CN117273408A - Panoramic digital operation management platform based on big data technology and enterprise operation management and control - Google Patents

Abstract

The invention discloses a panoramic digital operation management platform based on big data technology and enterprise operation management and control, which relates to the technical field of enterprise operation management and comprises the following steps: the system comprises a post data acquisition module, an employee data acquisition module, a data analysis module, a post matching degree analysis module and a control module; the post matching degree analysis module comprises a corresponding post matching degree calculation unit and a shift change post matching degree calculation unit, wherein the corresponding post matching degree calculation unit is used for calculating the corresponding post matching degree of staff when the corresponding post works; the shift-replacing shift-changing shift matching degree calculating unit is used for analyzing the shift matching degree of the shift replacing shift according to the skill data required by the shift of the shift replacing shift required by the shift replacing shift. The invention can provide decision basis for enterprises when the enterprises need to carry out staff shift replacement and change, and avoid the condition of reduced working efficiency caused by selecting unsuitable staff.

Description

Panoramic digital operation management platform based on big data technology and enterprise operation management and control

Technical Field

The invention relates to the technical field of enterprise operation management, in particular to a panoramic digital operation management platform based on big data technology and enterprise operation management and control.

Background

At present, research and analysis related to enterprise management is in a rapid development stage, a plurality of enterprises can integrate and optimize the operation flow of the enterprises by establishing an enterprise operation management platform, the enterprise operation management platform helps the enterprises to collect and analyze various enterprise data through big data and analysis technology, and the management platform can provide functions of data analysis and forecast management for the enterprises and provide a series of help for the enterprises to adjust operation strategies in time; the matching degree of staff and the position can influence the working efficiency of the staff, and the lower position matching degree can lead to talent loss, so that the normal operation management of enterprises is influenced. Especially, in the enterprise operation management process, the situation that staff is required to go to other posts to replace or change shifts often occurs, if staff which is not matched with the posts is selected to go to the posts to replace or change shifts at this time, the working difficulty of the staff can be improved, the working efficiency of the staff can be reduced, further, if staff which is not matched with the posts is subjected to learning training, the enterprise operation cost can be increased, the working satisfaction of the staff is reduced, and the talent loss of the enterprise is further caused, so that the enterprise operation management is seriously influenced.

The Chinese patent with the application publication number of CN113610367A discloses a digital operation management platform for manufacturing enterprises. The invention obtains a user order sent by an electronic commerce platform by utilizing an order management system, performs shipping processing on the user order when goods in the user order are available, generates a production order when the goods in the user order are not available, sends the production order to an intelligent manufacturing system, generates a production work order according to the production order to produce the goods when materials of the production order are aligned by utilizing the intelligent manufacturing system, sends product reporting information of the goods to the order management system, generates a purchase request when the materials are not aligned by utilizing the intelligent manufacturing system, sends the purchase request to a supply chain management system, generates the purchase order according to the purchase request by utilizing the supply chain management system, performs material sending processing on the purchase order, sends stock preparation information to the intelligent manufacturing system after materials in the purchase order are put in storage, realizes integrated operation management of manufacturing and supply chains, and improves operation management efficiency of manufacturing enterprises.

The problems presented in the background art exist in the above patents: the situation that staff are required to go to other posts to replace or change shifts frequently occurs in the enterprise operation management process is not considered. In order to solve the problem, the invention provides a panoramic digital operation management platform based on big data technology and enterprise operation management and control.

Disclosure of Invention

Aiming at the defects of the prior art, the invention mainly aims to provide a panoramic digital operation management platform based on big data technology and enterprise operation management and control, which can effectively solve the problems in the background technology. The specific technical scheme of the invention is as follows:

panoramic digital operation management platform based on big data technology and enterprise operation management and control, includes: the system comprises a post data acquisition module, an employee data acquisition module, a data analysis module, a post matching degree analysis module and a control module; the post data acquisition module is used for acquiring post required skill data, post corresponding employee age range data and post performance index data; the staff data acquisition module is used for acquiring staff corresponding post data, staff age, staff working years, staff attendance data, staff grading data and staff performance completion data; the data analysis module is used for calculating the work enthusiasm of the staff in the corresponding post based on the staff attendance data, the staff performance completion data and the post performance index data, and calculating the work capacity lifting value of the staff in the corresponding post based on the staff working age, the staff grading data and the staff performance completion data; the post matching degree analysis module comprises a corresponding post matching degree calculation unit and a shift change post matching degree calculation unit, wherein the corresponding post matching degree calculation unit is used for calculating the corresponding post matching degree of staff when the corresponding post works; the shift change position matching degree calculating unit is used for analyzing the position matching degree of the shift change position according to the skill data required by the shift change position required by the shift change according to the output result of the corresponding position matching degree calculating unit; the control module is used for managing and controlling the operation of each module.

The invention is further improved in that the work enthusiasm of the staff working at the corresponding positions is calculated in the data analysis module based on staff attendance data, staff performance completion data and position performance index data, and the method comprises the following specific steps:

s101, setting m posts for an enterprise, wherein n staff working at the ith post are provided, n staff attendance data and n staff performance completion data acquired by the staff data acquisition module are extracted, and the staff attendance data comprise a staff late-arrival day set DC= {}, wherein->The number of late days for the jth employee working at the ith post, and the employee absenteeism number of days set dj= { ∈ ->}, wherein->The number of absences of work days for the jth employee who works at the ith post, and the set of employee leave days dq= { { o }>}, wherein->Leave days for the jth employee working at the ith post; the staff performance completion data comprises a staff performance completion time set T= { }, and the staff performance completion data comprises staff performance completion time sets T= { ->}, wherein->For the j-th work at the i-th positionStaff performance completion time and staff performance completion amount set l= { }, staff performance completion time>}, wherein->Performance completion amount for the jth employee working at the ith post, where i is any one of 1 to m and j is any one of 1 to n;

s102, extracting the post performance index data acquired by the post data acquisition module; the post performance indicator data includes an i-th post required completion performance amount Lzi;

s103, calculating the late enthusiasm of the jth employee working at the ith position；

S104, calculating the absenteeism enthusiasm of the jth staff working at the ith position；

S105, calculating the enthusiasm of the j staff working at the i-th position。

The invention is further improved in that the data analysis module calculates the work enthusiasm of the staff working at the corresponding positions based on staff attendance data, staff performance completion data and post performance index data, and the invention further comprises the following specific steps:

s106, calculating the completion performance enthusiasm of the jth employee working at the ith position

；

S107, the enthusiasm of the j staff working at the i-th position

。

The invention further improves that the data analysis module calculates the working capacity lifting value of the staff at the corresponding post based on the staff working years, the staff grading data and the staff performance completion data, and comprises the following specific steps:

s201, extracting employee working years acquired by the employee data acquisition module, wherein the employee working years comprise an employee working years set Y= { working at the ith post}, wherein->The work years for the jth employee who is working at the ith post, and employee grading data comprising a employee grading data set Level = { { about employee who is working at the ith post>，/>}, wherein->For the current grading of the jth employee working at the ith station,for the grading of the j-th employee working at the i-th post when the employee is working, and employee performance completion data, the employee performance completion data further comprises a employee performance completion time difference set +.>Wherein->For the performance completion time of the jth employee working at the ith post +.>To be at the ith positionPerformance completion time of the j-th employee of the job just in-time;

s202, calculating a level capacity improvement value of a jth employee working at an ith position

；

S203, calculating a performance completion capability improvement value of the jth employee working at the ith position

；

S204, calculating the improvement value of the work capacity of the jth employee of the ith post work based on S202 and S203。

The invention further improves that the position matching degree of the staff working at the corresponding position is calculated in the corresponding position matching degree calculating unit, which comprises the following specific steps:

s301, extracting employee ages acquired by the employee data acquisition module, and establishing m employee age sets about work in the ith postWherein->The age of the jth employee for work at the ith post;

s302, extracting staff age range data corresponding to the posts, which are acquired by the post data acquisition module, wherein the staff age range data corresponding to the posts comprise m staff age range intervals corresponding to the posts, and setting the staff age range interval corresponding to the i-th post asWherein->For the employee age range area corresponding to the ith postLower limit value of>The upper limit value of the employee age range interval corresponding to the ith post;

s303, calculating the age matching degree of the jth employee。

The invention further improves that the position matching degree of staff working at the corresponding position is calculated in the corresponding position matching degree calculating unit, and the method further comprises the following specific steps:

s304, calculating the matching degree of the work enthusiasm of the jth employee；

S305, calculating the matching degree of the improvement value of the working capacity of the jth employee；

S306, calculating the position matching degree of the jth employee when working at the corresponding position based on S303, S304 and S305Wherein->Is age-matched degree duty ratio coefficient, < >>A duty ratio coefficient for matching the working enthusiasm,Duty factor for improving working capacity, +.>Are all greater than 0->。

The invention further improves the technical data needed by the shift change position according to the need in the shift change position matching degree calculating unit, and the specific steps of analyzing the position matching degree of the shift change position according to the output result of the position matching degree calculating unit are as follows:

s401, extracting skill data required by the posts acquired by the post data acquisition module, wherein the skill data required by the posts comprises m skill data sets required by the postsWherein->A skill data set required for the ith post, i being any one of 1 to m;

s402, calculating the skill matching degree between the positions needing to be substituted for shift change and the positions corresponding to the staffWherein->For the required skill data set of the corresponding post of the post which needs to be substituted for shift change,/for the post>Skill data required by corresponding positions of staff, symbol +.>Representing data-taking intersection operations within a set, +.>Representing the number of data in the set in brackets;

s403, calculating the matching degree of shift change positions。

The post matching degree analysis module is further improved in that the post matching degree analysis module further comprises an employee selection unit, wherein the employee selection unit is used for selecting an employee with the highest post matching degree for shift-changing and shift-changing according to posts for shift-changing and shift-changing.

The panoramic digital operation management method based on the big data technology and the enterprise operation control is used for realizing the panoramic digital operation management platform based on the big data technology and the enterprise operation control, and comprises the following specific steps:

a1, acquiring skill data required by posts, employee age range data corresponding to the posts and post performance index data;

a2, collecting employee corresponding post data, employee age, employee working years, employee attendance data, employee grading data and employee performance completion data;

a3, calculating the work enthusiasm of the staff in the corresponding post work based on the staff attendance data, the staff performance completion data and the post performance index data;

a4, calculating the working capacity lifting value of the staff at the corresponding post based on the staff working years, the staff grading data and the staff performance completion data;

a5, calculating the post matching degree of staff when working at the corresponding post based on the A3 and the A4;

a6, analyzing the position matching degree of the shift replacing position according to the skill data required by the shift replacing position and the position matching degree of the staff when the corresponding position works;

and A7, carrying out shift replacement and shift replacement according to the requirements, and selecting the staff with the highest shift replacement and shift replacement position matching degree to carry out shift replacement and shift replacement.

Compared with the prior art, the invention has the following beneficial effects:

collecting employee corresponding post data, employee age, employee working years, employee attendance data, employee grading data and employee performance completion data; calculating the work enthusiasm of the staff in the corresponding post work based on the staff attendance data, the staff performance completion data and the post performance index data; calculating the working capacity lifting value of the staff at the corresponding post based on the staff working years, the staff grading data and the staff performance completion data; calculating the post matching degree of staff when working at the corresponding post; analyzing the position matching degree of the shift replacing and shifting positions according to the skill data required by the positions for the shift replacing and shifting and the position matching degree of the staff when the corresponding positions work; and selecting the staff with the highest matching degree for the shift replacing shift to replace the shift according to the shift of the shift replacing shift required. The invention considers the situation that staff is required to go to other posts to replace or change shifts frequently in the enterprise operation management process, provides decision basis for the situation that the staff is required to replace shifts of the enterprise, and avoids the situation that the working efficiency is reduced due to the selection of unsuitable staff. The work difficulty of staff is reduced, the work efficiency of staff is improved, the enterprise operation cost is reduced, the work satisfaction of staff is improved, and the enterprise operation management efficiency is improved.

Drawings

FIG. 1 is a schematic diagram of a panoramic digital operation management platform based on big data technology and enterprise operation management and control according to the present invention;

fig. 2 is a workflow diagram of a panoramic digital operation management method based on big data technology and enterprise operation management in accordance with the present invention.

Detailed Description

In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.

Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.

Example 1

The embodiment provides a panoramic digital operation management platform based on big data technology and enterprise operation management and control, as shown in fig. 1, including: the system comprises a post data acquisition module, an employee data acquisition module, a data analysis module, a post matching degree analysis module and a control module; the post data acquisition module is used for acquiring post required skill data, post corresponding employee age range data and post performance index data; the staff data acquisition module is used for acquiring staff corresponding post data, staff age, staff working years, staff attendance data, staff grading data and staff performance completion data; the data analysis module is used for calculating the work enthusiasm of the staff in the corresponding post based on the staff attendance data, the staff performance completion data and the post performance index data, and calculating the work capacity lifting value of the staff in the corresponding post based on the staff working age, the staff grading data and the staff performance completion data; the post matching degree analysis module comprises a corresponding post matching degree calculation unit and a shift change post matching degree calculation unit, wherein the corresponding post matching degree calculation unit is used for calculating the corresponding post matching degree of staff when the corresponding post works; the shift change position matching degree calculating unit is used for analyzing the position matching degree of the shift change position according to the skill data required by the shift change position required by the shift change according to the output result of the corresponding position matching degree calculating unit; the control module is used for managing and controlling the operation of each module.

In this embodiment, the working enthusiasm of the staff working at the corresponding post is calculated in the data analysis module based on the staff attendance data, the staff performance completion data and the post performance index data, and the method includes the following specific steps:

s101, setting m posts for an enterprise, wherein n staff working at the ith post are provided, n staff attendance data and n staff performance completion data acquired by the staff data acquisition module are extracted, and the staff attendance data comprise a staff late-arrival day set DC= {}, wherein->The number of late days for the jth employee working at the ith post, and the employee absenteeism number of days set dj= { ∈ ->}, wherein->The number of absences of work days for the jth employee who works at the ith post, and the set of employee leave days dq= { { o }>}, wherein->Leave days for the jth employee working at the ith post; the staff performance completion data comprises a staff performance completion time set T= { }, and the staff performance completion data comprises staff performance completion time sets T= { ->}, wherein->Performance completion time for the jth employee working at the ith post, and an employee performance completion amount set l= { +.>}, wherein->Performance completion amount for the jth employee working at the ith post, where i is any one of 1 to m and j is any one of 1 to n;

s102, extracting the post performance index data acquired by the post data acquisition module; the post performance indicator data includes an i-th post required completion performance amount Lzi;

s103, calculating the late enthusiasm of the jth employee working at the ith position；

S104, calculating the absenteeism enthusiasm of the jth staff working at the ith position；

S105, calculating the enthusiasm of the j staff working at the i-th position。

In this embodiment, the data analysis module calculates the work enthusiasm of the employee in the corresponding post based on the employee attendance data, the employee performance completion data, and the post performance index data, and further includes the following specific steps:

s106, calculating the completion performance enthusiasm of the jth employee working at the ith position

；

S107, the enthusiasm of the j staff working at the i-th position

。

In this embodiment, the data analysis module calculates the working capacity improvement value of the employee at the corresponding post based on the working years of the employee, the employee grading data and the employee performance completion data, and includes the following specific steps:

s201, extracting employee working years acquired by the employee data acquisition module, wherein the employee working years comprise an employee working years set Y= { working at the ith post}, wherein->The work years for the jth employee who is working at the ith post, and employee grading data comprising a employee grading data set Level = { { about employee who is working at the ith post>，/>}, wherein->For the current grading of the jth employee working at the ith station,for the grading of the j-th employee working at the i-th post when the employee is working, and employee performance completion data, the employee performance completion data further comprises a employee performance completion time difference set +.>Wherein->For the performance completion time of the jth employee working at the ith post +.>Performance completion time for the j-th employee who is working at the i-th post just entered the job;

s202, calculating a level capacity improvement value of a jth employee working at an ith position

；

S203, calculating a performance completion capability improvement value of the jth employee working at the ith position

；

S204, calculating the improvement value of the work capacity of the jth employee of the ith post work based on S202 and S203。

In this embodiment, the step of calculating the step matching degree of the employee when the employee works at the corresponding step in the corresponding step matching degree calculating unit includes the following specific steps:

s301, extracting employee ages acquired by the employee data acquisition module, and establishing m employee age sets about work in the ith postWherein->The age of the jth employee for work at the ith post;

s302, extracting staff age range data corresponding to the posts, which are acquired by the post data acquisition module, wherein the staff age range data corresponding to the posts comprise m staff age range intervals corresponding to the posts, and setting the staff age range interval corresponding to the i-th post asWherein->For the lower limit value of the employee age range corresponding to the ith post, < +.>The upper limit value of the employee age range interval corresponding to the ith post;

s303, calculating the age matching degree of the jth employee。

In this embodiment, the step of calculating the step matching degree of the employee when the employee works at the corresponding step in the corresponding step matching degree calculating unit further includes the following specific steps:

s304, calculating the matching degree of the work enthusiasm of the jth employee；

S305, calculating the matching degree of the improvement value of the working capacity of the jth employee；

S306, calculating the position matching degree of the jth employee when working at the corresponding position based on S303, S304 and S305Wherein->Is age-matched degree duty ratio coefficient, < >>A duty ratio coefficient for matching the working enthusiasm,Duty factor for improving working capacity, +.>Are all greater than 0->。

In this embodiment, the specific steps of analyzing the post matching degree of the shift-replacing shift according to the skill data required by the shift of the shift-replacing shift as required in the shift-replacing shift matching degree calculating unit and the output result of the corresponding shift matching degree calculating unit are as follows:

s401, extracting skill data required by the posts acquired by the post data acquisition module, wherein the skill data required by the posts comprises m skill data sets required by the postsWherein->A skill data set required for the ith post, i being any one of 1 to m;

s402, calculating the skill matching degree between the positions needing to be substituted for shift change and the positions corresponding to the staffWherein->For the required skill data set of the corresponding post of the post which needs to be substituted for shift change,/for the post>Skill data required by corresponding positions of staff, symbol +.>Representing data-taking intersection operations within a set, +.>Representing the number of data in the set in brackets;

s403, calculating the matching degree of shift change positions。

In this embodiment, the post matching degree analysis module further includes an employee selection unit, where the employee selection unit is configured to perform a shift change according to a post that needs to perform a shift change, and select an employee with the highest shift change post matching degree to perform a shift change.

Example 2

The embodiment provides a panoramic digital operation management method based on big data technology and enterprise operation control, which is used for realizing the panoramic digital operation management platform based on big data technology and enterprise operation control provided in embodiment 1, as shown in fig. 2, and the method comprises the following specific steps:

a1, acquiring skill data required by posts, employee age range data corresponding to the posts and post performance index data;

a2, collecting employee corresponding post data, employee age, employee working years, employee attendance data, employee grading data and employee performance completion data;

a3, calculating the work enthusiasm of the staff in the corresponding post work based on the staff attendance data, the staff performance completion data and the post performance index data;

a4, calculating the working capacity lifting value of the staff at the corresponding post based on the staff working years, the staff grading data and the staff performance completion data;

a5, calculating the post matching degree of staff when working at the corresponding post based on the A3 and the A4;

a6, analyzing the position matching degree of the shift replacing position according to the skill data required by the shift replacing position and the position matching degree of the staff when the corresponding position works;

and A7, carrying out shift replacement and shift replacement according to the requirements, and selecting the staff with the highest shift replacement and shift replacement position matching degree to carry out shift replacement and shift replacement.

Through the embodiment, multidimensional data are collected, and the working capacity improvement value of staff at the corresponding post is calculated; calculating the post matching degree of staff when working at the corresponding post; analyzing the position matching degree of the shift replacing and shifting positions according to the skill data required by the positions for the shift replacing and shifting and the position matching degree of the staff when the corresponding positions work; and selecting the staff with the highest matching degree for the shift replacing shift to replace the shift according to the shift of the shift replacing shift required. Under the condition that staff is required to go to other posts to replace or change shifts frequently in the enterprise operation management process, decision basis is provided for the situation that the staff is required to replace shifts of the enterprises, and the situation that the working efficiency is reduced due to the fact that unsuitable staff is selected is avoided. The work difficulty of staff is reduced, the work efficiency of staff is improved, the enterprise operation cost is reduced, the work satisfaction of staff is improved, and the enterprise operation management efficiency is improved.

The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (9)

1. Panoramic digital operation management platform based on big data technology and enterprise operation management and control, its characterized in that: comprising the following steps: the system comprises a post data acquisition module, an employee data acquisition module, a data analysis module, a post matching degree analysis module and a control module; the post data acquisition module is used for acquiring post required skill data, post corresponding employee age range data and post performance index data; the staff data acquisition module is used for acquiring staff corresponding post data, staff age, staff working years, staff attendance data, staff grading data and staff performance completion data; the data analysis module is used for calculating the work enthusiasm of the staff in the corresponding post based on the staff attendance data, the staff performance completion data and the post performance index data, and calculating the work capacity lifting value of the staff in the corresponding post based on the staff working age, the staff grading data and the staff performance completion data; the post matching degree analysis module comprises a corresponding post matching degree calculation unit and a shift change post matching degree calculation unit, wherein the corresponding post matching degree calculation unit is used for calculating the corresponding post matching degree of staff when the corresponding post works; the shift change position matching degree calculating unit is used for analyzing the position matching degree of the shift change position according to the skill data required by the shift change position required by the shift change according to the output result of the corresponding position matching degree calculating unit; the control module is used for managing and controlling the operation of each module.

2. The panoramic digital operation management platform based on big data technology and enterprise operation management and control of claim 1, wherein: the data analysis module calculates the work enthusiasm of staff working at the corresponding positions based on staff attendance data, staff performance completion data and position performance index data, and comprises the following specific steps:

s101, setting m posts for an enterprise, wherein n staff working at the ith post are provided, n staff attendance data and n staff performance completion data acquired by the staff data acquisition module are extracted, and the staff attendance data comprise a staff late-arrival day set DC= {}, wherein->The number of late days for the jth employee working at the ith post, and the employee absenteeism number of days set dj= { ∈ ->}, wherein->The number of absences of work days for the jth employee who works at the ith post, and the set of employee leave days dq= { { o }>}, wherein->Leave days for the jth employee working at the ith post; the staff performance completion data comprises a staff performance completion time set T= { }, and the staff performance completion data comprises staff performance completion time sets T= { ->}, wherein->Performance completion time for the jth employee working at the ith post, and an employee performance completion amount set l= { +.>}, wherein->Performance completion amount for the jth employee working at the ith post, where i is any one of 1 to m and j is any one of 1 to n;

s102, extracting the post performance index data acquired by the post data acquisition module; the post performance indicator data includes an i-th post required completion performance amount Lzi;

s103, calculating the late enthusiasm of the jth employee working at the ith position；

S104, calculating the absenteeism enthusiasm of the jth staff working at the ith position；

S105, calculating the enthusiasm of the j staff working at the i-th position。

3. The panoramic digital operation management platform based on big data technology and enterprise operation management and control of claim 2, wherein: the data analysis module calculates the work enthusiasm of the staff working at the corresponding positions based on staff attendance data, staff performance completion data and position performance index data, and the data analysis module further comprises the following specific steps:

s106, calculating the completion performance enthusiasm of the jth employee working at the ith position

；

S107, the enthusiasm of the j staff working at the i-th position。

4. The panoramic digital operation management platform based on big data technology and enterprise operation management and control of claim 3, wherein: the data analysis module calculates the work capacity lifting value of the staff at the corresponding post based on the staff work age, the staff grading data and the staff performance completion data, and comprises the following specific steps:

s201, extracting employee working years acquired by the employee data acquisition module, wherein the employee working years comprise an employee working years set Y= { working at the ith post}, wherein->The work years for the jth employee who is working at the ith post, and employee grading data comprising a employee grading data set Level = { { about employee who is working at the ith post>，/>}, wherein->For the current rating of the jth employee working at the ith station +.>For the grading of the j-th employee working at the i-th post when the employee is working, and employee performance completion data, the employee performance completion data further comprises a employee performance completion time difference set +.>Wherein->For the performance completion time of the jth employee working at the ith post +.>Performance completion time for the j-th employee who is working at the i-th post just entered the job;

s202, calculating a level capacity improvement value of a jth employee working at an ith position

；

S203, calculating a performance completion capability improvement value of the jth employee working at the ith position；

S204, calculating the improvement value of the work capacity of the jth employee of the ith post work based on S202 and S203。

5. The panoramic digital operation management platform based on big data technology and enterprise operation management and control of claim 4, wherein: the post matching degree calculation unit for calculating the post matching degree of the staff working at the corresponding post comprises the following specific steps:

s301, extracting employee ages acquired by the employee data acquisition module, and establishing m employee age sets about work in the ith postWherein->The age of the jth employee for work at the ith post;

s302, extracting staff age range data corresponding to the posts, which are acquired by the post data acquisition module, wherein the staff age range data corresponding to the posts comprise m staff age range intervals corresponding to the posts, and setting the staff age range interval corresponding to the i-th post asWherein->For the lower limit value of the employee age range corresponding to the ith post, < +.>The upper limit value of the employee age range interval corresponding to the ith post;

s303, calculating the age matching degree of the jth employee。

6. The panoramic digital operation management platform based on big data technology and enterprise operation management and control of claim 5, wherein: the position matching degree calculation unit for calculating the position matching degree of the staff working at the corresponding position further comprises the following specific steps:

s304, calculating the matching degree of the work enthusiasm of the jth employee；

S305, calculating the matching degree of the improvement value of the working capacity of the jth employee；

S306, calculating the position matching degree of the jth employee when working at the corresponding position based on S303, S304 and S305Wherein->Is age-matched degree duty ratio coefficient, < >>A duty ratio coefficient for matching the working enthusiasm,Duty factor for improving working capacity, +.>Are all greater than 0->。

7. The panoramic digital operation management platform based on big data technology and enterprise operation management and control of claim 6, wherein: the specific steps of analyzing the post matching degree of the shift change post according to the skill data required by the post of the shift change according to the requirement in the shift change post matching degree calculating unit and the output result of the corresponding post matching degree calculating unit are as follows:

s401, extracting skill data required by the posts acquired by the post data acquisition module, wherein the skill data required by the posts comprises m skill data sets required by the postsWherein->A skill data set required for the ith post, i being any one of 1 to m;

s402, calculating the skill matching degree between the positions needing to be substituted for shift change and the positions corresponding to the staffWherein->For the required skill data set of the corresponding post of the post which needs to be substituted for shift change,/for the post>Skill data required by corresponding positions of staff, symbol +.>Representing data-taking intersection operations within a set, +.>Representing the number of data in the set in brackets;

s403, calculating the matching degree of shift change positions。

8. The panoramic digital operation management platform based on big data technology and enterprise operation management and control of claim 7, wherein: the post matching degree analysis module further comprises an employee selection unit, wherein the employee selection unit is used for selecting an employee with the highest post matching degree for shift-changing and shift-changing according to posts for shift-changing and shift-changing.

9. The panoramic digital operation management method based on big data technology and enterprise operation control, which is used for realizing the panoramic digital operation management platform based on big data technology and enterprise operation control as claimed in any one of claims 1-8, and is characterized in that: the method comprises the following specific steps:

a1, acquiring skill data required by posts, employee age range data corresponding to the posts and post performance index data;

a2, collecting employee corresponding post data, employee age, employee working years, employee attendance data, employee grading data and employee performance completion data;

a3, calculating the work enthusiasm of the staff in the corresponding post work based on the staff attendance data, the staff performance completion data and the post performance index data;

a4, calculating the working capacity lifting value of the staff at the corresponding post based on the staff working years, the staff grading data and the staff performance completion data;

a5, calculating the post matching degree of staff when working at the corresponding post based on the A3 and the A4;

a6, analyzing the position matching degree of the shift replacing position according to the skill data required by the shift replacing position and the position matching degree of the staff when the corresponding position works;

and A7, carrying out shift replacement and shift replacement according to the requirements, and selecting the staff with the highest shift replacement and shift replacement position matching degree to carry out shift replacement and shift replacement.