementation, the work performance level determination device further includes a performance score ratio determination module, and the performance score ratio determination module 350 determines the target performance score ratio of the department to which the employee belongs through the following steps:

[0036] Obtain historical core mission performance indicator values ​​for the department;

[0037] Inputting the historical core task performance index value into an initial multiple regression linear model, taking different performance score ratios of the historical core task performance index value as independent variables, and taking the historical core business score corresponding to the historical core task performance index value as dependent variables to train the initial multiple regression linear model, so that the initial multiple regression linear model predicts the predicted performance score ratio corresponding to the historical core task performance index value;

[0038] Iteratively adjusting the parameters of the initial multiple regression linear model based on the loss value between the sample core business score corresponding to the predicted performance score ratio and the historical core business score to determine the multiple regression linear model;

[0039] The core task performance index value of the employee's department is input into the multivariate regression linear model, and the target performance score ratio is output.

[0040] An embodiment of the present application also provides an electronic device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the method for determining the work performance level of an employee as described above are performed.

[0041] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for determining the work performance level of an employee as described above are executed.

[0042] The embodiment of the present application provides a method, device, electronic device and storage medium for determining the work performance level of an employee, the method for determining the work performance level includes: processing the core business work data of the employee each month to determine the core task performance index value of the employee each month; wherein the core task performance index includes work timeliness, work task volume, work speed and work quality; calculating the core business score based on the predetermined target performance score ratio of the department where the employee is located and the core task performance index value to determine the core business score of the employee each month; calculating the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, adding the basic business score and the core business score in the same month to determine the monthly performance score of the employee; and evaluating the performance level of the multiple monthly performance scores of the employee based on the normal distribution function to determine the work performance level of the employee. Through clear evaluation criteria and quantitative indicators, the influence of subjective judgment on the evaluation results is reduced, the fairness and accuracy of performance evaluation are ensured, cumbersome manual operations are reduced, and evaluation efficiency is improved.

[0043] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 A flowchart of a method for determining an employee's work performance level provided in an embodiment of the present application;

[0046] Figure 2A schematic diagram of the training of the multivariate regression linear model provided in the embodiment of the present application;

[0047] Figure 3 One of the structural schematic diagrams of a device for determining the work performance level of an employee provided in an embodiment of the present application;

[0048] Figure 4 A second structural diagram of a device for determining an employee's work performance level provided in an embodiment of the present application;

[0049] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0051] First, the application scenarios to which this application is applicable are introduced. This application can be applied in the field of human resource management technology.

[0052] According to research, the point-based performance management method is a performance management method that quantifies employees' work contributions and work performance in the form of points. This method converts employees' work results into specific points by setting a series of quantifiable performance indicators, thereby achieving quantitative evaluation and management of employee performance. Point-based performance management also relies on a sound performance management system and process. Enterprises need to establish a complete performance management system, clarify the standards, methods and processes of performance evaluation, and ensure the standardization and fairness of performance management. At the same time, enterprises also need to establish corresponding incentive mechanisms to link performance points with employees' benefits such as salary, promotion, and training to stimulate employees' work enthusiasm and creativity. However, the point-based performance has the following problems: the performance level cannot be determined in advance within the performance appraisal cycle. This feature results in the inability to directly map the current accumulated scores to specific levels for colleagues whose performance does not meet expectations, thereby hindering the possibility of timely identification and taking remedial measures. Therefore, how to accurately evaluate the performance level has become a technical issue that cannot be underestimated.

[0053] Based on this, the embodiment of the present application provides a method for determining an employee's work performance level. Through clear evaluation criteria and quantitative indicators, it reduces the impact of subjective judgment on the evaluation results, ensures the fairness and accuracy of performance evaluation, reduces tedious manual operations, and improves evaluation efficiency.

[0054] See also Figure 1 , Figure 1 This is a flow chart of a method for determining an employee's work performance level provided in an embodiment of the present application. Figure 1 As shown in , the work performance level determination method provided in the embodiment of the present application includes:

[0055] S101: Process the core business work data of the employees each month to determine the core task performance index values ​​of the employees each month; wherein the core task performance indexes include work timeliness, work task volume, work speed and work quality.

[0056] In this step, the core business work data of employees each month is processed to determine the core task performance indicator values ​​of employees each month.

[0057] Among them, data processing is performed on the core business work data of employees every month to obtain the work timeliness rate, work task volume, work speed and work quality. Any technical means in the existing technology can be achieved, and this part will not be repeated.

[0058] S102: Calculate the core business score based on the predetermined target performance score ratio of the employee's department and the core task performance indicator value to determine the employee's core business score for each month.

[0059] In this step, the core business score is calculated based on the predetermined target performance score ratio of the employee's department and the core task performance indicator value to determine the employee's core business score for each month.

[0060] In a possible implementation manner, the target performance score ratio of the department to which the employee belongs is determined by the following steps:

[0061] A: Obtain the historical core task performance indicator values ​​and historical core business scores of the department.

[0062] Here, the historical core performance indicators of department personnel and the historical core business scores of personnel are collected.

[0063] B: Input the historical core task performance index value into the initial multiple regression linear model, use the different performance score ratios of the historical core task performance index value as independent variables, and use the historical core business score as the dependent variable to train the initial multiple regression linear model, so that the initial multiple regression linear model can predict the predicted performance score ratio corresponding to the historical core task performance index value.

[0064] Here, the historical core task performance index values ​​are input into the initial multiple regression linear model, the performance score ratios of different historical core task performance index values ​​are used as independent variables, and the historical core business scores are used as dependent variables to train the initial multiple regression linear model, so that the initial multiple regression linear model can predict the predicted performance score ratios corresponding to the historical core task performance index values.

[0065] Among them, the different performance score ratios are the proportional coefficients of the performance indicator values ​​of each core task in the multivariate regression linear model, which are x1, x2, x3, and x4 respectively.

[0066] C: Iteratively adjust the parameters of the initial multiple regression linear model based on the loss value between the sample core business score corresponding to the predicted performance score ratio and the historical core business score to determine the multiple regression linear model.

[0067] Here, the parameters of the initial multiple regression linear model are iteratively adjusted according to the loss value between the sample core business score and the historical core business score corresponding to the predicted performance score ratio to determine the multiple regression linear model.

[0068] The total score of the target performance score ratio may be other scores besides 100.

[0069] Among them, the data is divided into 70% training set and 30% test set, a multivariate regression linear model is established based on the training set, the proportional values ​​of different indicator features are used as the independent variables of the model, and the past performance scores are used as the dependent variables for model training, and the multivariate regression linear model based on the training set is output; the multivariate regression linear model based on the training set is used for the test set validation test to obtain the model with the best validation effect. In addition to adjusting according to the loss value, the multivariate regression linear model based on the training set is used for the test set validation test to obtain the model with the best validation effect. The R-square (goodness of fit) and SSE (residual sum of squares result) of the multivariate regression linear model based on the training set in the test set can be calculated to screen the optimal multivariate regression linear model with R-square approaching 1 and SSE approaching 0.

[0070] D: Input the core task performance index value of the employee's department into the multivariate regression linear model and output the target performance score ratio.

[0071] Here, the trained multivariate regression linear model is used to output the target performance score ratio corresponding to the department.

[0072] For further information, see Figure 2 , Figure 2 This is a schematic diagram of the training of the multivariate regression linear model provided in the embodiment of the present application. Figure 2 As shown in the figure, the past core performance indicators and past performance scores of department personnel are collected. The past core performance indicators include work timeliness, work task volume, work speed and work quality. The data set is divided into a training set and a test set. The proportional values ​​of different indicator characteristics are used as the independent variables of the model, and the past performance scores are used as the dependent variables for model training. The multivariate regression linear model based on the training set is output, and the accuracy of the multivariate regression linear model is determined according to the test set to obtain the model with the best verification effect.

[0073] In a possible implementation manner, the core business score is calculated based on the predetermined target performance score ratio of the employee's department and the core task performance indicator value to determine the employee's core business score for each month, including:

[0074] (1): If the work timeliness rate is 100%, the score corresponding to the work timeliness rate is the first performance score in the performance score ratio; if the work timeliness rate is less than 100%, the score corresponding to the work timeliness rate is 0.

[0075] Here, if the work timeliness rate is 100%, the score corresponding to the work timeliness rate is the first performance score (x1) in the performance score ratio; if the work timeliness rate is less than 100%, the score corresponding to the work timeliness rate is 0.

[0076] (2): Check whether the workload reaches the standard workload. If so, the score corresponding to the workload is the second performance score in the performance score ratio.

[0077] Here, it is detected whether the workload reaches the standard workload. If so, the score corresponding to the workload ok is the second performance score (x2) in the performance score ratio.

[0078] Among them, the standard workload is: the amount of completed tasks is 21.75 (the number of working days stipulated by the state) * the standard daily throughput per person for core business. The standard daily throughput per person is calculated by collecting the task volume and working hours of the entire team during the period when the task volume is saturated or even oversaturated, (total task volume / total working hours) * working day length = standard daily throughput per person.

[0079] The task amount in this embodiment refers to the number of cell readings.

[0080] In a possible implementation manner, after detecting whether the workload has reached the standard workload, the work performance level determination method further includes:

[0081] If not, the score corresponding to the workload is determined based on the product of the ratio of the workload to the standard workload and the second performance score.

[0082] Here, if not, the score corresponding to the workload is determined based on the product of the ratio of the workload to the standard workload and the second performance score.

[0083] (3): Check whether the work speed reaches a preset ratio of the average work speed of the department in that month. If so, the score corresponding to the work speed is the third performance score in the performance score ratio.

[0084] Here, it is detected whether the working speed reaches a preset proportion of the average working speed of the department in that month. If so, the score corresponding to the working speed is the third performance score in the performance score ratio.

[0085] Among them, for the task of selecting samples, the historical data of the speed of department personnel throughout the year are collected, the speed is sorted from small to large and a scatter plot is drawn, and the inflection point of the curve is determined according to the curve formed by the scatter point. Exemplarily, the task of this embodiment is cell interpretation, the historical data of the speed of department personnel throughout the year are collected, the speed is sorted from small to large and a scatter plot is drawn, and the three inflection points are determined by calculation to be near 30%, 80% and 120% of the average speed, respectively, so integers are directly taken to facilitate subsequent calculations. There are very few points with a speed below 30% of the average speed, accounting for less than 1% of the total; in the range of 30%-80% of the average speed, the interpretation speed first increases rapidly and then increases slowly. At this time, a calculation formula with a small score gap in the front section and a gap that can be widened in the back section should be selected. In the range of 80%-120%, the interpretation speed increases steadily, and at this time, a calculation formula that can quickly widen the gap should also be selected; when the speed is greater than 120%, the interpretation speed increases rapidly and the distribution of points gradually becomes sparse, and at this time, a calculation formula that is difficult to widen the gap should be selected.

[0086] Through the above calculation method, on the one hand, the score gap can be widened in the interval where the speed is intensively growing slowly to encourage personnel to make progress. On the other hand, the score gap can be controlled in the interval where the speed is sparsely growing rapidly to prevent personnel from only pursuing the interpretation speed to widen the score gap while ignoring the interpretation quality. Therefore, in this solution, the preset ratio of the average speed is set to 80%.

[0087] Here, when no inflection point appears in the historical data of department personnel's judgment speed collected throughout the year, a preset proportion of the average working speed can be determined based on expert experience.

[0088] Here, the average monthly departmental interpretation speed is calculated based on the departmental performance score requirements. When the monthly reading speed of department personnel reaches 80% of the average reading speed, 15 points can be obtained; when the monthly reading speed of department personnel reaches 0% of the average reading speed, 0 points can be obtained. There must be certain requirements for the growth rate of the score and the score range of the reading speed. When the reading speed is 0-30% of the average reading speed, the reading score shows an exponential growth curve trend; when the reading speed is 30%-130% of the average reading speed, the reading score shows a logarithmic growth curve trend; when the reading speed is above 130% of the average reading speed, the reading score grows more and more slowly. According to the above requirements, fit the calculation formula to meet the score requirements. By selecting elementary functions and composite functions for fitting, the score corresponding to the work speed can be determined.

[0089] In a possible implementation manner, after detecting whether the work speed reaches a preset proportion of the average work speed of the department in that month, the work performance level determination method further includes:

[0090] If not, the score corresponding to the working speed is determined by the following formula:

[0091] y=12.6+13.2*arctan(2x-1.4);

[0092] Among them, x is the working speed and y is the score corresponding to the working speed.

[0093] (4) If the work quality is 100%, the score corresponding to the work quality is the fourth performance score in the performance score ratio.

[0094] Here, for the work task of finding abnormal samples, the work quality = 1-number of missed cells / number of tasks * 100%. Based on the calculated daily throughput, the number of tasks that can be completed by each person per month = 10 cases * 21.75 working days = 217.5. The lower limit of the pass rate = 1-1 / 217.5*100% = 99.5%. In the process of formulating quality standards, it is expected that the pass rate of employees can be stably maintained in the range of 99.5% to 100%. Therefore, a corresponding scoring system is set to ensure the rigor and operability of the quality standards. Specifically, a pass rate of 100% will correspond to the highest score of the fourth performance score (x4), while a pass rate of 99.5% will correspond to a score of x4*0.75 points, which means that within this interval, a slight difference in the pass rate will be directly reflected in a significant change in the score. At the same time, in order to cope with possible fluctuations, a cache interval is reserved for situations where the pass rate is lower than 99.5%. The requirement that a pass rate of 99% will directly correspond to a score of 0 in the quality module is intended to emphasize strict adherence to quality standards and motivate all employees to work together to achieve or exceed established quality goals.

[0095] Fourth, the performance score can be adjusted according to the specific work tasks, and the scores under different pass rates can be adjusted according to the quality control requirements of the specific work tasks.

[0096] (5): Add the score corresponding to the work timeliness rate, the score corresponding to the workload, the score corresponding to the work speed, and the score corresponding to the work quality to determine the core business score of the employee.

[0097] Here, the scores corresponding to work timeliness, workload, work speed, and work quality are added together to determine the employee's core business score.

[0098] S103: Calculate the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, add the basic business score and the core business score in the same month to determine the monthly performance score of the employee.

[0099] In this step, the basic work business data of the employee is scored each month to determine the basic business score of the employee each month. The basic business score and core business score of the same month are added together to determine the employee's monthly performance score.

[0100] Among them, basic work business data refers to other work outside the core business, which is generally related to department work, such as writing documents, organizing projects and other tasks.

[0101] Here, the core business score of designer A is X, and the basic business score is Y. To adapt to the conventional calculation method, set X+Y=100.

[0102] In a possible implementation manner, the step of calculating a score of the basic work business data of the employee each month to determine the basic business score of the employee each month includes:

[0103] The time consumed in the basic work business data is ratioed to the daily working hours to determine a first ratio; the second performance score in the performance score ratio is ratioed to the number of working days in the basic work business data to determine a second ratio; the basic business score is determined based on the product of the first ratio and the second ratio.

[0104] Among them, basic business score = (second performance score / number of working days)*(time consumed / daily working hours).

[0105] S104: Evaluate the quarterly performance level of the employee's multiple monthly performance scores based on a normal distribution function to determine the employee's work performance level.

[0106] In this step, the performance level of the employee's multiple monthly performance scores is evaluated according to the normal distribution function to determine the employee's work performance level.

[0107] Here, three monthly performance scores can be used to assess quarterly performance levels.

[0108] In a possible implementation manner, the performance level assessment of the multiple monthly performance scores of the employee based on the normal distribution function to determine the work performance level of the employee includes:

[0109] a: Calculate the mean and standard deviation of each employee's multiple monthly performance scores to determine the average score and standard deviation.

[0110] Here, the mean and standard deviation of multiple monthly performance scores of each employee are calculated to determine the average score and standard deviation.

[0111] b: Quarterly performance levels are divided based on the normal distribution function, the average score and the standard deviation.

[0112] Here, quarterly performance levels are divided according to the normal distribution function, mean score, and standard deviation.

[0113] For example, if we calculate the arithmetic mean μ and standard deviation σ of the quarterly performance scores, then there exists a random variable X that follows a normal distribution X~N(μ,σ 2), x in P(X≤m)=0.1 is used as the score line for quarterly performance level C, x in P(X≤n)=0.02 is used as the score line for quarterly performance level D, and x in P(X≤b)=0.02 is used as the score line for quarterly performance level B, where the corresponding table of performance scores and quarterly performance levels is shown in Table 2 below:

[0114] Table 2 Correspondence between performance scores and quarterly performance levels

[0115] Performance Score Performance Level Performance-based salary payment ratio (b,+∞) A 110％ (M,b] B 100& (n,m] C 90％ [0,n] D 0％

[0116] c: performing matching processing based on the score intervals corresponding to the divided performance levels and the multiple monthly performance scores of the employee to determine the work performance level of the employee.

[0117] Here, matching processing is performed based on the score intervals corresponding to the divided quarterly performance levels and the multiple monthly performance scores of the employee to determine the employee's work performance level.

[0118] In a specific embodiment, assume that the performance scores for a certain quarter are as follows: Employee A: 90, Employee B: 85, Employee C: 80, Employee D: 75, Employee E: 70. After calculation, the mean performance score (μ) for the quarter is 80 points, and the standard deviation (σ) is 10 points. Quarterly performance level A: 90 points (\(\μ+\σ=90\)) Quarterly performance level B: 85 points (\(\μ+\σ / 2=85\)) Quarterly performance level C: 80 points (\(\μ\)) Quarterly performance level D: 75 points (\(\μ-\σ / 2=75\)) Quarterly performance level E: 70 points (\(\μ-\σ=70\)).

[0119] The beneficial effects of this program are as follows: Improve the objectivity and consistency of evaluation: Through clear evaluation standards and quantitative indicators, reduce the impact of subjective judgment on evaluation results, and ensure the fairness and accuracy of evaluation. Simplify the evaluation process: Modeling makes the evaluation process more standardized and streamlined, reduces tedious manual operations, and improves evaluation efficiency. Facilitate data analysis and comparison: Modeled performance evaluation data can be easily counted and analyzed, which helps to discover the strengths and weaknesses of employees and organizations and provide a basis for formulating improvement measures. Promote employee development and motivation: Through clear evaluation standards and feedback mechanisms, help employees understand their work performance, stimulate their work enthusiasm and creativity, and promote personal growth and career development.

[0120] The embodiment of the present application provides a method for determining the work performance level of an employee, and the method for determining the work performance level includes: processing the core business work data of the employee each month to determine the core task performance index value of the employee each month; wherein the core task performance index includes work timeliness, work task volume, work speed and work quality; calculating the core business score based on the predetermined target performance score ratio of the department where the employee is located and the core task performance index value to determine the core business score of the employee each month; calculating the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, adding the basic business score and the core business score in the same month to determine the monthly performance score of the employee; and evaluating the performance level of the multiple monthly performance scores of the employee based on the normal distribution function to determine the work performance level of the employee. Through clear evaluation criteria and quantitative indicators, the influence of subjective judgment on the evaluation results is reduced, the fairness and accuracy of performance evaluation are ensured, cumbersome manual operations are reduced, and evaluation efficiency is improved.

[0121] See also Figure 3 , Figure 4 , Figure 3 This is one of the structural schematic diagrams of a device for determining an employee's work performance level provided in an embodiment of the present application. Figure 4 This is a second structural diagram of a device for determining an employee's work performance level provided in an embodiment of the present application. Figure 3 As shown in , the work performance level determination device 300 includes:

[0122] The performance indicator value determination module 310 is used to process the core business work data of the employee each month to determine the core task performance indicator value of the employee each month; wherein the core task performance indicators include work timeliness rate, work task amount, work speed and work quality;

[0123] A core business score calculation module 320 is used to calculate the core business score based on the predetermined target performance score ratio of the employee's department and the core task performance index value, and determine the core business score of the employee every month;

[0124] The basic business score calculation module 330 is used to calculate the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, and to add the basic business score and the core business score in the same month to determine the monthly performance score of the employee;

[0125] The performance evaluation module 340 is used to evaluate the performance level of the employee's multiple monthly performance scores based on a normal distribution function to determine the employee's work performance level.

[0126] Further, such as Figure 4 As shown, the work performance level determination device 300 also includes a performance score ratio determination module 350. The performance score ratio determination module 350 determines the target performance score ratio of the department where the employee belongs through the following steps:

[0127] Obtain the historical core task performance indicator values ​​and historical core business scores of the department;

[0128] Inputting the historical core task performance index value into an initial multiple regression linear model, taking different performance score ratios of the historical core task performance index value as independent variables, and taking the historical core business score as a dependent variable to train the initial multiple regression linear model, so that the initial multiple regression linear model predicts the predicted performance score ratio corresponding to the historical core task performance index value;

[0129] Iteratively adjusting the parameters of the initial multiple regression linear model based on the loss value between the sample core business score corresponding to the predicted performance score ratio and the historical core business score to determine the multiple regression linear model;

[0130] The core task performance index value of the employee's department is input into the multivariate regression linear model, and the target performance score ratio is output. Further, when the core business score calculation module 330 is used to calculate the core business score based on the predetermined target performance score ratio of the employee's department and the core task performance index value, and to determine the core business score of the employee each month, the core business score calculation module 330 is specifically used to:

[0131] If the work timeliness rate is 100%, the score corresponding to the work timeliness rate is the first performance score in the performance score ratio; if the work timeliness rate is less than 100%, the score corresponding to the work timeliness rate is 0;

[0132] Detecting whether the workload reaches the standard workload, and if so, the score corresponding to the workload is the second performance score in the performance score ratio;

[0133] Detecting whether the work speed reaches a preset ratio of the average work speed of the department in that month, and if so, the score corresponding to the work speed is the third performance score in the performance score ratio;

[0134] If the work quality is 100%, the score corresponding to the work quality is the fourth performance score in the performance score ratio;

[0135] The score corresponding to the work timeliness rate, the score corresponding to the workload, the score corresponding to the work speed, and the score corresponding to the work quality are added together to determine the core business score value of the employee.

[0136] Furthermore, the core business score calculation module 330 is used to:

[0137] If not, the score corresponding to the workload is determined based on the product of the ratio of the workload to the standard workload and the second performance score.

[0138] Furthermore, when the basic business score calculation module 340 is used to calculate the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, the basic business score calculation module 340 is specifically used to:

[0139] Performing ratio processing on the time consumption and the daily working hours in the basic work business data to determine a first ratio;

[0140] Performing ratio processing on the second performance score in the performance score ratio and the number of working days in the basic work business data to determine a second ratio;

[0141] The basic business score is determined based on the product of the first ratio and the second ratio.

[0142] Furthermore, when the performance evaluation module 340 is used to evaluate the quarterly performance level of the employee's multiple monthly performance scores based on the normal distribution function to determine the employee's work performance level, the performance evaluation module 340 is specifically used to:

[0143] Calculate the mean and standard deviation of each employee's multiple monthly performance scores to determine the average score and standard deviation;

[0144] Performing quarterly performance grading based on the normal distribution function, the average score, and the standard deviation;

[0145] The work performance level of the employee is determined by performing matching processing based on the score intervals corresponding to the divided performance levels and the multiple monthly performance scores of the employee.

[0146] The embodiment of the present application provides a device for determining the work performance level of an employee, and the work performance level determination device includes: a performance index value determination module, which is used to process the core business work data of the employee each month to determine the core task performance index value of the employee each month; wherein the core task performance index includes work timeliness, work task volume, work speed and work quality; a core business score calculation module, which is used to calculate the core business score based on the predetermined target performance score ratio of the department where the employee is located and the core task performance index value, and determine the core business score of the employee each month; a basic business score calculation module, which is used to calculate the score of the basic work business data of the employee each month, determine the basic business score of the employee each month, add the basic business score and the core business score in the same month, and determine the monthly performance score of the employee; a performance evaluation module, which is used to evaluate the performance level of the employee's multiple monthly performance scores based on the normal distribution function, and determine the work performance level of the employee. Through clear evaluation criteria and quantitative indicators, the influence of subjective judgment on the evaluation results is reduced, the fairness and accuracy of performance evaluation are ensured, the cumbersome manual operation is reduced, and the evaluation efficiency is improved.

[0147] See also Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown in , the electronic device 500 includes a processor 510 , a memory 520 and a bus 530 .

[0148] The memory 520 stores machine-readable instructions executable by the processor 510. When the electronic device 500 is running, the processor 510 communicates with the memory 520 via the bus 530. When the machine-readable instructions are executed by the processor 510, the above-mentioned Figure 1 as well as Figure 2 The steps of the method for determining the work performance level of an employee in the method embodiment shown, and the specific implementation method thereof can be referred to the method embodiment, which will not be described in detail here.

[0149] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 as well as Figure 2 The steps of the method for determining the work performance level of an employee in the method embodiment shown, and the specific implementation method thereof can be referred to the method embodiment, which will not be described in detail here.

[0150] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0151] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0152] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0153] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0154] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0155] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for determining an employee's work performance level, characterized in that: The method for determining the work performance level includes: Process the core business work data of employees each month to determine the core task performance index value of the employees each month; wherein the core task performance index includes work timeliness rate, work task volume, work speed and work quality; Calculate the core business score based on the predetermined target performance score ratio of the employee's department and the core task performance index value to determine the employee's core business score for each month; Calculate the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, and add the basic business score and the core business score in the same month to determine the monthly performance score of the employee; The performance level of the employee's multiple monthly performance scores is evaluated based on a normal distribution function to determine the employee's work performance level.

2. The method for determining work performance level according to claim 1, characterized in that: Determine the target performance score ratio of the employee's department through the following steps: Obtain the historical core task performance indicator values ​​and historical core business scores of the department; Inputting the historical core task performance index value into an initial multiple regression linear model, taking different performance score ratios of the historical core task performance index value as independent variables, and taking the historical core business score as a dependent variable to train the initial multiple regression linear model, so that the initial multiple regression linear model predicts the predicted performance score ratio corresponding to the historical core task performance index value; Iteratively adjusting the parameters of the initial multiple regression linear model based on the loss value between the sample core business score corresponding to the predicted performance score ratio and the historical core business score to determine the multiple regression linear model; The core task performance index value of the employee's department is input into the multivariate regression linear model, and the target performance score ratio is output.

3. The method for determining work performance level according to claim 1, characterized in that: The core business score calculation based on the predetermined target performance score ratio of the employee's department and the core task performance indicator value is performed to determine the employee's core business score for each month, including: If the work timeliness rate is 100%, the score corresponding to the work timeliness rate is the first performance score in the performance score ratio; if the work timeliness rate is less than 100%, the score corresponding to the work timeliness rate is 0; Detecting whether the workload reaches the standard workload, and if so, the score corresponding to the workload is the second performance score in the performance score ratio; Detecting whether the work speed reaches a preset ratio of the average work speed of the department in that month, and if so, the score corresponding to the work speed is the third performance score in the performance score ratio; If the work quality is 100%, the score corresponding to the work quality is the fourth performance score in the performance score ratio; The score corresponding to the work timeliness rate, the score corresponding to the workload, the score corresponding to the work speed, and the score corresponding to the work quality are added together to determine the core business score value of the employee.

4. The method for determining work performance level according to claim 3, characterized in that: After detecting whether the workload reaches the standard workload, the work performance level determination method further includes: If not, the score corresponding to the workload is determined based on the product of the ratio of the workload to the standard workload and the second performance score.

5. The method for determining work performance level according to claim 1, characterized in that: The step of calculating the score of the basic work business data of the employee each month to determine the basic business score of the employee each month includes: Performing ratio processing on the time consumption and the daily working hours in the basic work business data to determine a first ratio; Performing ratio processing on the second performance score in the performance score ratio and the number of working days in the basic work business data to determine a second ratio; The basic business score is determined based on the product of the first ratio and the second ratio.

6. The method for determining work performance level according to claim 1, characterized in that: The performance level of the employee's multiple monthly performance scores is evaluated based on the normal distribution function to determine the employee's work performance level. Includes, including: Calculate the mean and standard deviation of each employee's multiple monthly performance scores to determine the average score and standard deviation; Performing performance level classification based on the normal distribution function, the average score and the standard deviation; The work performance level of the employee is determined by performing matching processing based on the score intervals corresponding to the divided performance levels and the multiple monthly performance scores of the employee.

7. A device for determining an employee's work performance level, characterized in that: The work performance level determination device comprises: The performance indicator value determination module is used to process the core business work data of employees every month to determine the core task performance indicator value of the employees every month; wherein the core task performance indicators include work timeliness rate, work task volume, work speed and work quality; A core business score calculation module, used to calculate the core business score based on the predetermined target performance score ratio of the employee's department and the core task performance index value, and determine the employee's core business score for each month; A basic business score calculation module is used to calculate the score of the basic work business data of the employee each month to determine the basic business score of the employee each month, and to add the basic business score and the core business score in the same month to determine the monthly performance score of the employee; The performance evaluation module is used to evaluate the performance level of the employee's multiple monthly performance scores based on a normal distribution function to determine the employee's work performance level.

8. The work performance level determination device according to claim 7, characterized in that: The work performance level determination device also includes a performance score ratio determination module. The performance score ratio determination module 350 determines the target performance score ratio of the department to which the employee belongs through the following steps: Obtain the historical core task performance indicator values ​​and historical core business scores of the department; Inputting the historical core task performance index value into an initial multiple regression linear model, taking different performance score ratios of the historical core task performance index value as independent variables, and taking the historical core business score as a dependent variable to train the initial multiple regression linear model, so that the initial multiple regression linear model predicts the predicted performance score ratio corresponding to the historical core task performance index value; Iteratively adjusting the parameters of the initial multiple regression linear model based on the loss value between the sample core business score corresponding to the predicted performance score ratio and the historical core business score to determine the multiple regression linear model; The core task performance index value of the employee's department is input into the multivariate regression linear model, and the target performance score ratio is output.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the method for determining the work performance level of an employee as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for determining the work performance level of an employee as described in any one of claims 1 to 6 are executed.

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