Automatic approval and data filing system, method and equipment for in-job process

Abstract

The invention provides an in-job process automatic approval and data archiving system, method and device, and belongs to the technical field of data processing. The system comprises a data acquisition unit, a data processing unit, a data approval unit and a data archiving unit; the method comprises the following steps: collecting condition information of a worker, correspondingly classifying the condition information under each piece of ID identity information according to categories, and performing unique weight assignment on each category of classification information under each piece of ID identity information; performing weighted summation on all weight assignments after corresponding coefficient setting by adopting a multiple logic algorithm to obtain multiple groups of weighted summation results of each piece of ID identity information; the weighted summation result of the first sequence is reserved, the unique output value is matched according to different set standards of all departments, the redundancy of later data processing work is greatly simplified, each possible application characteristic of talents is subjected to assignment prediction, the process is reasonable, the automation degree is high, and the method is suitable for application and popularization.

Description

Technical Field

[0001] This invention belongs to the field of data processing technology, and in particular to an automated onboarding process approval and document archiving system, method and device. Background Technology

[0002] In current personnel data management, the approval process for onboarding typically takes about 10 days. This lengthy manual processing method is increasingly unsuitable for today's fast-paced development, and significant manual labor is involved, for example:

[0003] ① The human resources department publishes and screens resumes online based on the staffing needs of each department. There is a lot of uncertainty in this process. Different human resources professionals have different understandings and ability levels, which inevitably leads to errors in analyzing and selecting talent resumes.

[0004] ② When it comes to the interview stage, there is a lot of repetitive work, such as filling out forms, holding meetings and discussions, communicating with various departments, conducting initial interviews, departmental interviews, and boss interviews. This wastes a lot of human and material resources and also puts a significant time and energy burden on job seekers and various departments of the hiring company.

[0005] To overcome the shortcomings of manual operations, existing technologies have designed an automated recruitment approval system for the onboarding process. Through automated management using computer languages, this system reduces errors caused by human intervention, improving fairness and scientific rigor while reducing overall time consumption. However, existing automated talent approval systems still have several design flaws, such as:

[0006] ① Limited cross-system integration capabilities;

[0007] Existing automated systems struggle to highlight key personnel data across different departments, requiring manual intervention for cross-departmental talent identification, which impacts process continuity.

[0008] ② Difficulty in adapting to complex approval processes;

[0009] Multi-level approval scenarios require in-depth configuration of system parameters, which places high demands on technical implementation. Non-standard processes may increase configuration costs.

[0010] ③ Insufficient depth of record management;

[0011] Existing systems primarily focus on basic information management and lack sufficient support for linking employees' records at multiple levels (such as linking performance and training records, and reminding employees to renew their qualification certificates). Additional tools are needed to assist in this process. Summary of the Invention

[0012] To address the aforementioned technical issues, this invention provides an automated onboarding process approval and document archiving system, method, and device. Through a scientific architecture design, it employs intelligent data collection and logical processing to more efficiently reduce the workload of personnel assessment in various departments. The standards are unified and fair, eliminating selection errors caused by human error. At the same time, it facilitates subsequent observation and employee information maintenance, dynamically monitoring the development status of each employee. The operation is safe and reliable, making it suitable for widespread adoption.

[0013] A system, method, and device for automating the onboarding process approval and document archiving, wherein:

[0014] Firstly, an automated onboarding process approval and document archiving system includes:

[0015] Data acquisition unit, data processing unit, data approval unit, and document archiving unit;

[0016] The data acquisition unit is used to collect the information of new employees; and classify the information according to the category under each ID identity information, and assign a unique weight to each category information under each ID identity information.

[0017] As an example, the information mentioned includes: the applicant's name, education, work experience, health status, age, gender, and salary expectations.

[0018] As an example, the ID identity information refers to: ID card number information or unique file number information given by the company.

[0019] As an example, the data acquisition unit includes: a big data acquisition port, a document scanning device, a video acquisition device, and an information input device;

[0020] The big data collection port is used to synchronize with recruitment platforms on the Internet and collect job seeker information that meets the hiring requirements of this organization.

[0021] The document scanning device is used to scan job seekers' resumes, certificates, and other relevant paper documents.

[0022] The video capture device is used to capture the interview process of job seekers, such as their self-introduction and answers to questions from HR.

[0023] The information input device is used to supplement the input of other relevant information of the job seeker.

[0024] The data processing unit is used to process all weight assignments. It employs multiple logical algorithms to perform weighted summation on all weight assignments after setting corresponding coefficients, thereby obtaining multiple sets of weighted summation results for each ID identity information.

[0025] As an example, the aforementioned multiple logical algorithms refer to: establishing categories such as stable talent, innovative talent, conservative talent, and unsuitable talent according to the requirements of the user unit; and assigning different proportional coefficients to the weights corresponding to each category of information based on the above different standards.

[0026] For example: For stable talent, the proportion of information related to stability in the company's philosophy is increased; the proportion of other information is a constant of 1.

[0027] For innovative talents: the proportion of information related to innovation in the company's philosophy is increased; the proportion of other information is a constant of 1.

[0028] Conservative talent: The proportion of information related to conservatism in the company's philosophy is increased; the proportion of other information is a constant of 1.

[0029] Unsuitable talent: The proportion of information in categories that conflict with the company's philosophy and culture is increased; the proportion of other categories is a constant of 1.

[0030] Among them, all the scaling factors have values ​​greater than the constant 1.

[0031] The data approval unit is used to sort multiple weighted summation results for each ID identity information, and retain the weighted summation result with the highest score for each ID identity information as the unique output value; and to match the unique output value according to the different standards set by each department to select suitable employees.

[0032] As an example, the different setting standards refer to:

[0033] When the hiring department is the finance department: the standard is to select the best conservative talents, which can minimize the operational risks of finance work;

[0034] When the hiring department is the sales department: the standard is to select stable talents based on merit. This can maximize the company's sales while reducing the risk of future customer churn.

[0035] When the hiring department is the R&D department: the standard is to select innovative talents based on merit. This can maximize creative R&D and is conducive to the company's technological advancement.

[0036] As an example, when the only output value is "Unsuitable for talent", the ID identity information data is directly deleted.

[0037] The data archiving unit is used to automatically archive the identity information of each ID, provide the corresponding offer, and generate a unique employee ID.

[0038] As an example, the data archiving unit is equipped with an input terminal for inputting employees' subsequent training, awards, attendance, performance and other dynamic information. According to the specified dates, it automatically generates a periodic dynamic score for each employee, providing data reference for promotion, salary increase or dismissal.

[0039] As an example, the specified dates are: one month, one quarter, or half a year.

[0040] Secondly, a method for automating the onboarding process approval and document archiving includes:

[0041] Step 1: The data acquisition unit collects the information of the new employees, and classifies the information according to the category under each ID identity information, and assigns a unique weight to each category information under each ID identity information;

[0042] By assigning a unique weight to each category of information, we can obtain the data information of each category under each ID identity information, which facilitates subsequent data processing operations.

[0043] Step 2: The data processing unit uses a multi-logic algorithm to assign all weights, set corresponding coefficients, and then sum them up to obtain multiple sets of weighted sums for each ID identity information.

[0044] Each ID identity information is scored to the maximum extent possible on demand, without overlooking the best job application potential for each ID identity information; that is, each ID identity information is weighted and summed for stable talents, innovative talents, conservative talents, and unsuitable talents, resulting in four weighted summation results respectively;

[0045] The multi-logic algorithm is designed as follows:

[0046] For stable talent: the proportion coefficient of the classification information related to stability in the company philosophy is increased; the proportion coefficient of other classification information is a constant of 1; the weighted summation result of stable talent is obtained by weighted summation;

[0047] Innovative talent: The proportion coefficient of the category information related to innovation in the company's philosophy is increased; the proportion coefficient of other category information is a constant of 1; the weighted summation result of innovative talent is obtained by weighted summation;

[0048] Conservative talent: The proportion coefficient of the information related to conservatism in the company philosophy is increased; the proportion coefficient of other information is a constant of 1; the weighted summation result of conservative talent is obtained by weighted summation.

[0049] Unsuitable talent: The proportion of information in categories that conflict with the company's philosophy and culture is increased; the proportion of other categories is a constant of 1; the weighted sum of unsuitable talent is obtained by weighted summation.

[0050] Among them, all the scaling factors have values ​​greater than the constant 1;

[0051] As an example, the aforementioned multi-logic algorithm can dynamically adjust the talent type setting logic and proportional coefficient assignment according to the actual needs of the enterprise.

[0052] Step 3: Through the data approval unit, sort the weighted sum of multiple sets of ID identity information, and retain the weighted sum of the first sorted result as the unique output value; and according to the different standards set for the staffing needs of each department, match the unique output value to select suitable employees.

[0053] Step 4: Automatically archive the identity information of each ID through the data archiving unit, issue the corresponding offer, and generate a unique employee ID;

[0054] The data archiving unit is equipped with an input terminal for inputting employees' subsequent dynamic onboarding information and automatically generating dynamic scores for each employee on a regular basis for performance evaluation.

[0055] Thirdly, an electronic device includes: a processor and a memory for storing processor-executable instructions; wherein the processor is configured to perform a method for automating onboarding process approval and document archiving.

[0056] Fourthly, this application discloses a non-transitory computer-readable storage medium that, when the instructions in the storage medium are executed by the processor of an electronic device, enables the electronic device to perform a method for automating onboarding process approval and document archiving.

[0057] Fifthly, this application discloses a computer program product that, when the instructions in the computer program product are executed by the processor of an electronic device, enables the electronic device to perform a method for automating onboarding process approval and document archiving.

[0058] The beneficial effects of this invention are:

[0059] ① This invention uses weighted assignment, which gives each collected data a unique weighted identity, greatly simplifies the redundancy of subsequent data processing and makes automation more efficient.

[0060] ② Through multiple logical algorithms, each possible application characteristic of the talent is assigned a score and predicted to obtain their best job potential, without missing the best corporate value of the new employees.

[0061] ③The overall architecture of this invention is scientifically designed, the process is reasonable, and the degree of automation is high, making it suitable for widespread application. Attached Figure Description

[0062] Figure 1 This is a flowchart illustrating the process structure design of an automated onboarding approval and document archiving method according to the present invention.

[0063] Figure 2 This is a schematic diagram of the structure of an electronic device for automated approval and document archiving of the onboarding process according to the present invention. Detailed Implementation

[0064] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Figures 1 to 2 As shown:

[0065] A system, method, and device for automating the onboarding process approval and document archiving, wherein:

[0066] Firstly, an automated onboarding process approval and document archiving system includes:

[0067] The system includes a data acquisition unit 101, a data processing unit 102, a data approval unit 103, and a document archiving unit 104.

[0068] The data acquisition unit 101 is used to collect the information of the new employees; and classify the information according to the category under each ID identity information, and assign a unique weight value to each category information under each ID identity information.

[0069] As an example, the information mentioned includes: the applicant's name, education, work experience, health status, age, gender, and salary expectations.

[0070] As an example, the ID identity information refers to: ID card number information or unique file number information given by the company.

[0071] As an example, the data acquisition unit includes: a big data acquisition port, a document scanning device, a video acquisition device, and an information input device;

[0072] The big data collection port is used to synchronize with recruitment platforms on the Internet and collect job seeker information that meets the hiring requirements of this organization.

[0073] The document scanning device is used to scan job seekers' resumes, certificates, and other relevant paper documents.

[0074] The video capture device is used to capture the interview process of job seekers, such as their self-introduction and answers to questions from HR.

[0075] The information input device is used to supplement the input of other relevant information of the job seeker.

[0076] The data processing unit 102 is used to process all weight assignments. It adopts a multi-logic algorithm 105 to set the corresponding coefficients for all weight assignments and then sum them up to obtain multiple sets of weighted sums for each ID identity information.

[0077] As an example, the multiple logical algorithms 105 refer to: according to the requirements of the user unit, establishing stable talents, innovative talents, conservative talents, and unsuitable talents, and setting different proportional coefficients for the weight assignment corresponding to each category of information based on the above different standards;

[0078] For example: For stable talent, the proportion of information related to stability in the company's philosophy is increased; the proportion of other information is a constant of 1.

[0079] For innovative talents: the proportion of information related to innovation in the company's philosophy is increased; the proportion of other information is a constant of 1.

[0080] Conservative talent: The proportion of information related to conservatism in the company's philosophy is increased; the proportion of other information is a constant of 1.

[0081] Unsuitable talent: The proportion of information in categories that conflict with the company's philosophy and culture is increased; the proportion of other categories is a constant of 1.

[0082] Among them, all the scaling factors have values ​​greater than the constant 1.

[0083] The data approval unit 103 is used to sort multiple weighted summation results for each ID identity information, and retain the weighted summation result with the highest score for each ID identity information as a unique output value; and to match the unique output value according to the different standards set by each department to select suitable employees.

[0084] As an example, the different setting standards refer to:

[0085] When the hiring department is the finance department: the standard is to select the best conservative talents, which can minimize the operational risks of finance work;

[0086] When the hiring department is the sales department: the standard is to select stable talents based on merit. This can maximize the company's sales while reducing the risk of future customer churn.

[0087] When the hiring department is the R&D department: the standard is to select innovative talents based on merit. This can maximize creative R&D and is conducive to the company's technological advancement.

[0088] As an example, when the only output value is "Unsuitable for talent", the ID identity information data is directly deleted.

[0089] The data archiving unit 104 is used to automatically archive the identity information of each ID, give it the corresponding offer, and generate a unique corresponding employee ID.

[0090] As an example, the data archiving unit is equipped with an input terminal 106: used to input the dynamic information of employees such as training, awards, attendance, and performance. According to the specified date, it automatically generates a periodic dynamic score for each employee, providing data reference for promotion, salary increase or dismissal.

[0091] As an example, the specified dates are: one month, one quarter, or half a year.

[0092] Secondly, a method for automating the onboarding process approval and document archiving includes:

[0093] Step 1: The data acquisition unit 101 collects the information of the new employees, and classifies the information according to the category under each ID identity information, and assigns a unique weight to each category information under each ID identity information;

[0094] By assigning a unique weight to each category of information, we can obtain the data information of each category under each ID identity information, which facilitates subsequent data processing operations.

[0095] Step 2: The data processing unit 102 uses a multi-logic algorithm 105 to assign all weights, set corresponding coefficients, and then perform weighted summation to obtain multiple sets of weighted summation results for each ID identity information.

[0096] We will maximize the on-demand scoring of each ID identity information and ensure that the best job application potential for each ID identity information is not overlooked.

[0097] The multi-logic algorithm 105 is designed as follows:

[0098] For stable talent: the proportion coefficient of the classification information related to stability in the company philosophy is increased; the proportion coefficient of other classification information is a constant of 1; the weighted summation result of stable talent is obtained by weighted summation;

[0099] Innovative talent: The proportion coefficient of the category information related to innovation in the company's philosophy is increased; the proportion coefficient of other category information is a constant of 1; the weighted summation result of innovative talent is obtained by weighted summation;

[0100] Conservative talent: The proportion coefficient of the information related to conservatism in the company philosophy is increased; the proportion coefficient of other information is a constant of 1; the weighted summation result of conservative talent is obtained by weighted summation.

[0101] Unsuitable talent: The proportion of information in categories that conflict with the company's philosophy and culture is increased; the proportion of other categories is a constant of 1; the weighted sum of unsuitable talent is obtained by weighted summation.

[0102] Among them, all the scaling factors have values ​​greater than the constant 1;

[0103] As an example, the aforementioned multi-logic algorithm can dynamically adjust the talent type setting logic and proportional coefficient assignment according to the actual needs of the enterprise.

[0104] Step 3: Through the data approval unit 103, sort the multiple weighted sums of each ID identity information, and retain the weighted sum of the first sorted result as the unique output value; and according to the different standards set for the staffing needs of each department, match the unique output value to select suitable employees.

[0105] Step 4: Automatically archive the identity information of each ID through the data archiving unit 104, and issue the corresponding offer to generate a unique employee ID.

[0106] The data archiving unit is equipped with an input terminal 106 for inputting the employee's subsequent dynamic onboarding status and automatically generating a dynamic score for each employee on a regular basis for evaluation.

[0107] Thirdly, an electronic device includes: a processor and a memory for storing processor-executable instructions; wherein the processor is configured to perform a method for automating onboarding process approval and document archiving.

[0108] Fourthly, this application discloses a non-transitory computer-readable storage medium that, when the instructions in the storage medium are executed by the processor of an electronic device, enables the electronic device to perform a method for automating onboarding process approval and document archiving.

[0109] Fifthly, this application discloses a computer program product that, when the instructions in the computer program product are executed by the processor of an electronic device, enables the electronic device to perform a method for automating onboarding process approval and document archiving.

[0110] To better illustrate the design principles of this invention, specific embodiments are provided below:

[0111] First, the system automatically searches for recruitment information. Through the big data collection port, it collects information on candidates A, B, C, and D who are waiting to be hired. Then, it uses a document scanning device to further input and complete the detailed information of each candidate and uses a video capture device to collect the interview results.

[0112] Secondly, the system employs a multi-logic algorithm to assign all weights with corresponding coefficients and then sum them up in a weighted manner to obtain a multi-weighted sum of the four sets of identity information.

[0113] ① At this time, the weighted sum of the results for employee A, who is about to be hired, are as follows:

[0114] Stable talent: 95 points;

[0115] Innovative talent: 80 points;

[0116] Conservative type: 72 points;

[0117] Unsuitable talent: 30 points;

[0118] ②At this time, the weighted sum of the results for employee B, who is about to be hired, are as follows:

[0119] Stable talent: 70 points;

[0120] Innovative talent: 93 points;

[0121] Conservative type: 66 points;

[0122] Unsuitable talent: 27 points;

[0123] ③ At this point, the weighted summation results for employee C are as follows:

[0124] Stable talent: 60 points;

[0125] Innovative talent: 55 points;

[0126] Conservative type: 57 points;

[0127] Unsuitable talent: 88 points;

[0128] ④ At this time, the weighted summation results of the candidate D are as follows:

[0129] Stable talent: 80 points;

[0130] Innovative talent: 61 points;

[0131] Conservative type: 94 points;

[0132] Unsuitable talent: 22 points;

[0133] Then, through the data approval unit, the weighted summation results of multiple sets of each ID identity information are sorted, and the weighted summation result ranked first is retained as the unique output value;

[0134] ① At this point, the only output value for employee A is:

[0135] Stable talent: 95 points;

[0136] ②At this point, the only output value for employee B is:

[0137] Innovative talent: 93 points;

[0138] ③ At this point, the only output value for the candidate C is:

[0139] Unsuitable talent: 88 points;

[0140] ④ At this point, the only output value for the candidate D is:

[0141] Conservative type: 94 points;

[0142] Based on the different staffing needs of each department, set different standards, match the unique output value, and select suitable employees.

[0143] At this point, candidate A will join the sales department, candidate B will join the technical department, candidate C will not be considered, and candidate D will join the finance department.

[0144] Finally, through the data archiving unit, the identity information of personnel A, B, and D is automatically archived, and corresponding offers are issued to them, generating unique employee ID numbers.

[0145] The data archiving unit is equipped with an input terminal for inputting employees' subsequent dynamic onboarding information and automatically generating dynamic scores for each employee on a regular basis for performance evaluation.

[0146] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions involved are not necessarily required by this application.

[0147] Optionally, this application also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the various processes of the above method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0148] This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0149] Figure 2 This is a block diagram of an electronic device 200 shown in this application; for example, the electronic device 200 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0150] Reference Figure 2 The electronic device 200 may include one or more of the following components: a processing component 201, a memory 202, a power supply component 203, a multimedia component 204, an audio component 205, an input / output (I / O) interface 207, a sensor component 209, and a communication component 208.

[0151] Processing component 201 typically controls the overall operation of electronic device 200, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 201 may include one or more processors 206 to execute instructions to complete all or part of the steps of the above methods. Furthermore, processing component 201 may include one or more modules to facilitate interaction between processing component 201 and other components; for example, processing component 201 may include a multimedia module to facilitate interaction between multimedia component 204 and processing component 201.

[0152] Memory 202 is configured to store various types of data to support the operation of device 200; examples of such data include instructions for any application or method operating on electronic device 200, contact data, phonebook data, messages, images, videos, etc. Memory 202 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0153] Power supply component 203 provides power to various components of electronic device 200. Power supply component 203 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 200.

[0154] Multimedia component 204 includes a screen that provides an output interface between the electronic device 200 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user; the touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel; the touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 204 includes a front-facing camera and / or a rear-facing camera. When the device 200 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0155] Audio component 205 is configured to output and / or input audio signals. For example, audio component 205 includes a microphone (MIC) configured to receive external audio signals when electronic device 200 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 202 or transmitted via communication component 208. In some embodiments, audio component 205 also includes a speaker for outputting audio signals.

[0156] I / O interface 207 provides an interface between processing component 201 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0157] Sensor assembly 209 includes one or more sensors for providing state assessments of various aspects of electronic device 200. For example, sensor assembly 209 may detect the on / off state of device 200, the relative positioning of components such as the display and keypad of electronic device 200, changes in position of electronic device 200 or a component of electronic device 200, the presence or absence of user contact with electronic device 200, orientation or acceleration / deceleration of electronic device 200, and temperature changes of electronic device 200. Sensor assembly 209 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 209 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 209 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0158] Communication component 208 is configured to facilitate wired or wireless communication between electronic device 200 and other devices. Electronic device 200 can access wireless networks based on communication standards, such as WiFi, carrier networks (such as 2G, 3G, 4G, or 5G), or combinations thereof. In one exemplary embodiment, communication component 208 receives broadcast signals or broadcast operation information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 208 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0159] In an exemplary embodiment, the electronic device 200 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0160] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 202 including instructions, which can be executed by a processor 206 of an electronic device 200 to perform the above method; for example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0161] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0162] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0163] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware; whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0164] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0165] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0166] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0167] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0168] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0169] The above description is only a preferred embodiment of the present invention. It should be understood that the above description of the embodiments is only for the purpose of helping to understand the method and core idea of ​​the present invention, and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, etc. made within the idea and principle of the present invention should be included within the scope of protection of the present invention.

Claims

1. An automated onboarding process approval and document archiving system, characterized in that, include: Data acquisition unit, data processing unit, data approval unit, and document archiving unit; The data acquisition unit is used to collect information about new hires; The aforementioned situation information is then categorized according to the corresponding category under each ID identity information, and a unique weight is assigned to each category information under each ID identity information; The data processing unit is used to process all weight assignments. It employs multiple logical algorithms to perform weighted summation on all weight assignments after setting corresponding coefficients, thereby obtaining multiple sets of weighted summation results for each ID identity information. The data approval unit is used to sort multiple weighted summation results for each ID identity information, and retain the weighted summation result with the first sort as the unique output value; Based on the different standards set by each department, the unique output value is matched to select suitable candidates for employment. The data archiving unit is used to automatically archive the identity information of each ID, provide the corresponding offer, and generate a unique employee ID.

2. The automated onboarding process approval and document archiving system according to claim 1, characterized in that, The information includes: the applicant's name, education, work experience, health status, age, gender, and salary expectations. The ID identity information refers to: ID card number or unique file number given by the company.

3. The automated onboarding process approval and document archiving system according to claim 1, characterized in that, The data acquisition unit includes: a big data acquisition port, a document scanning device, a video acquisition device, and an information input device; The big data collection port is used to synchronize with recruitment platforms on the Internet and collect job seeker information that meets the hiring requirements of this organization. The document scanning device is used to scan job seekers' resumes and certificates. The video capture device is used to collect real-time interview information of job seekers. The information input device is used to supplement the input of job seeker information.

4. The automated onboarding process approval and document archiving system according to claim 1, characterized in that, The aforementioned multiple logical algorithms refer to: establishing categories such as stable talent, innovative talent, conservative talent, and unsuitable talent according to the requirements of the user unit, and assigning different proportional coefficients to the weights corresponding to each category of information based on the above different standards.

5. The automated onboarding process approval and document archiving system according to claim 1, characterized in that, The different setting standards refer to: When the hiring department is the finance department: the standard is to select the best conservative talent. When the hiring department is the sales department: the standard is to select stable talent based on merit. When the hiring department is the R&D department: the standard is to select innovative talents based on merit; When the only output value is "Unsuitable for talent", delete the ID identity information data directly.

6. The automated onboarding process approval and document archiving system according to claim 1, characterized in that, The data archiving unit is equipped with an input terminal.

7. A method for automating the approval and document archiving of the onboarding process, characterized in that, include: Step 1: The data acquisition unit collects the information of the new employees, and classifies the information according to the category under each ID identity information, and assigns a unique weight to each category information under each ID identity information; Step 2: The data processing unit uses a multi-logic algorithm to assign all weights, set corresponding coefficients, and then sum them up to obtain multiple sets of weighted sums for each ID identity information. The multi-logic algorithm is designed as follows: For stable talent: the proportion of information related to stability in the company's philosophy should be increased; The proportion coefficient for other classification information is a constant of 1; the weighted summation result for stable talents is obtained by weighted summation; Innovative talent: The proportion of their information related to innovation in the company's philosophy is increased; The proportion coefficient for other classification information is a constant of 1; the weighted summation result for innovative talents is obtained by weighted summation; Conservative talent: Increase the proportion of information related to conservatism in the company's philosophy; The proportion coefficient for other classification information is a constant of 1; the weighted summation result for conservative talents is obtained by weighted summation; Unsuitable talent: The proportion of information categorized as conflicting with the company's philosophy and culture is increased. The proportion coefficient for other classification information is a constant of 1; the weighted summation result for unsuitable talents is obtained by weighted summation; Among them, all the scaling factors have values ​​greater than the constant 1; Step 3: Through the data approval unit, sort the weighted sum of multiple sets of ID identity information, and retain the weighted sum of the first sorted result as the unique output value; and according to the different standards set for the staffing needs of each department, match the unique output value to select suitable employees. Step 4: Automatically archive the identity information of each ID through the data archiving unit, and issue the corresponding offer to generate a unique employee ID.

8. An electronic device, characterized in that, The electronic device includes: a processor, and a memory for storing processor-executable instructions; wherein the processor is configured to perform the method of claim 7.

9. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform the method of claim 7.

10. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device is able to perform the method of claim 7.

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