Digital human resource management method and system

Abstract

The invention discloses a digital human resource management method and system, and relates to the field of human resource management. According to the method, human resource parameters and production resource parameters of all production departments in an organization structure in a plurality of continuous production quarters are obtained by constructing an enterprise organization structure diagram, and human resource configuration twist degrees of all the production departments are calculated according to the obtained resource parameters; evaluating the human resource configuration efficiency of the production department by taking the obtained human resource configuration torsion degree as a representation value of the human resource configuration efficiency, and setting a human resource configuration torsion degree threshold value, correcting and adjusting the human resource parameters of the production departments which do not meet a set threshold value in the production quarters and the production resource parameters, and recalculating to obtain the human resource configuration twist degrees of the production departments in a plurality of continuous production quarters according to the corrected and adjusted resource parameters, and constructing a correction and adjustment effect evaluation function to evaluate the correction and adjustment effect.

Description

Technical Field

[0001] The present invention relates to the field of human resource management, and particularly to a digital human resource management method and system. Background Art

[0002] The digitization of human resources is achieved by introducing advanced technical means such as big data analysis, artificial intelligence, etc., to improve the efficiency of human resource management. Specific application scenarios include human resource demand forecasting, recruitment process optimization, training effect evaluation, etc. Through big data analysis technology, enterprises can accurately predict future human resource needs and provide a scientific basis for recruitment plans; intelligent recruitment systems can automatically screen resumes, improving recruitment efficiency and quality; data analysis technology can also track the training progress and effects of employees, providing a basis for the adjustment and optimization of training plans.

[0003] Formulating a matching recruitment plan according to the development status of an enterprise is one of the daily tasks of the human resource management department. Traditional human resource demand forecasting mainly relies on the experience judgment and manual estimation of managers, lacking quantitative analysis methods and scientific forecasting models, making it difficult to accurately grasp the medium- and long-term human resource demand change trends of enterprises. Furthermore, it is impossible to dynamically analyze the human resource demand changes of enterprises, resulting in the inability of enterprises to reasonably allocate labor according to production needs. Especially for front-line functional departments in manufacturing, due to the large mobility of manufacturing personnel, the uncertainty of human resource demand changes is difficult to estimate, further increasing the difficulty of human resource allocation. Therefore, how to rationally utilize big data analysis technology under the background of big data, analyze the current situation of human resource supply and demand in enterprises, accurately match the talent demand and supply of enterprises, and provide decision-making references for human resource optimization and allocation is a technical problem that the current human resource management departments of enterprises urgently need to solve. For this reason, we propose a digital human resource management method and system. Summary of the Invention

[0004] The main object of the present invention is to provide a digital human resource management method and system, which can effectively solve the problems in the background art.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A digital human resource management method includes:

[0007] Step 1: Construct an enterprise organizational structure diagram, and obtain the human resource parameters and production resource parameters of each production department in the organizational structure in a continuous number of production quarters. Among them, the human resource parameters include the average salary of employees and the number of employees; the production resource parameters include the product output, sales volume, and unit sales price of products.

[0008] Step 2: Calculate the distortion degree of human resource allocation for each production department based on the obtained resource parameters, and use the obtained distortion degree of human resource allocation as a characterization value of the human resource allocation efficiency of the production department to evaluate the human resource allocation efficiency of the production department. The evaluation principle is: the larger the absolute value of the distortion degree of human resource allocation, the lower the human resource allocation efficiency; on the contrary, the smaller the absolute value of the distortion degree of human resource allocation, the higher the human resource allocation efficiency.

[0009] The formula for calculating the distortion degree of human resource allocation in the production department is:

[0010]

[0011] In the formula, σ is the product elasticity coefficient; β is the output elasticity coefficient; P ij is the unit price of product sales of the jth production department in the ith production quarter; Y ij is the product output of the jth production department in the ith production quarter; L ij is the number of employees in the jth production department in the ith production quarter; W ij is the average wage of employees in the jth production department in the ith production quarter; λ ij is the distortion degree of human resource allocation of the jth production department in the ith production quarter; the formula for calculating the output elasticity coefficient β is: β = Q / W, where Q represents the change rate of the product output of the production department within a fixed time dimension; W represents the change rate of the employee wage expenditure of the production department within a fixed time dimension.

[0012] Step 3: Set the threshold of the distortion degree of human resource allocation, and correct and adjust the human resource parameters and the production resource parameters of the production department that do not meet the set threshold in the current production quarter.

[0013] Step 4: According to the corrected and adjusted resource parameters, recalculate and obtain the distortion degree of human resource allocation λ kq of each production department within a continuous number of production quarters, where λ kq represents the distortion degree of human resource allocation of the qth production department in the kth production quarter after the resource parameters are corrected and adjusted;

[0014] Step 5: According to the obtained distortion degree of human resource allocation λ kq , construct an evaluation function f(λ kq ) of the correction and adjustment effect, and evaluate the correction and adjustment effect according to the value of the function f(λ kq ). The evaluation principle is:

[0015] When f(λ kq ) = 1, it indicates that the correction and adjustment of the resource parameters have achieved a positive effect;

[0016] When f(λ kq ) = 0, indicating that the effect of modifying and adjusting the resource parameters is not obvious;

[0017] When f(λ kq )=-1, it indicates that the correction and adjustment of resource parameters have the opposite effect.

[0018] Function f(λ kq ) is expressed as:

[0019]

[0020] Wherein, K is a constant greater than 0.

[0021] Step 6: When the correction adjustment effect evaluation function f(λ kq ) is not 1, the resource parameters are adjusted again to f(λ kq )=1.

[0022] A digital human resources management system, comprising:

[0023] An organizational structure building block for building enterprise organizational charts;

[0024] A resource parameter acquisition module for acquiring human resource parameters and production resource parameters of each production department;

[0025] A resource parameter data processing module for calculating the human resource allocation distortion of each production department, wherein the resource parameter data processing module is further used to evaluate the human resource allocation efficiency of the production department by taking the obtained human resource allocation distortion as a representation value of human resource allocation efficiency;

[0026] A resource parameter correction module for setting a threshold value of distortion in human resource allocation and correcting and adjusting the human resource parameters and production resource parameters of the production department that do not meet the set threshold value in the current production quarter;

[0027] A correction adjustment effect evaluation module for evaluating the correction adjustment effect, wherein the correction adjustment effect evaluation module evaluates the correction adjustment effect according to the obtained human resource configuration distortion λ kq , construct the correction adjustment effect evaluation function f(λ kq ), according to the function f(λ kq ) is used to evaluate the correction and adjustment effect.

[0028] The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0029] The present invention has the following beneficial effects:

[0030] Compared with the prior art, by constructing an enterprise organizational structure diagram, obtaining the human resource parameters and production resource parameters of each production department in the organizational structure in a number of consecutive production quarters, calculating the human resource allocation distortion degree of each production department according to the obtained resource parameters, using the obtained human resource allocation distortion degree as a characterization value of the human resource allocation efficiency, evaluating the human resource allocation efficiency of the production department, setting a human resource allocation distortion degree threshold, correcting and adjusting the human resource parameters and the production resource parameters of the production department that does not meet the set threshold in the current production quarter, recalculating and obtaining the human resource allocation distortion degree of each production department within a number of consecutive production quarters according to the corrected and adjusted resource parameters, constructing a correction and adjustment effect evaluation function to evaluate the correction and adjustment effect, and when the value of the correction and adjustment effect evaluation function is not 1, correcting and adjusting the resource parameters again; quantitatively analyzing the human resource allocation of the department, so as to accurately grasp the changing trend of the human resource demand of the front-line functional departments of the manufacturing enterprise, and then dynamically analyzing the changing of the enterprise's human resource demand, so that the enterprise can reasonably allocate the labor resources of relevant departments according to the production demand. Brief Description of the Drawings

[0031] Figure 1 is a flowchart of a digital human resource management method of the present invention;

[0032] Figure 2 is a schematic structural diagram of a digital human resource management system of the present invention. Detailed Embodiment

[0033] The following further describes the present invention in conjunction with the detailed embodiment. Among them, the drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and should not be construed as a limitation of the present invention. In order to better illustrate the detailed embodiment of the present invention, some components in the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0034] In this embodiment, taking the production center of a manufacturing enterprise as an example, the technical solution of the present invention is described. Among them, the production center of the manufacturing enterprise includes a number of production lines, each production line is used as an independent production department, and each independent production department is equipped with a number of employees. It is assumed that the products produced by each production department are of the same type, but the product quality grades are different, and the selling prices of products with different quality grades in the market are also different. How to use the technical solution of the present invention to reasonably allocate the human resources of each production department, the specific implementation process includes the following steps:

[0035] Step 1: Construct the enterprise organizational structure diagram to obtain the basic organizational situation of the production department, such as the number of production departments, the resource allocation situation of each department, the number of employees allocated, the proportion of employees with different working years, etc.

[0036] Step 2: Obtain the human resource parameters and production resource parameters of each production department in the organizational structure in a number of consecutive production quarters;

[0037] Among them, the human resource parameters include the average salary of employees and the number of employees; the production resource parameters include the product output, sales volume, and unit sales price of products.

[0038] Step 3: Calculate the distortion degree of human resource allocation of each production department according to the obtained resource parameters. The calculation formula is:

[0039]

[0040] In the formula, σ is the product elasticity coefficient; β is the output elasticity coefficient; P ij is the unit sales price of the product of the jth production department in the ith production quarter; Y ij is the product output of the jth production department in the ith production quarter; L ij is the number of employees in the jth production department in the ith production quarter; W ij is the average salary of employees in the jth production department in the ith production quarter; λ ij is the distortion degree of human resource allocation of the jth production department in the ith production quarter; the calculation formula of the output elasticity coefficient β is: β = Q / W. In the formula, Q represents the change rate of the product output of the production department within a fixed time dimension; W represents the change rate of the employee salary expenditure of the production department within a fixed time dimension.

[0041] Step 4: Use the obtained distortion degree of human resource allocation as a characterization value of the human resource allocation efficiency of the production department to evaluate the human resource allocation efficiency of the production department;

[0042] The evaluation principle is: the larger the absolute value of the distortion degree of human resource allocation, the lower the human resource allocation efficiency, and further indicates that the current human resource allocation of this production department needs to be adjusted more;

[0043] On the contrary, the smaller the absolute value of the distortion degree of human resource allocation, the higher the human resource allocation efficiency; through this step, the current situation of the human resource allocation efficiency of each production department can be determined. For human resource managers, they can formulate human resource allocation strategies according to the current human resource allocation efficiency to optimize the human resource distribution structure of each production department of the enterprise.

[0044] Step 5: Set the threshold of human resource allocation distortion. For a production department that does not meet the set threshold in a production quarter, it indicates that the human resource allocation efficiency of this department is low, and it is necessary to adjust the resource parameters to improve the human resource allocation efficiency. Therefore, it is necessary to first correct and adjust the human resource parameters and production resource parameters of this production department;

[0045] It should be noted that when correcting and adjusting the human resource parameters and production resource parameters, a preliminary strategic adjustment plan can be formulated first according to the index parameters involved in the human resource allocation distortion calculation formula, such as adjusting the number of employees in this production department, the average salary of employees, adjusting the quality grade of the products produced, adjusting the production volume plan, etc.;

[0046] According to the formula: It can be seen that for a production department, if it is necessary to reduce the value of the human resource allocation distortion λ ij The preliminary adjustment strategies that can be taken at least include the following:

[0047] Strategy 1: Increase the number of employees L in the production department ij To reduce the human resource allocation distortion;

[0048] Strategy 2: Increase the average salary W of employees in the production department ij To reduce the human resource allocation distortion;

[0049] Strategy 3: Reduce the unit selling price P of the products in the production department ij To reduce the human resource allocation distortion;

[0050] It should be noted that in the actual process, the quality grade of the products produced can be reduced. For example, if this production department has been producing products of high-quality grade specifications before, after adjustment, this production line can be adjusted to produce products of medium-quality grade specifications. Since the unit selling prices of products of different qualities are different, and for the same product, the unit selling price of products of high-quality grade specifications is higher than that of products of medium-quality grade specifications, therefore, by changing the grade specifications of the products produced, the adjustment of the unit selling price of the products is realized;

[0051] Strategy 4: Change the production plan and reduce the product output Y of this production department ij To reduce the human resource allocation distortion;

[0052] For an enterprise, which adjustment strategy to adopt specifically needs to be further determined under the comprehensive consideration of the combined effects of various factors such as the enterprise's production plan, the current business situation, and market feedback;

[0053] Step 6: According to the corrected and adjusted resource parameters, recalculate and obtain the distortion degree λ of the human resource allocation in each production department within several consecutive production quarters. kq , λ kq represents the distortion degree of the human resource allocation in the q-th production department in the k-th production quarter after the correction and adjustment of the resource parameters;

[0054] Step 7: According to the obtained distortion degree λ of the human resource allocation kq , construct an evaluation function f(λ kq ) for the correction and adjustment effect;

[0055] The specific expression of the function f(λ kq ) is:

[0056]

[0057] In the formula, K is a constant greater than 0.

[0058] Step 8: Evaluate the correction and adjustment effect according to the value of the function f(λ kq ), and the evaluation principle is:

[0059] When f(λ kq ) = 1, it indicates that the correction and adjustment of the resource parameters have achieved a positive effect, further indicating that the adopted adjustment strategy has played a positive role, and the human resource allocation efficiency of this production department shows an improving trend;

[0060] When f(λ kq ) = 0, it indicates that the effect of the correction and adjustment of the resource parameters is not obvious, further indicating that the adopted adjustment strategy has little effect on improving the human resource allocation efficiency of this production department, and the current adopted adjustment strategy is an ineffective strategy;

[0061] When f(λ kq ) = -1, it indicates that the correction and adjustment of the resource parameters have achieved a negative effect, further indicating that the adopted adjustment strategy has played a negative role, and the human resource allocation efficiency of this production department shows a deteriorating trend.

[0062] Step 9: When the value of the correction and adjustment effect evaluation function f(λ kq ) is not 1, it means that the adopted adjustment strategy cannot improve the human resource allocation efficiency of this production department, further indicating that the adopted adjustment strategy is ineffective and even plays a negative role. Therefore, it is necessary to re-evaluate the human resource allocation efficiency of this production department and re-correct and adjust the resource parameters according to the evaluation results.

[0063] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification is only to illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A digital human resource management method, characterized in that, Including: Step 1: Construct an enterprise organizational structure diagram, and obtain the human resource parameters and production resource parameters of each production department in the organizational structure in a number of consecutive production quarters. Among them, the human resource parameters include the average employee salary and the number of employees; the production resource parameters include the product output, sales volume, and product unit selling price. Step 2: Calculate the human resource allocation distortion degree of each production department according to the obtained resource parameters, and use the obtained human resource allocation distortion degree as a characterization value of the human resource allocation efficiency of the production department to evaluate the human resource allocation efficiency of the production department. The evaluation principle is: the larger the absolute value of the human resource allocation distortion degree, the lower the human resource allocation efficiency; on the contrary, the smaller the absolute value of the human resource allocation distortion degree, the higher the human resource allocation efficiency. Step 3: Set a threshold for the human resource allocation distortion degree, and correct and adjust the human resource parameters and the production resource parameters of the production departments that do not meet the set threshold in the current production quarter.

2. The digital human resource management method according to claim 1, characterized in that The calculation formula for the human resource allocation distortion degree of the production department is: Where, σ is the product elasticity coefficient; β is the output elasticity coefficient; P ij is the unit sales price of the product of the j-th production department in the i-th production quarter; Y ij is the output of the product of the j-th production department in the i-th production quarter; L ij is the number of employees in the j-th production department in the i-th production quarter; W ij is the average wage of employees in the j-th production department in the i-th production quarter; λ ij is the distortion degree of human resource allocation in the j-th production department in the i-th production quarter.

3. A digital human resource management method according to claim 1, characterized in that, The method further includes: Step 4: According to the corrected and adjusted resource parameters, recalculate and obtain the distortion degree λ of the human resource allocation of each production department within several consecutive production quarters kq , λ kq represents the distortion degree of the human resource allocation of the q-th production department in the k-th production quarter after the correction and adjustment of the resource parameters; Step Five: Based on the obtained distortion degree of human resource allocation λ kq , construct an evaluation function f(λ kq ) for the correction and adjustment effect, and evaluate the correction and adjustment effect according to the value of the function f(λ kq ). The evaluation principle is as follows: When f(λ kq ) = 1, it indicates that a positive effect has been achieved in the correction and adjustment of resource parameters; When f(λ kq ) = 0, it indicates that the effect of correcting and adjusting the resource parameters is not obvious; When f(λ kq ) = -1, it indicates that the correction adjustment of the resource parameters has a reverse effect.

4. A digital human resource management method according to claim 3, characterized in that The function f(λ kq ) has the following specific expression: In the formula, K is a constant greater than 0.

5. A digital human resource management method according to claim 3, characterized in that The method further includes: Step 6: When the value of the correction and adjustment effect evaluation function f(λ kq ) is not 1, the resource parameters are corrected and adjusted again until f(λ kq ) = 1.

6. A digital human resource management method according to claim 2, characterized in that, The calculation formula for the output elasticity coefficient β is: β = Q / W. In the formula, Q represents the change rate of the product output of the production department within a fixed time dimension; W represents the change rate of the employee salary expenditure of the production department within a fixed time dimension.

7. A digital human resource management system, characterized in that: The system is used to implement the steps of a digital human resource management method described in any one of claims 1-6, and includes: An organizational structure construction module for constructing an enterprise organizational structure diagram; A resource parameter acquisition module for obtaining the human resource parameters and production resource parameters of each production department in the organizational structure in a number of consecutive production quarters. Among them, the human resource parameters include the average employee salary and the number of employees; the production resource parameters include the product output, sales volume, and product unit selling price. A resource parameter data processing module for calculating the human resource allocation distortion degree of each production department. The resource parameter data processing module is also used to use the obtained human resource allocation distortion degree as a characterization value of the human resource allocation efficiency of the production department to evaluate the human resource allocation efficiency of the production department. The evaluation principle is: the larger the absolute value of the human resource allocation distortion degree, the lower the human resource allocation efficiency; on the contrary, the smaller the absolute value of the human resource allocation distortion degree, the higher the human resource allocation efficiency. A resource parameter correction module for setting a threshold for the human resource allocation distortion degree and correcting and adjusting the human resource parameters and the production resource parameters of the production departments that do not meet the set threshold in the current production quarter. A correction adjustment effect evaluation module for evaluating the correction adjustment effect, wherein the correction adjustment effect evaluation module evaluates the correction adjustment effect according to the obtained human resource configuration distortion λ kq , construct the correction adjustment effect evaluation function f(λ kq ), according to the function f(λ kq ) is used to evaluate the correction and adjustment effect, and the evaluation principle is: When f(λ kq ) = 1, it indicates that the correction and adjustment of the resource parameters have achieved a positive effect; When f(λ kq ) = 0, it indicates that the effect of correcting and adjusting the resource parameters is not obvious; When f(λ kq ) = -1, it indicates that the correction adjustment of the resource parameters has a reverse effect.

8. A digital human resource management system according to claim 7, characterized in that, The system includes a memory, a processor, and a computer program stored on the memory and executable on the processor. Among them, when the processor executes the program, it can implement the steps of a digital human resource management method described in any one of claims 1-6.

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