Human Resource Management System and its Methods

Abstract

A human resource management system includes an external data retrieval unit, a data storage unit, an adaptation scoring unit, and a job matching unit. The external data retrieval unit stores an employee identification number, which corresponds to a plurality of external accounts. The external data retrieval unit periodically retrieves current status data of a plurality of employees corresponding to the corresponding external accounts. The data storage unit stores this current status data in an employee status database. The adaptation scoring unit inputs this current status data into a job scoring model to output a personnel rotation evaluation. The job matching unit stores the employee identification number and a plurality of jobs, receives personnel rotation evaluations from the adaptation scoring unit to determine if the employee identification number is matched to a particular job, and stores this as an adaptation result.

Description

Technical Field

[0001] This invention relates to a management system and a method thereof, particularly a human resource management system and a method thereof. Prior Technology

[0002] In medium to large-sized enterprises, existing employee rotation systems often face the problem of insufficient personnel suitability. This is because the rotation process fails to adequately consider employees' professional backgrounds, personal interests, and personality traits, resulting in some employees being assigned to unsuitable units or positions, unable to fully utilize their abilities. Especially when employees lacking management experience or skills are transferred to management positions, it can lead to decreased team performance and increased internal conflicts. Furthermore, the adaptation period and potential inefficiencies caused by rotation increase resource consumption and human resource costs, further reducing employee satisfaction and even triggering a wave of resignations.

[0003] In addition, individual employee behavior, including rewards and punishments within the workplace, statements on social media outside the workplace, and financial handling methods, is usually not fully considered in the current employee rotation process, or there are inconsistent rotation standards due to the subjective views of supervisors. Summary of the Invention

[0004] Therefore, one of the objectives of this invention is to provide a human resource management system that can solve any of the above-mentioned deficiencies.

[0005] Therefore, the human resource management system of the present invention includes an external data acquisition unit, a data storage unit, an adaptation scoring unit, and a job matching unit. The external data acquisition unit stores an employee identification number, which corresponds to multiple external accounts. The external data acquisition unit periodically connects to multiple external websites corresponding to these external accounts via the Internet to acquire current employee information corresponding to these external accounts. The data storage unit is electrically connected to the external data acquisition unit and includes an employee information database storing the employee identification number. The data storage unit receives the employee information from the external data acquisition unit, stores it in the employee information database, and matches it to the corresponding employee identification number. The adaptation scoring unit is electrically connected to the data storage unit, stores the employee identification number, and executes a job scoring model. The adaptation scoring unit receives the employee information corresponding to the employee identification number and inputs it into the job scoring model to output a personnel rotation evaluation corresponding to the employee identification number. The job matching unit is electrically connected to the matching scoring unit and stores the employee identification number and multiple job titles. The job matching unit receives personnel rotation evaluation from the matching scoring unit to determine that the employee identification number is matched with one of the job titles and stores it as a matching result.

[0006] In some implementations, the matching scoring unit further implements a job risk model. In addition, the data storage unit includes an employee HR database containing the employee identification number and multiple employee HR data corresponding to the employee identification number, and an employee transaction database containing the employee identification number and multiple employee transaction data corresponding to the employee identification number. The matching scoring unit receives the employee status data, employee HR data and employee transaction data corresponding to the employee identification number from the data storage unit, and inputs the employee status data and employee HR data into the job scoring model, and inputs the employee transaction data into the job risk model.

[0007] In some implementations, the job matching unit is electrically connected to the data storage unit and transmits the matching result corresponding to the employee identification number to one of the employee human resources records in the employee human resources database of the data storage unit.

[0008] In some implementation scenarios, the job scoring model is one of a consumer finance personnel scoring model, a legal finance personnel scoring model, a financial advisor scoring model, and a credit granting personnel scoring model.

[0009] In some implementations, the adaptive scoring unit further implements an event detection model. The adaptive scoring unit receives at least one event data corresponding to the employee identification number and, in conjunction with the job scoring model and the job risk model, obtains the personnel rotation evaluation corresponding to the employee identification number.

[0010] Therefore, another objective of this invention is to provide a human resource management method that can solve any of the above-mentioned deficiencies.

[0011] Therefore, the interbank transaction management method of the present invention is implemented by a human resource management system. The human resource management system includes an external data retrieval unit storing the employee identification number and a plurality of corresponding external accounts, a data storage unit electrically connected to the external data retrieval unit and storing the employee identification number, an adaptation scoring unit electrically connected to the data storage unit and storing the employee identification number, and a job matching unit electrically connected to the adaptation scoring unit and storing the employee identification number and a plurality of job titles. The human resource management method includes the following steps: First, the external data retrieval unit periodically connects to a plurality of external websites corresponding to the corresponding external accounts via the Internet to retrieve employee status data corresponding to the corresponding external accounts. Next, the data storage unit receives the employee status data from the external data retrieval unit, stores it in the employee status database, and matches it with the corresponding employee identification number. Furthermore, the matching and scoring unit receives the current status data of the employees corresponding to the employee identification number, and inputs the current status data into a job scoring model of the matching and scoring unit to output a personnel rotation evaluation corresponding to the employee identification number. Then, the job matching unit receives the personnel rotation evaluation from the matching and scoring unit to determine that the employee identification number is matched with a job, and stores it as a matching result.

[0012] In some implementations, the matching scoring unit further implements a job risk model. In addition, the data storage unit includes an employee HR database containing the employee identification number and multiple employee HR data corresponding to the employee identification number, and an employee transaction database containing the employee identification number and multiple employee transaction data corresponding to the employee identification number. The matching scoring unit receives the employee status data, employee HR data and employee transaction data corresponding to the employee identification number from the data storage unit, and inputs the employee status data and employee HR data into the job scoring model, and inputs the employee transaction data into the job risk model.

[0013] In some implementations, the job matching unit is electrically connected to the data storage unit and transmits the matching result corresponding to the employee identification number to one of the employee human resources records in the employee human resources database of the data storage unit.

[0014] In some implementation models, the job scoring model is one of a consumer finance personnel scoring model, a legal finance personnel scoring model, a financial advisor scoring model, and a credit granting personnel scoring model.

[0015] In some implementations, the adaptive scoring unit further implements an event detection model. The adaptive scoring unit receives at least one event data corresponding to the employee identification number and, in conjunction with the job scoring model and the job risk model, obtains the personnel rotation evaluation corresponding to the employee identification number.

[0016] The benefits of this invention are: it collects detailed information on each employee within an enterprise to calculate the performance evaluation for each employee in various job rotations. When the enterprise conducts regular rotations or project-specific rotations, it ensures that the right employees are placed in suitable positions at the right time, achieving the goal of matching talent to the job and optimizing talent and job management. This not only helps enterprises cultivate and retain talent, develop employee potential, and improve employee retention rates, but also reduces talent loss and turnover rates, while simultaneously strengthening internal controls to prevent employee fraud. Simple Explanation of the Diagram

[0017] Other features and effects of the present invention will be clearly presented in the embodiments with reference to the drawings, wherein: Figure 1 is a hardware block diagram illustrating an embodiment of the human resource management system of the present invention; and Figure 2 is a flowchart illustrating, by way of example, how a human resource management method is implemented in this embodiment. Implementation

[0018] Before this invention is described in detail, it should be noted that, unless otherwise defined, the term "electrically connected" in this patent specification refers to the "coupled" relationship between computer hardware (e.g., electronic systems, devices, apparatuses, units, components), and broadly refers to "wired electrical connections" achieved by physically connecting multiple computer hardware components through conductor / semiconductor materials, and "radio connections" that achieve wireless data transmission using wireless communication technologies (e.g., but not limited to wireless networks, Bluetooth, and electromagnetic induction). On the other hand, unless otherwise defined, the term "electrical connection" in this patent specification also broadly refers to "direct electrical connections" achieved by directly coupling multiple computer hardware components to each other, and "indirect electrical connections" achieved by indirectly coupling multiple computer hardware components through other computer hardware components.

[0019] Before this invention is described in detail, it should be noted that the term "unit" in this patent specification refers to computer hardware rather than software. For example, "processing unit" is used to represent computer hardware or a combination of multiple computer hardware that have data processing functions.

[0020] Referring to Figure 1, one embodiment of the human resource management system of the present invention includes an external data acquisition unit 11, a data storage unit 12, an adaptation scoring unit 13, and a job adaptation unit 14.

[0021] In this embodiment, the external data acquisition unit 11 is a computer host executing a data crawler program. It stores multiple employee identification numbers of a company. These employee identification numbers are unique values ​​that are not repeated, such as employee ID card numbers or employee salary numbers, but are not limited to these. For ease of understanding, the following example uses the employee identification number A001234 corresponding to one of the employees, Wang Xiaoming. The external data acquisition unit 11 also stores multiple external accounts (such as Facebook accounts, PTT accounts, etc.) corresponding to the employee identification number A001234.

[0022] In this embodiment, the data storage unit 12 is a computer host, electrically connected to the external data acquisition unit 11, and includes an employee status database 121 storing the employee identification number, an employee personnel database 122 containing the employee identification number and multiple employee personnel data corresponding to that employee identification number, and an employee transaction database 123 containing the employee identification number and multiple employee transaction data corresponding to that employee identification number. Taking employee Wang Xiaoming as an example, the employee personnel database 122 stores Wang Xiaoming's employee personnel data, including: education, experience, job skills, personality trait questionnaire, and posts on internal company discussion forums, etc., while the employee transaction database 123 stores Wang Xiaoming's employee transaction data, including employee account transactions, linked accounts, credit card transactions, loans, and investment gains and losses, etc. Overall, the data storage unit 12 aims to collect as much information as possible about the employee to depict the employee's overall profile.

[0023] In this embodiment, the adaptive scoring unit 13 is a computer host, electrically connected to the data storage unit 12 and storing the employee identification number. It executes one or more job scoring models 131 and a job risk model 132. The job scoring model 131 is, for example, one of a consumer finance personnel scoring model, a legal finance personnel scoring model, a financial advisor scoring model, and a credit officer scoring model. Multiple different models can also be used simultaneously to obtain the evaluation of a single employee in the categories of consumer finance personnel, legal finance personnel, financial advisor, and credit officer. In this embodiment, four job scoring models 131 are used simultaneously, namely the consumer finance personnel scoring model, the legal finance personnel scoring model, the financial advisor scoring model, and the credit officer scoring model. In this embodiment, the job rating model 131 is an artificial intelligence model. During the pre-training phase, it inputs employee status information, employee HR information, and job titles (such as consumer finance personnel, legal finance personnel, financial advisors, credit officers, etc.) corresponding to many employee identification numbers, and labels the score for each job title corresponding to each employee identification number. The higher the score, the more suitable the employee is for the job, enabling the job rating model 131 to determine suitable job titles. The job risk model 132, for example, is an artificial intelligence model. During the pre-training phase, it inputs employee transaction data (such as the number of cash flows, the amount of cash flows, the number of associated accounts, the number of purchases from luxury stores on credit cards, the number of high-risk investments in securities accounts, etc.) and fraud results corresponding to many employee identification numbers, and labels the probability of fraud for each employee identification number. The higher the probability of fraud, the higher the risk of the employee's dereliction of duty, enabling the job risk model 132 to determine fraud risk. The job scoring model 131 and the job risk model 132 are not limited to the above-described implementation methods. They can also be a set of judgment models designed through algorithms or logical judgment rules. In addition, the job scoring model 131 is not limited to the above-described scoring model for consumer finance personnel, legal finance personnel, financial advisors, and credit personnel. It can also be designed according to actual needs to correspond to specific job scoring models.

[0024] In this embodiment, the job matching unit 14 is a computer host, electrically connected to the matching scoring unit 13 and the data storage unit 12, and stores the employee identification number and multiple job titles (such as: consumer finance personnel, legal finance personnel, financial advisors, credit personnel).

[0025] Referring to Figures 1 and 2, the operation of the human resource management method in this embodiment will be explained below.

[0026] First, as shown in step S01, the external data extraction unit 11 periodically (e.g., every seven days) connects to multiple external websites 2 (such as Facebook, PTT BBS, etc.) corresponding to the corresponding external accounts via the Internet to extract multiple employee status data corresponding to the corresponding external accounts. For example, the external data extraction unit 11 uses an existing web crawler to extract the posts and replies of Wang Xiaoming's Facebook account on the Facebook website as one of the employee status data. The external website 2 can also be, for example, the server of the Financial Credit Reference Center, and the external data extraction unit 11 extracts credit report data such as credit cards and loans belonging to Wang Xiaoming as one of the employee status data.

[0027] Next, as shown in step S02, the data storage unit 12 receives the employee status data (such as Wang Xiaoming's Facebook website comments, loan credit reports, etc.) from the external data retrieval unit 11 and stores it in the employee status database 121, and stores the employee human resources data in the employee human resources database 122, and stores the employee transaction data in the employee transaction database 123, all of which correspond to the employee identification number A001234.

[0028] Furthermore, as shown in step S03, the matching scoring unit 13 receives the current status data, human resources data, and transaction data of the employee corresponding to the employee identification number, and inputs the current status data and human resources data into the job scoring model 131, and inputs the transaction data into the job risk model 132. The matching scoring unit 13 also stores a risk probability threshold (e.g., 0.7) to comprehensively output a personnel rotation evaluation corresponding to the employee identification number. For example, based on employee identification number A001234 and employee HR data, the job scoring model 131 calculates scores of 670 for consumer finance personnel, 710 for legal finance personnel, 600 for financial advisors, and 590 for credit officers. The job risk model 132 yields risk probability values ​​of 0.1 for consumer finance personnel, 0.8 for legal finance personnel, 0.6 for financial advisors, and 0.4 for credit officers. Specifically, the matching scoring unit 13 first analyzes employee identification number A001234, finding the highest possible score of 710 for the legal finance position. However, because the risk probability value of 0.8 exceeds the risk probability threshold, it is deemed unsuitable for the legal finance position. Next, it analyzes the second highest score of 670 for the consumer finance position, with a risk probability value of only 0.1, less than the risk probability threshold. Therefore, the personnel rotation evaluation determines Wang Xiaoming to be a consumer finance personnel, meaning that the most suitable job for Wang Xiaoming is consumer finance personnel.

[0029] Periodic job transfers inevitably have the drawback of rigidity. Therefore, the matching scoring unit 13 further implements an event detection model 133. The event detection model 133 of the matching scoring unit 13 receives at least one event data corresponding to the employee identification number, and works with the job scoring model 131 and the job risk model 132 to obtain the personnel rotation evaluation corresponding to the employee identification number. For example, the event data is that of a high-risk employee monitored by the personnel unit as a financial advisor. The employee's transaction data corresponding to the employee identification number is automatically entered into the job risk model 132 irregularly or frequently (e.g., every 7 days). If the risk probability value is 0.8 at one time, and it is higher than the risk probability threshold (e.g., 0.7), the personnel rotation evaluation corresponding to the employee identification number is automatically updated to trigger the personnel unit to adjust the employee's job. The event data is not limited to the above examples, but can also include, for example: employee KPI is less than the threshold, employee voluntarily submits a transfer application, supervisor submits a human resources request, company organizational changes, employee job score is lower than the threshold, employee job risk is higher than the threshold, etc. Usually, the event detection model 133 is triggered by the personnel unit's specialist operating the terminal (not shown) to connect to the matching scoring unit 13 to receive the event data.

[0030] Then, as shown in step S04, the job matching unit 14 receives the personnel rotation evaluation from the matching scoring unit 13 to determine that the employee identification number is matched to one of the positions, and stores it as an matching result. For example, the employee identification number A001234 corresponding to Wang Xiaoming is matched to the legal personnel.

[0031] Next, as shown in step S05, in order to improve the accuracy of the personnel rotation evaluation of the matching scoring unit 13, the job matching unit 14 can transmit the matching result corresponding to the employee identification number to one of the employee personnel data in the employee personnel database 122 of the data storage unit 12. In other words, using the employee personnel data can help improve the effect of the job scoring model 131.

[0032] In summary, the human resource management system and method of this invention can calculate the personnel rotation evaluation for each employee in an enterprise relative to various positions. When an enterprise conducts regular rotations or project-specific rotations, it strives to place the right employees in suitable positions at the right time, achieving the goal of matching talent to the right job and optimizing talent and job management. It also helps enterprises to cultivate and retain talent, develop employee potential, and improve employee retention rates, thereby reducing talent loss and turnover. At the same time, it strengthens internal controls to prevent employee fraud, thus effectively achieving the objectives of this invention.

[0033] However, the above description is merely an embodiment of the present invention and should not be construed as limiting the scope of the present invention. Any simple equivalent changes and modifications made in accordance with the scope of the patent application and the contents of the patent specification shall still fall within the scope of the patent of the present invention.

[0034] 11: External Data Acquisition Unit 12: Data Storage Unit 121: Employee Status Database 122: Employee Human Resources Database 123: Employee Transaction Database 13: Adaptation to scoring units 131: Job Performance Evaluation Model 132: Job Risk Model 133: Event Detection Model 14: Job Matching Unit 2: External websites S01~S05: Steps

Claims

1. A human resource management system, comprising: an external data acquisition unit storing an employee identification number corresponding to a plurality of external accounts, the external data acquisition unit periodically connecting to a plurality of external websites corresponding to the corresponding external accounts via the Internet to acquire a plurality of employee status data corresponding to the corresponding external accounts, wherein, The employee status data indicates the employee's social or credit behavior; a data storage unit, electrically connected to the external data retrieval unit and including an employee status database storing the employee identification number, an employee HR database having the employee identification number and a plurality of employee HR data corresponding to the employee identification number, and an employee transaction database having the employee identification number and a plurality of employee transaction data corresponding to the employee identification number, the data storage unit receiving the employee status data from the external data retrieval unit and storing it in the employee status database and corresponding to the employee identification number, wherein the employee transaction data indicates the employee's transaction or investment behavior; An adaptation scoring unit, electrically connected to the data storage unit and storing the employee identification number, executes a job scoring model and a job risk model. The adaptation scoring unit receives employee status data, employee HR data, and employee transaction data corresponding to the employee identification number from the data storage unit, and inputs the employee status data and HR data into the job scoring model and the employee transaction data into the job risk model. Based on a risk probability threshold, it outputs a personnel rotation evaluation corresponding to the employee identification number. The adaptation scoring unit executes an event detection model, receiving at least one event data corresponding to the employee identification number, and combining it with the job scoring model and the job risk model to obtain the personnel rotation evaluation corresponding to the employee identification number. A job matching unit, electrically connected to the adaptation scoring unit and storing the employee identification number and multiple jobs, receives the personnel rotation evaluation from the adaptation scoring unit to determine if the employee identification number is matched to one of the jobs, and stores it as a matching result.

2. The human resource management system as described in claim 1, wherein, The job matching unit is electrically connected to the data storage unit and transmits the matching result corresponding to the employee identification number to one of the employee human resources records in the employee human resources database of the data storage unit.

3. The human resource management system as described in claim 1, wherein, This job scoring model is one of the scoring models for consumer finance personnel, legal finance personnel, financial advisors, and credit officers.

4. A human resource management method, implemented by a human resource management system, the human resource management system comprising: an external data retrieval unit storing an employee identification number and a plurality of corresponding external accounts; a data storage unit electrically connected to the external data retrieval unit and comprising an employee status database storing the employee identification number, an employee personnel database containing the employee identification number and personnel data of a plurality of employees corresponding to the employee identification number, and an employee transaction database containing the employee identification number and transaction data of a plurality of employees corresponding to the employee identification number; an adaptation scoring unit electrically connected to the data storage unit and storing the employee identification number; and a job matching unit electrically connected to the adaptation scoring unit and storing the employee identification number and a plurality of job titles. The human resource management method comprises the following steps: the external data retrieval unit periodically connects to a plurality of external websites corresponding to the corresponding external accounts via the Internet to retrieve a plurality of employee status data corresponding to the corresponding external accounts, wherein... The employee status data indicates the employee's social or credit behavior; the data storage unit receives the employee status data from the external data acquisition unit, stores it in the employee status database and corresponds it to the employee identification number, wherein the employee transaction data indicates the employee's transaction or investment behavior. The matching and scoring unit receives employee status data, employee HR data, and employee transaction data corresponding to the employee ID from the data storage unit. It inputs the employee status data and HR data into a job scoring model and the employee transaction data into a job risk model. Based on a risk probability threshold, it outputs a personnel rotation evaluation corresponding to the employee ID. The matching and scoring unit executes an event detection model, receiving at least one event data corresponding to the employee ID and combining it with the job scoring model and the job risk model to obtain the personnel rotation evaluation corresponding to the employee ID. The job matching unit receives the personnel rotation evaluation from the matching and scoring unit to determine if the employee ID is matched to a specific job and stores it as a matching result.

5. The human resource management method as described in claim 4, wherein, The job matching unit is electrically connected to the data storage unit and transmits the matching result corresponding to the employee identification number to one of the employee human resources records in the employee human resources database of the data storage unit.

6. The human resource management method as described in claim 4, wherein, This job scoring model is one of the scoring models for consumer finance personnel, legal finance personnel, financial advisors, and credit officers.

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