29 results about "Staffing" patented technology

A system is provided.SOLUTION: A generative AI model means for analyzing the optimal matching between the crew and the shops by using the integrated database, a means for generating an optimal manpower allocation scheme based on the analysis result, a means for notifying the staff of the manpower allocation scheme based on the characteristics of the crew and the characteristics of the shops, and a means for collecting feedback information on the manpower allocation scheme; Means for updating the generative AI model to reflect the collected feedback in a next placement proposal.SELECTED DRAWING: Figure 1

The invention provides a post recommendation method and device, a storage medium and a product, and relates to the technical field of software, and the method comprises the steps: receiving a post recommendation request message sent by a client; acquiring employee data of the to-be-recommended employees from a database based on the employee identifiers; determining an adaptation index of at least one candidate post based on the employee data and the post demand data; generating matching scores of the candidate posts based on the adaptation indexes of the candidate posts; determining a target post from the at least one candidate post based on the matching score of each candidate post; and sending a post recommendation response message to the client. According to the method, on the premise of not additionally increasing the data acquisition cost and being compatible with the existing human resource system architecture of the enterprise, efficient adaptive recommendation of flexible employment posts and employees in the enterprise is realized, and the recommendation accuracy and employment configuration efficiency are remarkably improved.

A method for incentivizing contact center agents with scheduling perks that includes: receiving a workload forecast and staffing plan for a current shift; receiving a service level target; receiving types of scheduling perks; performing a selection routine for determining a select scheduling perk for offering to a select agent; and sending a scheduling perk offer via electronic communication to the select agent. The selection routine may include: selecting a proposed scheduling perks and a proposed agent; modifying the staffing plan to create a proposed staffing plan that reflects the proposed scheduling perk; predicting a proposed forecasted target adherence using the modified staffing plan; determining whether the proposed forecasted target adherence satisfies a threshold defined by an acceptable forecasted target adherence and, if so, deeming the proposed scheduling perk as select scheduling perk and proposed agent as select agent.

A system is provided.SOLUTION: A system comprising: means for collecting information on skills and career vision of employees; database means for storing and analyzing the information; generation and AI means for proposing optimum staffing based on the analyzed result; means for periodically performing condition check of employees and analyzing the result; and means for providing feedback based on the result of the condition check.SELECTED DRAWING: Figure 1

We provide the system. [Solution] A data analysis means for collecting and preprocessing surveys, emails, chats, and meeting records, A personality trait evaluation means that uses a generative AI model to perform a process that objectively evaluates the user's personality traits and skills, A personnel placement recommendation tool that calculates the optimal team structure and staffing based on evaluation results and creates a specific placement plan, A feedback analysis tool that analyzes user-provided feedback to evaluate actual performance and team harmony, A database update mechanism that updates personality profiles and skill maps based on feedback and newly collected data, A system that includes this.

The system according to the embodiment aims to automate the process of evaluating the validity of estimates and enable flexible staffing. [Solution] A system according to an embodiment includes a reception unit, a collection unit, an evaluation unit, and a provision unit. The reception unit receives input of quotation data. The collection unit analyzes the quotation data received by the reception unit and collects data on similar past cases or market prices. The evaluation unit evaluates the validity of the quotation based on the data collected by the collection unit. The provision unit provides the evaluation results obtained by the evaluation unit.

A system and method of automated case costing for surgical procedures can include the operations of tracking a real time location of a plurality of staff within a surgery center using wearable tracking devices that monitor the real time location of staff members among the plurality of staff within the surgery center to provide tracked time information, and allocating staffing costs based on actual time spent in an operating room and in other areas of the surgery center including one or more among a waiting room, a Pre-Op area, a recovery area, and a post-recovery area using one or more processors. Such a system can use and integrate with human resources clocking and surgery scheduling software modules.

The system according to the embodiment aims to predict future demand and propose appropriate staffing arrangements. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, a prediction unit, and a proposal unit. The collection unit collects past event data and shift data. The analysis unit analyzes the data collected by the collection unit. The prediction unit predicts future demand based on the analysis results obtained by the analysis unit. The proposal unit proposes staffing arrangements based on the demand predicted by the prediction unit.

A system and methods for optimizing labor scheduling in retail environments by incorporating shrink factors alongside traditional considerations are provided. A machine learning model (MLM) receives traffic data, hourly labor data, overall shrink data, and proven shrink incidents as inputs. The MLM learns the labor-shrink causality across stores, connecting staffing levels to shrink impact. The MLM outputs a recommended labor scheduling plan for both assisted and self-checkout lanes, optimized for overall store margins rather than just labor costs. This approach balances labor efficiency with shrink prevention, potentially improving store profitability. In an embodiment, an application programming interface (API) is provided for consuming recommendations from the MLM as a service to integrate insights into business intelligence dashboards, providing a comprehensive solution for retail labor management.

This invention provides a method and system for evaluating organizational structure and staffing based on a large language model. The method includes: collecting industry standard data and evaluation reference data related to organizational structure and staffing; constructing scoring rules for multiple preset dimensions based on the industry standard data and evaluation reference data; obtaining a level judgment threshold for each preset dimension; constructing an evaluation standard knowledge base based on the scoring rules and the level judgment thresholds; collecting data from multiple set data sources to obtain multi-source data of the target organization; using a large language model to perform semantic extraction on the multi-source data to obtain the organizational entities within the target organization and the relationships between them, as well as the operational feedback data of the target organization; and using the evaluation standard database to evaluate the operational feedback data to obtain the evaluation result of the organizational structure and staffing system of the target organization. The technical solution of this invention can improve the accuracy and efficiency of organizational structure and staffing evaluation.

The application discloses a personnel configuration information security storage method and system based on a blockchain, relates to the technical field of blockchain storage, and comprises the following steps: constructing a personnel configuration graph, using an encrypted public key of an employee, and storing the personnel configuration graph into a personnel configuration blockchain; dividing the employee into K employee clustering clusters; setting a minimum data access permission set for each employee clustering cluster according to a historical access data subset of the employee contained in the employee clustering cluster; searching for an employee clustering cluster in which an inquiring employee is located as a target clustering cluster; receiving a knowledge graph query statement input by the inquiring employee; obtaining corresponding query data from the personnel configuration blockchain; and using a decryption private key corresponding to the inquiring employee to decrypt the query data.

The application discloses a kind of medical skill examination intelligent reservation and resource scheduling system based on rule engine, it is related to medical information technology field, including data acquisition module, rule engine module, intelligent reservation module, the dynamic analysis and matching of medical business rules are realized by introducing rule engine module, and resource scheduling strategy and reservation priority sequence are generated;Intelligent reservation module provides personalized recommendation using reservation priority sequence and rehearses detection conflict, realizes zero conflict reservation;Resource scheduling module optimizes equipment, clinic and personnel configuration according to strategy in real time, improves resource utilization;Process control module carries out closed loop tracking and synchronization to reservation and scheduling result.Each module cooperates and operates, it is jointly relieved that traditional medical skill examination is uneven, reservation process rigid, multiple system coordination difficult and the problem that rule adaptation is not flexible, finally reach shorten patient waiting time, reduce hospital operation cost, improve the effect of overall efficiency and intelligent level of medical service.

An object of a system according to an embodiment is to appropriately grasp desires and needs of employees and propose an optimal career plan and an appropriate arrangement of materials.SOLUTION: A system includes a collection unit, an analysis unit, an evaluation unit, and a proposal unit. The collection unit collects requests and needs of employees. The analysis unit analyzes the information collected by the collection unit and proposes a career plan. The evaluation part analyzes the resume of the applicant and evaluates the aptitude and skill. The proposal unit proposes an appropriate material arrangement based on the information obtained by the evaluation unit.SELECTED DRAWING: Figure 1

The invention discloses a staff and quota optimization system and method based on power grid enterprise operation performance analysis, and belongs to the technical field of power enterprise management. Comprising a data acquisition module used for acquiring instantaneous state data of each factor; the index calculation module is used for calculating a real-time business fluctuation index; the mode judgment module is used for dynamically judging whether a current operation mode should be in a standard operation mode or an elastic regulation and control mode according to a comparison result; the interval calculation module is used for calculating and outputting an elastic fixed personnel interval; and the parameter correction module is used for carrying out posteriori correction on weight parameters of various impact factors for calculating the real-time business fluctuation index. By constructing the multi-source business fluctuation factor set, calculating the real-time business fluctuation index and outputting the elastic fixed-staff interval, the effect of accurate matching of human resource configuration and dynamic business requirements is achieved, and the problem of insufficient business fluctuation adaptability caused by a static prediction model in the prior art is solved.

A system is provided.SOLUTION: This system is provided with a means for acquiring the ability and desire of an employee by using interactive artificial intelligence, a means for proposing personnel arrangement corresponding to the ability and desire of the employee based on the acquired data, a means for evaluating the effect of the proposed personnel arrangement, and a means for continuously improving the precision of the personnel arrangement based on the evaluated result.SELECTED DRAWING: Figure 1

A method and apparatus for integrating multiple disjunct processes into a cohesive workflow can involve receiving proposal development inputs through a system linked to a back-end processor and user interface, and collecting with the proposal development, data for staffing and cost estimation, customizable per case. The data can be processed by a baseline development component to confirm realistic paths, establish target dates, and maintain cost and schedule metrics within tolerances. The system can update tasks, displays critical paths, and monitor performance metrics while integrating with a portfolio workforce planning component, staffing data across proposal, baseline development, and program execution components. This integration of staffing data can allow for strategic decision making and / or program prioritization.

A method for automatedly determining hours of operation (HOO) is provided. A system for work allocation is also provided. A method for generating staffing forecasts is also provided. The method for automatedly determining hours of operation includes performing historical data analysis on historical data comprising past data for a plurality of skills, queue reports for the plurality of skills, or a combination thereof; identifying trends in skills demand for each of the plurality of skills based on the historical data analysis; performing analysis on forecasted reports for skills allocation to generate future demand patterns for each of the plurality of skills; performing HOO analysis for each of the plurality of skills based on the generated future demand patterns and identified skills demand trends; generating a report of the HOO analysis for the plurality of skills; and providing the analysis report to a user.

A system is provided.SOLUTION: The system includes a means for collecting data on job history, results, strengths / weaknesses, characteristics, desires, and human relationships of employees, a means for preprocessing and analyzing the collected data, a means for learning a generation AI model for predicting appropriateness and allocation of employees based on an analysis result, a means for generating an optimal personnel allocation plan using the learned generation AI model, a means for suggesting appropriate project members, and a means for monitoring an organization result after allocation and improving accuracy of the generation AI model.SELECTED DRAWING: Figure 1

Methods and a system for determining understaffed periods in retail stores leverages self-checkout (SCO) usage patterns and machine learning. The methods and system select stores with medium to high SCO adoption rates, identifies “busy” hours based on SCO and point-of-sale (POS) idle times, and trains a classification machine learning model using various transactional features. This model then predicts understaffed hours for all stores, including those without SCOs. The methods and system provide real-time alerts and reports, enabling retailers to make informed staffing decisions, improve customer satisfaction, and optimize labor costs. By analyzing existing transactional data, the methods and system offer a novel approach to staffing management in modern retail environments.

Apparatuses, systems, and methods described herein include receiving by a quantum hybrid branch simulation engine, a request for a next task by a branch personnel or worker. The branch simulation engine may receive data representing a simulated branch environment and apply a deep reinforcement learning (DRL) staffing operations model to predict a next action or task. The model may weigh impacts of a reward to substantially maximize the reward in light of a policy to determine the next action and update a database to store / represent a next state of the simulated or real-life branch environment after the next action is performed.

We provide a system that enables efficient staffing and high customer satisfaction simultaneously, thereby optimizing store operations. [Solution] A system including means for collecting customer information, means for storing the collected customer information in a database, means for inputting the shift information of store employees, means for analyzing the input shift information and storing it in a database, means for calculating the optimal staffing arrangement based on customer information and shift information, means for displaying the optimized schedule to the user and prompting confirmation and correction, means for proposing measures to improve the quality of customer service based on customer satisfaction, means for displaying the proposed improvement measures and prompting their implementation, and means for calculating brand evaluation points and notifying the achievement target.

The invention relates to the technical field of power supply enterprise human resource management, in particular to a power supply enterprise dynamic accurate personnel fixing method and system based on multi-dimensional data association, and the method comprises the steps: collecting multi-source heterogeneous data, covering six types of data sources, such as equipment, business and work orders, and completing ETL processing; fusing linear / nonlinear correlation, knowledge graph calibration and structure dimension adjustment to generate a dynamic correlation coefficient; based on machine learning, precise working hours are measured and calculated, and measurement and verification of quota and non-quota time are completed; calculating the number of fixed persons in combination with the comprehensive efficiency coefficient; and dynamic iterative optimization is implemented. The system comprises seven modules of data acquisition, processing, correlation modeling, man-hour measurement and calculation, fixed-staff calculation, dynamic optimization and output display. According to the method, equipment-business-personnel full-chain association is realized, the dynamic adaptability is high, the method fits the business reality of a power supply enterprise, and the human resource configuration efficiency is greatly improved.

A method, system, and article of manufacture for modifying a queue assignment for a contact center are provided. At least one computing device determines, by solving for constraints, at least one staffing change for at least one of the first queue or the second queue, using as inputs (a) first time-based service metrics, (b) second time-based service metrics, (c) data describing eligible staffing changes, and (d) at least one predetermined constraint. The at least one staffing change is a modification to the queue assignment of a subset of the computing device instances that is predicted to improve net staffing relating to service targets selected from (a) an average speed of answer (ASA) specifying an average time for one of the computing device instances to initiate handling of a particular task after the particular task has been assigned to the relevant queue and (b) a service level specifying a percentage of tasks for which handling is initiated within a specified time frame after the tasks are assigned to the queue. The at least one staffing change can be implemented by modifying the queue assignment of the subset of the computing device instances.

Disclosed is a platform that manages worker users in a temporary staffing environment via an artificial machine learning model. The temporary staffing platform matches available workers to available shifts / gigs. Additional features include generating provisional or near-miss matches and informing workers how to turn those near-misses into full matches, plotting a gig-career path to develop additional skills, gamify development, and automatically generate resumes. The platform generates a set of skill tags associated with each shift / gig performed by the user. Designing of resume text files by the artificial machine learning model includes procedurally generated descriptions of experience the a user has based on the recording of each shift / gig performed by the user and the skill tags associated with each recorded shift / gig, wherein a format of the resume text file is formulated by the artificial machine learning model evaluating a mix of skill tags and employers amassed by the user.

This invention relates to the field of computer technology and discloses a personnel allocation decision-making method, system, electronic device, and storage medium based on working hour data. The method includes acquiring working hour data, classifying and structuring it, and performing multi-dimensional statistical analysis on the classified working hour data to generate a working hour distribution map; calculating the maximum number of personnel at full capacity based on the total annual working hour demand and the standard working hours available per person per year; acquiring data on the difference between actual working hours and statutory standard working hours, as well as unused leave, and calculating the equivalent personnel shortage based on an overtime compensation model; establishing a resource balance model that includes constraints such as shift work, skill level matching, time period distribution, and management redundancy, calculating the resource balance coefficient, and correcting the maximum number of personnel at full capacity to obtain an executable personnel allocation base; and determining the personnel allocation plan by combining the equivalent personnel shortage, the personnel allocation base, and future working hour demand. This invention can improve the executability of personnel allocation decisions.

A system is provided.SOLUTION: A system comprising: means for providing an interactive interface for inputting employee skills, experiences, and desired positions; means for collecting and analyzing said employee interactions; means for generating and storing employee profile data based on said analysis; means for matching said profile data with enterprise needs and generating optimal staffing plans; means for presenting said generated staffing plans to employees and receiving feedback; and means for re-evaluating and generating re-staffing plans based on said feedback.SELECTED DRAWING: Figure 1

A system is provided.SOLUTION: A system comprising: means for collecting personnel information from each department or organization; means for complementing missing values of the collected personnel information and detecting and correcting abnormal values; means for analyzing characteristics of active personnel using generated AI based on the preprocessed personnel information; means for generating an optimal personnel allocation plan based on the characteristics of the active personnel; and means for informing a user of the generated allocation plan.SELECTED DRAWING: Figure 1

This invention relates to the field of information technology service management technology, and discloses a method, system, and storage medium for processing the allocation of maintenance personnel. The method includes: acquiring work order fulfillment data, workload data, on-call duty requirement data, and automation coverage data of the target maintenance object within a preset statistical period; determining the basic configuration number based on the workload data, and generating a risk adjustment factor based on the work order fulfillment data; determining the additional on-call duty requirement based on the on-call duty requirement data, and determining the automation reduction number based on the automation coverage data, and generating a preliminary staffing number; constraining and calibrating the preliminary staffing number to obtain the target staffing number; and dynamically adjusting the target staffing number based on the correspondence between the risk adjustment factor and a preset risk threshold range, combined with the judgment results of the continuous statistical period. This application improves the accuracy, stability, and executability of the maintenance personnel allocation results.

For example, when generating staffing plans at various locations in industries such as logistics, the system predicts future staffing needs based on past work performance, thereby improving the accuracy of the generated staffing plans. [Solution] The plan generation device 100 comprises a memory 120 and a processor 110. The processor 110 works in cooperation with the memory 120 to acquire daily division information 121 and employee work condition information 122 for the unit period to be planned, and work performance information 123 for the target organization in a predetermined past period which is a longer period than the unit period. Using the daily division information 121 and work performance information 123, the processor determines the average man-hour ratio for each unit period for each daily division in the predetermined past period. Using the employee work condition information 122, the processor determines the total man-hours for the unit period to be planned. For each day of the unit period to be planned, the processor outputs the required man-hour information for each day by multiplying the total man-hours by the average man-hour ratio for each day in the unit period.