CN112308401A - Task allocation method and device, computer equipment and readable storage medium - Google Patents
Task allocation method and device, computer equipment and readable storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a task allocation method, a task allocation device, computer equipment and a readable storage medium, wherein the task allocation method comprises the following steps: acquiring task information, the plurality of employee information, compensation parameters corresponding to each employee information and the distribution reference factors; calculating the matching degree between the task information and each employee information according to the distribution reference factors; determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information; and sending the task information to a target staff terminal matched with the target staff information, and realizing an efficient task allocation process through the steps.
Description
Technical Field
The present application relates to the field of process management technologies, and in particular, to a task allocation method, an apparatus, a computer device, and a readable storage medium.
Background
With the explosion of new retail, great effort is made by the expansion of the major merchants beyond retail channels, however, the task allocation and management for employees in terms of store operations is always problematic. In the prior art, the task allocation is generally performed on the staff manually by a store keeper, so that the allocation efficiency is low.
In view of this, it is necessary for those skilled in the art to provide a more intelligent task allocation scheme.
Disclosure of Invention
The application provides a task allocation method, a task allocation device, computer equipment and a readable storage medium.
The embodiment of the application can be realized as follows:
in a first aspect, an embodiment of the present application provides a task allocation method, which is applied to a computer device, where the computer device is in communication connection with a plurality of employee terminals; the computer equipment stores a plurality of employee information and compensation parameters corresponding to the employee information, the compensation parameters are used for representing task completion efficiency of employees, the employee information is matched with the employee terminals one by one, and the computer equipment is used for storing distribution reference factors updated in real time;
the method comprises the following steps:
acquiring task information, a plurality of employee information, compensation parameters corresponding to each employee information and distribution reference factors;
calculating the matching degree between the task information and each employee information according to the distribution reference factors;
determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information;
and sending the task information to a target staff terminal matched with the target staff information.
In an alternative embodiment, the allocation reference factor comprises task priority, and the task information comprises task type; the computer equipment stores a historical task type list corresponding to each employee information, wherein the historical task type list comprises a plurality of historical task types;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
acquiring a task type under the condition that the task priority reaches a preset priority level;
acquiring any pending employee information from the plurality of employee information;
acquiring a pending historical task type list corresponding to information of a pending employee, wherein the pending historical task type list comprises a plurality of pending historical task types;
calculating to obtain a list of undetermined historical task types and the similarity of the task types according to the coincidence degree of each undetermined historical task type and the task type;
and calculating the matching degree between the task information and the information of the staff to be determined according to the similarity.
In an alternative embodiment, the allocation reference factor comprises an employee representation corresponding to each employee information, the employee representation comprises employee characteristics, and the employee characteristics are used for representing the ability of the employee to process different types of tasks; the task information comprises a task type;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
acquiring any pending employee information from the plurality of employee information;
acquiring an undetermined employee portrait corresponding to undetermined employee information, wherein the undetermined employee portrait comprises characteristics of the undetermined employee;
determining an adaptation coefficient of the characteristics of the staff to be determined according to the portrait of the staff to be determined and the task type;
and calculating the matching degree between the task information and the information of the staff to be determined according to the adaptation coefficient.
In an optional embodiment, the computer device stores a task scoring table, the task scoring table includes a plurality of task completion rate intervals and a task completion scoring coefficient corresponding to each task completion rate interval, and the allocation reference factor includes an employee completion rate corresponding to each employee information;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
acquiring any pending employee information from the plurality of employee information;
acquiring the completion rate of the undetermined staff corresponding to the undetermined staff information;
determining a task completion rate interval of the completion rate of the undetermined staff according to the task scoring table;
acquiring a score coefficient of the completion of the undetermined task corresponding to the interval of the completion rate of the undetermined task;
and calculating the matching degree between the task information and the information of the staff to be determined according to the score coefficient for completing the task to be determined.
In an optional embodiment, the computer device further stores a task processing list, the task processing list includes task information to be processed and task time associated with each employee information, and the allocation reference factor includes employee task saturation corresponding to each employee information;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
acquiring any pending employee information from the plurality of employee information;
acquiring information of pending processing tasks and time of pending tasks associated with information of the pending employees from a task processing list;
acquiring task saturation of the undetermined staff corresponding to the undetermined staff information;
determining a saturation state coefficient according to the information of the task to be processed, the time of the task to be processed and the task saturation of the staff to be determined;
and calculating the matching degree between the task information and the information of the staff to be determined according to the saturation state coefficient.
In an optional embodiment, the allocation reference factor includes task timeliness, and the computer device further stores a corresponding relationship between the task timeliness and the timeliness coefficient;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
determining an aging coefficient corresponding to the task timeliness according to the corresponding relation;
and calculating the matching degree between the task information and each employee information according to the time efficiency coefficient.
In an optional implementation mode, the computer device further stores a task efficiency parameter, a task joining time parameter and a task total amount parameter corresponding to each employee information;
the step of obtaining the compensation parameter corresponding to each employee information comprises the following steps:
acquiring any pending employee information from the plurality of employee information;
acquiring an efficiency parameter of a task to be determined, a time parameter of the task to be participated in and a total quantity parameter of the task to be determined corresponding to the information of the staff to be determined;
and calculating to obtain compensation parameters corresponding to the information of the staff to be determined according to the efficiency parameters of the staff to be determined, the time parameters of the staff to be determined and the total quantity parameters of the staff to be determined.
In a second aspect, an embodiment of the present application provides a task allocation apparatus, which is applied to a computer device, where the computer device is in communication connection with a plurality of employee terminals; the computer equipment stores a plurality of employee information and compensation parameters corresponding to the employee information, the compensation parameters are used for representing task completion efficiency of employees, the employee information is matched with the employee terminals one by one, and the computer equipment is used for storing distribution reference factors updated in real time;
the device comprises:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring task information, a plurality of staff information, compensation parameters corresponding to each staff information and distribution reference factors;
the calculation module is used for calculating the matching degree between the task information and each employee information according to the distribution reference factors;
the distribution module is used for determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information; and sending the task information to a target staff terminal matched with the target staff information.
In a third aspect, an embodiment of the present application provides a computer device, where the computer device includes a processor and a non-volatile memory storing computer instructions, and when the computer instructions are executed by the processor, the computer device executes the task allocation method in any one of the foregoing embodiments.
In a fourth aspect, an embodiment of the present application provides a readable storage medium, where the readable storage medium includes a computer program, and the computer program controls, when running, a computer device in the readable storage medium to perform the task allocation method in any one of the foregoing embodiments.
The beneficial effects of the embodiment of the application include, for example: the embodiment of the application provides a task allocation method, a task allocation device, computer equipment and a readable storage medium, wherein task information, a plurality of staff information, compensation parameters corresponding to each staff information and allocation reference factors are obtained; calculating the matching degree between the task information and each employee information according to the distribution reference factors; determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information; and sending the task information to a target staff terminal matched with the target staff information, and skillfully utilizing the matching degree and the compensation parameters through the steps to efficiently distribute the tasks.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is an interaction diagram of a task allocation system according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart illustrating steps of a task allocation method according to an embodiment of the present application;
FIG. 3 is a schematic diagram illustrating a relationship between employee completion rates and scores according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram illustrating a relationship between employee representation and score according to an embodiment of the present disclosure;
FIG. 5 is a block diagram schematically illustrating a structure of a task allocation apparatus according to an embodiment of the present disclosure;
fig. 6 is a block diagram schematically illustrating a structure of a computer device according to an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Furthermore, the appearances of the terms "first," "second," and the like, if any, are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
It should be noted that the features of the embodiments of the present application may be combined with each other without conflict.
At present, normalized management of physical stores is popularized, and people management systems are more regular in stores and stores. In real-life mall stores, most businesses still need to be manually implemented, such as audit, stocking, etc. When the task allocation of the staff is carried out, the task allocation is carried out by adopting a mode of manually allocating tasks by a store leader, a group leader and the like, and the allocation efficiency is very low.
Based on this, reference may be made to fig. 1, where fig. 1 is an interaction schematic diagram of a task allocation system provided in an embodiment of the present application, and the task allocation system includes a computer device 100 and a plurality of employee terminals 200 communicatively connected to the computer device 100. The computer device 100 stores a plurality of employee information and compensation parameters corresponding to each employee information, the compensation parameters are used for representing task completion efficiency of employees, the plurality of employee information are matched with the plurality of employee terminals 200 one by one, and the computer device 100 is used for storing distribution reference factors updated in real time. In other embodiments of the present application, the task allocation system may be implemented by more or fewer components, and is not limited herein.
On the basis of the above, please refer to fig. 2 in combination, fig. 2 is a schematic flowchart illustrating steps of a task allocation method according to an embodiment of the present application, where the task allocation method is implemented by the computer device 100 in fig. 1. The task allocation method is described below.
Step 201, acquiring task information, a plurality of employee information, compensation parameters corresponding to each employee information and distribution reference factors.
And 202, calculating the matching degree between the task information and each employee information according to the distribution reference factors.
And step 203, determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information.
And step 204, sending the task information to the target staff terminal 200 matched with the target staff information.
In the embodiment of the present application, since the employee is continuously working, the information of each employee may be updated according to the preset time unit, and the acquired task information may be generated by the computer device 100 in response to an external operation. Through the steps, after the matching degree between the task information and each employee information is determined through the distribution reference factors, the task information is not directly distributed to the employee with the largest matching degree represented by the employee information, the compensation parameter corresponding to each employee information is further calculated, and finally the target employee information is determined according to the matching degree and the compensation parameter capable of correcting the matching degree, so that the task information can be sent to the target employee terminal 200 matched with the target employee information, the employee can execute the task information after receiving the task information, and the task distribution efficiency is improved.
On the basis, the distribution reference factors comprise task priorities, and the task information comprises task types; the computer device 100 stores a historical task type list corresponding to each employee information, and the historical task type list includes a plurality of historical task types. As an alternative embodiment, the foregoing step 202 can be implemented by the following detailed description.
Sub-step 202-1, obtaining the task type when the task priority reaches the preset priority level.
And a substep 202-2 of obtaining information of any one of the pending employees from the plurality of employee information.
And a substep 202-3 of obtaining a pending historical task type list corresponding to the pending employee information.
The pending historical task type list comprises a plurality of pending historical task types.
And a substep 202-4, calculating the similarity between the pending historical task type list and the task type according to the coincidence degree of each pending historical task type and the task type.
And a substep 202-5 of calculating the matching degree between the task information and the information of the staff to be determined according to the similarity.
In the embodiment of the present application, a preset priority level may be set, for example, for a store, the priority level of the task information "sort goods" may be 1, and the priority level of the task information "lead customer" may be 3, that is, the task information of "lead customer" is higher than the priority level of the task information of "sort goods", and needs to be processed preferentially, for example, the preset priority level may be set to 2, when the "lead customer" meets the above condition, and the "sort goods" does not meet the condition.
Optionally, when the task priority reaches the preset priority level, the type included in the task information may be acquired, for example, the task information of "lead customer reception" includes a task type of "reception class", and the task information of "sort goods" includes a task type of "sort class". The method comprises the steps of performing traversal search on a historical task type list corresponding to each employee information, taking the employee information to be determined as an example, calculating the similarity between the undetermined historical task type list and the task type according to the coincidence degree of each undetermined historical task type and the task type, namely determining whether the employee represented by the undetermined employee information is "familiar" with the current task information, and storing data of the last 60 days in the undetermined historical task type list as reference to determine the similarity, namely whether the employee often performs tasks similar to the task type of the task information. Based on this, the matching degree can be calculated based on the assignment reference factor of task priority. It should be understood that after task information co-distribution, in which the task priority reaches the preset priority level, staff information corresponding to staff performing the task information can be automatically used as a second type of candidate during subsequent task distribution, so that the purpose of a special person who specializes the task information, in which the task priority reaches the preset priority level, can be achieved.
On the basis, the distribution reference factors comprise employee figures corresponding to the information of each employee, wherein the employee figures comprise employee characteristics, and the employee characteristics are used for representing the capability of the employees for processing different types of tasks; the task information includes a task type. As an alternative embodiment, the foregoing step 202 can be implemented by the following detailed description.
And a substep 202-6 of obtaining information of any one of the pending employees from the plurality of employee information.
And a substep 202-7 of obtaining the drawing of the undetermined staff corresponding to the undetermined staff information.
Wherein the image of the undetermined employee comprises characteristics of the undetermined employee.
And a substep 202-8, determining an adaptive coefficient of the characteristics of the undetermined employee according to the undetermined employee portrait and the task type.
And a substep 202-9 of calculating the matching degree between the task information and the information of the staff to be determined according to the adaptation coefficient.
In another implementation manner of the embodiment of the application, an employee portrait corresponding to each employee information may be pre-established, where the employee portrait includes employee features, and the employee features are used to characterize the ability of the employee to process different types of tasks. Optionally, on the employee representation, the employee features of the task that the employee excels in correspond to a characterization form (e.g., numerical value, vector length, etc. are larger). For example, if an employee is often assigned to an "audit" task, then the employee's profile associated with the "audit" is highlighted.
By taking the information of the undetermined staff as an example, after the image of the undetermined staff and the task type are determined, the characteristics of the undetermined staff related to the task type can be searched in the staff image, and then the adaptive coefficient can be obtained. In the embodiment of the application, a characteristic threshold of the undetermined staff can be set, when the characteristic of the undetermined staff exceeds the characteristic threshold of the undetermined staff, the adaptation coefficient of the characteristic of the undetermined staff can be 1.5, and when the characteristic of the undetermined staff does not exceed the characteristic threshold of the undetermined staff, the adaptation coefficient of the characteristic of the undetermined staff can be 0.8, so that the task of distributing staff for excellence is realized.
On the basis of the foregoing, the computer device 100 stores a task scoring table, where the task scoring table includes a plurality of task completion rate intervals and a task completion scoring coefficient corresponding to each task completion rate interval, and the allocation reference factor includes an employee completion rate corresponding to each employee information. As an alternative embodiment, the foregoing step 202 can be implemented by the following detailed description.
And a substep 202-10 of obtaining information of any one of the pending employees from the plurality of employee information.
And a substep 202-11 of obtaining the completion rate of the undetermined staff corresponding to the undetermined staff information.
And a substep 202-12 of determining a task completion rate interval in which the completion rate of the staff to be determined is located according to the task scoring table.
And a substep 202-13 of obtaining a score coefficient of the completion of the undetermined task corresponding to the interval of the completion rate of the undetermined task.
And a substep 202-14 of calculating the matching degree between the task information and the information of the staff to be determined according to the score coefficient of the completion of the task to be determined.
On the basis, the staff completion rate corresponding to each staff information can be counted, taking the pending staff information as an example, a task scoring table can be searched, optionally three task completion rate intervals of 'the task completion rate is greater than 90%', 'the task completion rate is less than 90% and greater than 70%', and 'the task completion rate is less than 70%', are allocated and configured with the task completion scoring coefficients of 1.3, 1 and 0, so as to represent the scores of the staff in the item. Optionally, the completion rate of the undetermined staff corresponding to the information of the undetermined staff is 85%, so that the undetermined task completion rate interval is "the task completion rate is less than 90% and greater than 70%", and a score coefficient for the completion of the undetermined task is 1. Through the steps, the matching value can be calculated based on the distribution reference factor of the task completion rate.
On the basis, the computer device 100 further stores a task processing list, wherein the task processing list comprises task waiting information and task time which are associated with each employee information, and the allocation reference factor comprises the employee task saturation corresponding to each employee information. As an alternative embodiment, the foregoing step 202 can be implemented by the following detailed description.
And a substep 202-15 of obtaining information of any one of the pending employees from the plurality of employee information.
And a substep 202-16, obtaining task information to be processed and task time to be processed associated with the staff information to be processed from the task processing list.
And a substep 202-17, obtaining task saturation of the undetermined staff corresponding to the undetermined staff information.
And a substep 202-18, determining a saturation state coefficient according to the information of the task to be processed, the time of the task to be processed and the task saturation of the staff to be processed.
And a substep 202-19 of calculating the matching degree between the task information and the information of the staff to be determined according to the saturation state coefficient.
In addition to the scheme, the allocation reference factor may further include staff task saturation corresponding to each staff information, and the saturation of the task of the staff to be determined may be determined according to the task information to be processed and the time to be determined, so as to determine the saturation state coefficient. Optionally, if the staff corresponding to the undetermined staff information is connected with the next task, 2 tasks (namely, waiting for processing the task information) are also distributed, and the average processing time of each task is longer than sixty minutes (undetermined task time), the saturation of the task of the undetermined staff corresponding to the undetermined staff information can be considered to be saturated, a smaller saturation state coefficient can be configured at the moment, and correspondingly, if the saturation of the task of the staff to be determined is unsaturated, a larger saturation state coefficient can be configured, so that the calculation of the matching degree based on the saturation of the task of the staff is realized.
On the basis of the above, the allocation reference factor includes task timeliness, and the computer device 100 further stores the correspondence between the task timeliness and the timeliness coefficient. As an alternative embodiment, the foregoing step 202 can be implemented by the following detailed description.
And a substep 202-20, determining an aging coefficient corresponding to the task timeliness according to the corresponding relation.
And a substep 202-21 of calculating the matching degree between the task information and each employee information according to the aging factor.
The task information can also comprise task timeliness, namely whether the task information is urgent or not, and the completion time and the effect of each task are different, for example, a 'replenishment' task, the sequential execution of replenishment and the length of execution time directly influence the sales volume of merchants and stores, so that the timeliness requirement of the replenishment task is high. Therefore, the aging factor can be determined according to the corresponding relation between the task aging performance and the aging factor, the aging factor with relatively urgent aging performance is large, and the aging factor with relatively abundant aging performance is small. Through the steps, the matching degree can be calculated according to the task timeliness.
In addition, the computer device 100 stores a task efficiency parameter, a task participation time parameter, and a task total amount parameter corresponding to each employee information. In order to express the scheme of the present application more clearly, the following provides an embodiment of obtaining a compensation parameter corresponding to each employee information, and specifically includes the following steps.
Step 301, obtaining any pending employee information from a plurality of employee information.
And 302, acquiring an efficiency parameter of the task to be determined, a time parameter of the task to be determined and a total quantity parameter of the task to be determined corresponding to the information of the staff to be determined.
And step 303, calculating to obtain a compensation parameter corresponding to the information of the staff to be determined according to the efficiency parameter of the staff to be determined, the time parameter of the staff to be determined and the total quantity parameter of the staff to be determined.
As described above, a compensation coefficient for correcting the degree of matching can be set, thereby improving the accuracy of task allocation. Alternatively, the compensation factor may be according to the formula:
calculated, wherein i is a compensation factor, CiRepresents the compensation fraction of the compensation factor i. In the embodiment of the application, the compensation factors may include a task efficiency parameter, a task participation time parameter and a task total amount parameter, for example, for the task efficiency parameter, it may mean that the task completion rate of the employee in the last 30 days is general, but the task completion rate in the last 14 days is higher, and a forward compensation is performed on the score of the employee, and the 14 days is taken as the reason of most of the current merchants, and the task of the store is taken as a period of 7 days, and the situation becomes better in two periods, which indicates that the employee performs better recently. The time parameter for joining the task may refer to the staff who joined the system within the last 30 days, is not very familiar with the business and related processes, and adds a reverse compensation. For the total task quantity parameter, the number of tasks completed by the staff in the current day is more than 10, a reverse compensation is added, and a compensation coefficient can be calculated.
On the basis of the scheme, in order to describe the scheme more clearly, all the related allocation reference factors comprise task priority, employee portraits corresponding to each employee information, employee completion rates corresponding to each employee information, employee task saturation corresponding to each employee information and task timeliness. Can be determined by the formula:
wherein, f (n) is the final matching degree of the employee information n and the task information,
for the matching degree of the employee information n and the task information,
for the compensation parameter of the employee information n, k is 1,2,3 … n for each reference factor, λkTo assign a weight of reference factor k, SkTo assign a score of reference factor k, i is a compensation factor, CiRepresents the compensation fraction of the compensation factor i. Through the formula, the target employee information which is most matched with the task information can be found from the plurality of employee information, the whole process does not need human participation, and the task allocation efficiency is improved. For example, fig. 3 and 4 may be combined to determine an employee representation corresponding to each employee information and a score corresponding to an employee completion rate corresponding to each employee information. In actual life, the initial values of the parameters may be manually adjusted by a merchant or an employee according to actual conditions, which is not limited herein.
It should be understood that in the calculation process, a strategy of DFS (depth first search) + pruning is adopted, for completely unmatched employees, related branches are directly pruned, so that the algorithm execution efficiency is improved, and meanwhile, the algorithm time complexity is as follows: o (n-c) k) + t, where n is the number of members, c is the branch subtracted, and t is the factor calculation (constant) for compensation.
The embodiment of the present application provides a task allocation apparatus 110, which is applied to a computer device 100, wherein the computer device 100 is in communication connection with a plurality of employee terminals 200; the computer device 100 stores a plurality of employee information and compensation parameters corresponding to each employee information, the compensation parameters are used for representing task completion efficiency of employees, the plurality of employee information are matched with the plurality of employee terminals 200 one by one, and the computer device 100 is used for storing distribution reference factors updated in real time. Referring to fig. 5, the task assigning apparatus 110 includes:
the obtaining module 1101 is configured to obtain task information, a plurality of employee information, a compensation parameter corresponding to each employee information, and an allocation reference factor.
And the calculating module 1102 is used for calculating the matching degree between the task information and each employee information according to the distribution reference factors.
The distribution module 1103 is configured to determine target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information; and sending the task information to the target staff terminal 200 matched with the target staff information.
Further, the allocation reference factor comprises task priority, and the task information comprises task type; the computer device 100 stores a historical task type list corresponding to each employee information, and the historical task type list includes a plurality of historical task types.
The calculation module 1102 is specifically configured to:
acquiring a task type under the condition that the task priority reaches a preset priority level; acquiring any pending employee information from the plurality of employee information; acquiring a pending historical task type list corresponding to information of a pending employee, wherein the pending historical task type list comprises a plurality of pending historical task types; calculating to obtain a list of undetermined historical task types and the similarity of the task types according to the coincidence degree of each undetermined historical task type and the task type; and calculating the matching degree between the task information and the information of the staff to be determined according to the similarity.
Further, the allocation reference factors comprise employee figures corresponding to the information of each employee, wherein the employee figures comprise employee characteristics, and the employee characteristics are used for representing the capability of the employees for processing different types of tasks; the task information includes a task type.
The calculation module 1102 is specifically configured to:
acquiring any pending employee information from the plurality of employee information; acquiring an undetermined employee portrait corresponding to undetermined employee information, wherein the undetermined employee portrait comprises characteristics of the undetermined employee; determining an adaptation coefficient of the characteristics of the staff to be determined according to the portrait of the staff to be determined and the task type; and calculating the matching degree between the task information and the information of the staff to be determined according to the adaptation coefficient.
Further, the computer device 100 stores a task scoring table, where the task scoring table includes a plurality of task completion rate intervals and a task completion scoring coefficient corresponding to each task completion rate interval, and the allocation reference factor includes an employee completion rate corresponding to each employee information.
The calculation module 1102 is specifically configured to:
acquiring any pending employee information from the plurality of employee information; acquiring the completion rate of the undetermined staff corresponding to the undetermined staff information; determining a task completion rate interval of the completion rate of the undetermined staff according to the task scoring table; acquiring a score coefficient of the completion of the undetermined task corresponding to the interval of the completion rate of the undetermined task; and calculating the matching degree between the task information and the information of the staff to be determined according to the score coefficient for completing the task to be determined.
Further, the computer device 100 further stores a task processing list, the task processing list includes task waiting information and task time associated with each employee information, and the allocation reference factor includes employee task saturation corresponding to each employee information.
The calculation module 1102 is specifically configured to:
acquiring any pending employee information from the plurality of employee information; acquiring information of pending processing tasks and time of pending tasks associated with information of the pending employees from a task processing list; acquiring task saturation of the undetermined staff corresponding to the undetermined staff information; determining a saturation state coefficient according to the information of the task to be processed, the time of the task to be processed and the task saturation of the staff to be determined; and calculating the matching degree between the task information and the information of the staff to be determined according to the saturation state coefficient.
Further, the assignment reference factor includes task timeliness, and the computer device 100 further stores a correspondence between the task timeliness and the aging factor.
The calculation module 1102 is specifically configured to:
determining an aging coefficient corresponding to the task timeliness according to the corresponding relation; and calculating the matching degree between the task information and each employee information according to the time efficiency coefficient.
Further, the computer device 100 further stores a task efficiency parameter, a task participation time parameter, and a task total amount parameter corresponding to each employee information.
The obtaining module 1101 is further configured to:
acquiring any pending employee information from the plurality of employee information; acquiring an efficiency parameter of a task to be determined, a time parameter of the task to be participated in and a total quantity parameter of the task to be determined corresponding to the information of the staff to be determined; and calculating to obtain compensation parameters corresponding to the information of the staff to be determined according to the efficiency parameters of the staff to be determined, the time parameters of the staff to be determined and the total quantity parameters of the staff to be determined.
The embodiment of the present application provides a computer device 100, where the computer device 100 includes a processor and a non-volatile memory storing computer instructions, and when the computer instructions are executed by the processor, the computer device 100 executes the task allocation method described above. As shown in fig. 6, fig. 6 is a block diagram of a computer device 100 according to an embodiment of the present disclosure. The computer apparatus 100 includes a task assigning device 110, a memory 111, a processor 112, and a communication unit 113.
To facilitate the transfer or interaction of data, the elements of the memory 111, the processor 112 and the communication unit 113 are electrically connected to each other, directly or indirectly. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The task assigning means 110 includes at least one software function module which can be stored in the memory 111 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the computer device 100. The processor 112 is used for executing executable modules stored in the memory 111, such as software functional modules and computer programs included in the task assigning apparatus 110.
The embodiment of the present application provides a readable storage medium, where the readable storage medium includes a computer program, and when the computer program runs, the computer device 100 in which the readable storage medium is located is controlled to execute the foregoing task allocation method.
In summary, the embodiment of the present application provides a task allocation method, a device, a computer device, and a readable storage medium, by acquiring task information, a plurality of employee information, a compensation parameter corresponding to each employee information, and an allocation reference factor; calculating the matching degree between the task information and each employee information according to the distribution reference factors; determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information; and sending the task information to a target staff terminal matched with the target staff information, and skillfully utilizing the matching degree and the compensation parameters through the steps to efficiently distribute the tasks.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A task allocation method is characterized by being applied to computer equipment, wherein the computer equipment is in communication connection with a plurality of employee terminals; the computer equipment stores a plurality of employee information and compensation parameters corresponding to each employee information, the compensation parameters are used for representing task completion efficiency of employees, the employee information is matched with the employee terminals one by one, and the computer equipment is used for storing distribution reference factors updated in real time;
the method comprises the following steps:
acquiring task information, the plurality of employee information, compensation parameters corresponding to each employee information and the distribution reference factors;
calculating the matching degree between the task information and each employee information according to the distribution reference factors;
determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information;
and sending the task information to a target staff terminal matched with the target staff information.
2. The method of claim 1, wherein the allocation reference factor comprises a task priority, and wherein the task information comprises a task type; the computer equipment stores a historical task type list corresponding to each employee information, wherein the historical task type list comprises a plurality of historical task types;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
under the condition that the task priority reaches a preset priority level, acquiring the task type;
acquiring any pending employee information from the plurality of employee information;
acquiring a pending historical task type list corresponding to the information of the pending staff, wherein the pending historical task type list comprises a plurality of pending historical task types;
calculating to obtain the similarity between the pending historical task type list and the task type according to the coincidence degree of each pending historical task type and the task type;
and calculating the matching degree between the task information and the information of the staff to be determined according to the similarity.
3. The method of claim 1, wherein the assignment reference factors include a staff representation for each of the staff information, the staff representation including staff features that characterize the staff's ability to handle different types of tasks; the task information comprises a task type;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
acquiring any pending employee information from the plurality of employee information;
acquiring an undetermined employee portrait corresponding to the undetermined employee information, wherein the undetermined employee portrait comprises characteristics of the undetermined employee;
determining an adaptation coefficient of the characteristics of the undetermined employee according to the undetermined employee portrait and the task type;
and calculating the matching degree between the task information and the information of the staff to be determined according to the adaptation coefficient.
4. The method of claim 1, wherein the computer device stores a task scoring table, wherein the task scoring table includes a plurality of task completion rate intervals and a task completion scoring coefficient corresponding to each of the task completion rate intervals, and wherein the allocation reference factor includes a staff completion rate corresponding to each of the staff information;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
acquiring any pending employee information from the plurality of employee information;
acquiring the completion rate of the undetermined staff corresponding to the undetermined staff information;
determining a task completion rate interval of the to-be-determined staff in which the completion rate is located according to the task scoring table;
acquiring a score coefficient of the completion of the to-be-determined task corresponding to the interval of the completion rate of the to-be-determined task;
and calculating the matching degree between the task information and the information of the staff to be determined according to the score coefficient for completing the task to be determined.
5. The method of claim 1, wherein the computer device further stores a task processing list, wherein the task processing list comprises task waiting information and task time associated with each of the employee information, and wherein the assignment reference factor comprises employee task saturation for each of the employee information;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
acquiring any pending employee information from the plurality of employee information;
acquiring pending processing task information and pending task time associated with the pending employee information from the task processing list;
acquiring task saturation of the undetermined staff corresponding to the undetermined staff information;
determining a saturation state coefficient according to the information of the task to be processed, the time of the task to be processed and the task saturation of the staff to be processed;
and calculating the matching degree between the task information and the information of the staff to be determined according to the saturation state coefficient.
6. The method of claim 1, wherein the allocation reference factor comprises a task timeliness, and the computer device further stores a correspondence between the task timeliness and an aging factor;
the step of calculating the matching degree between the task information and each employee information according to the distribution reference factors comprises the following steps:
determining an aging coefficient corresponding to the task timeliness according to the corresponding relation;
and calculating the matching degree between the task information and each employee information according to the aging coefficient.
7. The method according to claim 1, wherein the computer device further stores a task efficiency parameter, a task participation time parameter and a task total amount parameter corresponding to each of the employee information;
the step of obtaining the compensation parameter corresponding to each employee information includes:
acquiring any pending employee information from the plurality of employee information;
acquiring an efficiency parameter of a task to be determined, a time parameter of the task to be determined and a total quantity parameter of the task to be determined corresponding to the information of the staff to be determined;
and calculating to obtain the compensation parameter corresponding to the information of the staff to be determined according to the efficiency parameter of the staff to be determined, the time parameter of the staff to be determined and the total quantity parameter of the staff to be determined.
8. The task allocation device is applied to computer equipment, and the computer equipment is in communication connection with a plurality of staff terminals; the computer equipment stores a plurality of employee information and compensation parameters corresponding to each employee information, the compensation parameters are used for representing task completion efficiency of employees, the employee information is matched with the employee terminals one by one, and the computer equipment is used for storing distribution reference factors updated in real time;
the device comprises:
the acquisition module is used for acquiring task information, the plurality of employee information, compensation parameters corresponding to the employee information and the distribution reference factors;
the calculation module is used for calculating the matching degree between the task information and each employee information according to the distribution reference factors;
the distribution module is used for determining target employee information from the plurality of employee information according to the matching degree between the task information and each employee information and the compensation parameter corresponding to each employee information; and sending the task information to a target staff terminal matched with the target staff information.
9. A computer device comprising a processor and a non-volatile memory having computer instructions stored thereon, wherein when the computer instructions are executed by the processor, the computer device performs the task assignment method of any one of claims 1-7.
10. A readable storage medium, characterized in that the readable storage medium comprises a computer program which, when running, controls a computer device on which the readable storage medium is located to perform the task assigning method according to any one of claims 1-7.
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| CN202011180412.XA CN112308401A (en) | 2020-10-29 | 2020-10-29 | Task allocation method and device, computer equipment and readable storage medium |
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