A human resource comprehensive management system based on big data analysis

Abstract

The application discloses a kind of human resources comprehensive management system based on big data analysis, it is related to human resource management technical field, it is solved in prior art, the evaluation of existing system to post system anti-interference ability lacks quantitative index support, cannot accurately identify load abnormal problem in continuous operation process, specifically with the operation process of management end (enterprise) as core, first through post distribution system detection unit builds the distribution system of post, node, enterprise linkage, realizes risk screening in combination with operation speed float and delay time length ratio;Again, the system of risk detection normality is evaluated to anti-interference, judges anti-interference ability based on the delay frequency same period increase and progress speed ring ratio decrease, and optimizes load operation;Finally, through the collection office environment multidimensional sensing data and work output efficient characteristics, the correlation of both is analyzed to identify post efficiency interference factor and implement targeted control.

Description

Technical Field

[0001] This invention relates to the field of human resource management technology, specifically to a comprehensive human resource management system based on big data analysis. Background Technology

[0002] Currently, with the deepening of digital transformation, enterprise human resource management is upgrading from the traditional manual control model to a data-driven intelligent model. In large enterprises and group operation scenarios, the job settings are complex and the departments are closely linked. Human resource management faces multiple challenges, such as difficulty in assessing the rationality of job distribution, weak anti-interference ability during operation, and ambiguity of factors affecting job effectiveness.

[0003] Existing human resource management systems mostly focus on basic functions such as personnel file management, attendance statistics, and payroll calculation, lacking the ability to detect risks in the operation of the job distribution system in real time. They often only take remedial measures after risks occur, resulting in damage to the company's operational efficiency.

[0004] Meanwhile, the existing system lacks quantitative indicators to support the assessment of the job system's anti-interference capability, and cannot accurately identify load anomalies during continuous operation.

[0005] Furthermore, existing technologies for analyzing factors influencing job performance are mostly limited to assessing the individual's own qualities, ignoring the potential interference of external factors such as the office environment on work output, and lacking a quantitative analysis mechanism for the relationship between environmental factors and performance, making it difficult to achieve precise control over performance.

[0006] To address the aforementioned technical shortcomings, a solution is proposed that establishes a comprehensive human resource management system with multi-dimensional control, closed-loop management throughout the entire process, and full quantitative analysis, thereby meeting the needs of enterprises for refined human resource management. Summary of the Invention

[0007] The purpose of this invention is to solve the problems mentioned above by proposing a comprehensive human resources management system based on big data analysis.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] A comprehensive human resources management system based on big data analytics includes a comprehensive management platform, wherein the comprehensive management platform has communication connections to:

[0010] The job distribution system detection unit identifies the management end, sets up a job distribution system for the enterprise, and conducts system detection based on the set distribution system to complete the enterprise's human resource risk detection.

[0011] The system anti-interference assessment unit performs system anti-interference assessment on the management end and determines the anti-interference characteristics of the management end through the anti-interference assessment.

[0012] The system performance interference detection unit analyzes and detects interference with the performance of management positions through working environment monitoring, and makes control decisions accordingly.

[0013] Furthermore, the process for the job distribution system detection unit is as follows:

[0014] Enterprises requiring human resource management are marked as management units. Based on the operational processes of the management units, the corresponding departments for each operational process node are determined, and the corresponding departments are marked as management nodes. Based on the operational processes of the management nodes, each management position is determined. Management positions, management nodes, and the management units construct a position distribution system, and the position distribution system operates in coordination. During the operation phase of the position distribution system, risk detection of the position distribution system is carried out.

[0015] Furthermore, when the management terminal issues an operational signal, it obtains the execution speed of the operational process at each management node, calculates the average speed based on the execution speed, collects the fluctuation frequency of the ratio of the average execution speed of the operational process at each management node, and marks the fluctuation frequency as the system operation fluctuation value; simultaneously, after receiving the operational signal, the management node obtains the delay caused by the execution of the operational process by the corresponding management position.

[0016] The duration and delay duration are generated, and the delay duration of the management node operation is calculated based on the delay duration ratio, which is marked as the system operation risk ratio.

[0017] Furthermore, the system operation fluctuation value and system operation risk ratio are compared with the fluctuation frequency threshold and duration threshold, respectively:

[0018] If the system operation fluctuation value exceeds the fluctuation frequency threshold, or the system operation risk ratio does not exceed the duration ratio threshold, it is inferred that the current management end's job distribution system risk detection is abnormal, generating a system risk signal and sending it to the integrated management platform. Upon receiving the system risk signal, the integrated management platform performs job distribution system detection on the management end and conducts operational detection on each management position and management node to ensure the operational efficiency of the job distribution system. If the system operation fluctuation value does not exceed the fluctuation frequency threshold, and the system operation risk ratio exceeds the duration ratio threshold, it is inferred that the current management end's job distribution system risk detection is normal, generating a system safety signal and sending it to the integrated management platform.

[0019] Furthermore, the process for evaluating the system's anti-interference capabilities is as follows:

[0020] Get the year-on-year increase in the frequency of operational process completion delays for management nodes during the continuous operation phase of the management terminal, and also get the month-on-month decrease in the speed at which management positions execute operational processes during the continuous operation phase of the management terminal:

[0021] If the year-on-year increase in the frequency of the operation process completion delay corresponding to the management node exceeds the threshold for the year-on-year increase in frequency during the continuous operation phase of the management terminal, or if the month-on-month decrease in the speed of the operation process execution by the management position exceeds the threshold for the month-on-month decrease in speed during the continuous operation phase of the management terminal, it is inferred that the anti-interference assessment of the position distribution system is abnormal, a low anti-interference signal is generated and sent to the integrated management platform.

[0022] If the year-on-year increase in the frequency of operational process completion delay corresponding to the management node during the continuous operation phase of the management end does not exceed the threshold for the year-on-year increase in frequency, and the month-on-month decrease in the speed of the management position executing the operational process during the continuous operation phase of the management end does not exceed the threshold for the month-on-month decrease in speed, then it is inferred that the anti-interference assessment of the position distribution system is normal, and a high anti-interference signal is generated and sent to the integrated management platform.

[0023] Furthermore, after receiving a low interference resistance signal, the integrated management platform marks the cycle length and corresponding workload of the current continuous operation phase as load operation characteristics, and performs load operation characteristic identification and detection during operation at the management end. If an anomaly occurs, the cycle length and workload are adjusted.

[0024] Furthermore, the process of the system performance interference detection unit is as follows:

[0025] Based on the office area where the management position is located, collect IoT sensor data for the corresponding office area. The IoT sensor data includes temperature, humidity, CO2 concentration, light intensity, and noise. Based on the data monitoring of the IoT sensor data, any fluctuation in any data exceeding the set range is marked as an abnormal feature of the working environment. Based on the office area where the management position is located, obtain the high efficiency characteristics of the corresponding management position's work output.

[0026] The system acquires the time periods during which abnormal work environment characteristics occur, and collects the cumulative value of high-efficiency work output characteristics generated within the floating time periods of these abnormal work environment characteristics. Simultaneously, it acquires the time periods during which high-efficiency work output characteristics occur, and collects the cumulative floating frequency value of abnormal work environment characteristics within these time periods.

[0027] Furthermore, the cumulative value of the high-efficiency work output characteristics generated during the period when abnormal work environment characteristics occurred, and the cumulative fluctuation frequency value of abnormal work environment characteristics during the period when high-efficiency work output characteristics occurred, were analyzed:

[0028] If the cumulative value of the high-efficiency work output characteristics generated during the period when the abnormal work environment characteristics are generated is lower than the cumulative generation threshold, and the cumulative floating frequency value of the abnormal work environment characteristics generated during the period when the high-efficiency work output characteristics are generated is higher than the cumulative floating frequency threshold, then it is inferred that the management post efficiency interference analysis detection is abnormal, and the corresponding abnormal work environment characteristics are sent to the comprehensive management platform.

[0029] If the cumulative value of the high-efficiency work output characteristics generated during the period when the abnormal work environment characteristics are generated is not lower than the cumulative generation threshold, or if the cumulative floating frequency value of the abnormal work environment characteristics generated during the period when the high-efficiency work output characteristics are generated is not higher than the cumulative floating frequency threshold, then it is inferred that the management post efficiency interference analysis detection is abnormal, and the corresponding abnormal work environment characteristics are sent to the integrated management platform.

[0030] Furthermore, after receiving abnormal characteristics of the work environment, the integrated management platform uses these abnormal characteristics as control data to conduct operational control of the management positions in order to stabilize the position distribution system. After receiving abnormal characteristics of the work environment, the integrated management platform uses these abnormal characteristics as monitoring data. If fluctuations occur during the monitoring phase and the cumulative value of the high-efficiency work output characteristic decreases, then characteristic control is implemented; otherwise, continuous monitoring is conducted.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] 1. By constructing a job distribution system that links positions, management nodes, and management terminals, and combining it with quantitative analysis of the ratio of operational speed fluctuation frequency to delay duration, the system enables precise and real-time detection of enterprise human resource risks. It accurately defines the management nodes and positions corresponding to each operational process node, ensuring the rationality of the job distribution system and laying a solid foundation for subsequent risk detection. This effectively avoids operational inefficiencies caused by chaotic job settings and poor node linkage. By collecting operational speed data in real time and calculating the ratio of average speed to fluctuation frequency and system operational risk ratio, the system achieves quantitative risk assessment and timely early warning, breaking the subjectivity and lag of traditional manual risk assessment. This allows enterprises to intervene and handle risks in their early stages, reducing their impact on operations. Based on differentiated thresholds for risk assessment, the system adapts to the operational characteristics of enterprises in different industries and of different sizes. Dynamic threshold calibration ensures the accuracy of risk assessment, providing scientific data support for optimizing the enterprise job distribution system and adjusting personnel allocation, thereby improving the accuracy and targeting of human resource management.

[0033] 2. To address the need for quantitative assessment of the anti-interference capability of the job distribution system, the introduction of indicators such as the year-on-year increase range of delay frequency and the month-on-month decrease range of speed enables precise assessment and optimization of anti-interference capability. This quantitative assessment of the job distribution system's anti-interference capability during continuous operation breaks through the qualitative limitations of traditional anti-interference assessments, allowing enterprises to clearly understand the system's stability level. Based on the assessment results, abnormal load operation characteristics (cycle length, workload) are accurately identified, and targeted adjustment measures are implemented to effectively reduce system operational disorder and efficiency decline caused by excessive load, thereby improving the system's continuous operation capability. Through dynamic threshold adaptation, the anti-interference assessment needs of enterprises at different operational stages and in different business scenarios are met, providing a scientific basis for enterprises to optimize operational processes and rationally allocate workloads, thereby improving the overall operational stability and sustainability of the enterprise.

[0034] 3. Focusing on the impact of the office environment on job performance, through multi-dimensional data collection and correlation analysis, we have achieved accurate identification and control of performance interference. This breaks through the limitations of traditional performance evaluation, which only focuses on the individual's own qualities, by incorporating office environment factors into the scope of performance management, thus constructing a more comprehensive performance evaluation system and improving the integrity of performance management. By simultaneously collecting environmental sensor data and high-efficiency work output characteristic data, we have established a correlation analysis mechanism between the two to accurately identify the interference of environmental anomalies on performance, providing targeted data support for enterprises to optimize the office environment and improve job performance. We implement differentiated management strategies (direct management or dynamic monitoring) for different abnormal detection results, which not only ensures the stable improvement of performance but also avoids the waste of resources caused by over-management, thus improving the effectiveness and economy of performance management. Attached Figure Description

[0035] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0036] Figure 1 This is a system principle block diagram of the present invention;

[0037] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0038] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0040] Please see Figures 1-2 As shown, a human resource integrated management system based on big data analysis includes an integrated management platform, wherein the integrated management platform is communicatively connected to a job distribution system detection unit, a system anti-interference assessment unit, and a system effectiveness interference detection unit;

[0041] The integrated management platform generates a job distribution system detection signal and sends it to the job distribution system detection unit. After receiving the job distribution system detection signal, the job distribution system detection unit sets the distribution system for the company's jobs and performs system detection based on the set distribution system to complete the company's human resource risk detection.

[0042] Enterprises that need human resource management are marked as management terminals. Based on the operational process of the management terminals, the corresponding departments for each operational process node are determined and marked as management nodes. Based on the operational process of the management nodes, each management position is determined. Management positions, management nodes, and management terminals construct a position distribution system, and the position distribution system operates in coordination.

[0043] During the operational phase of the job distribution system, risk assessment of the job distribution system will be conducted.

[0044] When the management terminal issues an operation signal, the execution speed of the operation process of each management node is obtained, and the average speed is obtained based on the execution speed. The fluctuation frequency of the ratio of the average execution speed of the operation process of each management node is collected, and the fluctuation frequency is marked as the system operation fluctuation value.

[0045] Simultaneously, after the management node receives the operational signal, a delay occurs in the execution of the operational process by the corresponding management position.

[0046] The duration and delay duration are generated, and the delay duration of the management node operation is calculated based on the delay duration ratio, which is marked as the system operation risk ratio;

[0047] Compare the system operation fluctuation value and the system operation risk ratio with the fluctuation frequency threshold and the duration ratio threshold, respectively:

[0048] If the fluctuation value of the system operation exceeds the fluctuation frequency threshold, or the system operation risk ratio does not exceed the duration ratio threshold, it is inferred that the current management end's job distribution system risk detection is abnormal, a system risk signal is generated and sent to the integrated management platform. Upon receiving the system risk signal, the integrated management platform performs job distribution system detection on the management end and performs operational detection on each management position and management node to ensure the operational efficiency of the job distribution system.

[0049] If the system operation fluctuation value does not exceed the fluctuation frequency threshold and the system operation risk ratio exceeds the duration ratio threshold, it is inferred that the current management end job distribution system risk detection is normal, a system safety signal is generated and sent to the comprehensive management platform;

[0050] It can be explained that the job distribution system detection unit involves a floating frequency threshold and a duration ratio threshold, the origin and acquisition method of which are as follows:

[0051] Floating frequency threshold: This refers to the critical value of the floating frequency ratio of the average execution speed of the management node's operational processes, used to determine whether fluctuations in the system's operational speed are abnormal. It is obtained using a combination of "industry benchmark data + enterprise historical data + dynamic calibration." First, industry benchmark ranges for the floating frequency ratio of the average execution speed ratio in the operational systems of similar companies of the same industry and scale are obtained through industry research institutions and human resource management industry associations. Second, historical operational data from the management end (target company) over the past 1-3 years are collected, and the floating frequency ratio of the average speed ratio under different operational stages and task types is statistically analyzed to calculate the company's internal historical average critical value. Finally, considering the company's current operational scale, business complexity, staffing, and other actual conditions, the industry benchmark value and the company's historical average are weighted and adjusted (weights are set according to the company's individual needs, with the industry benchmark weighting at 0.4-0.6 and the historical average weighting at 0.4-0.6), resulting in an initial floating frequency threshold. Subsequent quarterly dynamic calibration and adjustments are made based on changes in the company's operational data to ensure the threshold's adaptability.

[0052] Duration Ratio Threshold: This refers to the critical value of the ratio of the execution delay time of management positions to the overall operational delay time of management nodes. It is used to determine the degree of impact of position delays on system operation. It is obtained primarily from the company's internal historical data, combined with expert evaluation and optimization. First, during the target company's historical operations, data on the ratio of the execution delay time of each management position to the overall delay time of the corresponding management node during the normal operation phase of the position distribution system is collected. The distribution range of the ratio is statistically analyzed, and the upper limit of the 95% confidence interval is used as the initial threshold value. Second, the company's human resources management experts and operations management experts are invited to evaluate and score the initial threshold value based on factors such as the importance of job responsibilities and the closeness of the linkage between positions and nodes (a maximum score of 10 points, with 8 points or above considered reasonable and scores below 8 points requiring adjustment). Finally, based on the expert evaluation opinions, the initial threshold value is revised to obtain the final duration ratio threshold. For newly established companies without historical data, the threshold of benchmark companies in the same industry can be used as the initial value, and then replaced and revised after accumulating a certain amount of operational data.

[0053] After receiving the system security signal, the integrated management platform generates a system anti-interference assessment signal and sends it to the system anti-interference assessment unit.

[0054] After receiving the system anti-interference assessment signal, the system anti-interference assessment unit performs a system anti-interference assessment on the management terminal.

[0055] The system obtains the year-on-year increase span of the operational process completion delay frequency corresponding to management nodes during the continuous operation phase of the management terminal, and the month-on-month decrease span of the operational process execution speed of management positions during the continuous operation phase of the management terminal. These two spans are then compared with thresholds for the year-on-year increase span of frequency and the month-on-month decrease span of speed, respectively.

[0056] If the year-on-year increase in the frequency of the operational process completion delay corresponding to the management node exceeds the threshold for the year-on-year increase in frequency during the continuous operation phase of the management terminal, or if the month-on-month decrease in the speed of the operational process execution by the management position exceeds the threshold for the month-on-month decrease in speed during the continuous operation phase of the management terminal, it is inferred that the anti-interference assessment of the position distribution system is abnormal, a low anti-interference signal is generated and sent to the integrated management platform. After receiving the low anti-interference signal, the integrated management platform marks the cycle length and corresponding workload of the current continuous operation phase as load operation characteristics, and performs load operation characteristic identification and detection during the operation of the management terminal. If there is an abnormality, the cycle length and workload are adjusted.

[0057] If the year-on-year increase in the frequency of the operational process completion delay corresponding to the management node during the continuous operation phase of the management end does not exceed the threshold for the year-on-year increase in frequency, and the month-on-month decrease in the speed of the operational process execution by the management position during the continuous operation phase of the management end does not exceed the threshold for the month-on-month decrease in speed, then it is inferred that the anti-interference assessment of the position distribution system is normal, and a high anti-interference signal is generated and sent to the integrated management platform.

[0058] Understandably, the system's anti-interference evaluation unit involves thresholds for the year-on-year increase in frequency and the year-on-year decrease in speed. The specific origins and acquisition methods are as follows:

[0059] The year-on-year increase threshold for frequency refers to the critical span value for the year-on-year increase in the frequency of operational process completion at management nodes. It is used to determine whether the increase in delay frequency is abnormal during continuous operation. It is obtained using a "year-on-year data statistics + trend analysis + risk level adaptation" model. First, operational delay frequency data for the target company over the past 2-3 years (e.g., the first quarter of last year and the first quarter of this year) is collected. The increase span for delay frequency in each year is calculated, and the maximum increase value under normal operating conditions is used as the basic critical value. Second, through a trend analysis model, the trend of delay frequency changes for the company over the next 1-2 operating cycles is predicted. Combined with the company's acceptable operational risk level (low risk, medium risk, high risk), the basic critical value is adjusted (the threshold is reduced by 10%-20% for low-risk levels and increased by 10%-20% for high-risk levels). Finally, the threshold is calibrated by referring to the threshold standards of companies with similar risk levels in the same industry, ensuring that the threshold is both consistent with the company's actual operating conditions and reasonable within the industry.

[0060] Speed ​​Decline Threshold: This refers to the critical threshold value at which the speed of operational process execution by management positions decreases month-on-month. It is used to determine whether the speed decrease is abnormal during continuous operation. Its acquisition method revolves around "month-on-month data statistics + business scenario adaptation." First, monthly / quarterly operational speed data from the target company over the past 6-12 months is collected. The month-on-month speed decline span is calculated, and the maximum decline value under normal operating conditions is used as the initial threshold. Second, the initial threshold is adjusted according to the operational characteristics of different business scenarios (such as peak season, off-season, and new project launch period). For example, during peak season when business volume is large, a certain degree of speed decrease is allowed, and the threshold can be increased by 15%-25%; during the new project launch period when speed fluctuations are large, the threshold can be increased by 20%-30%. Finally, a small-scale pilot operation (selecting 2-3 core management nodes for pilot testing) is conducted to verify the rationality of the threshold. Fine-tuning is made based on the pilot results to determine the final threshold.

[0061] After receiving a high anti-interference signal, the integrated management platform generates a system performance interference detection signal and sends it to the system performance interference detection unit.

[0062] After receiving the system performance interference detection signal, the system performance interference detection unit performs interference analysis and detection on the management position performance through working environment detection;

[0063] Based on the office area where the management position is located, collect IoT sensor data for the corresponding office area. The IoT sensor data includes temperature, humidity, CO2 concentration, light intensity, and noise. Based on the data monitoring of the IoT sensor data, any fluctuation in any data exceeding the set range is marked as an abnormal feature of the working environment.

[0064] Based on the office area where the management position is located, obtain the high efficiency characteristics of the corresponding management position's work output. The high efficiency characteristics of work output are reflected by parameters such as the range of increase in product output, the increase in product qualification rate, and the increase in process execution speed.

[0065] The system acquires the time periods during which abnormal work environment characteristics occur, and collects the cumulative value of high-efficiency work output characteristics generated within the time periods during which abnormal work environment characteristics occur. Simultaneously, it acquires the time periods during which high-efficiency work output characteristics occur, and collects the cumulative floating frequency value of abnormal work environment characteristics within the time periods during which high-efficiency work output characteristics occur.

[0066] The cumulative value of high-efficiency work output characteristics generated during the period when abnormal work environment characteristics occurred, and the cumulative fluctuation frequency value of abnormal work environment characteristics generated during the period when high-efficiency work output characteristics occurred, were analyzed:

[0067] If the cumulative value of the high-efficiency work output characteristics during the period when the abnormal work environment characteristics occur is lower than the cumulative threshold, and the cumulative floating frequency value of the abnormal work environment characteristics during the period when the high-efficiency work output characteristics occur is higher than the cumulative floating frequency threshold, then it is inferred that the management position efficiency interference analysis and detection is abnormal, and the corresponding abnormal work environment characteristics are sent to the integrated management platform. After receiving the data, the integrated management platform uses the abnormal work environment characteristics of each management position as control data to carry out management position operation control in order to stabilize the position distribution system.

[0068] If the cumulative value of the high-efficiency work output characteristic during the period when the abnormal work environment characteristic occurs is not lower than the cumulative threshold, or if the cumulative fluctuation frequency value of the abnormal work environment characteristic during the period when the high-efficiency work output characteristic occurs is not higher than the cumulative fluctuation frequency threshold, then it is inferred that the management position efficiency interference analysis detection is abnormal, and the corresponding abnormal work environment characteristic is sent to the integrated management platform. After receiving it, the integrated management platform uses the abnormal work environment characteristic as monitoring data. If the cumulative value of the high-efficiency work output characteristic decreases when fluctuation occurs during the monitoring period, then characteristic control is implemented; otherwise, monitoring continues.

[0069] Understandably, the system performance interference detection unit involves generating cumulative thresholds and cumulative floating frequency thresholds, the specific origins and acquisition methods of which are as follows:

[0070] The cumulative threshold is the critical value at which the cumulative value of high-efficiency work output characteristics is generated within a period of abnormal work environment characteristics. It is used to determine the degree of impact of environmental anomalies on work output. It is obtained using a "high-efficiency output benchmark statistics + abnormal scenario comparison" model. First, the cumulative values ​​of high-efficiency work output characteristics for each management position in the target company are collected under normal work environment conditions over a certain period (e.g., one month, one quarter). High-efficiency output benchmark values ​​for different positions and business types are calculated, and 70%-80% of the benchmark value is used as the initial cumulative threshold (i.e., when the cumulative value of high-efficiency characteristics during an abnormal period is lower than 70%-80% of the benchmark value, it is considered abnormal). Second, scenarios where abnormal work environments have occurred in the company's history are selected, and the differences in the cumulative values ​​of high-efficiency characteristics between abnormal and normal periods are compared. The initial threshold is adjusted according to the degree of difference. Finally, considering the importance of the position (core positions have higher requirements for high-efficiency output, and the threshold can be increased by 5%-10%), the final cumulative threshold is determined and dynamically updated every six months based on adjustments to job content and changes in business objectives.

[0071] Cumulative Floating Frequency Threshold: This refers to the critical value of the cumulative floating frequency of abnormal working environment characteristics during the period when high-efficiency work output is generated. It is used to determine whether the interference frequency of environmental anomalies on high-efficiency output exceeds the standard. Its acquisition method is based on "environmental anomaly frequency statistics + efficiency impact correlation analysis". First, data on the floating frequency of environmental anomalies is collected during periods when the target company's working environment is normal and work output is high. The maximum value of the anomaly frequency during this period is used as the basic threshold. Second, through a correlation analysis model, the correlation between environmental anomaly frequency and high-efficiency output is analyzed (the higher the correlation coefficient, the greater the impact of environmental anomalies on high-efficiency output, and the lower the threshold should be). The basic threshold is then corrected based on the correlation coefficient (e.g., if the correlation coefficient is above 0.8, the threshold is reduced by 20%-30%; if the correlation coefficient is below 0.5, the threshold is increased by 10%-20%). Finally, the corrected threshold is verified for compliance with national office environment standards (such as the relevant requirements for office environments in GB / T50353-2013 "Code for Calculation of Building Area of ​​Building Engineering") to ensure that the threshold meets both the company's efficiency management needs and relevant national standards.

[0072] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A comprehensive human resource management system based on big data analytics, characterized in that: This includes a comprehensive management platform, whose communication connections include: The job distribution system detection unit identifies the management end, sets up a job distribution system for the enterprise, and conducts system detection based on the set distribution system to complete the enterprise's human resource risk detection. The system anti-interference assessment unit performs system anti-interference assessment on the management end and determines the anti-interference characteristics of the management end through the anti-interference assessment. The system performance interference detection unit analyzes and detects interference with the performance of management positions through working environment monitoring, and makes control decisions accordingly.

2. The comprehensive human resource management system based on big data analysis according to claim 1, characterized in that, The process for the job distribution system detection unit is as follows: Enterprises requiring human resource management are marked as management units. Based on the operational processes of the management units, the corresponding departments for each operational process node are determined, and the corresponding departments are marked as management nodes. Based on the operational processes of the management nodes, each management position is determined. Management positions, management nodes, and the management units construct a position distribution system, and the position distribution system operates in coordination. During the operation phase of the position distribution system, risk detection of the position distribution system is carried out.

3. The comprehensive human resource management system based on big data analysis according to claim 2, characterized in that, When the management terminal issues an operational signal, it obtains the execution speed of the operational processes at each management node, calculates the average speed, and collects the fluctuation frequency of the ratio of the average execution speed of the operational processes at each management node to the system's operational fluctuation value. Simultaneously, after receiving the operational signal, the management node obtains the delay caused by the execution of the operational processes by the corresponding management position. The duration and delay duration are generated, and the delay duration of the management node operation is calculated based on the delay duration ratio, which is marked as the system operation risk ratio.

4. The comprehensive human resource management system based on big data analysis according to claim 3, characterized in that, Compare the system operation fluctuation value and the system operation risk ratio with the fluctuation frequency threshold and the duration ratio threshold, respectively: If the fluctuation value of the system operation exceeds the fluctuation frequency threshold, or the system operation risk ratio does not exceed the duration ratio threshold, it is inferred that the current management end's job distribution system risk detection is abnormal, a system risk signal is generated and sent to the integrated management platform. Upon receiving the system risk signal, the integrated management platform performs job distribution system detection on the management end and performs operational detection on each management position and management node to ensure the operational efficiency of the job distribution system. If the system operation fluctuation value does not exceed the fluctuation frequency threshold and the system operation risk ratio exceeds the duration ratio threshold, it is inferred that the current management end's job distribution system risk detection is normal, and a system safety signal is generated and sent to the integrated management platform.

5. A comprehensive human resource management system based on big data analysis according to claim 1, characterized in that, The process of evaluating the system's anti-interference capabilities is as follows: Get the year-on-year increase in the frequency of operational process completion delays for management nodes during the continuous operation phase of the management terminal, and also get the month-on-month decrease in the speed at which management positions execute operational processes during the continuous operation phase of the management terminal: If the year-on-year increase in the frequency of the operation process completion delay corresponding to the management node exceeds the threshold for the year-on-year increase in frequency during the continuous operation phase of the management terminal, or if the month-on-month decrease in the speed of the operation process execution by the management position exceeds the threshold for the month-on-month decrease in speed during the continuous operation phase of the management terminal, it is inferred that the anti-interference assessment of the position distribution system is abnormal, a low anti-interference signal is generated and sent to the integrated management platform. If the year-on-year increase in the frequency of operational process completion delay corresponding to the management node during the continuous operation phase of the management end does not exceed the threshold for the year-on-year increase in frequency, and the month-on-month decrease in the speed of the management position executing the operational process during the continuous operation phase of the management end does not exceed the threshold for the month-on-month decrease in speed, then it is inferred that the anti-interference assessment of the position distribution system is normal, and a high anti-interference signal is generated and sent to the integrated management platform.

6. A comprehensive human resource management system based on big data analysis according to claim 5, characterized in that, After receiving a low interference signal, the integrated management platform marks the cycle length and corresponding workload of the current continuous operation phase as load operation characteristics. During operation at the management end, load operation characteristics are identified and detected, and the cycle length and workload are adjusted when abnormalities occur.

7. A comprehensive human resource management system based on big data analysis according to claim 1, characterized in that, The process of the system performance interference detection unit is as follows: Based on the office area where the management position is located, collect IoT sensor data for the corresponding office area. The IoT sensor data includes temperature, humidity, CO2 concentration, light intensity, and noise. Based on the data monitoring of the IoT sensor data, any fluctuation in any data exceeding the set range is marked as an abnormal feature of the working environment. Based on the office area where the management position is located, obtain the high efficiency characteristics of the corresponding management position's work output. The system acquires the time periods during which abnormal work environment characteristics occur, and collects the cumulative value of high-efficiency work output characteristics generated within the floating time periods of these abnormal work environment characteristics. Simultaneously, it acquires the time periods during which high-efficiency work output characteristics occur, and collects the cumulative floating frequency value of abnormal work environment characteristics within these time periods.

8. A comprehensive human resource management system based on big data analysis according to claim 7, characterized in that, The cumulative value of high-efficiency work output characteristics generated during the period when abnormal work environment characteristics occurred, and the cumulative fluctuation frequency value of abnormal work environment characteristics generated during the period when high-efficiency work output characteristics occurred, were analyzed: If the cumulative value of the high-efficiency work output characteristics generated during the period when the abnormal work environment characteristics are generated is lower than the cumulative generation threshold, and the cumulative floating frequency value of the abnormal work environment characteristics generated during the period when the high-efficiency work output characteristics are generated is higher than the cumulative floating frequency threshold, then it is inferred that the management post efficiency interference analysis detection is abnormal, and the corresponding abnormal work environment characteristics are sent to the comprehensive management platform. If the cumulative value of the high-efficiency work output characteristics generated during the period when the abnormal work environment characteristics are generated is not lower than the cumulative generation threshold, or if the cumulative floating frequency value of the abnormal work environment characteristics generated during the period when the high-efficiency work output characteristics are generated is not higher than the cumulative floating frequency threshold, then it is inferred that the management post efficiency interference analysis detection is abnormal, and the corresponding abnormal work environment characteristics are sent to the integrated management platform.

9. A comprehensive human resource management system based on big data analysis according to claim 8, characterized in that, After receiving abnormal characteristics of the work environment, the integrated management platform uses these characteristics as control data to manage the operation of each management position, thereby stabilizing the position distribution system. The platform also uses these abnormal characteristics as monitoring data. If fluctuations occur during the monitoring phase and the cumulative value of the high-efficiency work output characteristic decreases, then characteristic control is implemented; otherwise, continuous monitoring continues.

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