CN114066207A - Performance assessment method and system based on subjective and objective combination - Google Patents
Performance assessment method and system based on subjective and objective combination Download PDFInfo
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- CN114066207A CN114066207A CN202111332696.4A CN202111332696A CN114066207A CN 114066207 A CN114066207 A CN 114066207A CN 202111332696 A CN202111332696 A CN 202111332696A CN 114066207 A CN114066207 A CN 114066207A
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Abstract
The application discloses a performance assessment method and system based on subjective and objective combination, wherein the method comprises the following steps: obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise; obtaining a first department characteristic of a first enterprise employee; constructing a relevant department analysis model; obtaining first output information, wherein the first output information is a first associated department; obtaining a first associated department feature; constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics; obtaining first scoring information of a first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information; and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model. The method solves the technical problems that the performance assessment method in the prior art is poor in adaptability and single in assessment form, so that the assessment result is not scientific.
Description
Technical Field
The application relates to the field of artificial intelligence, in particular to a performance assessment method and system based on subjective and objective combination.
Background
Performance assessment (performance amine) is a link in enterprise performance management, and refers to a process that an assessment subject assesses the completion condition of work tasks of employees, the performance degree of the work duties of the employees and the development condition of the employees by adopting a scientific assessment mode according to a work target and a performance standard, and feeds back assessment results to the employees. In the enterprise operation process, in order to improve the enthusiasm of employees, various incentive means such as performance bonus, annual terminal award and the like are often used, meanwhile, for the long-term development of enterprises and the survival of enterprises in fierce market competition, whether the professional ability of employees is matched with the culture atmosphere advocated by companies needs to be identified, and therefore most companies have a set of performance assessment methods. However, performance assessment is a system project, and how to organically combine subjective assessment among managers and colleagues with objective assessment based on data to form a scientific and reasonable performance assessment method, so that improvement of performance management effects of employees is a very meaningful research direction.
In the process of implementing the technical solution in the embodiment of the present application, the inventor of the present application finds that the above-mentioned technology has at least the following technical problems:
the technical problems that the performance assessment method is poor in adaptability and single in assessment form, and assessment results are not scientific exist in the prior art.
Disclosure of Invention
The application aims to provide a performance assessment method and system based on subjective and objective combination, and the method and system are used for solving the technical problem that assessment results are not scientific due to poor adaptability and single assessment form of the performance assessment method in the prior art.
In view of the above problems, the embodiments of the present application provide a performance assessment method and system based on subjective and objective combination.
In a first aspect, the present application provides a performance assessment method based on a combination of subjective and objective measures, the method being implemented by a performance assessment system based on a combination of subjective and objective measures, wherein the method includes: obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise; obtaining a first department characteristic of a first enterprise employee; constructing a relevant department analysis model; inputting the first affiliated department into the associated department analysis model, and obtaining first output information according to the associated department analysis model, wherein the first output information is a first associated department; obtaining a first associated department characteristic according to the first associated department; constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training; obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information; and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model.
In another aspect, the present application further provides a system for performing a performance assessment method according to the first aspect, wherein the system comprises: a first obtaining unit: the first obtaining unit is used for obtaining first enterprise characteristics by performing enterprise characteristic extraction on a first enterprise; a second obtaining unit: the second obtaining unit is used for obtaining the first department characteristic of the first enterprise employee; a first building unit: the first construction unit is used for constructing a correlation department analysis model; a third obtaining unit: the third obtaining unit is configured to input the first affiliated department into the associated department analysis model, and obtain first output information according to the associated department analysis model, where the first output information is a first associated department; a fourth obtaining unit: the fourth obtaining unit is used for obtaining the characteristics of the first associated department according to the first associated department; a second building element: the second construction unit is used for constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training; a fifth obtaining unit: the fifth obtaining unit is used for obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information; a sixth obtaining unit: the sixth obtaining unit is configured to input the first scoring information into the first assessment auxiliary model, and obtain a first assessment result according to the first assessment auxiliary model.
In a third aspect, an embodiment of the present application further provides a performance assessment system based on subjective and objective combination, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method according to the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
1. obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise; obtaining a first department characteristic of a first enterprise employee; constructing a relevant department analysis model; inputting the first affiliated department into the associated department analysis model, and obtaining first output information according to the associated department analysis model, wherein the first output information is a first associated department; obtaining a first associated department characteristic according to the first associated department; constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training; obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information; and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model. The method achieves the technical effects of multiple data sources based on subjective and objective evaluation, ensures the assessment diversity and further improves the fairness and scientificity of performance assessment.
2. By carrying out data training on the first assessment auxiliary model, the first assessment auxiliary model can process input data more accurately, and further output first scoring information is more accurate, so that the technical effects of accurately obtaining data information and improving the intellectualization of assessment results are achieved.
3. And determining the staff of the upstream and downstream departments with larger work correlation with the staff to be checked in each correlation department as the first screening staff through the calculation and analysis of a performance assessment system which is subjectively and objectively combined, and further obtaining a real and effective co-worker mutual evaluation result based on the evaluation of the first screening staff, thereby achieving the technical effect of reducing the subjective evaluation distortion of the related co-workers.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only exemplary, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic flow chart illustrating a performance assessment method based on subjective and objective combination according to an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating a process of generating the first scoring information according to the first self-scoring information, the first scoring information, and the first mutual-scoring information in the performance assessment method based on subjective and objective combination according to the embodiment of the present application;
fig. 3 is a schematic flow chart illustrating a third assessment result obtained by performing qualitative calculation on the first assessment result and the second assessment result in the performance assessment method based on subjective and objective combination according to the embodiment of the present application;
fig. 4 is a schematic flow chart illustrating that first reminding information is obtained if the first abnormal self-checking result is the first result in the performance assessment method based on subjective and objective combination according to the embodiment of the present application;
FIG. 5 is a schematic structural diagram of a performance assessment system based on subjective and objective combination according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals:
a first obtaining unit 11, a second obtaining unit 12, a first constructing unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a second constructing unit 16, a fifth obtaining unit 17, a sixth obtaining unit 18, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, a bus interface 305.
Detailed Description
The embodiment of the application provides a performance assessment method and system based on subjective and objective combination, and solves the technical problem that in the prior art, the assessment result is unscientific due to poor adaptability and single assessment form of the performance assessment method. The method achieves the technical effects of multiple data sources based on subjective and objective evaluation, ensures the assessment diversity and further improves the fairness and scientificity of performance assessment.
In the following, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the elements relevant to the present application are shown in the drawings.
Summary of the application
Performance assessment (performance amine) is a link in enterprise performance management, and refers to a process that an assessment subject assesses the completion condition of work tasks of employees, the performance degree of the work duties of the employees and the development condition of the employees by adopting a scientific assessment mode according to a work target and a performance standard, and feeds back assessment results to the employees. In the enterprise operation process, in order to improve the enthusiasm of employees, various incentive means such as performance bonus, annual terminal award and the like are often used, meanwhile, for the long-term development of enterprises and the survival of enterprises in fierce market competition, whether the professional ability of employees is matched with the culture atmosphere advocated by companies needs to be identified, and therefore most companies have a set of performance assessment methods. However, performance assessment is a system project, and how to organically combine subjective assessment among managers and colleagues with objective assessment based on data to form a scientific and reasonable performance assessment method, so that improvement of performance management effects of employees is a very meaningful research direction.
The technical problems that the performance assessment method is poor in adaptability and single in assessment form, and assessment results are not scientific exist in the prior art.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the application provides a performance assessment method based on subjective and objective combination, which is applied to a performance assessment system based on subjective and objective combination, wherein the method comprises the following steps: obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise; obtaining a first department characteristic of a first enterprise employee; constructing a relevant department analysis model; inputting the first affiliated department into the associated department analysis model, and obtaining first output information according to the associated department analysis model, wherein the first output information is a first associated department; obtaining a first associated department characteristic according to the first associated department; constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training; obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information; and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
Referring to fig. 1, an embodiment of the present application provides a performance assessment method based on subjective and objective combination, where the method is applied to a performance assessment system based on subjective and objective combination, and the method specifically includes the following steps:
step S100: obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise;
specifically, the performance assessment method based on subjective and objective combination is applied to the performance assessment system based on subjective and objective combination, comprehensive conditions of staff can be assessed through multi-party data sources obtained based on subjective and objective evaluation, assessment diversity is guaranteed, and accordingly fairness and scientificity of performance assessment are improved. The first enterprise refers to any enterprise which utilizes the performance assessment system which subjectively and objectively combines to assess the performance of the staff. And obtaining the enterprise characteristics of the first enterprise, namely the first enterprise characteristics, by performing enterprise characteristic extraction on the first enterprise. The first enterprise characteristics comprise industries, industry value standards and the like of the first enterprise. For example, in the manufacturing industry, the quantity, the work efficiency, the product qualification rate, and the like of the products produced by the staff can represent the work value of the staff. By extracting the enterprise characteristics of the first enterprise, the technical effect of fully knowing the industry characteristics and the industry value evaluation index of the first enterprise is achieved, and a reference index is provided for subsequently evaluating the performance of the staff.
Step S200: obtaining a first department characteristic of a first enterprise employee;
specifically, the first enterprise employee refers to any employee to be performance-assessed in the first enterprise. And performing characteristic analysis on the department to which the first enterprise employee belongs based on the actual condition of the first enterprise employee, and determining the department characteristic of the department to which the first enterprise employee belongs, namely the first affiliated department characteristic. The first affiliated department characteristics comprise main work categories of departments, department value embodiment and the like. For example, if the main work of the enterprise personnel administration is enterprise personnel management, the value of the administration can be embodied by data indexes such as the number of recruiters of the enterprise and the like in a certain time. By analyzing the characteristics of the first affiliated department, a reference index is provided for subsequently evaluating the performance of the staff of the corresponding department, and the technical effect of scientifically and reasonably evaluating the performance of each staff in the department based on the actual working condition of the department is achieved.
Step S300: constructing a relevant department analysis model;
step S400: inputting the first affiliated department into the associated department analysis model, and obtaining first output information according to the associated department analysis model, wherein the first output information is a first associated department;
specifically, the associated department analysis model may intelligently analyze other department information of the enterprise associated with the first affiliated department, that is, the first output information, based on a situation of the department to which the first enterprise employee belongs. And the first output information comprises all departments which intersect and are related to the work of the first affiliated department. For example, after the enterprise production department is input into the related department analysis model, the obtained first output information may include other related departments in the enterprise, such as the enterprise sales department, the enterprise process department, and the enterprise quality inspection department. Through the associated department analysis model, the technical goal of intelligently acquiring other departments associated with the current department to which the employee to be assessed belongs is achieved, and assessment reference is provided for subsequently evaluating the performance of the current first enterprise employee.
Step S500: obtaining a first associated department characteristic according to the first associated department;
specifically, based on the first associated department obtained through intelligent analysis by the associated department analysis model, the work category, the work value and other conditions of each associated department are respectively analyzed, so as to obtain the characteristic of each associated department, namely the characteristic of the first associated department. The characteristics of the first association department are obtained through analysis, and based on the evaluation of the association department, the technical effect of providing reference for the subsequent evaluation of the performance of the first enterprise employee is achieved, meanwhile, the colleagues collaborating around the employee participate in the evaluation, the influence of the personal extreme evaluation on the performance evaluation of the employee is effectively avoided, and the result of the performance evaluation of the employee is more in line with the actual situation.
Step S600: constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training;
step S700: obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information;
specifically, the first assessment auxiliary model is a neural network model and has the characteristics of the neural network model. The neural network model is a neural network model in machine learning, reflects many basic characteristics of human brain functions, is a deep feedforward neural network with the characteristics of local connection, weight sharing and the like, and is a highly complex nonlinear dynamic learning system. The first assessment auxiliary model established based on the neural network model can output accurate first scoring information of the first enterprise employee, so that the analysis and calculation capacity is high, and accurate and efficient technical effects are achieved. The first scoring information comprises subjective scoring information and objective scoring information. In addition, the first assessment auxiliary model can perform continuous self-training learning according to training data, and through continuous self-correction, when the output information of the first assessment auxiliary model reaches a preset accuracy rate/convergence state, the supervised learning process is ended.
By carrying out data training on the first assessment auxiliary model, the first assessment auxiliary model can process input data more accurately, the output first scoring information comprises subjective scoring information and objective scoring information, the comprehensive assessment result is more accurate, accurate data information is obtained, and the intelligent technical effect of the assessment result is improved.
Step S800: and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model.
Specifically, the first assessment auxiliary model intelligently analyzes to obtain subjective and objective assessment on the performance of the first enterprise employee, and finally obtains the first assessment result of the first enterprise employee based on data of multi-party assessment, so that extreme assessment of individuals is avoided, diversity of employee performance assessment is guaranteed, and fairness and scientificity of performance assessment are finally improved.
Further, as shown in fig. 2, step S700 in the embodiment of the present application further includes:
step S710: obtaining a first work objective of the first enterprise employee;
step S720: obtaining first self-evaluation information of the first enterprise employee according to the first work target;
step S730: obtaining first scoring information according to the information of the first department;
step S740: obtaining first mutual evaluation information according to the first associated department information;
step S750: and generating the first grading information according to the first self-grading information, the first grading information and the first mutual-grading information.
Specifically, the work target of the first enterprise employee is obtained first, and based on the first work target, the employee personally evaluates the target completion condition of the employee to obtain the first self-evaluation information. And based on the work target of the first enterprise employee, the administrator layer of the first enterprise employee scores the target completion condition, and the administrator forms the first scoring information for the superior administrator of the enterprise employee. And the first scoring information comprises all scoring results of the first enterprise employee direct administrator and the non-direct administrator. And finally, based on the work target of the first enterprise employee, evaluating the work target completion condition of the department colleagues related to the actual work of the first enterprise employee to obtain the first mutual evaluation information. And finally, integrating the self-evaluation, administrator layer evaluation and co-worker mutual evaluation results of the first enterprise employee to generate a subjective evaluation result of the working condition of the first enterprise employee, namely the first grading information.
And obtaining the subjective evaluation result of the first enterprise employee by combining three subjective evaluation results of employee self evaluation, administrator evaluation and co-worker mutual evaluation and weight comprehensive analysis. The multi-party subjective evaluation data is synthesized, the influence of individual extreme evaluation on the performance assessment result of the first enterprise employee is avoided, the multi-layer administrator evaluation also avoids the situation that the basic level employee is completely mastered by the directly superior or the indirectly subordinate superior loses understanding, speaking right and influence on the indirectly subordinate employee, the fairness of the performance assessment is finally improved, and the goal of exciting the employee is better achieved.
Further, step S740 in the embodiment of the present application further includes:
step S741: obtaining first position information of the first enterprise employee;
step S742: performing relevance analysis on the staff of the first relevant department according to the first post information to obtain a first correlation coefficient;
step S743: when the first correlation coefficient is larger than a preset correlation coefficient, obtaining a first screening instruction;
step S744: and obtaining a first screening person according to the first screening instruction, wherein the first screening person is a person with higher relevance in the first relevant department.
Specifically, based on the position situation of the first enterprise employee, other department employees in upstream and downstream, which are related to the position work content of the first enterprise employee, and the like, are analyzed, and a corresponding correlation coefficient is calculated. And when the calculated correlation coefficient is larger than the preset correlation coefficient, screening the information of the staff of the corresponding department, namely obtaining a first screening staff. The preset correlation coefficient is a post correlation coefficient value set by a performance assessment system based on the actual working condition of the employee to be examined and the associated colleague condition in the work, wherein the performance assessment system is subjectively and objectively combined. Once the correlation coefficient exceeds the preset correlation coefficient, the result shows that the work correlation between the corresponding staff and the staff to be checked is larger, the working condition of the staff to be checked is more understood, and the evaluation result can be used as the evaluation reference of the working condition of the staff to be checked. The first screening person is the person with larger relevance in the first relevant department.
And determining the staff of the upstream and downstream departments with larger work correlation with the staff to be checked in each correlation department as the first screening staff through the calculation and analysis of a performance assessment system which is subjectively and objectively combined, and further obtaining a real and effective co-worker mutual evaluation result based on the evaluation of the first screening staff, thereby achieving the technical effect of reducing the subjective evaluation distortion of the related co-workers.
Further, step S740 in the embodiment of the present application further includes:
step S745: obtaining a first post level according to the first post information;
step S746: classifying the first screening personnel according to the first post grade to obtain first classified personnel information;
step S747: obtaining a weight distribution index by performing weight distribution on all classes of people in the first classification personnel information;
step S748: and adjusting the first mutual evaluation information based on the weight distribution index to obtain second mutual evaluation information.
Specifically, according to the first position information of the first enterprise employee, the position level corresponding to the first enterprise employee is determined, so that the level of the first screening person is determined based on the position level of the employee to be assessed, that is, the first classified person information is obtained. And further performing corresponding weight distribution on all classes of people in the first classified personnel information to obtain a weight distribution index of each screening person, and finally adjusting the first mutual evaluation information based on the weight distribution index, wherein the adjusted mutual evaluation information is the second mutual evaluation information. For example, if the first enterprise employee is in the assistant level, the post level of each screening person is determined to be the general worker level and the main level by analyzing the posts of the first screening person, the evaluation right of the whole colleague is higher, and the evaluation right of the general worker is lower. The technical effect that the mutual evaluation results of the colleagues are adjusted based on the post level of the first screening personnel and the subjective mutual evaluation results of the colleagues are real and effective is ensured.
Further, as shown in fig. 3, the embodiment of the present application further includes step S900:
step S910: obtaining the first enterprise cultural characteristic according to the first enterprise characteristic;
step S920: determining a first culture evaluation index according to the first enterprise culture characteristics;
step S930: generating a second assessment result based on the first culture evaluation index;
step S940: and qualitatively calculating the first examination result and the second examination result to obtain a third examination result.
Specifically, the first enterprise cultural characteristics are determined based on the first enterprise characteristics, and specific indexes for assessing employee cultural value views, namely the first cultural evaluation indexes, are further determined, so that a second assessment result is generated. And finally, integrating the first assessment result and the second assessment result to obtain a third assessment result. And by combining enterprise culture, the cultural value view of the staff is evaluated. Due to the fact that the subjective initiative of the staff is heavily examined by the cultural value viewer, relevant staff designate specific evaluation indexes in combination with company culture, and conduct cultural evaluation on the staff of the enterprise based on the specific indexes, multi-angle, multi-aspect and multi-level staff performance assessment is achieved, and the problems of incomplete assessment and unscientific assessment caused by single assessment are avoided.
Further, as shown in fig. 4, step S800 in this embodiment of the present application further includes:
step S810: obtaining a first random extraction rule;
step S820: sampling the first scoring information according to a first random extraction rule to obtain first sampling scoring information;
step S830: inputting the first sampling grading information into a grading abnormity self-checking model, and obtaining a first abnormity self-checking result according to the grading abnormity self-checking model, wherein the first abnormity self-checking result comprises a first result and a second result, the first result is that abnormity exists, and the second result is that abnormity does not exist;
step S840: and if the first abnormal self-checking result is the first result, obtaining first reminding information.
Specifically, the first random extraction rule is a staff evaluation random sampling inspection method preset in a performance assessment system based on subjective and objective combination. Take the form of random sampling methods such as direct sampling, drawing-lots, random number methods, etc. And sampling the first grading information based on the first random extraction rule to obtain first sampling grading information. And further inputting the first sampling scoring information into a scoring abnormity self-checking model, and intelligently analyzing according to the scoring abnormity self-checking model to obtain an abnormity self-checking result of the first sampling scoring information. The first anomaly self-checking result comprises a first result and a second result, the first result is that an anomaly exists, and the second result is that no anomaly exists. When the first abnormal self-checking result is the first result, namely, when abnormality exists, the performance assessment system which is subjectively and objectively combined automatically sends out first reminding information for reminding relevant personnel of evaluating data abnormality, and after manual review, abnormal data is rescued in modes of re-evaluation and the like. The method achieves the technical effects of ensuring the accuracy of evaluation data and providing the scientificity of performance assessment of the staff.
Further, the embodiment of the present application further includes step S1000:
step S1010: obtaining first real-time incentive data for the first enterprise;
step S1020: judging whether the first real-time excitation data and the first historical excitation data have first updating data or not;
step S1030: and if the first real-time excitation data and the first historical excitation data have the first updating data, updating the first assessment auxiliary model by using the first updating data as a newly added constraint condition to obtain a second assessment auxiliary model.
Specifically, by comparing first real-time incentive data of the first enterprise with first historical incentive data, whether the first real-time incentive data changes or not is judged, namely whether the first real-time incentive data is different from the first historical incentive data or not is judged, if the first real-time incentive data is different from the first historical incentive data, corresponding first updating data is analyzed and determined, the first updating data is used as a newly-added constraint condition to update the first assessment auxiliary model, and a second assessment auxiliary model is obtained. For example, when the newly added performance bonus of an enterprise is used for exciting an operator, firstly, whether the newly added performance bonus system is the same as the existing exciting system in the system is judged, different places are added into the model, the real-time updating of the model is realized, and finally, the assessment result is ensured to be in accordance with the latest regulation of the enterprise.
In summary, the performance assessment method based on subjective and objective combination provided by the embodiment of the application has the following technical effects:
1. obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise; obtaining a first department characteristic of a first enterprise employee; constructing a relevant department analysis model; inputting the first affiliated department into the associated department analysis model, and obtaining first output information according to the associated department analysis model, wherein the first output information is a first associated department; obtaining a first associated department characteristic according to the first associated department; constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training; obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information; and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model. The method achieves the technical effects of multiple data sources based on subjective and objective evaluation, ensures the assessment diversity and further improves the fairness and scientificity of performance assessment.
2. By carrying out data training on the first assessment auxiliary model, the first assessment auxiliary model can process input data more accurately, and further output first scoring information is more accurate, so that the technical effects of accurately obtaining data information and improving the intellectualization of assessment results are achieved.
3. And determining the staff of the upstream and downstream departments with larger work correlation with the staff to be checked in each correlation department as the first screening staff through the calculation and analysis of a performance assessment system which is subjectively and objectively combined, and further obtaining a real and effective co-worker mutual evaluation result based on the evaluation of the first screening staff, thereby achieving the technical effect of reducing the subjective evaluation distortion of the related co-workers.
Example two
Based on the performance assessment method combined subjectively and objectively with the previous embodiment, the invention also provides a performance assessment system combined subjectively and objectively with the same inventive concept, please refer to fig. 5, the system includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain a first enterprise feature by performing enterprise feature extraction on a first enterprise;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain a first department attribute of the first enterprise employee;
the first building unit 13, the first building unit 13 is used for building the related department analysis model;
a third obtaining unit 14, where the third obtaining unit 14 is configured to input the first affiliated department into the associated department analysis model, and obtain first output information according to the associated department analysis model, where the first output information is a first associated department;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain a first associated department feature according to the first associated department;
a second constructing unit 16, where the second constructing unit 16 is configured to construct a first assessment auxiliary model according to the first enterprise characteristic, the first affiliated department characteristic, and the first associated department characteristic, where the first assessment auxiliary model is obtained through multiple sets of data training;
a fifth obtaining unit 17, where the fifth obtaining unit 17 is configured to obtain first scoring information of the first enterprise employee, where the first scoring information includes subjective scoring information and objective scoring information;
a sixth obtaining unit 18, where the sixth obtaining unit 18 is configured to input the first scoring information into the first assessment auxiliary model, and obtain a first assessment result according to the first assessment auxiliary model.
Further, the system further comprises:
a seventh obtaining unit, configured to obtain a first work target of the first enterprise employee;
the eighth obtaining unit is used for obtaining first self-evaluation information of the first enterprise employee according to the first working target;
a ninth obtaining unit configured to obtain first scoring information based on the belonging first department information;
a tenth obtaining unit, configured to obtain first mutual evaluation information according to the first relevant department information;
the first generation unit is used for generating the first scoring information according to the first self-scoring information, the first scoring information and the first mutual-scoring information.
Further, the system further comprises:
an eleventh obtaining unit, configured to obtain first position information of the first enterprise employee;
a twelfth obtaining unit, configured to perform relevance analysis on the staff of the first relevant department according to the first position information, so as to obtain a first correlation coefficient;
a thirteenth obtaining unit configured to obtain a first filtering instruction when the first correlation coefficient is greater than a preset correlation coefficient;
a fourteenth obtaining unit, configured to obtain a first screening person according to the first screening instruction, where the first screening person is a person with a greater relevance in the first relevant department.
Further, the system further comprises:
a fifteenth obtaining unit, configured to obtain a first post level according to the first post information;
a sixteenth obtaining unit, configured to perform level classification on the first screening person according to the first post level, and obtain first classified person information;
a seventeenth obtaining unit configured to obtain a weight distribution index by performing weight distribution on the persons of all the categories in the first categorized person information;
an eighteenth obtaining unit, configured to adjust the first mutual evaluation information based on the weight distribution index, and obtain second mutual evaluation information.
Further, the system further comprises:
a nineteenth obtaining unit, configured to obtain the first corporate cultural characteristic according to the first corporate characteristic;
the first determining unit is used for determining a first culture evaluation index according to the first enterprise culture characteristics;
the second generating unit is used for generating a second assessment result based on the first culture evaluation index;
a twentieth obtaining unit, configured to obtain a third assessment result by performing qualitative calculation on the first assessment result and the second assessment result.
Further, the system further comprises:
a twenty-first obtaining unit, configured to obtain a first random drawing rule;
a twenty-second obtaining unit, configured to sample the first scoring information according to a first random extraction rule, and obtain first sampled scoring information;
a twenty-third obtaining unit, configured to input the first sampling scoring information into a scoring anomaly self-checking model, and obtain a first anomaly self-checking result according to the scoring anomaly self-checking model, where the first anomaly self-checking result includes a first result and a second result, the first result is that an anomaly exists, and the second result is that no anomaly exists;
a twenty-fourth obtaining unit, configured to obtain first reminding information if the first abnormal self-test result is the first result.
Further, the system further comprises:
a twenty-fifth obtaining unit, configured to obtain first real-time incentive data of the first enterprise;
the first judging unit is used for judging whether the first real-time excitation data and the first historical excitation data have first updating data or not;
a twenty-sixth obtaining unit, configured to, if the first real-time excitation data and the first historical excitation data have the first update data, update the first assessment auxiliary model by using the first update data as a newly-added constraint condition, and obtain a second assessment auxiliary model.
In the present specification, each embodiment is described in a progressive manner, and the main description of each embodiment is different from other embodiments, and the aforementioned subjective and objective combined performance assessment method in the first embodiment of fig. 1 and the specific example are also applicable to a subjective and objective combined performance assessment system in the present embodiment, and through the foregoing detailed description of the subjective and objective combined performance assessment method, a person skilled in the art can clearly know the subjective and objective combined performance assessment system in the present embodiment, so for the brevity of the description, detailed descriptions are not repeated here. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Exemplary electronic device
The electronic apparatus of the embodiment of the present application is described below with reference to fig. 6.
Fig. 6 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the performance assessment method combined subjectively and objectively with the aforementioned embodiments, the present invention further provides a performance assessment system combined subjectively and objectively, on which a computer program is stored, which, when executed by a processor, implements the steps of any one of the aforementioned performance assessment methods combined subjectively and objectively.
Where in fig. 6 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The application provides a performance assessment method based on subjective and objective combination, which is applied to a performance assessment system based on subjective and objective combination, wherein the method comprises the following steps: obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise; obtaining a first department characteristic of a first enterprise employee; constructing a relevant department analysis model; inputting the first affiliated department into the associated department analysis model, and obtaining first output information according to the associated department analysis model, wherein the first output information is a first associated department; obtaining a first associated department characteristic according to the first associated department; constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training; obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information; and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model. The method solves the technical problems that the performance assessment method in the prior art is poor in adaptability and single in assessment form, so that the assessment result is not scientific. The method achieves the technical effects of multiple data sources based on subjective and objective evaluation, ensures the assessment diversity and further improves the fairness and scientificity of performance assessment.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present application may take the form of an entirely software embodiment, an entirely hardware embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application is in the form of a computer program product that may be embodied on one or more computer-usable storage media having computer-usable program code embodied therewith. And such computer-usable storage media include, but are not limited to: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk Memory, a Compact Disc Read-Only Memory (CD-ROM), and an optical Memory.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. A method of subjectively and objectively combined performance assessment, wherein the method comprises:
obtaining a first enterprise characteristic by performing enterprise characteristic extraction on a first enterprise;
obtaining a first department characteristic of a first enterprise employee;
constructing a relevant department analysis model;
inputting the first affiliated department into the associated department analysis model, and obtaining first output information according to the associated department analysis model, wherein the first output information is a first associated department;
obtaining a first associated department characteristic according to the first associated department;
constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training;
obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information;
and inputting the first scoring information into the first assessment auxiliary model, and obtaining a first assessment result according to the first assessment auxiliary model.
2. The method of claim 1, wherein the obtaining first scoring information for the first business employee further comprises:
obtaining a first work objective of the first enterprise employee;
obtaining first self-evaluation information of the first enterprise employee according to the first work target;
obtaining first scoring information according to the information of the first department;
obtaining first mutual evaluation information according to the first associated department information;
and generating the first grading information according to the first self-grading information, the first grading information and the first mutual-grading information.
3. The method of claim 2, wherein the method further comprises:
obtaining first position information of the first enterprise employee;
performing relevance analysis on the staff of the first relevant department according to the first post information to obtain a first correlation coefficient;
when the first correlation coefficient is larger than a preset correlation coefficient, obtaining a first screening instruction;
and obtaining a first screening person according to the first screening instruction, wherein the first screening person is a person with higher relevance in the first relevant department.
4. The method of claim 3, wherein the method further comprises:
obtaining a first post level according to the first post information;
classifying the first screening personnel according to the first post grade to obtain first classified personnel information;
obtaining a weight distribution index by performing weight distribution on all classes of people in the first classification personnel information;
and adjusting the first mutual evaluation information based on the weight distribution index to obtain second mutual evaluation information.
5. The method of claim 1, wherein the method further comprises:
obtaining the first enterprise cultural characteristic according to the first enterprise characteristic;
determining a first culture evaluation index according to the first enterprise culture characteristics;
generating a second assessment result based on the first culture evaluation index;
and qualitatively calculating the first examination result and the second examination result to obtain a third examination result.
6. The method of claim 1, wherein prior to said inputting said first scoring information into said first qualifying assistive model, said method further comprises:
obtaining a first random extraction rule;
sampling the first scoring information according to a first random extraction rule to obtain first sampling scoring information;
inputting the first sampling grading information into a grading abnormity self-checking model, and obtaining a first abnormity self-checking result according to the grading abnormity self-checking model, wherein the first abnormity self-checking result comprises a first result and a second result, the first result is that abnormity exists, and the second result is that abnormity does not exist;
and if the first abnormal self-checking result is the first result, obtaining first reminding information.
7. The method of claim 1, wherein the method further comprises:
obtaining first real-time incentive data for the first enterprise;
judging whether the first real-time excitation data and the first historical excitation data have first updating data or not;
and if the first real-time excitation data and the first historical excitation data have the first updating data, updating the first assessment auxiliary model by using the first updating data as a newly added constraint condition to obtain a second assessment auxiliary model.
8. A system for subjectively and objectively combined performance assessment, wherein the system comprises:
a first obtaining unit: the first obtaining unit is used for obtaining first enterprise characteristics by performing enterprise characteristic extraction on a first enterprise;
a second obtaining unit: the second obtaining unit is used for obtaining the first department characteristic of the first enterprise employee;
a first building unit: the first construction unit is used for constructing a correlation department analysis model;
a third obtaining unit: the third obtaining unit is configured to input the first affiliated department into the associated department analysis model, and obtain first output information according to the associated department analysis model, where the first output information is a first associated department;
a fourth obtaining unit: the fourth obtaining unit is used for obtaining the characteristics of the first associated department according to the first associated department;
a second building element: the second construction unit is used for constructing a first assessment auxiliary model according to the first enterprise characteristics, the first affiliated department characteristics and the first associated department characteristics, wherein the first assessment auxiliary model is obtained through multiple groups of data training;
a fifth obtaining unit: the fifth obtaining unit is used for obtaining first scoring information of the first enterprise employee, wherein the first scoring information comprises subjective scoring information and objective scoring information;
a sixth obtaining unit: the sixth obtaining unit is configured to input the first scoring information into the first assessment auxiliary model, and obtain a first assessment result according to the first assessment auxiliary model.
9. A system for performance assessment with subjective and objective combination, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method of any one of claims 1 to 7.
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| CN114593960A (en) * | 2022-03-07 | 2022-06-07 | 无锡维邦工业设备成套技术有限公司 | Pure steam sampling method and system under multiple elements |
| CN114593960B (en) * | 2022-03-07 | 2023-12-05 | 无锡维邦工业设备成套技术有限公司 | Pure steam sampling method and system under multiple factors |
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