CN114971434B - Performance comparison analysis system based on distributed computation - Google Patents
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Abstract
The invention provides a performance comparison and analysis system based on distributed computation, which comprises a terminal input module, a computation processing module, a transmission module and a central processing module, wherein the terminal input module is used for inputting task completion information of individuals, the computation processing module is used for preprocessing the task completion information, the transmission module is used for sending a preprocessed result to the central processing module, and the central processing module is used for performing comparison and analysis on all preprocessed results to obtain a final performance result of each individual. The system adds two factors of longitudinal comparison and transverse comparison when performing final performance evaluation, so that the performance result is more three-dimensional, and meanwhile, when preprocessing data, a time evaluation coefficient is added to correct the deviation by taking a task sub-project as a basic unit, so that the preprocessing result can more accurately reflect the actual efficiency condition of an individual.
Description
Technical Field
The invention relates to the field of enterprise planning, in particular to a performance comparison and analysis system based on distributed computing.
Background
The performance appraisal is one of core functions of human resource management, means that an appraiser uses scientific methods, standards and programs to observe, collect, organize, store, extract and integrate performance information of behavior subjects related to an appraisal task and make accurate evaluation as far as possible, and is a link in enterprise performance management.
The foregoing discussion of the background art is intended only to facilitate an understanding of the present invention. This discussion is not an acknowledgement or admission that any of the material referred to is part of the common general knowledge.
Now, a plurality of performance appraisal systems are developed, and through a large number of searches and references, the existing performance appraisal systems are found to be disclosed as CN112101918B, and generally comprise a performance appraisal index system and appraisal tasks configured on a server; the performance assessment index system and the assessment tasks are issued to a data acquisition unit and an assessed assessment unit; the data acquisition unit receives the index data reported by the evaluated assessment unit, and performs assessment scoring on the index data to obtain assessment scoring corresponding to the index data; and the server side summarizes the assessment scores corresponding to the index data and feeds the summarized assessment scores corresponding to the index data back to the assessed assessment unit. However, the system adopts the traditional mode of issuing tasks and analyzing the completion condition, but the mode has the defects of unfair final evaluation and is not beneficial to mobilizing the enthusiasm of staff due to the fact that different work types and tasks are different and the issued tasks are artificially controllable and the like.
Disclosure of Invention
The invention aims to provide a performance comparison and analysis system based on distributed computation, aiming at the existing defects.
The invention adopts the following technical scheme:
a performance comparison and analysis system based on distributed computation comprises a terminal input module, a computation processing module, a transmission module and a central processing module, wherein the terminal input module is used for inputting task completion information of individuals, the computation processing module preprocesses the task completion information, the transmission module sends a preprocessed result to the central processing module, and the central processing module compares and analyzes all preprocessed results to obtain a final performance result of each individual;
the task completion information comprises task items, task sub-items, sub-item states and completion time, the task items are composed of a plurality of task sub-items, the sub-item states are used for representing the completion states of all the task sub-items, and the completion time is used for showing the completion states of all the task sub-itemsIndicating the time spent on the task sub-item in the finished state, and the calculation processing module calculates the performance index of each individual in the current month according to the following formula
：
Wherein n is the number of task sub-items completed by an individual in the current month,
is the standard monthly working time and is the standard monthly working time,
for a project completion index, name is the number of task sub-project,
for the completion time of the task sub-item numbered name,
the time evaluation coefficient of the task sub-item with the individual number of name;
the computing processing module uploads the performance index to the central processing module;
the central processing module ranks the performance indexes P of all individuals in the current month from high to low to obtain a ranking serial number Rk of each individual in the current month, and the central processing module calculates a performance evaluation value Q of each individual in the current month according to the following formula:
wherein, the first and the second end of the pipe are connected with each other,
is the performance index of the individual for the last month,
is the ranking serial number of the individual in the last month, and N is the number of the individual;
furthermore, a storage unit, a statistical unit and a time processing unit are arranged in the central processing module, the storage unit is used for storing the task sub-project data completed by each individual in each month, the statistical unit acquires all the completion time data of the task sub-projects numbered as the name from the storage unit and processes the completion time data to obtain a group of time series
The time processing unit calculates a time evaluation coefficient according to the following formula
：
Wherein m is a time series
The number of elements in (1);
the central processing module sends the time evaluation coefficient to each calculation processing module;
further, the formula for calculating the project completion index is as follows:
wherein, the first and the second end of the pipe are connected with each other,
the number of task items that an individual has completed in the month,
the number of task items that an individual does not complete in the month,
the completion progress of the task project which is not completely completed in the current month for an individual;
furthermore, a sub-project evaluation unit is arranged in the central processing module, and the sub-project evaluation unit calculates a performance influence index of a task sub-project according to the following formula
：
Wherein a is a difficulty coefficient, and b is a complexity coefficient;
when the performance influence index Ef exceeds a first threshold, the task sub-project is represented to be segmented again, and when the performance influence index Ef is smaller than a second threshold, the task sub-project is represented to be merged into the rest task sub-projects;
further, the performance evaluation process of the system comprises the following steps:
s21, the terminal input module collects task completion information of each individual and sends the task completion information to the central processing module;
s22, the central processing module obtains a time evaluation coefficient according to all historical data statistics and feeds the time evaluation coefficient back to the calculation processing module;
s23, the calculation processing module calculates the performance index of an individual according to the time evaluation coefficient and sends the performance index to the central processing module;
and S24, the central processing module obtains the performance evaluation value of the individual according to the performance index comparison analysis of all the individuals.
The beneficial effects obtained by the invention are as follows:
the system cancels the traditional task issuing link, instead subdivides the task into task sub-items, submits the completion conditions of the task sub-items by individuals, compares the completion condition data of all the people, and all the task sub-items have the same level performance influence indexes, so that a fair performance result is finally obtained.
For a better understanding of the features and technical content of the present invention, reference should be made to the following detailed description of the invention and accompanying drawings, which are provided for purposes of illustration and description only and are not intended to limit the invention.
Drawings
FIG. 1 is a schematic view of the overall structural framework of the present invention;
FIG. 2 is a schematic diagram of task completion information according to the present invention;
FIG. 3 is a schematic diagram of the CPU module of the present invention;
FIG. 4 is a schematic diagram of a performance evaluation flow of the present invention;
fig. 5 is a schematic diagram of performance evaluation information transmission according to the present invention.
Detailed Description
The following is a description of embodiments of the present invention with reference to specific embodiments, and those skilled in the art will understand the advantages and effects of the present invention from the disclosure of the present specification. The invention is capable of other and different embodiments and its several details are capable of modifications and various changes in detail without departing from the spirit and scope of the present invention. The drawings of the present invention are for illustrative purposes only and are not intended to be drawn to scale. The following embodiments will further explain the related art of the present invention in detail, but the disclosure is not intended to limit the scope of the present invention.
The first embodiment.
The embodiment provides a performance comparison and analysis system based on distributed computing, which, with reference to fig. 1, includes a terminal input module, a computing processing module, a transmission module and a central processing module, wherein the terminal input module is used for inputting task completion information of individuals, the computing processing module preprocesses the task completion information, the transmission module sends a preprocessed result to the central processing module, and the central processing module performs comparison and analysis on all preprocessed results to obtain a final performance result of each individual;
the task completion information comprises task items, task sub-items, sub-item states and completion time, the task items are composed of a plurality of task sub-items, the sub-item states are used for representing the completion states of the task sub-items, the completion time is used for representing the time consumed by the task sub-items in the completion states, and the calculation processing module calculates the performance index of each individual in the current month according to the following formula
：
Wherein n is the number of task sub-items completed by an individual in the current month,
is the standard monthly working time and is the standard monthly working time,
for a project completion index, name is the number of task sub-project,
for the completion time of the task sub-item numbered name,
the time evaluation coefficient of the task sub-item with the individual number of name;
the computing processing module uploads the performance index to the central processing module;
the central processing module ranks the performance indexes P of all individuals in the current month from high to low to obtain a ranking serial number Rk of each individual in the current month, and the central processing module calculates a performance evaluation value Q of each individual in the current month according to the following formula:
wherein the content of the first and second substances,
is the performance index of the individual in the last month,
is the ranking serial number of the individual in the last month, and N is the number of the individual;
the central processing module is internally provided with a storage unit, a statistical unit and a time processing unit, the storage unit is used for storing task sub-project data finished by each individual in each month, and the statistical unit acquires all finishing time data of task sub-projects numbered as name from the storage unit and processes the finishing time data to obtain a group of time series
The time processing unit calculates a time evaluation coefficient according to the following formula
：
Wherein m is a time series
The number of elements in (1);
the central processing module sends the time evaluation coefficient to each calculation processing module;
the calculation formula of the project completion index is as follows:
wherein the content of the first and second substances,
the number of task items that an individual has completed in the month,
the number of task items that an individual does not complete in the month,
the completion progress of the task project which is not completely completed in the current month for an individual;
a sub-project evaluation unit is arranged in the central processing module, and the sub-project evaluation unit calculates a performance influence index of a task sub-project according to the following formula
：
Wherein a is a difficulty coefficient, and b is a complexity coefficient;
when the performance influence index Ef exceeds a first threshold, the task sub-project is represented to be segmented again, and when the performance influence index Ef is smaller than a second threshold, the task sub-project is represented to be merged into the rest task sub-projects;
the system for performance evaluation comprises the following steps:
s21, the terminal input module collects task completion information of each individual and sends the task completion information to the central processing module;
s22, the central processing module obtains a time evaluation coefficient according to all historical data statistics and feeds the time evaluation coefficient back to the calculation processing module;
s23, the calculation processing module calculates the performance index of an individual according to the time evaluation coefficient and sends the performance index to the central processing module;
and S24, the central processing module obtains the performance evaluation value of the individual according to the performance index comparison analysis of all the individuals.
Example two.
The embodiment includes all contents in the first embodiment, and provides a performance comparison and analysis system based on distributed computing, which includes a terminal input module, a computing processing module, a transmission module and a central processing module, wherein the terminal input module is used for inputting task completion information of an individual, the computing processing module preprocesses the task completion information, the transmission module sends a preprocessing result to the central processing module, and the central processing module performs comparison and analysis on all preprocessing results to obtain a final performance result of each individual;
with reference to fig. 2, the task completion information input in the terminal input module includes a task item, a task sub-item, sub-item states, and completion time, where the task item is composed of a plurality of task sub-items, each task sub-item is a minimum unit constituting the task item, the states of the task sub-items include a completed state and an uncompleted state, and the completion time is a time consumed by the task sub-item in the completed state;
each individual updates task completion information once a month on the terminal input module, the computing processing module obtains task sub-project data completed by the individual in the current month according to the two adjacent task completion information, and the data are uploaded to the central processing module;
referring to fig. 3, a storage unit is provided in the central processing module, and the storage unit is used for storing that each individual finishes every monthThe central processing module is provided with a statistical unit which acquires all completion time data of the same task sub-project from the storage unit and processes the completion time data to obtain a group of time series
I represents the serial number of the element in the time series, and the name is the number of the task sub-item;
in this embodiment, the value range of i is
Said statistical unit determining
The method comprises the following steps:
s1, calculating the average value of all completion times, and recording the average value as
；
S2, obtaining more than
And calculating the average value, and recording as
；
S3, obtaining less than
And calculating an average value of
；
S4, obtaining more than
And calculating the average value, and recording as
；
S5, obtaining less than
And calculating the average value, and recording as
；
The central processing module is provided with a time processing unit which is used for calculating a time evaluation coefficient of each task sub-item finished in the current month by combining with the corresponding time series
：
Wherein the content of the first and second substances,
for the individuals to complete the time of the task sub-item numbered as name, it should be noted that, because the completion time of each individual is different, the time evaluation coefficients of the same task sub-item of different individuals
There are also differences;
the central processing module feeds back the time evaluation coefficients of all task sub-items finished by each individual in the current month to the calculation processing module;
the calculation processing module calculates the performance index of each individual in the current month according to the following formula
：
Wherein n is the number of task sub-items completed by an individual in the current month,
is the working time of a standard month,
is a project completion index;
the calculation formula of the project completion index is as follows:
wherein the content of the first and second substances,
the number of task items that an individual has completed in the month,
the number of task items that an individual may not have completed in its entirety in the month,
the completion progress of the task project which is not completely completed in the current month for an individual;
the completion progress is the ratio of the number of task sub-projects completed in one task project to the number of task sub-projects contained in the task project;
the computing processing module uploads the performance index to the central processing module;
the central processing module ranks the performance indexes P of all individuals in the current month from high to low to obtain a ranking serial number Rk of each individual in the current month, and the central processing module calculates a performance evaluation value Q of each individual in the current month according to the following formula:
wherein the content of the first and second substances,
is the performance index of the individual in the last month,
is the ranking number of the individual in the last month, and N is the number of the individual;
with reference to fig. 4 and 5, the performance evaluation process of the system includes the following steps:
s21, the terminal input module collects task completion information of each individual and sends the task completion information to the central processing module;
s22, the central processing module obtains a time evaluation coefficient according to all historical data statistics and feeds the time evaluation coefficient back to the calculation processing module;
s23, the calculation processing module calculates the performance index of an individual according to the time evaluation coefficient and sends the performance index to the central processing module;
s24, the central processing module obtains performance evaluation values of the individuals according to the performance indexes of all the individuals through comparative analysis;
a sub-project evaluation unit is arranged in the central processing module and used for judging whether newly added task sub-projects need to be subdivided again or not so that all task sub-projects in the system have performance influence of one level, and the sub-project evaluation unit calculates the performance influence index of one task sub-project according to the following formula
：
Wherein, a is a difficulty coefficient, and b is a complex coefficient;
the difficulty coefficient represents the difficulty of solving the problem of the task sub-project, the complexity coefficient represents the number level of the steps of executing the task sub-project, and the values of the complexity coefficient and the difficulty coefficient are natural numbers from 1 to 10 and are evaluated by workers;
when the performance influence index Ef exceeds a first threshold, the task sub-project is represented to be cut again, and when the performance influence index Ef is smaller than a second threshold, the task sub-project is represented to be merged into the rest task sub-projects, so that the performance influence indexes of all the task sub-projects are between the first threshold and the second threshold.
The above disclosure is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, so that all the modifications and equivalents of the technical changes and equivalents made by the disclosure and drawings are included in the scope of the present invention, and the elements thereof may be updated as the technology develops.
Claims (1)
1. A performance comparison and analysis system based on distributed computation is characterized by comprising a terminal input module, a computation processing module, a transmission module and a central processing module, wherein the terminal input module is used for inputting task completion information of individuals, the computation processing module preprocesses the task completion information, the transmission module sends a preprocessed result to the central processing module, and the central processing module performs comparison and analysis on all preprocessed results to obtain a final performance result of each individual;
the task completion information comprises task items, task sub-items, sub-item states and completion time, the task items are composed of a plurality of task sub-items, the sub-item states are used for representing the completion states of the task sub-items, the completion time is used for representing the time consumed by the task sub-items in the completion states, and the computing processing module computes the performance index P of each individual in the month according to the following formula:
wherein n is the number of task sub-items completed by an individual in the current month,
is the working time of a standard month,
for a project completion index, name is the number of task sub-project,
for the completion time of the task sub-item numbered name,
the time evaluation coefficient of the task sub-item with the individual number of name;
the computing processing module uploads the performance index to the central processing module;
the central processing module ranks the performance indexes P of all individuals in the current month from high to low to obtain a ranking serial number Rk of each individual in the current month, and the central processing module calculates a performance evaluation value Q of each individual in the current month according to the following formula:
wherein the content of the first and second substances,
is the performance index of the individual in the last month,
is the ranking serial number of the individual in the last month, and N is the number of the individual;
the central processing module is internally provided with a storage unit, a statistical unit and a time processing unit, wherein the storage unit is used for storing that each individual completes each monthThe statistical unit obtains all the completion time data of the task sub-items with the number of name from the storage unit and processes the completion time data to obtain a group of time series
The time processing unit calculates a time evaluation coefficient according to the following formula
：
Wherein m is a time series
The number of elements in (1);
the central processing module sends the time evaluation coefficient to each calculation processing module;
the calculation formula of the project completion index is as follows:
wherein the content of the first and second substances,
the number of task items that an individual has completed in the month,
the number of task items that an individual does not complete in the month,
the completion progress of the task project which is not completely completed in the current month for an individual;
the central processing moduleA sub-project evaluation unit is arranged in the system, and the sub-project evaluation unit calculates a performance influence index of a task sub-project according to the following formula
：
Wherein, a is a difficulty coefficient, and b is a complex coefficient;
when the performance influence index Ef exceeds a first threshold, the task sub-project is represented to be segmented again, and when the performance influence index Ef is smaller than a second threshold, the task sub-project is represented to be merged into the rest task sub-projects;
the system for performance evaluation comprises the following steps:
s21, the terminal input module collects task completion information of each individual and sends the task completion information to the central processing module;
s22, the central processing module obtains a time evaluation coefficient according to all historical data statistics and feeds the time evaluation coefficient back to the calculation processing module;
s23, the calculation processing module calculates the performance index of an individual according to the time evaluation coefficient and sends the performance index to the central processing module;
and S24, the central processing module obtains the performance evaluation value of the individual according to the performance index comparison analysis of all the individuals.
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