CN112288223A - Data processing method, device, equipment and storage medium - Google Patents
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Abstract
The embodiment of the application provides a data processing method, a data processing device, data processing equipment and a storage medium. The method comprises the following steps: under the condition of acquiring a user query request, determining whether the performance of the employee meets the lowest performance requirement or not based on performance data of the employee; the user query request is used for requesting the extraction data of the employee; if the performance of the employee reaches the minimum performance requirement, determining contribution data corresponding to the performance data of the employee based on the performance data and a contribution point of the employee; and outputting the extracted data of the staff. This application can use manpower sparingly the cost.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a data processing method, apparatus, device, and storage medium.
Background
To incentivize the aggressiveness of employees, performance may be embodied in salaries by way of performance improvement.
Currently, a manual calculation mode is adopted to determine the submission condition corresponding to the performance condition of an employee. For example, if an employee needs to know his/her contribution at the end of the month, the employee needs to perform manual calculations based on his/her current performance in the month to obtain the contribution in the month. For another example, if the financial staff needs to account for the previous monthly profits of each employee at the beginning of the month, the financial staff needs to perform manual calculation based on the previous monthly profits of each employee to obtain the previous monthly profits of each employee.
However, the above method has a problem of high labor cost.
Disclosure of Invention
The embodiment of the application provides a data processing method, a data processing device, data processing equipment and a storage medium, and aims to solve the problem that in the prior art, labor cost is high.
In a first aspect, an embodiment of the present application provides a data processing method, including:
under the condition of acquiring a user query request, determining whether the performance of the employee meets the lowest performance requirement or not based on performance data of the employee; the user query request is used for requesting the extraction data of the employee;
if the performance of the employee reaches the minimum performance requirement, determining contribution data corresponding to the performance data of the employee based on the performance data and a contribution point of the employee;
and outputting the extracted data of the staff.
Optionally, the minimum performance requirement is associated with a first employee attribute of the employee.
Optionally, the first employee attribute comprises a position and/or a place of employment.
Optionally, before determining whether the performance of the employee meets the minimum performance requirement based on the performance data of the employee, the method further includes:
acquiring first configuration information, wherein the first configuration information is used for configuring first corresponding relations between different first employee attributes and lowest performance requirements;
and determining the lowest performance requirement corresponding to the employee based on the first corresponding relation.
Optionally, the submission point is positively correlated with the level of the target performance requirement; wherein the target performance requirement is a performance requirement that is achievable by the employee's highest performance, the target performance requirement being ranked higher than or equal to the lowest performance requirement.
Optionally, the method further includes:
if the performance of the employee does not meet the minimum performance requirement, determining whether the employee is a new entry employee meeting preset conditions;
and if the employee is a newly-entered employee, determining that the submission data corresponding to the performance data of the employee is specific submission data.
Optionally, the specific contribution data is associated with a second employee attribute of the employee.
Optionally, before determining whether the performance of the employee meets the minimum performance requirement based on the performance data of the employee, the method further includes:
acquiring second configuration information, wherein the second configuration information is used for configuring second corresponding relations between different second employee attributes and specific extraction data;
and determining the specific extraction data corresponding to the employee based on the second corresponding relation.
Optionally, after determining the contribution data of the employee, the method further includes: and determining and outputting the salary data of the staff by adopting a salary strategy of dispensing the salary in proportion to time based on the salary data of the staff.
Optionally, the method further includes: and under the condition that the performance data of the employee is updated, updating the contribution data of the employee in real time based on the updated performance data of the user.
In a second aspect, an embodiment of the present application provides a data processing apparatus, including:
the system comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining whether the performance of an employee reaches the lowest performance requirement or not based on the performance data of the employee under the condition of acquiring a user query request; the user query request is used for requesting the extraction data of the employee;
the second determination module is used for determining the contribution data corresponding to the performance data of the employee based on the performance data and the contribution point of the employee if the performance of the employee reaches the lowest performance requirement;
and the output module is used for outputting the extracted data of the staff.
In a third aspect, an embodiment of the present application provides a computer storage medium for storing a computer program, where the computer program includes a program for executing the data processing method according to any one of the first aspect.
In a fourth aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the method of any of the first aspects.
An embodiment of the present application further provides a computer program, which is used to implement the data processing method according to any one of the first aspect when the computer program is executed by a computer.
According to the data processing method, the data processing device, the data processing equipment and the data processing storage medium, under the condition that the user query request is obtained, whether the performance of the employee meets the minimum performance requirement or not is determined based on the performance data of the employee, if the performance of the employee meets the minimum performance requirement, the submission data corresponding to the performance data of the employee is determined and output based on the performance data and the submission point of the employee, and the automatic determination of the submission data based on the performance data of the employee is achieved. In addition, the flexibility of the lifting calculation is facilitated by the minimum performance requirement.
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, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic view of an application scenario according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a data processing method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a data processing method according to another embodiment of the present application;
fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and "a" and "an" typically include at least two, but do not exclude the presence of at least one.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a commodity or system that includes the element.
In addition, the sequence of steps in each method embodiment described below is only an example and is not strictly limited.
The data processing method provided by the embodiment of the application can be applied to an application scenario shown in fig. 1, where the application scenario shown in fig. 1 may include a terminal 11 and a server 12, the terminal 11 is in communication connection with the server 12, the terminal may be, for example, a smart phone, a desktop, a notebook computer, a tablet computer, and the like, and the server 12 may be, for example, a stand-alone server, a cluster server, a distributed server, and the like.
The server 12 may store the sign-in information and the receipt-returning information of different operators, and it is understood that both the sign-in information and the receipt-returning information relate to corresponding orders. In one embodiment, the performance data may be obtained by counting the order amount of the order, and for convenience of description, the performance data is mainly illustrated by taking the order amount as an example. The order information may include the order amount of the order signed by the business, and the order amount of the order signed may be the positive performance of the business. The order refund information can include the order amount of the returned order of the business staff, and the order amount of the returned order can be used as the performance of the business staff. Furthermore, the operators can be grouped, each group can be allocated with a service supervisor, and the performance of the service supervisor can be determined by the sign-in information and the receipt-out information of the operators in the group. Both the clerk and the supervisor of the business may be considered employees.
The user may use the terminal 11 to query the contribution data of one or more employees. In order to ensure the privacy of the contribution data, the contribution data which can be inquired by the user can be related to the role of the user, for example, if the user is a business member, the contribution data of the user can be inquired, if the user is a financial staff, the contribution data of all employees can be inquired, and if the user is a business supervisor, the contribution data of the user and the business members in the group can be obtained.
In an embodiment, after obtaining the query operation of the user, the terminal 11 may send a user query request to the server 12, and the server 12 performs processing by using the method provided in the embodiment of the present application to output the contribution data of the employee. The server 12 outputting the employee's contribution data may be understood as that the server 12 outputs the employee's contribution data to the terminal 11, so that the terminal 11 outputs the employee's contribution data to the user. It should be noted that, in other embodiments, the server for storing the ticket information and the receipt information and the server for processing by using the method provided by the embodiment of the present application may be different servers.
In another embodiment, the query operation of the terminal 11 to the user may represent that a query request of the user is obtained, and the terminal 11 performs processing by using the method provided in the embodiment of the present application, so as to output the extraction data of the employee. The terminal 11 outputting the extraction data of the employee may be understood as that the terminal 11 outputs the extraction data of the employee to the user, for example, the extraction data may be output to the user through screen display, short message prompt, voice playing, and the like. During the data processing of the terminal 11, the server 12 may assist the terminal 11 so that the terminal 11 obtains performance data of the employee.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Fig. 2 is a flowchart illustrating a data processing method according to an embodiment of the present application, where an execution subject of the embodiment may be the terminal 11 or the server 12 in fig. 1. As shown in fig. 2, the method of this embodiment may include:
In the case that the execution subject in step 21 is the terminal 11 used by the user, acquiring the user query request may specifically include acquiring a user query request operation, where the user query request operation may be, for example, a click operation of the user on a query button.
In the case that the execution subject of step 21 is the server 12, acquiring the user query request may specifically include acquiring a user query request message, and the user query request message may be sent to the server 12 by the terminal 11 when the user query request operation is acquired.
It should be noted that the number of the employees may be one or more.
In this step, the performance data may specifically be performance data of the employee over a period of time (hereinafter referred to as a first time period). Where an employee is a clerk, performance data for the employee may be determined based on the employee's endorsement information during a first time period and the reimbursement information during a second time period, which may be the same time period as the first time period or which may be a time period prior to the first time period. Where an employee is a business supervisor, the employee's performance data may be obtained by accumulating the performance data of the business employees in their group.
For example, the first time period may be indicated by the user query request, for example, assuming that the user query request may be specifically used for requesting the employee's contribution data in month a, which is the first time period. Alternatively, for example, the first period may be determined by the current time, for example, assuming that the current time is B years, C month, D days, the first period may be determined as C month.
Taking the monthly determined contribution data as an example, the performance data of the employee in a month may be determined based on the employee's endorsement information in the month and the return information in the previous month, for example, and the contribution data of the employee in the month may be obtained based on the performance data of the employee in the month.
Taking the example of obtaining the performance data by counting the order amount of the order, the performance data being performed can be obtained by extracting the order amount of the order signed by the employee in the first period and performing order amount counting (for example, summing up). In addition, performance data of negative performance can also be obtained by extracting the order amount of the order returned by the staff in the second time period and counting (for example, summing) the order amount.
Wherein the performance data for the employee may be derived based on positive performance data and negative performance data. It should be noted that in practical applications, the performance data of the employee may also take into account other factors, such as the working age, etc.
The minimum performance requirement refers to the minimum requirement that the performance data can meet for carrying out the submission calculation. Performance data is used for calculation of the performance only if it meets the minimum performance requirements, while performance data that does not meet the minimum performance requirements is not used for calculation of the performance. Performance data for the pull-up calculations can be controlled by setting minimum performance requirements, which is beneficial in providing flexibility in the pull-up calculations.
The specific content of the minimum performance requirement can be flexibly realized according to the requirement. In one embodiment, the minimum performance requirement may be preset. In another embodiment, the minimum performance requirements may be configurable to increase flexibility of the minimum performance requirements. Taking the case that the performance data is the money data obtained based on the money amount of the order as an example, the lowest performance requirement may be a recent money amount requirement (for example, 5 ten thousand dollars), when the performance data of the employee is smaller than the recent money amount requirement, it may be indicated that the performance of the employee does not reach the lowest performance requirement, and when the performance data of the employee is greater than or equal to the recent money amount requirement, it may be indicated that the performance of the employee reaches the lowest performance requirement.
And step 22, if the performance of the employee reaches the minimum performance requirement, determining the contribution data corresponding to the performance data of the employee based on the performance data and the contribution point of the employee.
In this step, if the performance of an employee reaches the minimum performance requirement, it can be indicated that the performance data of the employee can be used for the contribution calculation, and thus the contribution data corresponding to the performance data of the employee can be determined based on the performance data of the employee and the contribution point.
Wherein, the lifting point can be flexibly realized according to the requirement. In one embodiment, the lifting point may be preset. In another embodiment, the lifting point is configurable to increase flexibility of the lifting point. The point to be referred to may be, for example, 1 point or 2 points, and one percent of the performance data of the employee may be determined as the point to be referred to corresponding to the performance data of the employee, taking the point to be referred to as 1 point and the performance data as the money data as an example.
If the employee's performance does not meet the minimum performance requirement, it may indicate that the employee's performance data is not available for contribution calculations, thereby eliminating the need to determine contribution data corresponding to the employee's performance data based on the employee's performance data and the contribution point. In one embodiment, for employees whose performance data does not meet the minimum performance requirements, the contribution data may be determined to be null or 0, i.e., the contribution obtained by an employee whose performance data does not meet the minimum performance requirements may be 0.
And 23, outputting the extracted data of the staff.
In the case that the execution subject of step 23 is the terminal 11 used by the user, outputting the submission data of the employee may specifically include: and outputting the extraction data of the staff to the user. The output mode can be, for example, screen display, voice playing, etc.
In the case that the execution subject of step 23 is the server 12, outputting the contribution data of the employee may specifically include: and outputting the extraction data of the staff to the terminal 11 so as to output the extraction data of the staff to the user by the terminal 11.
In one embodiment, when the number of the employees is multiple, the submission data of the employees may be output in a table manner.
According to the data processing method provided by the embodiment, under the condition that the user query request is obtained, whether the performance of the employee meets the lowest performance requirement is determined based on the performance data of the employee, and if the performance of the employee meets the lowest performance requirement, the submission data corresponding to the performance data of the employee is determined and output based on the performance data and the submission point of the employee, so that the submission data can be automatically determined based on the performance data of the employee. In addition, the flexibility of the lifting calculation is facilitated by the minimum performance requirement.
Fig. 3 is a schematic flow diagram of a data processing method according to another embodiment of the present application, and this embodiment mainly describes an optional implementation manner based on the embodiment shown in fig. 2, and as shown in fig. 3, the method of this embodiment may include:
In this step, optionally, the minimum performance requirement may be associated with a first employee attribute of the employee. Through the correlation between the minimum performance requirement and the first employee attribute of the employee, the minimum performance requirements corresponding to the employees with different first employee attributes can be different, the flexibility of the minimum performance requirement is improved, and the flexibility of the achievement calculation is further improved.
The first employee attribute can be flexibly realized according to requirements, and the specific relation between the first employee attribute and the lowest performance requirement can also be flexibly realized according to requirements. In one embodiment, the first employee attribute may include a position and/or a place of employment. For example, the first employee attribute includes a position, the minimum performance requirement corresponding to the employee of the business executive position may be lower than the minimum performance requirement corresponding to the employee of the business executive position, for example, the minimum performance requirement corresponding to the employee of the business executive position may be 5 ten thousand yuan, and the minimum performance requirement corresponding to the employee of the business executive position may be 20 ten thousand yuan. Taking the example where the first employee attribute includes a workplace, the minimum performance requirement for employees whose workplace is a more economically developed city 1 may be higher than the minimum performance requirement for employees whose workplace is a less economically developed city 2, for example, the minimum performance requirement for employees whose workplace is city 1 may be 5 ten thousand dollars, and the minimum performance requirement for employees whose workplace is city 2 may be 2 ten thousand dollars.
Optionally, before determining whether the performance of the employee meets the minimum performance requirement based on the performance data of the employee, the method may further include: acquiring first configuration information, wherein the first configuration information is used for configuring first corresponding relations between different first employee attributes and lowest performance requirements; and determining the lowest performance requirement corresponding to the employee based on the first corresponding relation. Therefore, a mode for configuring the minimum performance requirements corresponding to the employees with different first employee attributes can be provided, and the flexible configuration of the minimum performance requirements can be realized.
The obtaining of the first configuration information may include, for example, receiving input first configuration information, or receiving first configuration information sent by other devices, and the like, and of course, in other embodiments, the first configuration information may also be obtained in other manners.
Taking the first employee attribute including position and place of work as an example, the first correspondence relationship may be shown in table 1 below, for example, and it should be noted that the correspondence relationship shown in table 1 is only an example.
TABLE 1
| Working place | Position of employment | Minimum performance requirement |
| City 1 | Business staff | 5 ten thousand yuan |
| City 1 | Business supervisor | 20 ten thousand yuan |
| City 2 | Business staff | 4 ten thousand yuan |
| City 2 | Business supervisor | 16 ten thousand yuan |
| City 3 | Business staff | 3 ten thousand yuan |
| City 3 | Business supervisor | 12 ten thousand yuan |
| …… | …… | …… |
Assuming that the workplace of an employee is city 1 and the job position is a business director, the minimum performance requirement for the employee can be determined to be 20 ten thousand yuan based on the first correspondence shown in table 1.
And step 32, if the performance of the employee reaches the minimum performance requirement, determining the contribution data corresponding to the performance data of the employee based on the performance data and the contribution point of the employee.
In this step, optionally, the withdrawal point may be positively correlated with the grade of the target performance requirement; wherein the target performance requirement is a performance requirement that is achievable by the employee's highest performance, the target performance requirement being ranked higher than or equal to the lowest performance requirement. Through positive correlation between the achievement point and the grade of the target achievement requirement, the achievement data can reach the higher grade of the achievement requirement, the higher the achievement point can be, the flexibility of the achievement point is improved, and the flexibility of the achievement point is further improved. In addition, the achievement point is positively correlated with the grade of the target achievement requirement, so that the enthusiasm of the staff is stimulated, and the working benefit of the staff is improved.
For example, 3 performance requirements may be set, 3 ten thousand, 5 ten thousand and 10 ten thousand, respectively, with the 3 ten thousand being the lowest (i.e., 3 ten thousand being the lowest performance requirement) and 5 ten thousand being the highest, and the 10 ten thousand being the higher. Assuming that the performance data of the employee is 4 ten thousand yuan, the target performance requirement is 3 ten thousand, and the promotion point may be 1 point, for example; assuming that the performance data of the employee is 6 ten thousand yuan, the target performance requirement is 5 ten thousand, and the promotion point may be 2 points, for example; assuming that the performance data of the employee is 10 ten thousand yuan, the target performance requirement is 10 ten thousand, and the promotion point may be, for example, 3 points.
It should be noted that step 35 may be executed after step 32 is executed.
And step 33, if the performance of the employee does not reach the minimum performance requirement, determining whether the employee is a new entry employee meeting preset conditions.
In this step, the preset condition can be flexibly implemented according to the requirement. Illustratively, the preset condition may be a duration condition, for example, the duration of the enrollment is less than 3 months. Or, for example, the preset condition may specifically be a time condition, for example, the time of employment is later than a certain day of a certain month of a certain year.
And step 34, if the employee is a new entry employee, determining that the contribution data corresponding to the performance data of the employee is specific contribution data.
In this step, the specific value of the specific extracted data can be flexibly implemented according to the requirement. In one embodiment, the special mention data may be preset. In another embodiment, the special offer data may be configured to increase flexibility of the special offer data. Considering that the business capability of a new employee is generally weak and the performance is difficult to reach the minimum performance requirement, when the employee is the new employee, the achievement data corresponding to the performance data of the employee is determined to be the specific achievement data, so that the probability that the new employee leaves due to the fact that the salary is too low because the performance does not reach the minimum performance requirement can be reduced.
Optionally, the specific contribution data may be associated with a second employee attribute of the employee. The specific contribution data is related to the second employee attribute of the employee, so that the specific contribution data corresponding to the newly-enrolled employee with different second employee attributes can be different, and the flexibility of the specific contribution data is improved. The second employee attribute and the first employee attribute may be the same employee attribute or different employee attributes.
The second employee attribute can be flexibly realized according to requirements, and the specific relation between the second employee attribute and the specific extraction data can also be flexibly realized according to requirements. In one embodiment, the second employee attributes may include job title and/or work place. Taking the second employee attribute as an example, the specific contribution data corresponding to the employee of the employee position may be, for example, 1 thousand yuan, and the specific contribution data corresponding to the business supervisor may be, for example, 2 thousand yuan. Taking the second employee attribute as an example, the specific contribution data corresponding to employees whose workplace is the economically more developed city 1 may be 1.5 kilo-dollars, and the specific contribution data corresponding to employees whose workplace is the economically less developed city 2 may be 1 kilo-dollars, for example.
Optionally, before determining whether the performance of the employee meets the minimum performance requirement based on the performance data of the employee, the method may further include: acquiring second configuration information, wherein the second configuration information is used for configuring second corresponding relations between different second employee attributes and specific extraction data; and determining the specific extraction data corresponding to the employee based on the second corresponding relation. Therefore, a mode of configuring specific extraction data corresponding to the employees with different second employee attributes can be provided, and flexible configuration of the specific extraction data can be realized.
The obtaining of the second configuration information may include, for example, receiving input second configuration information, or receiving second configuration information sent by other devices, and the like, and of course, in other embodiments, the second configuration information may also be obtained in other manners.
Taking the second employee attribute including position and place of work as an example, the second correspondence relationship may be shown in table 2 below, for example, it should be noted that the correspondence relationship shown in table 2 is only an example.
TABLE 2
| Working place | Position of employment | Specific abstract data |
| City 1 | Business staff | 1 thousand yuan |
| City 1 | Business supervisor | 2 thousand yuan |
| City 2 | Business staff | 0.8 thousand yuan |
| City 2 | Business supervisor | 1.5 thousand yuan |
| City 3 | Business staff | 0.5 thousand yuan |
| City 3 | Business supervisor | 1 thousand yuan |
| …… | …… | …… |
Assuming that the work place of a newly entered employee is city 1 and the position is a job director, the specific contribution data corresponding to the employee can be determined to be 2 thousand yuan based on the second correspondence shown in table 2.
In one embodiment, for non-new entry employees whose performance data does not meet the minimum performance requirements, the contribution data may be determined to be null or 0, i.e., the contribution obtained by non-new entry employees whose performance data does not meet the minimum performance requirements may be 0.
And step 35, outputting the extracted data of the staff.
According to the data processing method provided by the embodiment of the application, whether the employee is a new employee meeting the preset condition is determined if the performance of the employee does not reach the lowest performance requirement, and if the employee is the new employee, the fact that the submission data corresponding to the performance data of the employee is the specific submission data is determined, so that the fact that the submission data corresponding to the performance data of the employee is the specific submission data is determined when the employee is the new employee is achieved, and the probability of leaving the employee of the new employee is reduced.
Optionally, on the basis of the above method embodiment, after determining the contribution data of the employee, the method may further include: and determining and outputting the salary data of the staff by adopting a salary strategy of dispensing the salary in proportion to time based on the salary data of the staff. The salary data of the staff can be automatically calculated by determining and outputting the salary data of the staff by adopting a salary strategy of dispensing the salary in proportion to time based on the salary data of the staff, and compared with the manual salary data calculation in the traditional technology, the salary data calculation method reduces the workload of manual processing and saves the labor cost. In addition, the salary strategy of providing the winnings according to the proportion and time is adopted, so that the probability of staff leaving is favorably reduced.
For example, the monthly payroll may include the first proportion of the contribution data of the previous month in the payroll data of the employee in the current month, and include the second proportion of the contribution data of the previous month in the payroll data of the employee in a subsequent month (e.g., the next month), where a sum of the first proportion and the second proportion is equal to 1. For example, assuming that the performance data for 1 month corresponds to the contribution data of 1 ten thousand dollars, 60% of the 1 ten thousand dollars may be included in the salary data for 2 months (i.e., 60% of 1 ten thousand dollars are released in 2 months), 20% of the 1 ten thousand may be included in the salary data for 3 months (i.e., 20% of 1 ten thousand dollars are released in 3 months), and 20% of the 1 ten thousand may be included in the salary data for 4 months (i.e., 20% of 1 ten thousand dollars are released in 4 months).
Optionally, on the basis of the above method embodiment, the method may further include: and under the condition that the performance data of the employee is updated, updating the contribution data of the employee in real time based on the updated performance data of the user. By refreshing the extraction data of the staff in real time, the real-time performance of the extraction data output to the user can be ensured.
Fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application; referring to fig. 4, the present embodiment provides a data processing apparatus, which may execute the data processing method described above, and specifically, the data processing apparatus may include:
the first determining module 41 is configured to determine whether the performance of the employee meets the minimum performance requirement based on the performance data of the employee when the user query request is obtained; the user query request is used for requesting the extraction data of the employee;
a second determining module 42, configured to determine, based on the performance data of the employee and a contribution point, contribution data corresponding to the performance data of the employee if the performance of the employee meets the minimum performance requirement;
and the output module 43 is used for outputting the extracted data of the staff.
Optionally, the minimum performance requirement is associated with a first employee attribute of the employee.
Optionally, the first employee attribute comprises a position and/or a place of employment.
Optionally, the apparatus further includes a first configuration module, configured to obtain first configuration information, where the first configuration information is used to configure a first corresponding relationship between different first employee attributes and a minimum performance requirement; and determining the lowest performance requirement corresponding to the employee based on the first corresponding relationship.
Optionally, the submission point is positively correlated with the level of the target performance requirement; wherein the target performance requirement is a performance requirement that is achievable by the employee's highest performance, the target performance requirement being ranked higher than or equal to the lowest performance requirement.
Optionally, the apparatus further comprises: the third determining module is used for determining whether the employee is a new entry employee meeting preset conditions or not if the performance of the employee does not meet the minimum performance requirement; and if the employee is a new entry employee, determining that the contribution data corresponding to the performance data of the employee is specific contribution data.
Optionally, the specific contribution data is associated with a second employee attribute of the employee.
Optionally, the apparatus further includes a second configuration module, configured to obtain second configuration information, where the second configuration information is used to configure a second correspondence between different second employee attributes and specific pickup data; and determining the specific extraction data corresponding to the employee based on the second corresponding relation.
Optionally, the apparatus further includes a fourth determining module, configured to determine and output salary data of the employee by using a salary policy of dispensing the donation in proportion to time based on the contribution data of the employee.
Optionally, the apparatus further includes a refreshing module, configured to refresh the contribution data of the employee in real time based on the updated performance data of the user when the performance data of the employee is updated.
The apparatus shown in fig. 4 can perform the method of the embodiment shown in fig. 2-3, and the detailed description of this embodiment can refer to the related description of the embodiment shown in fig. 2-3. The implementation process and technical effect of the technical solution refer to the descriptions in the embodiments shown in fig. 2 to fig. 3, and are not described herein again.
In one possible implementation, the structure of the data processing apparatus shown in fig. 4 may be implemented as an electronic device. As shown in fig. 5, the electronic device may include: a processor 51 and a memory 52. Wherein the memory 52 is used for storing programs that support the electronic device to execute the data processing method provided in the embodiments shown in fig. 2-3, and the processor 51 is configured for executing the programs stored in the memory 52.
The program comprises one or more computer instructions which, when executed by the processor 51, are capable of performing the steps of:
under the condition of acquiring a user query request, determining whether the performance of the employee meets the lowest performance requirement or not based on performance data of the employee; the user query request is used for requesting the extraction data of the employee;
if the performance of the employee reaches the minimum performance requirement, determining contribution data corresponding to the performance data of the employee based on the performance data and a contribution point of the employee;
and outputting the extracted data of the staff.
Optionally, the processor 51 is further configured to perform all or part of the steps in the embodiments shown in fig. 2 to 3.
The electronic device may further include a communication interface 53 for communicating with other devices or a communication network.
In addition, the present application provides a computer storage medium for storing a computer program for an electronic device, which includes a program for executing the data processing method in the method embodiments shown in fig. 2 to 3.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course, can also be implemented by a combination of hardware and software. With this understanding in mind, the above-described technical solutions and/or portions thereof that contribute to the prior art may be embodied in the form of a computer program product, which may be embodied on one or more computer-usable storage media having computer-usable program code embodied therein (including but not limited to disk storage, CD-ROM, optical storage, etc.).
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means 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 apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means 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 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.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (13)
1. A data processing method, comprising:
under the condition of acquiring a user query request, determining whether the performance of the employee meets the lowest performance requirement or not based on performance data of the employee; the user query request is used for requesting the extraction data of the employee;
if the performance of the employee reaches the minimum performance requirement, determining contribution data corresponding to the performance data of the employee based on the performance data and a contribution point of the employee;
and outputting the extracted data of the staff.
2. The method of claim 1, wherein the minimum performance requirement relates to a first employee attribute of the employee.
3. The method of claim 2, wherein the first employee attributes comprise job title and/or work place.
4. The method of claim 2, wherein determining whether the employee's performance meets a minimum performance requirement based on the employee's performance data further comprises:
acquiring first configuration information, wherein the first configuration information is used for configuring first corresponding relations between different first employee attributes and lowest performance requirements;
and determining the lowest performance requirement corresponding to the employee based on the first corresponding relation.
5. The method of any of claims 1-4, wherein the submission point is positively correlated with a level of a target performance requirement; wherein the target performance requirement is a performance requirement that is achievable by the employee's highest performance, the target performance requirement being ranked higher than or equal to the lowest performance requirement.
6. The method according to any one of claims 1-4, further comprising:
if the performance of the employee does not meet the minimum performance requirement, determining whether the employee is a new entry employee meeting preset conditions;
and if the employee is a newly-entered employee, determining that the submission data corresponding to the performance data of the employee is specific submission data.
7. The method of claim 6, wherein the specific contribution data relates to a second employee attribute of the employee.
8. The method of claim 7, wherein determining whether the employee's performance meets a minimum performance requirement based on the employee's performance data further comprises:
acquiring second configuration information, wherein the second configuration information is used for configuring second corresponding relations between different second employee attributes and specific extraction data;
and determining the specific extraction data corresponding to the employee based on the second corresponding relation.
9. The method of claim 1, wherein after determining the employee's contribution data, further comprising:
and determining and outputting the salary data of the staff by adopting a salary strategy of dispensing the salary in proportion to time based on the salary data of the staff.
10. The method of claim 1, further comprising:
and under the condition that the performance data of the employee is updated, updating the contribution data of the employee in real time based on the updated performance data of the user.
11. A data processing apparatus, comprising:
the system comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining whether the performance of an employee reaches the lowest performance requirement or not based on the performance data of the employee under the condition of acquiring a user query request; the user query request is used for requesting the extraction data of the employee;
the second determination module is used for determining the contribution data corresponding to the performance data of the employee based on the performance data and the contribution point of the employee if the performance of the employee reaches the lowest performance requirement;
and the output module is used for outputting the extracted data of the staff.
12. A computer storage medium storing a computer program, characterized in that the computer program comprises a program involved in executing a data processing method according to any one of claims 1 to 10.
13. An electronic device, comprising: a memory, a processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the method of any of claims 1 to 10.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103198431A (en) * | 2013-03-18 | 2013-07-10 | 黄晓惠 | Employee performance computing method and employee bonus computing method in beauty industry |
| CN110059945A (en) * | 2019-04-02 | 2019-07-26 | 广州超联软件科技有限公司 | A kind of statistical analysis system of employee performance, method and medium |
| CN110135608A (en) * | 2019-04-02 | 2019-08-16 | 广州超联软件科技有限公司 | A kind of method, system and the computer readable storage medium of shops's management |
-
2020
- 2020-09-23 CN CN202011008965.7A patent/CN112288223A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103198431A (en) * | 2013-03-18 | 2013-07-10 | 黄晓惠 | Employee performance computing method and employee bonus computing method in beauty industry |
| CN110059945A (en) * | 2019-04-02 | 2019-07-26 | 广州超联软件科技有限公司 | A kind of statistical analysis system of employee performance, method and medium |
| CN110135608A (en) * | 2019-04-02 | 2019-08-16 | 广州超联软件科技有限公司 | A kind of method, system and the computer readable storage medium of shops's management |
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Application publication date: 20210129 |