Human efficiency evaluation method and device, equipment, storage medium and computer program product

Abstract

The invention discloses a human efficiency assessment method, device and equipment, a storage medium and a computer program product, and relates to the technical field of human resource data processing, and the method comprises the steps: obtaining to-be-assessed human efficiency index data; based on a pre-constructed human resource efficiency evaluation model, human efficiency evaluation is carried out on the to-be-evaluated human efficiency index data, a human efficiency evaluation result is obtained, the human resource efficiency evaluation model is constructed based on a preset evaluation analysis framework, and the evaluation analysis framework is suitable for human efficiency evaluation of business units of different levels. According to the method and the device, the management business units are divided according to the levels or the evaluation indexes are adjusted according to the business content, the human resource efficiency evaluation model of the corresponding caliber is established, standardization and replicability of the model are realized, and human resources are evaluated under the unified standard. Therefore, the problem that a human effect evaluation model which can be completely copied is not formed in an existing method is solved, standardization of enterprise human effect evaluation is achieved, and higher applicability is achieved.

Description

Technical Field

[0001] This application relates to the technical field of human resource data processing, and particularly to a human efficiency evaluation method, device, equipment, storage medium, and computer program product. Background Art

[0003] The evaluation of human resource efficiency is a prerequisite for improving human efficiency. Without analysis, there is no judgment, and without judgment, it is difficult to make decisions. The ultimate goal of human resource efficiency evaluation is still to improve human efficiency. Through the positioning judgment of human efficiency evaluation and the tracing of the development trend or state of human efficiency, it can provide more sufficient decision-making basis for the formulation of human efficiency improvement policies.

[0004] However, from the general market rules, the standards for enterprise human efficiency evaluation are relatively complex, and a completely replicable human efficiency evaluation model has not been formed.

[0005] The above content is only used to assist in understanding the technical solution of this application, and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main purpose of this application is to provide a human efficiency evaluation method, device, equipment, storage medium, and computer program product, aiming to solve the technical problem that the existing enterprise human efficiency evaluation method has not formed a completely replicable human efficiency evaluation model.

[0007] To achieve the above purpose, this application proposes a human efficiency evaluation method, which includes:

[0008] Obtain the human efficiency index data to be evaluated;

[0009] Based on the pre-constructed human resource efficiency evaluation model, conduct a human efficiency evaluation on the human efficiency index data to be evaluated, and obtain a human efficiency evaluation result. The human resource efficiency evaluation model is constructed based on a preset evaluation analysis framework, and the evaluation analysis framework is applicable to the human efficiency evaluation of business units at different levels.

[0010] In one embodiment, before the step of conducting a human efficiency evaluation on the human efficiency index data to be evaluated based on the pre-constructed human resource efficiency evaluation model and obtaining a human efficiency evaluation result, it further includes:

[0011] Obtain historical human efficiency index data and industry human efficiency index data;

[0012] Construct the human resource efficiency evaluation model according to the historical human efficiency index data and the industry human efficiency index data.

[0013] In one embodiment, the step of constructing the human resource efficiency evaluation model includes:

[0014] Based on a preset regression analysis algorithm, perform a regression analysis on the industry labor efficiency index data to obtain external benchmark configuration data;

[0015] Based on a preset comparative analysis algorithm, compare and analyze the historical labor efficiency index data and the industry labor efficiency index data to obtain internal benchmark configuration data;

[0016] According to the external benchmark configuration data, the internal benchmark configuration data, the preset dynamic analysis configuration data, and the multi-dimensional analysis configuration data, configure the parameters of the preset business unit evaluation and analysis framework to obtain the human resource efficiency evaluation model.

[0017] In one embodiment, the step of performing a labor efficiency evaluation on the to-be-evaluated labor efficiency index data based on the pre-constructed human resource efficiency evaluation model to obtain a labor efficiency evaluation result includes:

[0018] Based on the human resource efficiency evaluation model, perform a static analysis on the to-be-evaluated labor efficiency index data to obtain a static analysis result;

[0019] Based on the human resource efficiency evaluation model, perform a dynamic analysis on the to-be-evaluated labor efficiency index data to obtain a dynamic analysis result;

[0020] Based on the labor efficiency analysis matrix in the human resource efficiency evaluation model, perform a multi-dimensional matrix analysis on the to-be-evaluated labor efficiency index data to obtain a multi-dimensional analysis result;

[0021] According to the static analysis result, the dynamic analysis result, and the multi-dimensional analysis result, obtain the labor efficiency evaluation result.

[0022] In one embodiment, the step of performing a static analysis on the to-be-evaluated labor efficiency index data based on the human resource efficiency evaluation model to obtain a static analysis result includes:

[0023] Based on the dynamic return analysis algorithm in the human resource efficiency evaluation model, perform a dynamic return analysis on the labor cost growth data, the profit growth data, and the operating income growth data in the to-be-evaluated labor efficiency index data to obtain a dynamic return analysis result;

[0024] Based on the investment quality analysis algorithm in the human resource efficiency evaluation model, perform an investment quality analysis on the labor cost growth data and the personnel scale growth data in the to-be-evaluated labor efficiency index data to obtain an investment quality analysis result;

[0025] According to the dynamic return analysis result and the investment quality analysis result, generate the dynamic analysis result.

[0026] In one embodiment, the step of performing multi-dimensional matrix analysis on the to-be-evaluated human resource efficiency index data based on the human resource efficiency analysis matrix in the human resource efficiency evaluation model to obtain a multi-dimensional analysis result includes:

[0027] Based on the human resource efficiency analysis matrix, perform payment level analysis on the average labor cost data in the to-be-evaluated human resource efficiency index data to obtain a payment level analysis result;

[0028] Based on the human resource efficiency analysis matrix, perform payment efficiency analysis on the labor cost data and operating profit data in the to-be-evaluated human resource efficiency index data to obtain a payment efficiency analysis result;

[0029] Obtain the multi-dimensional analysis result according to the payment level analysis result and the payment efficiency analysis result.

[0030] In addition, to achieve the above object, the present application also proposes a human resource efficiency evaluation device, which includes:

[0031] A data acquisition module, configured to acquire to-be-evaluated human resource efficiency index data;

[0032] A human resource efficiency evaluation module, configured to perform human resource efficiency evaluation on the to-be-evaluated human resource efficiency index data based on a pre-constructed human resource efficiency evaluation model, and obtain a human resource efficiency evaluation result. The human resource efficiency evaluation model is constructed based on a preset evaluation analysis framework, and the evaluation analysis framework is applicable to the human resource efficiency evaluation of business units at different levels.

[0033] In addition, to achieve the above object, the present application also proposes a human resource efficiency evaluation device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. The computer program is configured to implement the steps of the human resource efficiency evaluation method as described above.

[0034] In addition, to achieve the above object, the present application also proposes a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the human resource efficiency evaluation method as described above are implemented.

[0035] In addition, to achieve the above object, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the human resource efficiency evaluation method as described above are implemented.

[0036] The present application provides a human efficiency evaluation method, which can establish a human resource efficiency evaluation model with corresponding caliber by dividing business units according to levels or adjusting evaluation indicators according to business content, realizing the standardization and replicability of the model, and evaluating human resources under a unified standard. Thus, the technical problem that the existing enterprise human efficiency evaluation method has not formed a completely replicable human efficiency evaluation model is solved, the standardization of enterprise human efficiency evaluation is realized, and it has stronger applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present application and, together with the specification, are used to explain the principles of the present application.

[0038] 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 accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 It is a schematic flowchart provided for the first embodiment of the human efficiency evaluation method of the present applicant;

[0040] Figure 2 It is a schematic flowchart provided for the second embodiment of the human efficiency evaluation method of the present applicant;

[0041] Figure 3 It is a schematic content diagram of the dynamic income analysis result provided for the second embodiment of the present application;

[0042] Figure 4 It is a schematic content diagram of the investment quality analysis result provided for the second embodiment of the present application;

[0043] Figure 5 It is a schematic module structure diagram of the human efficiency evaluation device in the embodiment of the present application;

[0044] Figure 6 It is a schematic device structure diagram of the hardware operating environment involved in the human efficiency evaluation method in the embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0046] In order to better understand the technical solutions of the present application, the following will be described in detail in conjunction with the accompanying drawings of the specification and the specific embodiments.

[0047] The main solution of the embodiment of the present application is:

[0048] Obtain the human resource efficiency index data to be evaluated;

[0049] Based on the pre - constructed human resource efficiency evaluation model, conduct a human resource efficiency evaluation on the human resource efficiency index data to be evaluated, and obtain a human resource efficiency evaluation result. The human resource efficiency evaluation model is constructed based on a preset evaluation analysis framework, and the evaluation analysis framework is applicable to the human resource efficiency evaluation of business units at different levels.

[0050] In the existing technology, human resource efficiency evaluation is the premise of human resource efficiency improvement. Without analysis, there is no judgment, and without judgment, it is difficult to form a decision. The ultimate goal of human resource efficiency evaluation is still human resource efficiency improvement. Through the positioning judgment of human resource efficiency evaluation and the tracing of the development trend or state of human resource efficiency, it can provide more sufficient decision - making basis for the formulation of human resource efficiency improvement policies.

[0051] However, from the general market rules, the criteria for enterprise human resource efficiency evaluation are relatively complex, and a completely replicable human resource efficiency evaluation model has not been formed.

[0052] This application provides a solution. By dividing business units according to levels or adjusting evaluation indicators according to business content, a human resource efficiency evaluation model with corresponding calibers can be established to achieve the standardization and replicability of the model, and evaluate human resources under a unified standard. Thus, it solves the technical problem that the existing enterprise human resource efficiency evaluation methods have not formed a completely replicable human resource efficiency evaluation model, realizes the standardization of enterprise human resource efficiency evaluation, and has stronger applicability.

[0053] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a human resource efficiency evaluation system, etc. that can implement the above functions. Hereinafter, taking the human resource efficiency evaluation system as an example, this embodiment and the following embodiments will be described.

[0054] Based on this, the embodiments of this application provide a human resource efficiency evaluation method, referring to Figure 1 , Figure 1 which is the flow chart of the first embodiment of the human resource efficiency evaluation method of this application.

[0055] In this embodiment, the human resource efficiency evaluation method includes steps S10 - S20:

[0056] Step S10, obtain the human resource efficiency index data to be evaluated;

[0057] The human efficiency evaluation system obtains data related to human resource efficiency, which can include employees' work performance, working hours, project completion, employee satisfaction, team collaboration efficiency, etc., to obtain the to-be-evaluated human efficiency index data. The purpose is to obtain sufficient information to evaluate the efficiency of human resources, that is, the work performance and efficiency of employees or teams. These data will be used as the input of the evaluation model for subsequent analysis and evaluation.

[0058] It should be noted that the to-be-evaluated human efficiency index data refers to the original data related to the efficiency of employees or teams that have not been analyzed and evaluated. These data can be quantitative, such as sales volume and production volume; or qualitative, such as customer feedback and colleague evaluations.

[0059] Step S20: Based on the pre-constructed human resource efficiency evaluation model, conduct a human efficiency evaluation on the to-be-evaluated human efficiency index data to obtain a human efficiency evaluation result. The human resource efficiency evaluation model is constructed based on a preset evaluation analysis framework, and the evaluation analysis framework is applicable to the human efficiency evaluation of business units at different levels.

[0060] The human efficiency evaluation system conducts a human efficiency evaluation on the to-be-evaluated human efficiency index data based on the pre-constructed human resource efficiency evaluation model to obtain a human efficiency evaluation result. The purpose is to quantify the efficiency of human resources through the evaluation model for comparison, decision-making, and improvement, which helps the organization understand the actual performance of its human resources and make more informed management decisions accordingly.

[0061] It should be noted that the human resource efficiency evaluation model is a predefined model used to calculate and predict the efficiency of human resources based on the input data. The model can be based on multiple factors, such as employees' work performance, working hours, project completion, etc.; the human efficiency evaluation result is a quantitative result about the human resource efficiency obtained according to the evaluation model, and these results can be scores, grades, or other forms of indicators; the human resource efficiency evaluation model is constructed based on a preset evaluation analysis framework, and the evaluation analysis framework is applicable to the human efficiency evaluation of business units at different levels.

[0062] In a feasible implementation manner, before step S20, steps S301 to S302 may also be included:

[0063] Step S301: Obtain historical human efficiency index data and industry human efficiency index data;

[0064] Step S302: Construct the human resource efficiency evaluation model according to the historical human efficiency index data and industry human efficiency index data.

[0065] The human efficiency evaluation system obtains historical human efficiency index data and industry human efficiency index data.

[0066] It should be noted that historical human resource efficiency index data refers to the data related to human resource efficiency collected by an organization over a past period, such as employees' work performance, working hours, project completion status, etc. Industry human resource efficiency index data refers to the efficiency data of other organizations or the industry average level within the same industry, which is usually used as a comparison benchmark. By collecting historical data, an organization can understand the changing trends of its human resource efficiency in different time periods, and obtaining industry data helps to compare the organization's efficiency with that of other organizations in the same industry, so as to evaluate its competitive position in the industry. Then, based on the principle of data modeling, that is, using historical human resource efficiency index data and industry human resource efficiency index data to develop a model that can predict and evaluate human resource efficiency, namely the human resource efficiency evaluation model. This model will help the organization understand the efficiency of human resources and make more informed management decisions accordingly.

[0067] In this embodiment, through historical human resource efficiency index data and industry human resource efficiency index data, the system can establish a benchmark reference system for evaluating and comparing the current human resource efficiency; construct a human resource efficiency evaluation model based on the collected data, enabling the system to quantify and evaluate the effect of human resource management; these steps provide data-based decision support to help the management make more scientific human resource management decisions based on historical trends and industry standards; by analyzing historical data and industry data, the system can predict future human resource efficiency trends and make long-term planning and strategy adjustments accordingly. Thus, the system can build a solid data foundation and develop an evaluation model that can reflect the actual human resource efficiency, which is crucial for improving the efficiency and effect of human resource management.

[0068] In another feasible embodiment, step S302 may include steps S3021 to S3023:

[0069] Step S3021, based on a preset regression analysis algorithm, perform regression analysis according to the industry human resource efficiency index data to obtain external benchmark configuration data;

[0070] Step S3022, based on a preset comparative analysis algorithm, compare and analyze the historical human resource efficiency index data and the industry human resource efficiency index data to obtain internal benchmark configuration data;

[0071] Step S3023, according to the external benchmark configuration data, internal benchmark configuration data, and preset dynamic analysis configuration data and multi-dimensional analysis configuration data, configure the parameters of a preset business unit evaluation analysis framework to obtain the human resource efficiency evaluation model.

[0072] Based on a preset regression analysis algorithm, the human efficiency evaluation system conducts regression analysis on industry human efficiency indicator data to obtain external benchmark configuration data, that is, data on industry standards or industry averages. This helps the organization compare its own efficiency with industry standards, thereby evaluating its competitive position in the industry. The external benchmark configuration data obtained through regression analysis can be an important part of the evaluation model, helping the organization identify its position in the industry and providing data support for future strategic planning. Regression analysis is used to analyze the relationship between one variable (such as revenue) and one or more other variables (such as labor costs) and predict future trends. Then, based on a preset comparative analysis algorithm, the system compares and analyzes historical human efficiency indicator data and industry human efficiency indicator data to obtain internal benchmark configuration data, that is, the organization's own historical performance data. This helps evaluate the organization's progress and changes over time and compare with industry standards. The internal benchmark configuration data obtained through comparative analysis can be an important part of the evaluation model, helping the organization identify its position in historical performance and industry competition and providing data support for future strategic planning. Comparative analysis helps identify changes in the organization's efficiency at different time points and compare with industry standards, thereby evaluating the organization's performance and competitiveness. Then, external benchmark configuration data (industry standards), internal benchmark configuration data (organization's historical performance), as well as dynamic analysis configuration data and multi-dimensional analysis configuration data are used to adjust and optimize the parameters of the preset business unit evaluation analysis framework. This parameter configuration is based on a data-driven approach, aiming to improve the accuracy and applicability of the model. Through parameter configuration, the model can more accurately predict and evaluate human resource efficiency, help the organization identify efficiency bottlenecks, optimize resource allocation, and formulate effective human resource strategies.

[0073] Among them, the regression analysis algorithm is a method in statistics used to estimate the relationship between variables, especially the relationship between a dependent variable and one or more independent variables. The following are examples of several common regression analysis algorithms:

[0074] 1) Linear Regression:

[0075] Linear regression is the most basic form of regression analysis, which assumes a linear relationship between the dependent variable and the independent variable.

[0076] 2) Multiple Linear Regression:

[0077] Multiple linear regression is an extension of linear regression, which includes two or more independent variables. This model can help us understand how multiple independent variables affect the dependent variable simultaneously.

[0078] 3) Logistic Regression:

[0079] Logistic regression is used in cases where the dependent variable is a categorical variable, especially binary classification problems. It converts the linear prediction value into a probability value through the Sigmoid function to predict the likelihood of an event occurring.

[0080] 4) Ridge Regression:

[0081] Ridge regression is a linear regression method for dealing with the problem of multicollinearity among independent variables. It reduces the model complexity by adding an L2 regularization term (i.e., sum of squares penalty) to the loss function.

[0082] 5) Lasso Regression:

[0083] Lasso regression is also a linear regression method for dealing with multicollinearity, which realizes variable selection and sparsity through the L1 regularization term (i.e., sum of absolute values penalty).

[0084] 6) Elastic Net Regression:

[0085] Elastic net regression combines the characteristics of ridge regression and lasso regression, and controls the model complexity by using both L1 and L2 regularization terms simultaneously.

[0086] 7) Stepwise Regression:

[0087] Stepwise regression is an automatic variable selection method that constructs a model by gradually adding or deleting independent variables to find the best model.

[0088] 8) Quantile Regression:

[0089] Quantile regression is a regression method for estimating the quantiles of the conditional distribution of the dependent variable, rather than just the mean, and it can provide more information about the relationship between variables.

[0090] In this embodiment, the system can build a human resource efficiency evaluation model that integrates external benchmarks, internal benchmarks, dynamic analysis, and multi-dimensional analysis. This model can evaluate the efficiency of human resources from multiple perspectives and provide a more comprehensive analysis perspective. By using regression analysis and comparative analysis algorithms, the system can more accurately predict and evaluate human resource efficiency, improving the scientificity and accuracy of management decisions. The application of multi-dimensional analysis configuration data enables the system to analyze human resource efficiency from multiple dimensions, identify key influencing factors, and thus optimize human resource management. Through parameter configuration, the model can be adjusted according to new data and market changes to maintain its adaptability and flexibility to meet the changing business needs and market environment. Thus, a comprehensive, dynamic, and multi-dimensional human resource efficiency evaluation framework is provided, which helps to improve the efficiency and effectiveness of human resource management.

[0091] This embodiment provides a human efficiency evaluation method. By dividing business units according to levels or adjusting evaluation indicators according to business content, a human resource efficiency evaluation model with corresponding caliber can be established, realizing the standardization and replicability of the model, and evaluating human resources under a unified standard. Thus, the technical problem that the existing enterprise human efficiency evaluation methods do not form a completely replicable human efficiency evaluation model is solved, and the standardization of enterprise human efficiency evaluation is realized, with stronger applicability.

[0092] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as in the above-mentioned first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 2 , step S20 includes steps S201 to S204:

[0093] Step S201, based on the human resource efficiency evaluation model, perform static analysis on the to-be-evaluated human efficiency index data to obtain a static analysis result;

[0094] Step S202, based on the human resource efficiency evaluation model, perform dynamic analysis on the to-be-evaluated human efficiency index data to obtain a dynamic analysis result;

[0095] Step S203, based on the human efficiency analysis matrix in the human resource efficiency evaluation model, perform multi-dimensional matrix analysis on the to-be-evaluated human efficiency index data to obtain a multi-dimensional analysis result;

[0096] Step S204, according to the static analysis result, dynamic analysis result, and multi-dimensional analysis result, obtain the human efficiency evaluation result.

[0097] Based on the human resource effectiveness evaluation model, the human effectiveness evaluation system conducts static analysis on the human effectiveness indicator data to be evaluated and obtains the static analysis results. The purpose is to evaluate the human resource effectiveness at a specific time point or under specific conditions, so as to quickly understand the current effectiveness status of the organization, help identify the current effectiveness level and existing problems, and provide a basis for immediate decision-making and intervention. Static analysis is an analysis method that evaluates data at a specific time point or under specific conditions without considering dynamic factors that change over time. In the human resource effectiveness evaluation model, static analysis usually focuses on human effectiveness indicators at a certain moment, such as employee satisfaction, productivity, or sales, etc. Then, based on the human resource effectiveness evaluation model, dynamic analysis is conducted on the human effectiveness indicator data to be evaluated, and the dynamic analysis results are obtained. The purpose is to evaluate the changes in human resource effectiveness indicators over time, so as to identify trends, periodicity, and long-term changes, which is crucial for predicting future effectiveness and formulating long-term strategic plans, and providing a basis for long-term planning and strategy adjustment. Dynamic analysis is an analysis method that considers the changes in time series data and is used to evaluate the changing trends and patterns of human resource effectiveness indicators over time. This method can help the organization understand how the effectiveness indicators develop over time and potential seasonal or periodic factors. Then, based on the human effectiveness analysis matrix in the human resource effectiveness evaluation model, the system conducts multi-dimensional matrix analysis on the human effectiveness indicator data to be evaluated and obtains the multi-dimensional analysis results. The multi-dimensional matrix analysis results provide an in-depth understanding of the multi-dimensions of human effectiveness indicators. By conducting multi-dimensional analysis to evaluate human resource effectiveness, identifying key factors affecting effectiveness, and conducting more in-depth quantitative analysis, it helps to discover potential improvement opportunities and optimization strategies, and at the same time can also reveal the interrelationships and impacts between different factors. Multi-dimensional matrix analysis is a method that comprehensively considers data from multiple dimensions for analysis. In human resource effectiveness evaluation, this method can help the organization observe and analyze employees' performance and contributions, as well as the costs borne by the organization from different perspectives. By constructing a human effectiveness analysis matrix, the organization can observe the human effectiveness status of each department or individual, so as to conduct a more comprehensive evaluation. Finally, human resource effectiveness is a multi-dimensional and multi-time-scale phenomenon that requires comprehensive evaluation from static (the state at a certain moment), dynamic (changes over time), and multi-dimensional (interactions of different factors) perspectives. Therefore, integrating the static analysis results, dynamic analysis results, and multi-dimensional analysis results to obtain the human effectiveness evaluation results can help the organization identify the strengths and weaknesses of effectiveness, predict future trends, and discover potential improvement opportunities, and help the organization more accurately understand the effectiveness of human resources and make more reasonable management decisions accordingly.

[0098] It should be noted that the static analysis result is the human resource efficiency analysis result obtained at a specific time point or under certain conditions. The dynamic analysis result is the human resource efficiency analysis result based on time series data, reflecting the change of efficiency indicators over time. The multi-dimensional analysis result is the analysis result based on the human efficiency analysis matrix, reflecting the human efficiency performance and mutual relationship under different dimensions.

[0099] In a feasible implementation manner, step S202 may include steps S2021 to S2023:

[0100] Step S2021, based on the dynamic return analysis algorithm in the human resource efficiency evaluation model, perform dynamic return analysis on the labor cost growth data, profit growth data, and operating income growth data in the to-be-evaluated human efficiency indicator data, and obtain the dynamic return analysis result;

[0101] Step S2022, based on the investment quality analysis algorithm in the human resource efficiency evaluation model, perform investment quality analysis on the labor cost growth data and personnel scale growth data in the to-be-evaluated human efficiency indicator data, and obtain the investment quality analysis result;

[0102] Step S2023, generate the dynamic analysis result according to the dynamic return analysis result and the investment quality analysis result.

[0103] The human resource efficiency evaluation system conducts dynamic benefit analysis on the labor cost growth data, profit growth data, and operating revenue growth data in the human resource efficiency index data to be evaluated based on the dynamic benefit analysis algorithm in the human resource efficiency evaluation model, and obtains the dynamic benefit analysis result. The purpose is to measure the economic benefit of human resource investment, that is, how the growth of labor cost affects profit and operating revenue, so as to evaluate the return on human resource investment. The dynamic benefit analysis result helps to identify the balance point between cost control and benefit growth, provides a basis for cost optimization and benefit improvement, and also provides data support for human resource planning and budget allocation. The dynamic benefit analysis algorithm is a statistical method used to analyze and evaluate the relationship between human resource investment (such as labor cost) and enterprise benefits (such as profit and operating revenue). This method takes into account the time factor and can evaluate the impact of the change of human resource investment over time on enterprise benefits. Then, based on the investment quality analysis algorithm in the human resource efficiency evaluation model, investment quality analysis is conducted on the labor cost growth data and personnel scale growth data in the human resource efficiency index data to be evaluated, and the investment quality analysis result is obtained. The purpose is to evaluate the quality and effect of human resource investment, that is, whether the growth of labor cost is accompanied by the effective growth of the personnel scale, and whether this growth brings the expected benefits to the organization. The investment quality analysis result helps to identify the efficiency and effect of human resource investment, provides a basis for human resource planning and investment decision-making, and also helps to optimize the human resource allocation and improve the competitiveness of the organization. The investment quality analysis algorithm is a method to evaluate the efficiency of human resource investment. It measures the quality and effect of human resource investment by analyzing the relationship between the growth of labor cost and the growth of the personnel scale. This method helps the organization understand whether its human resource investment has led to effective personnel scale growth and whether this growth matches the organizational goals and strategies. Finally, the dynamic benefit analysis result and the investment quality analysis result are combined to generate the dynamic analysis result. The dynamic analysis result can help the organization understand how human resource investment affects benefits and investment quality, and how these factors change over time, so as to provide support for strategic planning and decision-making.

[0104] It should be noted that the dynamic benefit analysis algorithm is an algorithm used to analyze the relationship between human resource input and enterprise benefits. It usually involves time series analysis. The growth data of labor costs refers to the increase in labor costs of an organization over a certain period, including wages, benefits, etc. The growth data of profits refers to the increase in profits of an organization over a certain period. The growth data of operating revenues refers to the increase in operating revenues of an organization over a certain period. The dynamic benefit analysis result is the analysis result obtained based on the dynamic benefit analysis algorithm, reflecting the relationship between human resource input and enterprise benefits. The investment quality analysis algorithm is an algorithm used to evaluate the efficiency and effectiveness of human resource investment. It usually involves the analysis of labor cost and personnel scale data. The growth data of labor costs refers to the increase in labor costs of an organization over a certain period, including wages, benefits, etc. The growth data of personnel scale refers to the increase in the number of employees of an organization over a certain period. The investment quality analysis result is the analysis result obtained based on the investment quality analysis algorithm, reflecting the efficiency and effectiveness of human resource investment. The dynamic analysis result is a comprehensive analysis that combines the dynamic benefit and investment quality analysis results, providing a dynamic view of human resource effectiveness.

[0105] Exemplarily, referring to Figure 3 and Figure 4 , Figure 3 is a schematic diagram of the content of the dynamic benefit analysis result provided in the second embodiment of the present application. Figure 4 is a schematic diagram of the content of the investment quality analysis result provided in the second embodiment of the present application.

[0106] The dynamic analysis dimension of the human resource effectiveness evaluation model includes two main aspects. On the one hand, it longitudinally tracks the changing trend of human resource effectiveness from the time dimension. This is mainly achieved by combining the average number of employees, per capita profit, and per capita operating revenue of a certain business unit in recent years to observe whether the changing trends of the personnel scale and human resource effectiveness data are consistent. If the enterprise's personnel scale continues to expand while the human resource effectiveness indicators decline, it means that the organizational efficiency is also declining. This then requires reexamining the rationality of the enterprise's human resource planning or taking certain measures or means in terms of fixed-positioning and staffing and personnel recruitment.

[0107] On the other hand, it is to judge the human investment return and investment quality from the perspective of dynamic return and the dimension of investment quality. Starting from the perspective of dynamic return means considering the growth rate of labor costs, the growth rate of profits, and the growth rate of operating income in combination to determine whether the three can maintain a certain consistency. Labor costs are rigid, and the improvement of labor efficiency is not achieved by reducing the absolute value of labor costs, but by ensuring that the growth rate of enterprise benefits is greater than the growth rate of labor costs as much as possible. Starting from the perspective of investment quality, the enterprise not only needs to pay attention to the total amount of labor cost input, but also to the investment quality of labor costs. The improvement of investment quality is also the key to promoting the improvement of labor efficiency. Therefore, the talent investment quality of the business unit can be obtained through the comparative analysis of the growth rate of labor costs and the growth rate of the number of employees.

[0108] In this embodiment, through dynamic return analysis and investment quality analysis, the organization can obtain a comprehensive dynamic view of human resource efficiency, including return growth and investment efficiency; the results of dynamic return analysis provide the relationship between the growth of labor costs and the growth of profits and operating income, helping the organization understand the correlation between cost input and return output; the results of investment quality analysis quantify the efficiency of human resource investment, that is, the relationship between the growth of labor costs and the growth of the number of employees, providing data support for human resource planning and budget allocation; by combining the results of dynamic return and investment quality analysis, the organization can make more scientific and reasonable human resource management decisions and optimize human resource allocation.

[0109] In another feasible embodiment, step S203 may include steps S2031 to S2033:

[0110] Step S2031, based on the human efficiency analysis matrix, perform payment level analysis on the average labor cost data in the to-be-evaluated human efficiency index data to obtain the payment level analysis result;

[0111] Step S2032, based on the human efficiency analysis matrix, perform payment efficiency analysis on the labor cost data and operating profit data in the to-be-evaluated human efficiency index data to obtain the payment efficiency analysis result;

[0112] Step S2033, obtain the multi-dimensional analysis result according to the payment level analysis result and the payment efficiency analysis result.

[0113] The human efficiency evaluation system conducts a payment level analysis on the average labor cost data in the human efficiency index data to be evaluated based on the human efficiency analysis matrix, and obtains the payment level analysis result. The purpose is to measure whether the organization's compensation policy is reasonable, whether it can attract and retain the required talents, and whether it conforms to the organization's financial capabilities and market positioning. The payment level analysis result can help the organization understand its compensation competitiveness in the labor market and provide a basis for adjusting the compensation structure and budget. Payment level analysis is an analytical method that evaluates the average labor cost paid by an organization compared with market or industry standards. This method uses the human efficiency analysis matrix to identify and compare compensation data to determine whether the organization's payment level is competitive. Then, based on the human efficiency analysis matrix, a payment efficiency analysis is conducted on the labor cost data and operating profit data in the human efficiency index data to be evaluated, and the payment efficiency analysis result is obtained. The purpose is to measure whether the organization's human resources investment has obtained effective economic returns, that is, whether the input of labor costs has been converted into corresponding operating profits. The payment efficiency analysis result can help the organization understand its human resources utilization efficiency and identify opportunities to improve efficiency and optimize labor costs. Payment efficiency analysis is an analytical method that evaluates the relationship between an organization's labor costs and operating profits. Through the human efficiency analysis matrix, this method can quantify the profit generated per unit of labor cost, thereby evaluating the output efficiency of human resources investment. Finally, the payment level analysis result and the payment efficiency analysis result are combined to obtain a multi-dimensional analysis result. The purpose is to integrate the analysis results of payment level and payment efficiency and provide a comprehensive multi-dimensional perspective to more comprehensively evaluate human resources effectiveness. The multi-dimensional analysis result can help the organization understand the mutual influence between payment level and payment efficiency, and how they jointly affect the organization's human resources effectiveness and overall business performance.

[0114] It should be noted that the human efficiency analysis matrix is a tool or framework for analyzing human resources effectiveness from multiple dimensions, including payment level and payment efficiency. The average labor cost data refers to the cost averaged by the organization for each employee, including salary, benefits, and other related expenses. The payment level analysis result is the analysis result obtained based on the human efficiency analysis matrix, reflecting the difference between the organization's payment level and market or industry standards. The labor cost data refers to the total cost paid by the organization for employees, including salary, benefits, and other related expenses. The operating profit data refers to the operating profit of the organization within a certain period, usually the net amount after subtracting operating costs from operating income. The payment efficiency analysis result is the analysis result obtained based on the human efficiency analysis matrix, reflecting the relationship between the organization's labor costs and operating profits. The multi-dimensional analysis result is a comprehensive analysis that combines the payment level and payment efficiency analysis results, providing a multi-dimensional view of human resources effectiveness.

[0115] In this embodiment, through payment level analysis and payment efficiency analysis, the system can evaluate the effectiveness of human resources from multiple dimensions, providing a more comprehensive analysis perspective; payment level analysis helps the system understand the competitiveness of its compensation policy in the market, while payment efficiency analysis quantifies the return on human resources investment, ensuring the effective utilization of labor costs; through the results of multi-dimensional analysis, the system can identify key influencing factors, thereby optimizing the allocation of human resources and improving overall management efficiency; combining the analysis results of payment level and payment efficiency provides data-based decision support for management, helping them formulate more scientific human resources management strategies.

[0116] In this embodiment, through static, dynamic, and multi-dimensional matrix analysis, the system can evaluate the effectiveness of human resources from different perspectives and dimensions, providing a more comprehensive analysis perspective; using the results of static analysis, dynamic analysis, and multi-dimensional matrix analysis, the system can more accurately predict and evaluate the effectiveness of human resources, improving the scientificity and accuracy of management decisions; the results of multi-dimensional matrix analysis enable the system to analyze the effectiveness of human resources from multiple dimensions, identify key influencing factors, and thus optimize human resources management; by integrating different analysis results, the model can be adjusted according to new data and market changes, maintaining its adaptability and flexibility to adapt to changing business needs and market environments.

[0117] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the applicant's method for evaluating human effectiveness. Based on this technical concept, more forms of simple transformations are within the protection scope of this application.

[0118] This application also provides a human effectiveness evaluation device. Please refer to Figure 5 , and the human effectiveness evaluation device includes:

[0119] A data acquisition module 10 for acquiring data of human effectiveness indicators to be evaluated;

[0120] A human effectiveness evaluation module 20 for performing a human effectiveness evaluation on the data of human effectiveness indicators to be evaluated based on a pre-constructed human resources effectiveness evaluation model, obtaining a human effectiveness evaluation result. The human resources effectiveness evaluation model is constructed based on a preset evaluation analysis framework, and the evaluation analysis framework is applicable to the human effectiveness evaluation of business units at different levels.

[0121] Optionally, the human effectiveness evaluation module 20 is further configured to:

[0122] Acquire historical human effectiveness indicator data and industry human effectiveness indicator data;

[0123] Construct the human resources effectiveness evaluation model according to the historical human effectiveness indicator data and the industry human effectiveness indicator data.

[0124] Optionally, the human effectiveness evaluation module 20 is further configured to:

[0125] Based on a preset regression analysis algorithm, perform a regression analysis on the industry labor efficiency index data to obtain external benchmark configuration data;

[0126] Based on a preset comparative analysis algorithm, compare and analyze the historical labor efficiency index data and the industry labor efficiency index data to obtain internal benchmark configuration data;

[0127] According to the external benchmark configuration data, the internal benchmark configuration data, the preset dynamic analysis configuration data, and the multi-dimensional analysis configuration data, configure the parameters of a preset business unit evaluation and analysis framework to obtain the human resource efficiency evaluation model.

[0128] Optionally, the labor efficiency evaluation module 20 is further configured to:

[0129] Based on the human resource efficiency evaluation model, perform a static analysis on the to-be-evaluated labor efficiency index data to obtain a static analysis result;

[0130] Based on the human resource efficiency evaluation model, perform a dynamic analysis on the to-be-evaluated labor efficiency index data to obtain a dynamic analysis result;

[0131] Based on the labor efficiency analysis matrix in the human resource efficiency evaluation model, perform a multi-dimensional matrix analysis on the to-be-evaluated labor efficiency index data to obtain a multi-dimensional analysis result;

[0132] According to the static analysis result, the dynamic analysis result, and the multi-dimensional analysis result, obtain the labor efficiency evaluation result.

[0133] Optionally, the labor efficiency evaluation module 20 is further configured to:

[0134] Based on the dynamic return analysis algorithm in the human resource efficiency evaluation model, perform a dynamic return analysis on the labor cost growth data, the profit growth data, and the operating income growth data in the to-be-evaluated labor efficiency index data to obtain a dynamic return analysis result;

[0135] Based on the investment quality analysis algorithm in the human resource efficiency evaluation model, perform an investment quality analysis on the labor cost growth data and the personnel scale growth data in the to-be-evaluated labor efficiency index data to obtain an investment quality analysis result;

[0136] According to the dynamic return analysis result and the investment quality analysis result, generate the dynamic analysis result.

[0137] Optionally, the labor efficiency evaluation module 20 is further configured to:

[0138] Based on the human efficiency analysis matrix, perform a payment level analysis on the average labor cost data in the to-be-evaluated human efficiency index data to obtain a payment level analysis result;

[0139] Based on the human efficiency analysis matrix, perform a payment efficiency analysis on the labor cost data and operating profit data in the to-be-evaluated human efficiency index data to obtain a payment efficiency analysis result;

[0140] Obtain the multi-dimensional analysis result according to the payment level analysis result and the payment efficiency analysis result.

[0141] The human efficiency evaluation device provided by this application adopts the human efficiency evaluation method in the above embodiment, and can solve the technical problem that the existing enterprise human efficiency evaluation method does not form a completely replicable human efficiency evaluation model. Compared with the prior art, the beneficial effects of the human efficiency evaluation device provided by this application are the same as those of the human efficiency evaluation method provided by the above embodiment, and other technical features in the human efficiency evaluation device are the same as the features disclosed in the method of the above embodiment, and will not be elaborated here.

[0142] This application provides a human efficiency evaluation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the human efficiency evaluation method in the first embodiment above.

[0143] Next, refer to Figure 6 , which shows a schematic structural diagram of a human efficiency evaluation device suitable for implementing the embodiments of this application. The human efficiency evaluation device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The human efficiency evaluation device shown is only an example and should not impose any limitation on the functions and usage scope of the embodiments of this application.

[0144] As Figure 6As shown, the human efficiency evaluation device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 into the random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the human efficiency evaluation device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the human efficiency evaluation device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a human efficiency evaluation device with various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems can be alternatively implemented or had.

[0145] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above functions defined in the methods of the embodiments disclosed in the present application are executed.

[0146] The human efficiency evaluation device provided by the present application adopts the human efficiency evaluation method in the above embodiments, and can solve the technical problem that the existing enterprise human efficiency evaluation methods do not form a completely replicable human efficiency evaluation model. Compared with the prior art, the beneficial effects of the human efficiency evaluation device provided by the present application are the same as those of the human efficiency evaluation method provided by the above embodiments, and the other technical features in the human efficiency evaluation device are the same as the features disclosed in the method of the previous embodiment, and will not be elaborated here.

[0147] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0148] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0149] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the human efficiency evaluation method in the above embodiments.

[0150] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems, or devices, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or combined with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium can be transmitted by any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0151] The above computer-readable storage medium can be included in the human efficiency evaluation device; it can also exist separately without being assembled into the human efficiency evaluation device.

[0152] The above computer-readable storage medium carries one or more programs. When the above one or more programs are executed by the human efficiency evaluation device, the human efficiency evaluation device is caused to:

[0153] Obtain the data of the human efficiency index to be evaluated;

[0154] Based on a pre - constructed human resource efficiency evaluation model, perform a human resource efficiency evaluation on the to - be - evaluated human resource efficiency index data to obtain a human resource efficiency evaluation result. The human resource efficiency evaluation model is constructed based on a preset evaluation and analysis framework, and the evaluation and analysis framework is applicable to the human resource efficiency evaluation of business units at different levels.

[0155] Computer program code for performing the operations of the present application can be written in one or more programming languages or combinations thereof. The above - mentioned programming languages include object - oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0156] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware - based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0157] The modules involved in the embodiments of the present application can be implemented in software or in hardware. In some cases, the name of the module does not constitute a limitation on the unit itself.

[0158] The readable storage medium provided by this application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned human efficiency evaluation method, and can solve the technical problem that the existing enterprise human efficiency evaluation methods have not formed a completely replicable human efficiency evaluation model. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by this application are the same as those of the human efficiency evaluation method provided by the above embodiments, and will not be elaborated here.

[0159] This application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the steps of the human efficiency evaluation method as described above.

[0160] The computer program product provided by this application can solve the technical problem that the existing enterprise human efficiency evaluation methods have not formed a completely replicable human efficiency evaluation model. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as those of the human efficiency evaluation method provided by the above embodiments, and will not be elaborated here.

[0161] The above are only partial embodiments of this application, and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application by using the content of the specification and drawings of this application, or direct / indirect applications in other related technical fields are included in the patent protection scope of this application.

Claims

1. A human efficiency evaluation method, characterized in that: The method comprises: Obtain the human efficiency indicator data to be evaluated; Based on a pre-built human resource effectiveness evaluation model, a human efficiency evaluation is performed on the human efficiency indicator data to be evaluated to obtain a human efficiency evaluation result. The human resource effectiveness evaluation model is built based on a preset evaluation and analysis framework, and the evaluation and analysis framework is suitable for human efficiency evaluation of business units at different levels.

2. The method according to claim 1, characterized in that Before the step of performing human efficiency evaluation on the human efficiency index data to be evaluated based on the pre-built human resource effectiveness evaluation model and obtaining the human efficiency evaluation result, the step further includes: Obtain historical labor efficiency index data and industry labor efficiency index data; Based on the evaluation and analysis framework, the human resource effectiveness evaluation model is constructed according to the historical labor efficiency index data and the industry labor efficiency index data.

3. The method according to claim 2, characterized in that The steps of constructing the human resource effectiveness evaluation model include: Based on a preset regression analysis algorithm, regression analysis is performed on the industry labor efficiency index data to obtain external benchmark configuration data; Based on a preset comparative analysis algorithm, the historical labor efficiency index data and the industry labor efficiency index data are compared and analyzed to obtain internal benchmark configuration data; According to the external benchmark configuration data, the internal benchmark configuration data, the preset dynamic analysis configuration data and the multi-dimensional analysis configuration data, the parameters of the preset evaluation and analysis framework are configured to obtain the human resource effectiveness evaluation model.

4. The method according to claim 1, characterized in that The step of performing human efficiency evaluation on the human efficiency indicator data to be evaluated based on the pre-built human resource effectiveness evaluation model to obtain the human efficiency evaluation result comprises: Based on the human resource effectiveness evaluation model, static analysis is performed on the human efficiency index data to be evaluated to obtain static analysis results; Based on the human resource effectiveness evaluation model, dynamically analyzing the human efficiency index data to be evaluated to obtain dynamic analysis results; Based on the human efficiency analysis matrix in the human resource effectiveness evaluation model, a multidimensional matrix analysis is performed on the human efficiency indicator data to be evaluated to obtain a multidimensional analysis result; The human efficiency evaluation result is obtained according to the static analysis result, the dynamic analysis result and the multi-dimensional analysis result.

5. The method according to claim 4, characterized in that The step of performing static analysis on the human efficiency index data to be evaluated based on the human resource effectiveness evaluation model to obtain the static analysis result comprises: Based on the dynamic benefit analysis algorithm in the human resource effectiveness evaluation model, a dynamic benefit analysis is performed on the labor cost growth data, profit growth data, and operating income growth data in the human efficiency index data to be evaluated to obtain a dynamic benefit analysis result; Based on the investment quality analysis algorithm in the human resource effectiveness evaluation model, an investment quality analysis is performed on the labor cost growth data and the staff size growth data in the human efficiency index data to be evaluated to obtain an investment quality analysis result; The dynamic analysis result is generated according to the dynamic return analysis result and the investment quality analysis result.

6. The method according to claim 4, characterized in that The step of performing a multidimensional matrix analysis on the human efficiency index data to be evaluated based on the human efficiency analysis matrix in the human resource effectiveness evaluation model to obtain a multidimensional analysis result comprises: Based on the labor efficiency analysis matrix, performing payment level analysis on the average labor cost data in the labor efficiency index data to be evaluated to obtain a payment level analysis result; Based on the labor efficiency analysis matrix, performing payment efficiency analysis on the labor cost data and operating profit data in the labor efficiency indicator data to be evaluated to obtain a payment efficiency analysis result; The multi-dimensional analysis result is obtained according to the payment level analysis result and the payment efficiency analysis result.

7. A human efficiency evaluation device, characterized in that: The device comprises: A data acquisition module is used to obtain the human efficiency index data to be evaluated; The human efficiency evaluation module is used to perform human efficiency evaluation on the human efficiency indicator data to be evaluated based on a pre-built human efficiency evaluation model to obtain a human efficiency evaluation result. The human efficiency evaluation model is built based on a preset evaluation and analysis framework, and the evaluation and analysis framework is suitable for human efficiency evaluation of business units at different levels.

8. A human efficiency evaluation device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the human efficiency evaluation method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the human efficiency evaluation method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the human efficiency evaluation method according to any one of claims 1 to 6 are implemented.

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