Labor service dispatch data analysis processing method and system and storage medium

Abstract

The invention belongs to the field of labor dispatch data analysis, and discloses a labor dispatch data analysis processing method and system and a storage medium. According to the invention, through dynamic matching and multi-scheme comparison of the personnel capability labels and the post demand labels, the optimal matching scheme can be accurately generated, and the labor dispatch matching success rate and the matching effect are improved. According to the method, the matching coefficient is generated by combining actual working data such as the efficiency coefficient and the stability coefficient, upgrading from static label matching to dynamic data driving matching is achieved, adaptability abnormity can be accurately recognized, the situation that the adaptability of matched personnel posts is insufficient is avoided, and the problems that the task completion rate is low, and client feedback is poor are prevented. According to the invention, a bidirectional correction system is constructed based on customer feedback and personnel feedback, and the mechanism can respond to business changes in real time and autonomously trigger a correction mechanism so as to quickly respond to actual business requirements, reduce manual intervention, greatly improve delivery management efficiency and reduce resource waste.

Description

Technical Field

[0001] The present invention belongs to the technical field of labor dispatch data analysis, and relates to a labor dispatch data analysis and processing method, system and storage medium. Background Art

[0002] In the field of outbound labor dispatch, efficient matching of personnel with positions and dynamic management are key challenges in improving service quality. Traditional outbound labor dispatch management relies heavily on manual experience or static label matching, lacking dynamic analysis of actual work performance and job requirements.

[0003] Existing technologies often perform a crude matching of fixed employee skill tags with job requirement lists. This method fails to integrate real-time data from client timekeeping and attendance systems to evaluate the matching effect. This results in insufficient adaptability of matched employees to their positions, leading to low task completion rates and poor customer feedback. Furthermore, existing methods lack a systematic correction mechanism when employee capabilities or job requirements change, making it difficult to quickly respond to actual business needs. This leads to inefficient outsourced labor management and significant resource waste. Therefore, to achieve accurate matching of personnel and positions and continuous optimization, research on outsourced labor data analysis and processing is of great significance.

[0004] Traditional solutions for matching people to positions rely solely on initial employee competency tags and job requirement tags, failing to dynamically adjust the matching scheme based on actual work data. This results in a disconnect between matching results and actual requirements. When job requirements undergo subtle changes, existing technology is unable to identify them promptly and continues to use the old tags, resulting in a mismatch between employee competency and job requirements.

[0005] Traditional solutions lack an adaptive anomaly detection system based on customer feedback, employee feedback, and work time and attendance data. When employee performance declines or job requirements change, there's no automatic trigger for capacity or job requirement corrections. Manual intervention is required, which is time-consuming and costly.

[0006] Traditional solutions fail to integrate data from multiple sources, such as the client's timekeeping and attendance systems, for comprehensive analysis, making it difficult to fully evaluate matching results. Focusing solely on skill matching, they ignore key indicators like attendance stability and time consistency, leading to insufficient stability in the actual work of the matching group and fluctuating customer satisfaction. Summary of the Invention

[0007] In view of this, in order to solve the problems raised in the above background technology, a labor dispatch data analysis and processing method, system and storage medium are proposed.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides a labor dispatch data analysis and processing method, including: generating a personnel-position matching list based on personnel capability labels and position requirement labels, and further selecting and constructing a personnel-position matching group.

[0009] Based on the customer's working time system and attendance system, the actual matching coefficient of each personnel position matching group is generated, and it is determined whether there is any adaptability anomaly. If so, personnel capability correction and position requirement correction are triggered.

[0010] Based on the customer's working time system and attendance system, combined with customer feedback information, it is determined whether personnel capacity correction is needed. When it is identified as necessary, the personnel capacity correction direction is further identified.

[0011] Based on the customer's working time system and attendance system, combined with personnel feedback information, it is determined whether job demand correction is needed. When the need is identified, the direction of job demand correction is further identified.

[0012] A second aspect of the present invention provides a labor dispatch data analysis and processing system, including: a personnel-position matching module, which generates a personnel-position matching list based on personnel capability tags and position requirement tags, and further selects and constructs a personnel-position matching group.

[0013] The adaptation analysis module generates the actual matching coefficient of each personnel position matching group based on the customer's working time system and attendance system, and determines whether there is any adaptability anomaly. If so, it triggers personnel capability correction and position requirement correction.

[0014] The personnel capability correction module is based on the customer's working time system and attendance system, combined with customer feedback information to determine whether personnel capability correction is needed, and further identify the personnel capability correction direction when it is needed.

[0015] The job requirement correction module is based on the customer's working time system and attendance system, combined with personnel feedback information to determine whether job requirement correction is needed, and further identify the direction of job requirement correction when it is needed.

[0016] A third aspect of the present invention provides a storage medium storing one or more programs, which can be executed by one or more processors to implement the steps in the above-mentioned labor dispatch data analysis and processing method.

[0017] Compared with the existing technology, the beneficial effects of the present invention are as follows: (1) The present invention can accurately generate the best matching solution through dynamic matching of personnel ability labels and job requirement labels and comparison of multiple solutions, thereby improving the success rate and matching effect of labor dispatch matching.

[0018] (2) The present invention generates matching coefficients by combining actual work data such as efficiency coefficients and stability coefficients, thereby achieving an upgrade from static label matching to dynamic data-driven matching. It can accurately identify adaptability anomalies, avoid insufficient adaptability of personnel positions after matching, and prevent problems such as low task completion rate and poor customer feedback.

[0019] (3) The present invention builds a two-way correction system based on customer feedback and personnel feedback. This mechanism can respond to business changes in real time, trigger the correction mechanism autonomously, and then quickly respond to actual business needs, reduce manual intervention, greatly improve the efficiency of outsourcing management, and reduce resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 Schematic diagram of the steps of the method of the present invention.

[0022] Figure 2 This is a schematic diagram of the connection of various modules of the system of the present invention.

[0023] Figure 3 A schematic diagram of the storage medium structure provided by the present invention.

[0024] Figure 4 A flowchart of personnel capability correction analysis and judgment corresponding to an embodiment provided by the present invention. DETAILED DESCRIPTION

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0026] See also Figure 1 As shown, the first aspect of the present invention provides a labor dispatch data analysis and processing method, including: generating a personnel-position matching list based on personnel capability tags and position requirement tags, and further selecting and constructing a personnel-position matching group.

[0027] In a preferred embodiment of the present invention, the specific analysis method for generating the personnel-position matching list is as follows: extracting the position requirement label corresponding to each position and the personnel capability label corresponding to each personnel, and matching the personnel capability label with the position requirement label.

[0028] It's important to explain that personnel competency tags are structured data tags used to quantitatively describe the professional skills, work experience, and professional qualities of dispatched personnel. These tags include, but are not limited to, key information such as a person's skills, qualifications, work experience, and professional qualities, converted into quantifiable and comparable labeled data. They serve as the fundamental data unit for matching personnel with positions, helping the system quickly identify the fit between personnel and job requirements. They are a core element for achieving precise matching and dynamic management.

[0029] It's important to explain that job requirement tags are digital labels used to structuredly describe the capabilities, conditions, and requirements required for each position in labor dispatch. They represent a standardized expression of job requirements. By extracting key information such as the job's professional skills requirements, experience threshold, and professionalism standards, they are converted into quantifiable and comparable labeled data. These serve as benchmark data for matching positions with personnel, helping the system quickly screen qualified candidates and providing a basis for subsequent dynamic adjustments to job requirements. They are fundamental to achieving precise management of labor dispatch.

[0030] The personnel whose ability labels completely match the job requirement labels are regarded as the preliminary matching personnel for the corresponding positions, and then the list of preliminary matching personnel corresponding to each position is obtained.

[0031] The correspondence between the personnel and positions in the preliminary matching personnel list corresponding to each position is arranged to obtain a personnel-position matching list, where one position in the personnel-position matching list may include one or more preliminary matching personnel.

[0032] It should be noted that the list of preliminary matches for each position is arranged according to the position-person correspondence to form a structured person-position matching list. A position can include one or more preliminary matches, and if multiple people meet the requirements of the same position, this reflects the flexibility and alternative nature of the matching.

[0033] In a preferred embodiment of the present invention, the specific analysis method for selecting and constructing the personnel-position matching group is as follows: randomly select any preliminary matching person from the personnel-position matching list as the matching person for any position, and then repeat the matching operation until all matching operations are completed to generate a matching plan.

[0034] Further randomly select any other preliminary matching personnel as matching personnel for any other positions, and then repeat the matching operation until all matches are completed, generating several matching solutions.

[0035] Count the number of successfully matched positions corresponding to each matching plan, compare the number of successfully matched positions corresponding to each matching plan, and select the matching plan corresponding to the maximum number of successfully matched positions as the final matching plan.

[0036] Each person in the final matching plan is matched with a position one by one to generate a person-position matching group, in which each person and a position are matched with each other one by one.

[0037] It should be noted that this step uses the logical chain of random matching - multiple plan generation - quantitative comparison - optimal selection to screen out the optimal matching plan from the generated personnel-position matching list, forming a matching group with one-to-one correspondence between personnel and positions, and realizing the precise transformation from the preliminary matching list to the actual implementation plan.

[0038] It's important to note that this matching mechanism overcomes the limitations of traditional single-solution matching by randomly generating and quantitatively comparing multiple matching scenarios, ensuring the selected solution is the theoretically optimal. For example, when multiple possible combinations of employee competency tags and job requirement tags exist, it can find the matching solution that covers the greatest number of positions. Using the number of successfully matched positions as the sole screening criterion, the matching process shifts from being experience-driven to data-driven, avoiding subjective judgment errors and improving matching accuracy and reliability.

[0039] It should be noted that the reason for selecting the matching solution corresponding to the maximum number of successfully matched positions as the final matching solution is: this solution is selected because it can maximize position coverage and resource utilization, reduce the risk of adaptability anomalies, use quantitative data as an objective decision-making basis, avoid subjective bias, and reversely verify the label system. The algorithm complexity is controllable and connected with the subsequent closed-loop process to achieve the optimal allocation of labor dispatch resources.

[0040] It should be noted that the present invention can accurately generate the best matching solution through dynamic matching of personnel ability labels and job requirement labels and comparison of multiple solutions, thereby improving the success rate and matching effect of labor dispatch matching.

[0041] Based on the customer's working time system and attendance system, the actual matching coefficient of each personnel position matching group is generated, and it is determined whether there is any adaptability anomaly. If so, personnel capability correction and position requirement correction are triggered.

[0042] In a preferred embodiment of the present invention, the specific analysis method of the actual matching coefficient is as follows: based on the customer working hour system, the personnel task completion rate, effective working hour ratio and output quality score ratio are obtained, and then the average is calculated to obtain the efficiency coefficient.

[0043] Based on the attendance system, the normal attendance rate and working hours consistency are obtained, and then the mean is calculated to obtain the stability coefficient.

[0044] The efficiency coefficient and the stability coefficient are averaged to obtain the actual matching coefficient of each personnel position matching group.

[0045] It's important to note that actual matching coefficient analysis is conducted to quantitatively assess the actual compatibility of personnel-to-position matching groups across multiple dimensions by integrating work time systems and attendance data. This analysis verifies the effectiveness of preliminary matching plans, automatically identifies mismatches by comparing against preset thresholds, and triggers bidirectional adjustments to personnel capabilities or position requirements. This upgrades from label matching to dynamic performance verification, improving the accuracy and resource utilization of labor dispatch management.

[0046] It's important to note that the efficiency coefficient and stability coefficient were chosen as factors influencing the adaptability coefficient because they quantify the quality of the fit based on work efficiency and attendance stability, respectively. The efficiency coefficient incorporates work-hour data such as task completion rate to reflect employees' actual satisfaction with job skill requirements; the stability coefficient incorporates attendance data such as attendance rate to measure the continuity of employees' on-the-job status. Combining these two factors avoids the one-sidedness of a single metric, provides multi-source data support for determining adaptability anomalies, and directly links customer needs with employee performance, facilitating the triggering of a two-way correction mechanism.

[0047] The specific method for determining whether there is an adaptability anomaly is as follows: comparing the actual matching coefficient of each personnel position matching group with the preset actual matching coefficient threshold; if the actual matching coefficient of a personnel position matching group is greater than or equal to the actual matching coefficient threshold, it is determined that there is no adaptability anomaly in the personnel position matching group; otherwise, it is determined that there is an adaptability anomaly in the personnel position matching group.

[0048] It should be noted that the basis for setting the actual matching coefficient threshold is to combine the historical data of the labor dispatch industry and customer needs, the mean distribution of the comprehensive efficiency coefficient and the stability coefficient, and determine the benchmark value that can ensure job adaptability through statistical analysis. It must cover most effective matching scenarios and be able to trigger abnormal correction in time to ensure the quality of personnel job matching and management efficiency.

[0049] It should be noted that the present invention generates a matching coefficient by combining actual work data such as efficiency coefficient and stability coefficient, thereby realizing an upgrade from static label matching to dynamic data-driven matching. It can accurately identify adaptability anomalies, avoid insufficient adaptability of personnel positions after matching, and prevent problems such as low task completion rate and poor customer feedback.

[0050] See also Figure 4 As shown, based on the customer's working time system and attendance system, combined with customer feedback information, it is determined whether personnel capacity correction is needed, and when it is identified as necessary, the personnel capacity correction direction is further identified.

[0051] In a preferred embodiment of the present invention, the specific method of determining whether personnel capacity correction is needed is as follows: taking the current moment as the basis, dividing several historical monitoring periods based on the preset monitoring time, obtaining the efficiency coefficient of each historical monitoring period based on the customer working hours system, and comparing it with the preset efficiency coefficient threshold.

[0052] Obtain the personnel capability label score of each person from the customer for the corresponding position, and then compare it with the preset personnel capability label score threshold.

[0053] Based on the attendance system, the stability coefficient of each historical monitoring period is obtained and compared with the preset stability coefficient threshold.

[0054] Based on the above comparison results, the following criteria for determining the need for personnel capability correction are used for determination:

[0055] The efficiency coefficient of two consecutive historical monitoring periods is less than the preset efficiency coefficient threshold.

[0056] The score of any personnel capability label is lower than the preset personnel capability label score threshold.

[0057] The stability coefficient of two consecutive historical monitoring periods is less than the preset stability coefficient threshold.

[0058] If any of the above criteria exist, it is determined that personnel capability correction is required.

[0059] It should be noted that the above-mentioned efficiency coefficient threshold, capability label score threshold and stability coefficient threshold are set based on the following: 1. Efficiency coefficient threshold: based on the historical mean or percentile of data such as task completion rate and effective working hours ratio in the working hours system, to ensure coverage of efficiency standards in most effective matching scenarios.

[0060] 2. Competency label scoring threshold: This threshold is set based on the average customer feedback on personnel capabilities and the core skill requirements of the position.

[0061] 3. Stability coefficient threshold: Based on the industry's conventional standards for normal attendance rate and working hours consistency in the attendance system, ensure the continuity of job tasks.

[0062] It should be noted that the continuous period efficiency coefficient, personnel ability label score, and continuous period stability coefficient are used as the basis for judgment, because the three quantify the matching deviation between personnel capabilities and job requirements from the dimensions of work efficiency continuity, customer subjective evaluation, and attendance stability: 1. The efficiency coefficient is continuously lower than the threshold, reflecting that the personnel are continuously unable to meet the job skill requirements.

[0063] 2. The ability label score does not meet the standard, which directly reflects the customer's negative feedback on the personnel's ability.

[0064] 3. Continuous abnormality in the stability coefficient indicates that the personnel’s on-the-job status is unstable, which affects the continuity of job tasks.

[0065] The three indicators are cross-validated through multi-source data to avoid missed judgments in a single dimension and ensure timely triggering of capability correction to match the actual job requirements.

[0066] In a preferred embodiment of the present invention, the specific analysis method for identifying the personnel capability correction direction is as follows: pre-identification of the personnel capability correction direction label is performed based on the comparison of efficiency coefficients, personnel capability label scores and stability coefficients.

[0067] The pre-identification results are sent to the corresponding personnel for confirmation. If the personnel agrees, the personnel capability label correction is initiated. If the personnel disagrees, a third-party review is initiated, and the personnel capability correction is performed based on the third-party review results.

[0068] It's important to note that the reason pre-identification results are submitted to human verification is because competency label correction involves subjective perceptions, requiring integration with self-assessment to avoid system misjudgments, such as false anomalies caused by data fluctuations. If the human disagrees, a third-party review is initiated to verify the objectivity of the data from an independent perspective, preventing subjective objections from masking true competency shortcomings. This mechanism balances humanity and accuracy through self-verification and third-party arbitration, ensuring the rationality and credibility of correction decisions.

[0069] Based on the customer's working time system and attendance system, combined with personnel feedback information, it is determined whether job demand correction is needed. When the need is identified, the direction of job demand correction is further identified.

[0070] In a preferred embodiment of the present invention, the specific method of determining whether job requirement correction is required is as follows: extracting the personnel capability label scores of different personnel corresponding to the same position, and then comparing them with the preset personnel capability label score thresholds respectively.

[0071] The working hour consistency is obtained based on the attendance system, and the working hour consistency is compared with a preset working hour consistency threshold.

[0072] It's important to explain that work hour consistency is a quantitative indicator that measures the degree to which a position's actual working hours match the standard working hours, typically expressed as a percentage. Its core calculation logic involves calculating the absolute deviation between an employee's actual working hours in their attendance records and the position's preset standard working hours, and then calculating the ratio with the corresponding standard working hours.

[0073] Based on personnel feedback on positions, the actual number of skills required for each position is obtained, and then skill overlap analysis is performed with the corresponding position requirement tags to identify whether there are any non-overlapping skills.

[0074] It should be noted that the above-mentioned personnel capability label scoring threshold and working hour consistency threshold are set based on the following: the personnel capability label scoring threshold is set based on the average customer feedback on the capabilities of personnel in similar positions, combined with the core skill requirements of the position; the working hour consistency threshold is based on the historical average of the working hour consistency of similar positions in the attendance system or the industry's conventional standards, to ensure that the position working hour setting matches the actual load.

[0075] Based on the above comparison results, refer to the following job demand correction demand determination criteria for judgment:

[0076] Two people have the same personnel capability label score that is lower than the preset personnel capability label score threshold.

[0077] The working time consistency is less than the preset working time consistency threshold.

[0078] There are any non-overlapping skills.

[0079] If any of the above criteria exist, it is determined that job requirements need to be adjusted.

[0080] It's important to note that if multiple competency labels score below the threshold, it indicates that job requirements may overemphasize non-core skills or omit essential skills, resulting in a group mismatch. Abnormal work hour consistency directly reflects a mismatch between the job's set hours and actual workload, necessitating adjustments to task load or scheduling standards. Insufficient skill overlap indicates redundancy or hidden gaps in job requirement labels. Any abnormality in any of these indicators indicates a disconnect between the requirement definition and the actual scenario. This mechanism improves the sensitivity of anomaly detection through multi-dimensional cross-validation, avoiding missed detections and ensuring dynamic adaptation of requirements.

[0081] It's important to note that we use competency label scores, work-hour consistency, and skill overlap as the basis for determining job requirements corrections. This is because low scores from multiple people for the same competency label can indicate a collective bias in job requirements. Work-hour consistency reflects the alignment between job hours and actual workloads, and skill overlap identifies redundant or hidden skills within requirement labels. These three factors, combined through cross-validation with subjective and objective data, ensure that job requirements align with actual work scenarios and accurately identify deviations from requirement definitions.

[0082] In a preferred embodiment of the present invention, the specific method of identifying the job requirement correction direction is as follows: the ratio of the actual usage time corresponding to each skill to the total working hours is calculated, and then compared with the preset threshold. If the calculation result is less than the preset threshold, the skill is determined to be a redundant skill.

[0083] Any non-overlapping skill is treated as an invisible skill.

[0084] If the working time consistency is less than the preset working time consistency threshold, the actual working time correction is performed.

[0085] Correct job requirements based on redundant skills, invisible skills and actual working hours.

[0086] It should be noted that the present invention builds a two-way correction system based on customer feedback and personnel feedback. This mechanism can respond to business changes in real time, autonomously trigger the correction mechanism, and then quickly respond to actual business needs, reduce manual intervention, greatly improve the efficiency of expatriate management, and reduce resource waste.

[0087] See also Figure 2 As shown, the second aspect of the present invention provides a labor dispatch data analysis and processing system, including a personnel position matching module, an adaptation situation analysis module, a personnel capability correction module and a position requirement correction module, wherein the personnel position matching module is connected to the adaptation situation analysis module, and the adaptation situation analysis module is respectively connected to the personnel capability correction module and the position requirement correction module.

[0088] The personnel-position matching module is used to generate a personnel-position matching list based on personnel capability tags and position requirement tags, and further select and construct a personnel-position matching group.

[0089] The adaptation situation analysis module is used to generate the actual matching coefficient of each personnel position matching group based on the customer's working time system and attendance system, and determine whether there is an adaptability anomaly. If so, it triggers personnel capability correction and position requirement correction.

[0090] The personnel capability correction module is used to determine whether personnel capability correction is needed based on the customer's working time system and attendance system in combination with customer feedback information, and further identify the personnel capability correction direction when it is identified as necessary.

[0091] The job requirement correction module is used to determine whether job requirement correction is needed based on the customer's working time system and attendance system, combined with personnel feedback information, and further identify the direction of job requirement correction when it is identified as necessary.

[0092] See also Figure 3 As shown, the third aspect of the present invention provides a storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps in the above-mentioned labor dispatch data analysis and processing method.

[0093] The storage medium mentioned here includes random access memory RAM, internal memory, read-only memory ROM, electrically erasable programmable read-only memory EEPROM, register, hard disk, removable disk, or any other form of storage medium known in the technical field.

[0094] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A labor dispatch data analysis and processing method, characterized in that: include: Generate a personnel-position matching list based on personnel capability tags and position requirement tags, and select and build a personnel-position matching group; Generate the actual matching coefficient of each personnel position matching group based on the customer's working time system and attendance system, and determine whether there is any adaptability anomaly. If so, trigger personnel capability correction and position requirement correction; Based on the customer's working time system and attendance system, combined with customer feedback information, determine whether personnel capacity correction is needed, and identify the personnel capacity correction direction when it is necessary; Based on the customer's working time system and attendance system, combined with personnel feedback information, determine whether job demand correction is needed, and identify the direction of job demand correction when it is needed.

2. The labor dispatch data analysis and processing method according to claim 1, characterized in that: The specific analysis method for generating the personnel-position matching list is as follows: Extract the job requirement tags corresponding to each position and the personnel capability tags corresponding to each person, and match the personnel capability tags with the job requirement tags; The personnel whose capability tags completely match the job requirement tags are considered as the preliminary matching personnel for the corresponding positions, and then the preliminary matching personnel list corresponding to each position is obtained by statistics; The correspondence between the personnel and positions in the preliminary matching personnel list corresponding to each position is arranged to obtain a personnel-position matching list, where one position in the personnel-position matching list may include one or more preliminary matching personnel.

3. The labor dispatch data analysis and processing method according to claim 2, characterized in that: The specific analysis method for selecting and constructing the personnel position matching group is as follows: Randomly select any preliminary matching person from the person-position matching list as the matching person for any position, and then repeat the matching operation until all matching operations are completed to generate a matching plan; Randomly select any other preliminary matched personnel as the matching personnel for any other positions, and then repeat the matching operation until all matches are completed, generating several matching solutions; Count the number of successfully matched positions corresponding to each matching solution, compare the number of successfully matched positions corresponding to each matching solution, and select the matching solution with the largest number of successfully matched positions as the final matching solution; Each person in the final matching plan is matched with a position one by one to generate a person-position matching group, in which each person and a position are matched with each other one by one.

4. The labor dispatch data analysis and processing method according to claim 1, wherein: The specific analysis method of the actual matching coefficient is as follows: Based on the customer's working time system, we obtain the personnel task completion rate, effective working time ratio and output quality score ratio, and then calculate the average to obtain the efficiency coefficient; Based on the attendance system, the normal attendance rate and working hours consistency are obtained, and then the mean is calculated to obtain the stability coefficient; The efficiency coefficient and the stability coefficient are averaged to obtain the actual matching coefficient of each personnel position matching group; The specific method for determining whether there is an adaptability anomaly is as follows: The actual matching coefficient of each personnel position matching group is compared with the preset actual matching coefficient threshold. If the actual matching coefficient of a personnel position matching group is greater than or equal to the actual matching coefficient threshold, it is determined that there is no adaptability anomaly in the personnel position matching group. Otherwise, it is determined that there is an adaptability anomaly in the personnel position matching group.

5. The labor dispatch data analysis and processing method according to claim 1, wherein: The specific method for determining whether personnel capability correction is required is as follows: Taking the current moment as the benchmark, the system divides the historical monitoring periods into several periods based on the preset monitoring duration. The system obtains the efficiency coefficient of each historical monitoring period based on the customer's working hours and compares it with the preset efficiency coefficient threshold. Obtain the personnel capability label scores of each person's corresponding position from the customer, and then compare them with the preset personnel capability label score thresholds; Obtain the stability coefficient of each historical monitoring period based on the attendance system and compare it with the preset stability coefficient threshold; Based on the above comparison results, the following criteria for determining the need for personnel capability correction are used for determination: The efficiency coefficient of two consecutive historical monitoring periods is less than the preset efficiency coefficient threshold; Any personnel capability label score is lower than the preset personnel capability label score threshold; The stability coefficient of two consecutive historical monitoring periods is less than the preset stability coefficient threshold; If any of the above criteria exist, it is determined that personnel capability correction is required.

6. The labor dispatch data analysis and processing method according to claim 5, characterized in that: The specific analysis method for identifying the correction direction of personnel capabilities is as follows: Pre-identification of personnel capability correction pointing labels is performed based on the comparison of effectiveness coefficients, personnel capability label scores, and stability coefficients; The pre-identification results are sent to the corresponding personnel for confirmation. If the personnel agrees, the personnel capability label correction is initiated. If the personnel disagrees, a third-party review is initiated, and the personnel capability correction is performed based on the third-party review results.

7. The labor dispatch data analysis and processing method according to claim 1, characterized in that: The specific method for determining whether job requirement correction is required is as follows: Extract the competency label scores of different personnel corresponding to the same position, and then compare them with the preset competency label score thresholds; Obtaining working hour consistency based on the attendance system, and comparing the working hour consistency with a preset working hour consistency threshold; Based on employee feedback on each position, we obtain the actual number of skills required for each position, and then conduct skill overlap analysis with the corresponding position requirement tags to identify whether there are any non-overlapping skills. Based on the above comparison results, refer to the following job demand correction demand determination criteria for judgment: Two people have the same personnel capability label score, but their score is lower than the preset personnel capability label score threshold; The working hours consistency is less than the preset working hours consistency threshold; There are any non-overlapping skills; If any of the above criteria exist, it is determined that job requirements need to be adjusted.

8. The labor dispatch data analysis and processing method according to claim 7, characterized in that: The specific method of identifying the job demand correction direction is as follows: Calculate the ratio of the actual usage time of each skill to the total working hours, and then compare it with the preset threshold. If the calculated result is less than the preset threshold, the skill is determined to be redundant. Treat any non-overlapping skill as an invisible skill; If the working time consistency is less than the preset working time consistency threshold, the actual working time correction is performed; Correct job requirements based on redundant skills, invisible skills and actual working hours.

9. A labor dispatch data analysis and processing system, characterized in that: include: The personnel-position matching module generates a personnel-position matching list based on personnel capability tags and position requirement tags, and selects and builds personnel-position matching groups; The adaptation analysis module generates the actual matching coefficient of each personnel position matching group based on the customer's working time system and attendance system, and determines whether there are any adaptation anomalies. If so, it triggers personnel capability correction and position requirement correction; The personnel capability correction module determines whether personnel capability correction is needed based on the customer's working time system and attendance system, combined with customer feedback information, and identifies the personnel capability correction direction when it is needed; The job requirement correction module is based on the customer's working time system and attendance system, combined with personnel feedback information to determine whether job requirement correction is needed, and identify the direction of job requirement correction when it is needed.

10. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the labor dispatch data analysis and processing method as described in any one of claims 1-8.

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