CN113159724A - Enterprise management platform organizational framework task management method based on big data - Google Patents
Enterprise management platform organizational framework task management method based on big data Download PDFInfo
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Abstract
The invention discloses an enterprise management platform organizational framework task management method based on big data, which belongs to the field of enterprise management and relates to big data technology, and comprises a server, a registration login module, a permission distribution module, a task management module, a time supervision module, a plan management module, a task early warning module, an examination evaluation module and a management query module; through the mutual cooperation between each module, realize the clear management and control of task among the company enterprise, no longer just see the result and do not see a management mode of process, strengthen the management and control to each node of task, find the problem that task completion probably met before the task is not accomplished, manage and control in advance, the better on time basis of guaranteeing the task is accomplished according to the volume.
Description
Technical Field
The invention belongs to the field of enterprise management, relates to a big data technology, and particularly relates to a big data-based enterprise management platform organizational framework task management method.
Background
Big data (big data), an IT industry term, refers to a data set that cannot be captured, managed, and processed with a conventional software tool within a certain time range, and is a massive, high-growth-rate, diversified information asset that needs a new processing mode to have stronger decision-making power, insight discovery power, and process optimization capability.
In the existing enterprise management modes, most of enterprise tasks of companies do not have a clear management and control method and a clear management and control mode, the management and control method is a management mode that only results are seen but the process is not seen, management and control on all nodes of the tasks are lacked, problems possibly met by task completion are found before the tasks are not completed, management and control are carried out in advance, and timely completion of the tasks is better guaranteed.
Therefore, the enterprise management platform organizational framework task management method based on the big data is provided.
Disclosure of Invention
In order to solve the problems existing in the scheme, the invention provides a big data-based enterprise management platform organizational framework task management method.
The purpose of the invention can be realized by the following technical scheme:
an enterprise management platform organization framework task management method based on big data comprises a server, a registration login module, a permission distribution module, a task management module, a time supervision module, a plan management module, a task early warning module, an evaluation module and a management query module;
the registration login module is used for inputting personal information by a user to perform registration login and sending the personal information of the user who successfully registers to the server, and the server generates a registration account and a login password according to the registration time of the user, wherein the registration account and the login password are used for the user to login the server next time; the authority distribution module is in wireless communication connection with the server, acquires personal information of a user stored in the server, and sets authority distribution according to a work position in the personal information, wherein the user belongs to a first-level authority distributed by a base-level employee, the user belongs to a second-level authority distributed by a middle-level trunk, the user belongs to a third-level authority distributed by a high-level leader, and the higher the level authority is, the more the acquired authorities are;
the personal information input during the user registration comprises a user name, a user age, an identity card number of the user, a work position of the user and a mobile phone number of real-name authentication of the user; the work position of the user comprises a base layer staff, a middle layer cadre and a high-level leader;
the task management module is in wireless communication connection with the server and is divided into a primary task unit, a middle-level task unit and a high-level task unit, tasks in the primary task unit are directly distributed to base-level employees, tasks in the middle-level task unit need users with second-level authority and above-level authority to perform task assignment, and tasks in the high-level task unit need users with second-level authority to perform task assignment;
preferably, the high-level leader with the third-level authority has the right to directly assign the tasks, and all the tasks can be distributed to all the users; the middle layer cadre with the second grade authority has the right to assign the middle-grade task unit and the task in the primary task unit; and cannot assign tasks in the primary task unit or the intermediate task unit to an advanced leader having a third level of authority;
preferably, the schedule management module is in wireless communication connection with the task management module, the schedule management module directly acquires all tasks in the task management module, automatically generates a task monitoring node, and directly acquires a user who receives the tasks, the time monitoring module is used for monitoring the tasks in real time, and the specific operation process of the time monitoring module includes the following steps:
the method comprises the following steps: the time supervision module is in wireless communication connection with the plan management module, and acquires tasks, task supervision nodes and users receiving the tasks in the plan management module;
step two: the time supervision module marks the task supervision node and the user receiving the task as Ri and j respectively; where R denotes a task, i denotes a node, i ═ 1,2 … … n:
step three: acquiring the current time T, and comparing the current time T with the time of the task monitoring node Ri by the time monitoring module; if the current time T belongs to Rx time and Rx +1 time, the task is in the x-th planning time node, wherein 0< x < n; x is a positive integer;
step four: acquiring a current actual task completion node Rs; wherein s is a positive integer; when Rx is equal to Rs, the task is normally carried out, and the time supervision module sends a task normal signal to the server;
when Rx is not equal to Rs and s-x is larger than or equal to 3, indicating that the task is seriously disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j by a link server, and sending a task serious disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of serious task early warning of the user j is increased and is sent to a server for storage;
when Rx is not equal to Rs and 3 is larger than s-x and is larger than or equal to 1, indicating that the task is disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of slight early warning of the task of the user j is increased and is sent to the server for storage;
when Rx is not equal to Rs and x-s is larger than or equal to 1, indicating that the task is advanced, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task advance signal to a real-name authentication mobile phone of the user higher than the work position; and simultaneously, the task advance times of the user j are increased and are sent to the server for storage.
Preferably, the management query module is configured to query a task completion status of the user and feed the task completion status back to the assessment evaluation module, and a specific way for the assessment evaluation module to assess the user includes the following steps:
step S1: the management query module is linked with the server and acquires a user j which is stored in the server and receives the task;
step S2: the management query module acquires the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j; the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j are sent to the assessment module;
step S3: after receiving the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j, the assessment evaluation module marks the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times as Wcj, Qwj, Yzj and Cqj respectively;
step S4: the assessment evaluation module calculates an annual evaluation coefficient Pjj of the user j by using a calculation formula
Wherein a, b and c are preset proportionality coefficients, and a + b + c is 1;
step S5: the assessment evaluation module sets an annual evaluation coefficient threshold, and when the annual evaluation coefficient Pjj of the user j is greater than or equal to the annual evaluation coefficient threshold, the user j is qualified in annual performance; when the annual evaluation coefficient Pjj of the user j is smaller than the annual evaluation coefficient threshold, the user j is represented to be unqualified in annual performance; the assessment evaluation module sends the annual evaluation coefficient Pjj of the user j to the server for storage;
step S6: and the assessment evaluation module performs descending order arrangement on the annual evaluation coefficients of all the users, and defines the users ranked in the top three as excellent annual employees.
Preferably, the enterprise management platform organizational framework task management method based on big data specifically comprises the following steps:
step P1: distributing the authority;
the user inputs personal information to register and log in, the authority distribution module is in wireless communication connection with the server, authority distribution is set according to the work positions in the personal information, the user belongs to the first-level authority distributed by the base-level staff, the user belongs to the second-level authority distributed by the middle-level trunk, and the user belongs to the third-level authority distributed by the high-level leader;
step P2: distributing tasks;
the task management module is in wireless communication connection with the server and is divided into a primary task unit, a middle-level task unit and a high-level task unit, tasks in the primary task unit are directly distributed to base-level employees, tasks in the middle-level task unit need users with second-level authority and above-level authority to perform task assignment, and tasks in the high-level task unit need users with second-level authority to perform task assignment;
step P3: task supervision;
the time supervision module is in wireless communication connection with the plan management module, and acquires tasks, task supervision nodes and users receiving the tasks in the plan management module;
the time supervision module marks the task supervision node and the user receiving the task as Ri and j respectively; acquiring the current time T, and comparing the current time T with the time of the task monitoring node Ri by the time monitoring module; if the current time T belongs to Rx time and Rx +1 time, the task is in the x-th planning time node;
step P4: task early warning;
acquiring a current actual task completion node Rs;
when Rx is equal to Rs, the task is normally carried out, and the time supervision module sends a task normal signal to the server;
when Rx is not equal to Rs and s-x is larger than or equal to 3, indicating that the task is seriously disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j by a link server, and sending a task serious disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of serious task early warning of the user j is increased and is sent to a server for storage;
when Rx is not equal to Rs and 3 is larger than s-x and is larger than or equal to 1, indicating that the task is disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of slight early warning of the task of the user j is increased and is sent to the server for storage;
when Rx is not equal to Rs and x-s is larger than or equal to 1, indicating that the task is advanced, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task advance signal to a real-name authentication mobile phone of the user higher than the work position; and simultaneously, the task advance times of the user j are increased and are sent to the server for storage.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is provided with a time supervision module which is used for managing and controlling each time node of the task of the user, grasping the progress of the task and early warning the task which cannot be completed or is disconnected in time, thereby ensuring the punctual completion of the task.
2. The task management module is in wireless communication connection with the server and is divided into a primary task unit, a middle-level task unit and a high-level task unit, tasks in the primary task unit are directly distributed to base-level employees, tasks in the middle-level task unit need users with second-level authority and higher-level authority to perform task assignment, and tasks in the high-level task unit need users with the second-level authority to perform task assignment.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic block diagram of a big data-based enterprise management platform organizational framework task management method according to the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
As shown in fig. 1, a big data-based enterprise management platform organizational framework task management method includes a server, a registration login module, a permission allocation module, a task management module, a time supervision module, a plan management module, a task early warning module, an assessment and evaluation module, and a management query module;
the registration login module is used for inputting personal information by a user to perform registration login and sending the personal information of the user who successfully registers to the server, and the server generates a registration account and a login password according to the registration time of the user, wherein the registration account and the login password are used for the user to login the server next time; the authority distribution module is in wireless communication connection with the server, acquires personal information of a user stored in the server, and sets authority distribution according to a work position in the personal information, wherein the user belongs to a first-level authority distributed by a base-level employee, the user belongs to a second-level authority distributed by a middle-level trunk, the user belongs to a third-level authority distributed by a high-level leader, and the higher the level authority is, the more the acquired authorities are;
the personal information input during the user registration comprises a user name, a user age, an identity card number of the user, a work position of the user and a mobile phone number of real-name authentication of the user; the work position of the user comprises a base layer staff, a middle layer cadre and a high-level leader;
the task management module is in wireless communication connection with the server and is divided into a primary task unit, a middle-level task unit and a high-level task unit, tasks in the primary task unit are directly distributed to base-level employees, tasks in the middle-level task unit need users with second-level authority and above-level authority to perform task assignment, and tasks in the high-level task unit need users with second-level authority to perform task assignment;
the high-level leader with the third-level right has the right to directly assign tasks, and can distribute all the tasks to all the users; the middle layer cadre with the second grade authority has the right to assign the middle-grade task unit and the task in the primary task unit; and cannot assign tasks in the primary task unit or the intermediate task unit to an advanced leader having a third level of authority;
the system comprises a schedule management module, a task management module and a time supervision module, wherein the schedule management module is in wireless communication connection with the task management module, directly acquires all tasks in the task management module, automatically generates task supervision nodes and directly acquires users receiving the tasks, the time supervision module is used for supervising the tasks in real time, and the specific operation process of the time supervision module comprises the following steps:
the method comprises the following steps: the time supervision module is in wireless communication connection with the plan management module, and acquires tasks, task supervision nodes and users receiving the tasks in the plan management module;
step two: the time supervision module marks the task supervision node and the user receiving the task as Ri and j respectively; where R denotes a task, i denotes a node, i ═ 1,2 … … n:
step three: acquiring the current time T, and comparing the current time T with the time of the task monitoring node Ri by the time monitoring module; if the current time T belongs to Rx time and Rx +1 time, the task is in the x-th planning time node, wherein 0< x < n; x is a positive integer;
step four: acquiring a current actual task completion node Rs; wherein s is a positive integer; when Rx is equal to Rs, the task is normally carried out, and the time supervision module sends a task normal signal to the server;
when Rx is not equal to Rs and s-x is larger than or equal to 3, indicating that the task is seriously disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j by a link server, and sending a task serious disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of serious task early warning of the user j is increased and is sent to a server for storage;
when Rx is not equal to Rs and 3 is larger than s-x and is larger than or equal to 1, indicating that the task is disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of slight early warning of the task of the user j is increased and is sent to the server for storage;
when Rx is not equal to Rs and x-s is larger than or equal to 1, indicating that the task is advanced, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task advance signal to a real-name authentication mobile phone of the user higher than the work position; and simultaneously, the task advance times of the user j are increased and are sent to the server for storage.
The management query module is used for querying the task completion condition of the user and feeding the task completion condition back to the assessment evaluation module, and the specific assessment evaluation module assessment evaluation user mode comprises the following steps:
step S1: the management query module is linked with the server and acquires a user j which is stored in the server and receives the task;
step S2: the management query module acquires the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j; the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j are sent to the assessment module;
step S3: after receiving the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j, the assessment evaluation module marks the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times as Wcj, Qwj, Yzj and Cqj respectively;
step S4: the assessment evaluation module calculates an annual evaluation coefficient Pjj of the user j by using a calculation formula
Whereina. b and c are preset proportionality coefficients, and a + b + c is 1;
step S5: the assessment evaluation module sets an annual evaluation coefficient threshold, and when the annual evaluation coefficient Pjj of the user j is greater than or equal to the annual evaluation coefficient threshold, the user j is qualified in annual performance; when the annual evaluation coefficient Pjj of the user j is smaller than the annual evaluation coefficient threshold, the user j is represented to be unqualified in annual performance; the assessment evaluation module sends the annual evaluation coefficient Pjj of the user j to the server for storage;
step S6: and the assessment evaluation module performs descending order arrangement on the annual evaluation coefficients of all the users, and defines the users ranked in the top three as excellent annual employees.
The enterprise management platform organizational framework task management method based on the big data comprises the following specific steps:
step P1: distributing the authority;
the user inputs personal information to register and log in, the authority distribution module is in wireless communication connection with the server, authority distribution is set according to the work positions in the personal information, the user belongs to the first-level authority distributed by the base-level staff, the user belongs to the second-level authority distributed by the middle-level trunk, and the user belongs to the third-level authority distributed by the high-level leader;
step P2: distributing tasks;
the task management module is in wireless communication connection with the server and is divided into a primary task unit, a middle-level task unit and a high-level task unit, tasks in the primary task unit are directly distributed to base-level employees, tasks in the middle-level task unit need users with second-level authority and above-level authority to perform task assignment, and tasks in the high-level task unit need users with second-level authority to perform task assignment;
step P3: task supervision;
the time supervision module is in wireless communication connection with the plan management module, and acquires tasks, task supervision nodes and users receiving the tasks in the plan management module;
the time supervision module marks the task supervision node and the user receiving the task as Ri and j respectively; acquiring the current time T, and comparing the current time T with the time of the task monitoring node Ri by the time monitoring module; if the current time T belongs to Rx time and Rx +1 time, the task is in the x-th planning time node;
step P4: task early warning;
acquiring a current actual task completion node Rs;
when Rx is equal to Rs, the task is normally carried out, and the time supervision module sends a task normal signal to the server;
when Rx is not equal to Rs and s-x is larger than or equal to 3, indicating that the task is seriously disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j by a link server, and sending a task serious disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of serious task early warning of the user j is increased and is sent to a server for storage;
when Rx is not equal to Rs and 3 is larger than s-x and is larger than or equal to 1, indicating that the task is disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of slight early warning of the task of the user j is increased and is sent to the server for storage;
when Rx is not equal to Rs and x-s is larger than or equal to 1, indicating that the task is advanced, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task advance signal to a real-name authentication mobile phone of the user higher than the work position; and simultaneously, the task advance times of the user j are increased and are sent to the server for storage.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A big data-based enterprise management platform organizational framework task management method is characterized by comprising the following steps:
step P1: distributing the authority;
the user inputs personal information to register and log in, the authority distribution module is in wireless communication connection with the server, authority distribution is set according to the work positions in the personal information, the user belongs to the first-level authority distributed by the base-level staff, the user belongs to the second-level authority distributed by the middle-level trunk, and the user belongs to the third-level authority distributed by the high-level leader;
step P2: distributing tasks;
the task management module is in wireless communication connection with the server and is divided into a primary task unit, a middle-level task unit and a high-level task unit, tasks in the primary task unit are directly distributed to base-level employees, tasks in the middle-level task unit need users with second-level authority and above-level authority to perform task assignment, and tasks in the high-level task unit need users with second-level authority to perform task assignment;
step P3: task supervision;
the time supervision module is in wireless communication connection with the plan management module, and acquires tasks, task supervision nodes and users receiving the tasks in the plan management module;
the time supervision module marks the task supervision node and the user receiving the task as Ri and j respectively; acquiring the current time T, and comparing the current time T with the time of the task monitoring node Ri by the time monitoring module; if the current time T belongs to Rx time and Rx +1 time, the task is in the x-th planning time node;
step P4: task early warning;
acquiring a current actual task completion node Rs;
when Rx is equal to Rs, the task is normally carried out, and the time supervision module sends a task normal signal to the server;
when Rx is not equal to Rs and s-x is larger than or equal to 3, indicating that the task is seriously disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j by a link server, and sending a task serious disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of serious task early warning of the user j is increased and is sent to a server for storage;
when Rx is not equal to Rs and 3 is larger than s-x and is larger than or equal to 1, indicating that the task is disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of slight early warning of the task of the user j is increased and is sent to the server for storage;
when Rx is not equal to Rs and x-s is larger than or equal to 1, indicating that the task is advanced, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task advance signal to a real-name authentication mobile phone of the user higher than the work position; and simultaneously, the task advance times of the user j are increased and are sent to the server for storage.
2. The big data-based enterprise management platform organizational framework task management method according to claim 1, further comprising a registration login module, wherein the registration login module is used for inputting personal information by a user for registration login, and sending the personal information of the user who successfully registers to a server, the server generates a registration account and a login password according to the registration time of the user, and the registration account and the login password are used for the user to log in the server next time; the authority distribution module is in wireless communication connection with the server, acquires personal information of a user stored in the server, and sets authority distribution according to a work position in the personal information, wherein the user belongs to a first-level authority distributed by a base-level employee, the user belongs to a second-level authority distributed by a middle-level trunk, the user belongs to a third-level authority distributed by a high-level leader, and the higher the level authority is, the more the acquired authorities are;
the personal information input during the user registration comprises a user name, a user age, an identity card number of the user, a work position of the user and a mobile phone number of real-name authentication of the user; the work position of the user comprises base layer staff, a middle layer cadre and a high-level leader.
3. The enterprise management platform organizational framework task management method based on big data according to claim 1, further comprising a task management module, wherein the task management module is in wireless communication connection with a server, the task management module is divided into a primary task unit, a middle task unit and a high-level task unit, tasks in the primary task unit are directly distributed to base-level employees, tasks in the middle task unit need to be assigned by users with second-level authority and higher-level authority, and tasks in the high-level task unit need to be assigned by users with second-level authority.
4. The big-data-based task management method for the organizational framework of the enterprise management platform is characterized by further comprising a plan management module, wherein the plan management module is in wireless communication connection with the task management module, the plan management module directly acquires all tasks in the task management module, automatically generates a task supervision node and directly acquires users receiving the tasks, the time supervision module is used for supervising the tasks in real time, and the specific operation process of the time supervision module comprises the following steps:
the method comprises the following steps: the time supervision module is in wireless communication connection with the plan management module, and acquires tasks, task supervision nodes and users receiving the tasks in the plan management module;
step two: the time supervision module marks the task supervision node and the user receiving the task as Ri and j respectively; where R denotes a task, i denotes a node, i ═ 1,2 … … n:
step three: acquiring the current time T, and comparing the current time T with the time of the task monitoring node Ri by the time monitoring module; if the current time T belongs to Rx time and Rx +1 time, the task is in the x-th planning time node, wherein 0< x < n; x is a positive integer;
step four: acquiring a current actual task completion node Rs; wherein s is a positive integer; when Rx is equal to Rs, the task is normally carried out, and the time supervision module sends a task normal signal to the server;
when Rx is not equal to Rs and s-x is larger than or equal to 3, indicating that the task is seriously disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j by a link server, and sending a task serious disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of serious task early warning of the user j is increased and is sent to a server for storage;
when Rx is not equal to Rs and 3 is larger than s-x and is larger than or equal to 1, indicating that the task is disconnected, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task disconnection signal to a real-name authentication mobile phone of the user higher than the work position; the time supervision module is simultaneously linked with the task early warning module, and the task early warning module carries out task early warning; meanwhile, the number of times of slight early warning of the task of the user j is increased and is sent to the server for storage;
when Rx is not equal to Rs and x-s is larger than or equal to 1, indicating that the task is advanced, acquiring the work position of a user j receiving the task by a time supervision module, acquiring a user higher than the work position of the user j through a link server, and sending a task advance signal to a real-name authentication mobile phone of the user higher than the work position; and simultaneously, the task advance times of the user j are increased and are sent to the server for storage.
5. The big-data-based enterprise management platform organizational framework task management method according to claim 1, further comprising a management query module, wherein the management query module is used for querying task completion conditions of users and feeding the task completion conditions back to the assessment evaluation module, and the specific way of assessing and evaluating the users by the assessment evaluation module comprises the following steps:
step S1: the management query module is linked with the server and acquires a user j which is stored in the server and receives the task;
step S2: the management query module acquires the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j; the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j are sent to the assessment module;
step S3: after receiving the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times of the user j, the assessment evaluation module marks the annual task completion total amount, the slight early warning times, the serious early warning times and the task advance times as Wcj, Qwj, Yzj and Cqj respectively;
step S4: the assessment evaluation module calculates an annual evaluation coefficient Pjj of the user j by using a calculation formula
Wherein a, b and c are preset proportionality coefficients, and a + b + c is 1;
step S5: the assessment evaluation module sets an annual evaluation coefficient threshold, and when the annual evaluation coefficient Pjj of the user j is greater than or equal to the annual evaluation coefficient threshold, the user j is qualified in annual performance; when the annual evaluation coefficient Pjj of the user j is smaller than the annual evaluation coefficient threshold, the user j is represented to be unqualified in annual performance; the assessment evaluation module sends the annual evaluation coefficient Pjj of the user j to the server for storage;
step S6: and the assessment evaluation module performs descending order arrangement on the annual evaluation coefficients of all the users, and defines the users ranked in the top three as excellent annual employees.
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