CN-122022556-A - Enterprise employee dynamic point management method, device, equipment and medium

Abstract

The invention discloses an enterprise employee dynamic point management method which comprises the steps of obtaining strategic decision information of an enterprise and capability qualification information of an employee, inputting the strategic decision information into a pre-trained linear regression model, identifying skill demand signals of the enterprise, calculating skill attenuation factors and project value attenuation factors according to the skill demand signals, calculating a fixed integral value based on the learning authentication information, calculating a first dynamic integral value based on the history project completion record and the project value attenuation factors, calculating a second dynamic integral value based on the skill certificate information and the skill attenuation factors, and integrating the fixed integral value, the first dynamic integral value and the second dynamic integral value to obtain a total integral value of the employee. The invention can realize scientific calculation of employee points from fixed and dynamic multidimensional, realize real-time synchronization of employee skill evaluation and enterprise requirements, and is beneficial to reasonable resource allocation of enterprises.

Inventors

• LIU PEICHENG
• WANG FANG

Assignees

• 国家能源集团国源电力有限公司

Dates

Publication Date

20260512

Application Date

20260107

Claims (10)

1. 1. A method for dynamic point management of enterprise employees, comprising: The method comprises the steps of obtaining strategic decision information of an enterprise and capability qualification information of staff, wherein the strategic decision information comprises enterprise business data, market competition data and strategic planning documents, and the capability qualification information comprises academic authentication information, history project completion records and skill certificate information; Inputting the strategic decision information into a pre-trained linear regression model to identify skill demand signals of an enterprise, wherein the skill demand signals comprise skill demand types and demand intensity; Calculating a skill attenuation factor and a project value attenuation factor according to the skill demand signal, wherein the skill attenuation factor is used for representing the contribution degree of the skill corresponding to the skill certificate to the current strategic demand of the enterprise, and the project value attenuation factor is used for representing the contribution degree of the historical project experience of the staff to the current strategic demand of the enterprise; calculating a fixed integral value based on the academic authentication information, calculating a first dynamic integral value based on the history project completion record and the project value decay factor, and calculating a second dynamic integral value based on the skill certification information and the skill decay factor; and integrating the fixed integral value, the first dynamic integral value and the second dynamic integral value to obtain a total integral value of the staff.
2. 2. The method for dynamic point management of enterprise employee in accordance with claim 1, wherein said inputting the strategic decision information into a pre-trained linear regression model identifies skill need signals for the enterprise, comprising: acquiring post recruitment demand frequency in the enterprise business data, and carrying out normalization processing on the post recruitment demand frequency to generate a demand frequency coefficient; obtaining the skill salary premium rate in the market competition data, carrying out logarithmic conversion on the skill salary premium rate, and generating a premium coefficient; acquiring the keyword frequency in the strategic planning document, carrying out weighted statistics on the keyword frequency, and generating a strategic weight coefficient; And inputting the demand frequency coefficient, the premium coefficient and the strategic weight coefficient into a pre-trained linear regression model, and outputting skill demand signals of enterprises.
3. 3. An enterprise employee dynamic point management method as claimed in claim 1, wherein the training process of the linear regression model comprises: Respectively extracting a historical demand frequency coefficient, a historical overflow coefficient and a historical strategic weight coefficient of a historical strategic period from enterprise business data, market competition data and a strategic planning document to serve as model input vectors; taking the actual skill demand intensity value in the history period as the target output quantity of the model; And in the training process, a least square method is adopted to fit model parameters, the average absolute error of a model predicted value and an actual value is calculated, and when the average absolute error is smaller than a preset tolerance threshold, the model is judged to be qualified in training.
4. 4. An enterprise employee dynamic point management method as claimed in claim 1, wherein said calculating a first dynamic point value based on said historical project completion record and said project value decay factor comprises: Presetting a first initial integral value of the history item completion record; And multiplying the first initial integral value by the item value attenuation factor to obtain a first dynamic integral value.
5. 5. An enterprise employee dynamic point management method as claimed in claim 1, wherein said calculating a second dynamic point value based on said skill certificate information and said skill decay factor comprises: presetting a second initial integral value of the skill certificate information; And multiplying the second initial integral value by the skill decay factor to obtain a second dynamic integral value.
6. 6. An enterprise employee dynamic point management method as claimed in claim 1, wherein the method further comprises: Constructing a skill mastery density distribution diagram of all staff in an enterprise; Generating a skill saturation early warning signal when the mastery density of a certain skill in the skill mastery density distribution diagram exceeds a preset threshold value and the skill demand signal of the skill is continuously reduced; And correcting the skill attenuation factor and the project value attenuation factor according to the skill saturation early warning signal.
7. 7. An enterprise employee dynamic point management method as defined in claim 6, wherein the method further comprises: Monitoring the skill demand signal in real time, and calculating a historical demand intensity mean value in a preset period; if the skill demand signal is greater than the historical demand intensity average value and the intensity change rate of the skill demand signal is greater than a preset change rate threshold value during the skill saturation early warning signal activation period, generating a skill demand rebound signal; and correcting the skill attenuation factor and the project value attenuation factor based on the skill need rebound signal.
8. 8. An enterprise employee dynamic point management apparatus, comprising: The system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring strategic decision information of an enterprise and capability qualification information of staff, the strategic decision information comprises enterprise business data, market competition data and strategic planning documents, and the capability qualification information comprises academic authentication information, history project completion records and skill certificate information; The skill demand analysis module is used for inputting the strategic decision information into a pre-trained linear regression model and identifying skill demand signals of enterprises, wherein the skill demand signals comprise skill demand types and demand intensity; The skill attenuation factor is used for representing the contribution degree of the skill corresponding to the skill certificate to the current strategic requirements of the enterprise, and the project value attenuation factor is used for representing the contribution degree of the historical project experience of staff to the current strategic requirements of the enterprise; A first integral calculation module for calculating a fixed integral value based on the academic authentication information, calculating a first dynamic integral value based on the history item completion record and the item value decay factor, and calculating a second dynamic integral value based on the skill certification information and the skill decay factor; And the second integral calculation module is used for integrating the fixed integral value, the first dynamic integral value and the second dynamic integral value to obtain a total integral value of staff.
9. 9. An electronic device, comprising: A memory for storing a computer program; a processor for executing the computer program; wherein the processor, when executing the computer program, implements an enterprise employee dynamic point management method as claimed in any one of claims 1 to 7.
10. 10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which when executed implements the enterprise employee dynamic point management method according to any one of claims 1 to 7.

Description

Enterprise employee dynamic point management method, device, equipment and medium Technical Field The present invention relates to the field of point processing technologies, and in particular, to a method, an apparatus, a device, and a medium for dynamic point management of enterprise staff. Background In knowledge-intensive organizations such as large-scale scientific enterprises and manufacturing groups, staff skill assessment and culture resource allocation are core links of human resource management, and a traditional talent assessment system usually adopts a static score system, namely, a fixed weight is set according to elements such as academic backgrounds, historical project experiences, skill certificates and the like, and staff capability scores are calculated regularly. The traditional architecture based on the static rules cannot realize real-time synchronization of employee skill evaluation and enterprise demands, so that integral management is difficult to comprehensively reflect employee capability, and enterprise management efficiency is affected. Disclosure of Invention The embodiment of the invention provides a dynamic score management method for enterprise staff, which can realize scientific calculation of staff score from fixed and dynamic multidimensional, realize real-time synchronization of staff skill evaluation and enterprise demand and is beneficial to reasonable allocation of resources by enterprises. In a first aspect, an embodiment of the present invention provides a method for dynamically managing points of employees of an enterprise, including: The method comprises the steps of obtaining strategic decision information of an enterprise and capability qualification information of staff, wherein the strategic decision information comprises enterprise business data, market competition data and strategic planning documents, and the capability qualification information comprises academic authentication information, history project completion records and skill certificate information; Inputting the strategic decision information into a pre-trained linear regression model to identify skill demand signals of an enterprise, wherein the skill demand signals comprise skill demand types and demand intensity; Calculating a skill attenuation factor and a project value attenuation factor according to the skill demand signal, wherein the skill attenuation factor is used for representing the contribution degree of the skill corresponding to the skill certificate to the current strategic demand of the enterprise, and the project value attenuation factor is used for representing the contribution degree of the historical project experience of the staff to the current strategic demand of the enterprise; calculating a fixed integral value based on the academic authentication information, calculating a first dynamic integral value based on the history project completion record and the project value decay factor, and calculating a second dynamic integral value based on the skill certification information and the skill decay factor; and integrating the fixed integral value, the first dynamic integral value and the second dynamic integral value to obtain a total integral value of the staff. Further, the inputting the strategic decision information into a pre-trained linear regression model, and identifying the skill requirement signal of the enterprise includes: acquiring post recruitment demand frequency in the enterprise business data, and carrying out normalization processing on the post recruitment demand frequency to generate a demand frequency coefficient; obtaining the skill salary premium rate in the market competition data, carrying out logarithmic conversion on the skill salary premium rate, and generating a premium coefficient; acquiring the keyword frequency in the strategic planning document, carrying out weighted statistics on the keyword frequency, and generating a strategic weight coefficient; And inputting the demand frequency coefficient, the premium coefficient and the strategic weight coefficient into a pre-trained linear regression model, and outputting skill demand signals of enterprises. Further, the training process of the linear regression model includes: Respectively extracting a historical demand frequency coefficient, a historical overflow coefficient and a historical strategic weight coefficient of a historical strategic period from enterprise business data, market competition data and a strategic planning document to serve as model input vectors; taking the actual skill demand intensity value in the history period as the target output quantity of the model; And in the training process, a least square method is adopted to fit model parameters, the average absolute error of a model predicted value and an actual value is calculated, and when the average absolute error is smaller than a preset tolerance threshold, the model is judged to be qualified in training. Further, the c