CN115146921A - Work dynamic allocation method and device based on big data real-time analysis - Google Patents
Work dynamic allocation method and device based on big data real-time analysis Download PDFInfo
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- CN115146921A CN115146921A CN202210607323.1A CN202210607323A CN115146921A CN 115146921 A CN115146921 A CN 115146921A CN 202210607323 A CN202210607323 A CN 202210607323A CN 115146921 A CN115146921 A CN 115146921A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
- G06Q10/063112—Skill-based matching of a person or a group to a task
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
Abstract
The invention provides a work dynamic allocation method and device based on big data real-time analysis, which can dynamically allocate technical personnel and can also perform real-time analysis according to human resource related data. The method comprises the following steps: the task collection unit collects task information through a work order collection module, sends out a personnel allocation request according to the type of the task, and sends the task information to a data analysis module by combining the task information as a task parameter; after receiving the task parameters, the data analysis module calls basic data alpha, performs combined data analysis on the basic data and the task parameters, screens out parameters meeting requirements in the basic data, and obtains a group of result data A; the human resource unit reads the personnel allocation request and extracts related personnel information X; matching the personnel information X and the task parameters, and grading according to the matching degree; and the phase analysis unit performs phase analysis according to the data A and the data set B to finally obtain the assignable staff x.
Description
Technical Field
The invention belongs to the technical field of big data processing, and relates to a dynamic work allocation method and device based on big data real-time analysis.
Background
For service type and technical type enterprises, along with the development of enterprise business, the scale of service departments and the number of service personnel can be developed, but the increase speed of the number of clients is far greater than that of the number of the service personnel, and a mature technical service personnel can be formed only by a large amount of business practice. The problem how to train the service ability of service personnel on the premise of ensuring the customer experience and the enterprise service quality and continuously cultivate technical backbone personnel which become necessary thinking of enterprises is solved. Meanwhile, people figure the service personnel according to the ability and experience of the service personnel so that the enterprises can reasonably integrate the manpower resources, the enterprise resources are distributed, the vigorous growth of the enterprises is ensured, talents are reserved, and the problem which needs to be solved by the enterprises is also the problem which needs to be solved urgently.
The current mainstream solution is to generate a work order, which may include one or more specific tasks that effectively define the work order and, typically, a plurality of service personnel are available to perform the various work orders. However, in the prior art, real-time data analysis cannot be performed, a service personnel capacity growth curve cannot be defined accurately, and personnel capacity cannot be efficiently associated with human resources, such as: a method and technician assignment system for assigning field technicians having publication number CN113169888A, the technical solution of identifying characteristics of a received new work order to be executed for the technician assignment system, then obtaining similarity scores for the identified characteristics, also obtaining field technician experience scores for the identified characteristics for a set of field technician candidates, matching the field technician candidates with characteristics of the new work order based on the obtained field technician experience scores and similarity scores, and assigning at least one of the field technicians for executing the new work order based on the matching.
Therefore, the prior art can only support technical services with obvious identification features, can only consider technical capability and professional capability when distributing tasks, cannot perform weighted calculation in other dimensions (such as communication capability, service attitude and the like), can only store technical experiences after distribution is completed, cannot apply secondary data to perform figure portrayal on people, and provides data for a human resource system (or other management personnel systems) to support in time.
Disclosure of Invention
Based on the defects, the invention provides a work dynamic allocation method and a work dynamic allocation device based on big data real-time analysis, which can dynamically allocate technicians and perform real-time analysis according to human resource related data.
The invention is realized by the following technical scheme:
a work dynamic distribution method based on big data real-time analysis comprises the following steps:
the method comprises the following steps: the task collection unit collects task information through a work order collection module, sends out a personnel allocation request according to the type of the task, and sends the task information to a data analysis module by combining the task information as a task parameter;
step two: after receiving the task parameters, the data analysis module calls basic data alpha, performs combined data analysis on the basic data and the task parameters, screens out parameters meeting requirements in the basic data, and obtains a group of result data A for generating a basic quality requirement list corresponding to the task parameters;
step three: the human resource unit reads the personnel allocation request and extracts related personnel information X; matching the personnel information X and the task parameters, and grading according to the matching degree to obtain a group of result data sets B;
step four: the phase analysis unit performs phase analysis according to the data A and the data set B, namely screening according to the matching degree, and finally obtaining assignable employees x;
step five: after the employee x finishes the work task, feeding a result back to a data correction unit, correcting the alpha by the data correction unit according to the result, and analyzing according to the corrected data to obtain the staff information Y of the employee x;
and step six, the human resource unit acquires the personnel information Y and updates the personnel information X into the personnel information Y.
The invention has the beneficial effects that:
1. according to the invention, through real-time data analysis, not only can technicians be dynamically allocated, but also other types of work can be allocated according to the real-time analysis of the data related to human resources;
2. in addition to technical capability in the distribution basis, the figure portrait provided by a human system is also in a large proportion, and the figure portrait of technical service personnel depends on the service result collected by the invention to a great extent;
3. after the distribution work of the distribution method provided by the invention, relevant result information is collected, and the result information is imported into a human resource system (or other human management systems) and becomes an important basis for generating the portrait.
Detailed Description
The present invention is described in further detail below.
In this embodiment, a method for dynamically allocating work based on real-time analysis of big data specifically includes the following steps:
the method comprises the following steps: the task collection unit collects task information through a work order collection module, sends out a personnel allocation request according to the type of the task, and sends the task information to a data analysis module by combining the task information as a task parameter;
step two: after receiving the task parameters, the data analysis module calls basic data alpha, performs combined data analysis on the basic data and the task parameters, screens out parameters meeting requirements in the basic data, and obtains a group of result data A for generating a basic quality requirement list corresponding to the task parameters; for example, the task is described as network interruption, and the task can be solved by a technician with IT related skills after analysis;
in this embodiment, the basic data α is an incremental database, and is used to record relevant parameters in the process of completing each historical task; for example, a fault may require a certain level of skill to resolve, or a task goal may require a technician in a certain area to quickly handle.
Step three: the human resource unit reads the personnel allocation request and extracts related personnel information X; matching the personnel information X and the task parameters, and grading according to the matching degree to obtain a group of result data sets B, wherein the purpose of the step is to meet a personnel list of task requirements and attach the matching degree;
step four: the phase analysis unit performs phase analysis according to the data A and the data set B, namely performs screening according to the matching degree, and finally obtains the assignable staff x;
in the embodiment, after screening is performed according to the matching degree, human related parameters are further added for correction; for example, there are 3 employees satisfying the task condition, and only a little less capacity needs to be excluded according to the labor cost, and finally, assignable employee x is obtained.
Step five: after the employee x finishes the work task, feeding a result back to a data correction unit, correcting the alpha by the data correction unit according to the result, and analyzing according to the corrected data to obtain the staff information Y of the employee x;
and step six, the human resource unit acquires the personnel information Y and updates the personnel information X into the personnel information Y.
The embodiment of the invention further provides a working dynamic allocation device based on big data real-time analysis, which comprises:
the task collection module is used for collecting task information through the work order collection module, sending a personnel allocation request according to the type of the task, and sending the task information to the data analysis module by combining the task information as a task parameter;
the data analysis module is used for calling basic data alpha after receiving the task parameters, performing combined data analysis on the basic data and the task parameters, screening out parameters meeting requirements in the basic data, obtaining a group of result data A and generating a basic quality requirement list corresponding to the task parameters;
the human resource module is used for reading the personnel allocation request, extracting relevant personnel information X, matching the personnel information X and the task parameters, and grading according to the matching degree to obtain a group of result data sets B;
the phase analysis module is used for carrying out phase analysis according to the data A and the data set B, namely screening according to the matching degree, and finally obtaining assignable employees x;
and the data correction module is used for correcting the alpha according to the result and analyzing the corrected data to obtain the personnel information Y of the staff x.
The embodiment of the invention further provides electronic equipment for realizing dynamic work allocation based on big data real-time analysis, which comprises:
a processor for executing a plurality of instructions;
a memory for storing a plurality of instructions;
the instructions are used for being stored by the memory, and loaded and executed by the processor, so that the working dynamic allocation method based on the big data real-time analysis is realized.
Embodiments of the present invention further provide a computer-readable storage medium having a plurality of instructions stored therein; the instructions are used for loading and executing the working dynamic allocation method based on the big data real-time analysis by the processor.
Example 1:
1. when some client equipment has fault, the application program can be used for making repair (or making repair by telephone), and the user can obtain the related fault information, if the telephone is used for making repair, the customer service personnel can input the related repair information.
2. And the system compares the local data sample base according to the fault description, analyzes and obtains the professional skill and skill level required for solving the fault, and sends basic parameters such as fault occurrence place, maintenance time and the like to the next unit for processing.
3. And receiving the information sent by the previous unit, analyzing by a human system to obtain a personnel list meeting the requirement, attaching the matching degree, and sending the next unit.
4. And after receiving the information sent by the last unit, analyzing the matching degree, finally dispatching the personnel for solving the fault according to the correction parameters set by the human resource system, and sending the work task to the related personnel.
5. After the maintenance work is finished, the staff need to report the specific maintenance process, and the system corrects the basic data sample base according to the fault maintenance process; the customer will grade the maintenance process after the fault is resolved, the grade result will be fed back to the human resource module of the system, and then the corresponding personnel data will be updated
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A work dynamic allocation method based on big data real-time analysis is characterized by comprising the following steps:
the method comprises the following steps: the task collection unit collects task information through a work order collection module, sends out a personnel allocation request according to the type of the task, and sends the task information to a data analysis module by combining the task information as a task parameter;
step two: after receiving the task parameters, the data analysis module calls basic data alpha, performs combined data analysis on the basic data and the task parameters, screens out parameters meeting requirements in the basic data, and obtains a group of result data A for generating a basic quality requirement list corresponding to the task parameters;
step three: the human resource unit reads the personnel allocation request and extracts related personnel information X; matching the personnel information X and the task parameters, and grading according to the matching degree to obtain a group of result data sets B;
step four: the phase analysis unit performs phase analysis according to the data A and the data set B, namely screening according to the matching degree, and finally obtaining assignable employees x;
step five: after the employee x finishes the work task, feeding a result back to a data correction unit, correcting the alpha by the data correction unit according to the result, and analyzing the corrected data to obtain the staff information Y of the employee x;
and step six, the human resource unit acquires the personnel information Y and updates the personnel information X into the personnel information Y.
2. The dynamic work allocation method based on big data real-time analysis as claimed in claim 1, wherein the basic data α is an incremental database for recording relevant parameters during the completion of each historical task.
3. The dynamic work allocation method based on big data real-time analysis according to claim 1 or 2, characterized in that after screening according to the matching degree, human-related parameters are further added for correction.
4. A dynamic work allocation device based on big data real-time analysis is characterized by comprising:
the task collection module is used for collecting task information through the work order collection module, sending a personnel allocation request according to the type of the task, and sending the task information to the data analysis module by combining the task information as a task parameter;
the data analysis module is used for calling basic data alpha after receiving the task parameters, performing combined data analysis on the basic data and the task parameters, screening out parameters meeting requirements in the basic data, obtaining a group of result data A and generating a basic quality requirement list corresponding to the task parameters;
the human resource module is used for reading the personnel allocation request, extracting relevant personnel information X, matching the personnel information X and the task parameters, and grading according to the matching degree to obtain a group of result data sets B;
the phase analysis module is used for carrying out phase analysis according to the data A and the data set B, namely screening according to the matching degree, and finally obtaining assignable employees x;
and the data correction module is used for correcting the alpha according to the result and analyzing the corrected data to obtain the personnel information Y of the staff x.
5. The dynamic work allocation device based on big data real-time analysis as claimed in claim 4, wherein the basic data α is an incremental database for recording relevant parameters during the completion of each historical task.
6. The dynamic work allocation device based on big data real-time analysis as claimed in claim 4 or 5, wherein human-related parameters are further added for correction after screening according to the matching degree.
7. An electronic device for realizing dynamic work allocation based on real-time analysis of big data is characterized by comprising:
a processor for executing a plurality of instructions;
a memory to store a plurality of instructions;
wherein the plurality of instructions are to be stored by the memory and loaded and executed by the processor to perform the method for dynamic allocation of jobs based on real-time analysis of big data according to claims 1-3.
8. A computer-readable storage medium having stored therein a plurality of instructions; the instructions are used for loading and executing the working dynamic allocation method based on big data real-time analysis according to the claims 1-3.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210607323.1A CN115146921A (en) | 2022-05-31 | 2022-05-31 | Work dynamic allocation method and device based on big data real-time analysis |
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| CN202210607323.1A CN115146921A (en) | 2022-05-31 | 2022-05-31 | Work dynamic allocation method and device based on big data real-time analysis |
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| CN202210607323.1A Pending CN115146921A (en) | 2022-05-31 | 2022-05-31 | Work dynamic allocation method and device based on big data real-time analysis |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116502881A (en) * | 2023-06-29 | 2023-07-28 | 深圳市昊昱精密机电有限公司 | Personnel scheduling management method and system for equipment maintenance |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116502881A (en) * | 2023-06-29 | 2023-07-28 | 深圳市昊昱精密机电有限公司 | Personnel scheduling management method and system for equipment maintenance |
| CN116502881B (en) * | 2023-06-29 | 2023-12-22 | 深圳市昊昱精密机电有限公司 | Personnel scheduling management method and system for equipment maintenance |
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