Resource recombination method and device, electronic equipment, medium and program product

Abstract

The invention provides a resource recombination method and device, electronic equipment, a medium and a program product, relates to the technical field of information, and can accurately generate a resource recombination strategy. According to the specific technical scheme, the method comprises the steps of obtaining key business indexes of multiple business entities of a target business provider from a business database, and classifying the key business indexes corresponding to each business entity according to a preset business dimension to obtain key business indexes of multiple target business dimensions of each business entity; obtaining score information of the key business indexes of each target business dimension of each business entity, calculating score information corresponding to each target business dimension of the business entity based on the score information, and determining a comprehensive score of the business entity according to the score information; determining complementary service entity pairs capable of executing resource recombination based on the comprehensive score of each service entity; and generating a corresponding resource recombination strategy for each complementary service entity pair so as to execute resource recombination. The method is used for generating resource recombination strategies.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of information technology, and in particular, to a resource reorganization method and device, electronic equipment, medium and program product. BACKGROUND

[0002] Currently, in the enterprise operation and public service scenarios (for example, customer service center, etc.), how to efficiently allocate limited human resources to various business entities (such as service windows, processing centers, branches) is a core problem.

[0003] In related technologies, the existing resource allocation (such as human resource allocation) usually relies on the manual experience of managers or simple statistics based on a single dimension (such as the total amount of business processing), lacking intelligent and data-driven decision support. As a result, the accuracy of resource allocation is poor. SUMMARY

[0004] Embodiments of the present application provide a resource reorganization method and device, electronic equipment, medium and program product, which can improve the accuracy of resource allocation.

[0005] In a first aspect, a resource reorganization method is provided. The method includes: obtaining, from a business database, a plurality of key business indicators of a plurality of business entities of a target business provider, and classifying the plurality of key business indicators corresponding to each business entity according to a plurality of preset business dimensions to obtain key business indicators of each target business dimension of each business entity; for each business entity, obtaining score information of each key business indicator of each target business dimension of the business entity, calculating score information corresponding to each target business dimension of the business entity based on the score information of each key business indicator of each target business dimension, and determining a comprehensive score corresponding to the business entity according to the score information; based on the comprehensive score corresponding to each business entity in the plurality of business entities, determining at least one pair of complementary business entities that can perform resource reorganization from the plurality of business entities; generating a corresponding resource reorganization strategy for each pair of complementary business entities that can perform resource reorganization, and the resource reorganization strategy is used to perform resource reorganization on the complementary business pair.

[0006] The resource reorganization method provided in the embodiments of the present application first extracts key business indicators of each business entity from a business database, and classifies and integrates according to preset business dimensions; then, by obtaining indicator score information and through weighted calculation, dimension scores and comprehensive scores of business entities are obtained; finally, based on the comprehensive score ranking, a complementary business entity pair is identified by using a pairing rule, and a corresponding resource reorganization strategy is executed. In this way, by establishing a standardized indicator collection, score calculation and comprehensive evaluation process, the resource allocation process originally relying on manual experience analysis is converted into an automatic data processing process, so that data collection, score calculation and resource reorganization decision of multiple business entities can be quickly completed. On the one hand, a large amount of manual data arrangement and analysis work in the traditional way is avoided, so that the efficiency of resource reorganization decision is significantly improved. On the other hand, by constructing a multi-level indicator system (i.e., key business indicators, business dimensions and comprehensive scores), comprehensive and comprehensive evaluation of business entities is realized, the one-sidedness of single indicator evaluation is avoided, the final comprehensive score can more accurately reflect the real performance of the business entity, so that the resource reorganization strategy can be accurately generated, and the accuracy of resource allocation is improved.

[0007] In a possible implementation form of the first aspect, based on the score information of each key business indicator of each target business dimension, score information corresponding to each target business dimension of the business entity is calculated, including: based on the weight corresponding to each key business indicator under each target business dimension, the score information of each key business indicator under each target business dimension is weighted and summed to obtain the score information corresponding to each target business dimension.

[0008] In the embodiments of the present application, by introducing the weight coefficient, the finally calculated dimension score can more accurately reflect the real ability of the business entity in the dimension, avoiding the evaluation distortion that may be caused by simple average, and providing more reliable and more refined data basis for subsequent resource reorganization.

[0009] In another possible implementation form of the first aspect, according to the score information, the comprehensive score corresponding to the business entity is determined, including: based on the weight corresponding to each target business dimension, the score information corresponding to the multiple target business dimensions is weighted and summed to obtain the comprehensive score of the business entity.

[0010] In the embodiments of the present application, by assigning weights to different business dimensions and performing weighted summation, the limitation of regarding the performances of the dimensions as the same is avoided, so that the final comprehensive score can reflect the business dimension that is focused on, so that the subsequent resource reorganization decision is more flexible and meets the actual needs.

[0011] In another possible implementation of the first aspect, based on the comprehensive score corresponding to each of the multiple business entities, at least one pair of complementary business entities for executable resource reorganization is determined from the multiple business entities, including: sorting the multiple business entities from high to low according to their comprehensive scores; dividing the sorted multiple business entities into a first entity queue and a second entity queue of equal number; wherein the first entity queue contains the top half of the ranked business entities, and the second entity queue contains the bottom half of the ranked business entities; determining the business entity ranked i-th in the first entity queue and the business entity ranked i-th from the bottom in the second entity queue as a pair of complementary business entities; wherein i is an integer greater than 1, and i is less than or equal to the sum of the number of business entities in the first entity queue and the number of business entities in the second entity queue.

[0012] In this embodiment, by first sorting and equally dividing all entities, and then performing systematic cross-pairing, it is ensured that a high-performing entity and an entity to be improved can form a complementary pair, thereby greatly increasing the accuracy of the subsequent resource reorganization strategy.

[0013] In another possible implementation of the first aspect, before determining at least one pair of complementary business entities from multiple business entities that can perform resource reorganization, the method further includes: establishing a resource attribute profile for each business entity to obtain a resource attribute profile corresponding to each business entity, wherein the resource attribute profile includes the skill structure of the human resources of the corresponding business entity, and the type and quantity of equipment resources; determining the business entity ranked i-th in the first entity queue and the business entity ranked i-th from the bottom in the second entity queue as a pair of complementary business entities, including: verifying whether the resource attributes of the business entity ranked i-th in the first entity queue and the business entity ranked i-th from the bottom in the second entity queue match based on their respective resource attribute profiles; when the resource attribute matching degree exceeds a preset threshold, determining the business entity ranked i-th in the first entity queue and the business entity ranked i-th from the bottom in the second entity queue as a pair of complementary business entities.

[0014] In this embodiment of the application, by introducing resource attribute profiling and its matching verification mechanism, resource matching degree verification is added before reorganization, ensuring that the identified complementary entity pairs have an operable resource base in reality, fundamentally improving the feasibility and success rate of the generated resource reorganization strategy, and reducing the waste of implementation costs caused by resource mismatch.

[0015] In another possible implementation of the first aspect, a corresponding resource reorganization strategy is generated for each pair of complementary business entities that can perform resource reorganization, including: for each pair of complementary business entities, determining the first business entity located in the first entity queue and the second business entity located in the second entity queue; based on the score information corresponding to each target business dimension of the first business entity, determining its advantageous business dimension, and allocating the resources corresponding to the advantageous business dimension of the first business entity to the corresponding business domain of the second business entity; based on the score information corresponding to each target business dimension of the second business entity, determining its advantageous business dimension, and configuring the resources corresponding to the advantageous business dimension of the second business entity as shared resources with the first business entity.

[0016] In this embodiment of the application, by accurately identifying the strongest aspects and available resources of each business entity based on specific dimensional score information, the rationality and accuracy of the reorganization strategy are ensured, thereby improving the accuracy of subsequent resource reorganization and reducing the blindness and waste of resource allocation.

[0017] In another possible implementation of the first aspect, after generating a corresponding resource reorganization strategy for each pair of complementary business entities that can perform resource reorganization, the method further includes: after a preset time period following the execution of resource reorganization, retrieving new key business indicators for multiple business entities from the business database within the preset time period; calculating and generating new comprehensive scores for multiple business entities based on the new key business indicators; comparing the new comprehensive scores with the comprehensive scores before resource reorganization; if the increase in the new comprehensive scores of business entities in the second entity queue exceeds a preset threshold, and the new comprehensive scores of business entities in the first entity queue do not decrease, then the resource reorganization strategy is deemed effective, and the resource reorganization strategy is adaptively adjusted based on the new comprehensive scores of all complementary business entity pairs.

[0018] In this embodiment of the application, by introducing a closed loop of "execution-evaluation-adjustment", resource reorganization is upgraded into a continuously operating, self-optimizing intelligent management system. By verifying the effectiveness of its strategies and continuously adjusting and optimizing subsequent actions based on the results, resource allocation can dynamically adapt to changes in the internal and external environment, thereby achieving automation and intelligence in the management process.

[0019] In another possible implementation of the first aspect, for each business entity, the scoring information of each key business indicator for each target business dimension of the business entity is obtained, including: for each business entity, obtaining the quantitative information of each key business indicator under multiple target business dimensions from the associated business system through a data interface, and converting it into the first scoring information of each key business indicator through a scoring model; receiving the second scoring information input by the user for each key business indicator through a user operation interface; for each key business indicator, calculating the weighted average of the corresponding first scoring information and second scoring information, and using the weighted average as the scoring information of the corresponding key business indicator.

[0020] In this embodiment of the application, by integrating objective data (first scoring information) from the business system and scoring data judged by humans (second scoring information), it is possible to effectively combine objective data and subjective data to score business indicators. This hybrid evaluation mechanism avoids the context and subtle differences that exist in single objective data, and also prevents the inconsistency caused by relying entirely on subjective judgment. As a result, the final scoring information is more comprehensive and balanced, effectively improving the accuracy and reliability of the final output scoring information, and providing higher quality input for subsequent resource reorganization decisions.

[0021] In another possible implementation of the first aspect, the multiple preset business dimensions include at least two of the following dimensions: business processing efficiency dimension, service quality dimension, resource utilization dimension, and risk control dimension.

[0022] In this embodiment of the application, by dividing key business indicators into multiple dimensions such as business processing efficiency, service quality, resource utilization, and risk control, a structured, multi-perspective evaluation indicator system is constructed for each business entity, thereby enabling accurate evaluation of the comprehensive score of the business entity.

[0023] Secondly, a resource reorganization apparatus is provided, comprising: an acquisition module, a processing module, and a generation module, wherein: the acquisition module is used to acquire multiple key business indicators of multiple business entities of a target business provider from a business database; the processing module is used to classify the multiple key business indicators corresponding to each business entity acquired by the acquisition module according to multiple preset business dimensions to obtain key business indicators of multiple target business dimensions for each business entity; the processing module is also used to acquire, for each business entity, the scoring information of each key business indicator of each target business dimension of the business entity, calculate the score information corresponding to each target business dimension of the business entity based on the scoring information of each key business indicator of each target business dimension, and determine the comprehensive score corresponding to the business entity based on the score information; the processing module is also used to determine at least one pair of complementary business entities that can be reorganized by resource reorganization from the multiple business entities based on the comprehensive score corresponding to each business entity; and the generation module is used to generate a corresponding resource reorganization strategy for each pair of complementary business entities that can be reorganized by resource reorganization, the resource reorganization strategy being used to perform resource reorganization on the complementary business pair.

[0024] Thirdly, an electronic device is provided, the method comprising: a memory and at least one processor. The memory is communicatively connected to the processor. The memory is used to store computer program code, the computer program code including computer instructions. When the processor executes the computer instructions, it causes the electronic device to perform the method as described in the first aspect and any possible implementation thereof.

[0025] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions. When executed by a processor, these computer instructions are used to implement the method described in the first aspect and any possible implementation thereof.

[0026] Fifthly, embodiments of this application provide a computer program product that, when run on a computer or executed by a computer's processor, implements the method described in the first aspect and any possible design thereof. The computer may be the electronic device described in the third aspect and any possible implementation thereof.

[0027] It is understood that the beneficial effects achieved by the resource reorganization device described in the second aspect, the electronic device described in the third aspect, the computer-readable storage medium described in the fourth aspect, and the computer program product described in the fifth aspect can be referred to as the beneficial effects in the first aspect and any possible implementation thereof, which will not be repeated here. Attached Figure Description

[0028] Figure 1A flowchart illustrating a resource reorganization method provided in an embodiment of this application; Figure 2 A flowchart illustrating another resource reorganization method provided in this application embodiment; Figure 3 A flowchart illustrating another resource reorganization method provided in this application embodiment; Figure 4 A flowchart illustrating another resource reorganization method provided in this application embodiment; Figure 5 A flowchart illustrating another resource reorganization method provided in this application embodiment; Figure 6 This is a schematic diagram of the structure of a resource reorganization device provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0029] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this embodiment, unless otherwise stated, "a plurality of" means two or more.

[0030] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0031] The technical solutions provided in this application, including the collection, storage, use, processing, transmission, provision, and disclosure of financial data or user data, comply with relevant laws and regulations and do not violate public order and good morals.

[0032] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0033] The resource reorganization method provided in this application can be applied to scenarios of performance optimization and resource allocation in public services or internal business units of an enterprise.

[0034] In this scenario, there are typically multiple business units providing the same or similar services (e.g., different service windows in government services, different branch outlets in a bank, or different branches in a chain enterprise). These business units often have uneven distribution of human resources, professional skills, and equipment resources, leading to room for improvement in overall service efficiency, quality, and resource utilization. The core requirement for managers is to systematically identify the strengths and weaknesses of each business unit and, based on this, to conduct scientific and efficient resource reorganization to maximize overall effectiveness.

[0035] In related technologies, the evaluation of business units often relies on managers' personal experience or single-dimensional performance data (such as total business volume). This approach offers a one-sided perspective and fails to comprehensively and holistically reflect the business unit's overall capabilities across multiple dimensions (such as efficiency, quality, cost, and customer satisfaction). Furthermore, resource allocation is often based on fragmented and subjective judgments, lacking data-driven decision-making models and failing to systematically identify the complementary potential between business units, resulting in poor resource allocation effectiveness.

[0036] The business resource reorganization method provided in this application constructs an automated and structured evaluation system of "key business indicators → business dimension classification → dimension score → comprehensive score", and intelligently identifies business unit pairs with complementary potential based on the comprehensive score, generates and executes specific resource reorganization strategies, thereby realizing the transformation from experience-based decision-making to data-driven decision-making, and can quickly and accurately complete the cross-business unit resource optimization and allocation.

[0037] It should be noted that the resource reorganization method provided in this application embodiment can also be applied to multiple scenarios such as team resource integration in project management, allocation of teachers and teaching resources in educational institutions, and sharing of human resources between departments in medical institutions. It is applicable to any field that requires performance evaluation of multiple independent units and resource optimization based on the evaluation results. This application embodiment does not limit this.

[0038] The resource reorganization method provided in this application embodiment can be applied to a resource reorganization device, which can be an electronic device or a module in an electronic device for executing the resource reorganization method.

[0039] Figure 1 This is a flowchart illustrating a resource reorganization method provided in an embodiment of this application, as shown below. Figure 1 As shown, the resource reorganization method may include the following steps 201 to 204: Step 201: The resource reorganization device obtains multiple key business indicators of multiple business entities of the target business provider from the business database, and classifies the multiple key business indicators corresponding to each business entity according to multiple preset business dimensions to obtain multiple key business indicators of target business dimensions for each business entity.

[0040] In some embodiments of this application, the resource reorganization device connects to a business database via a data interface. This business database stores historical operational data of multiple business entities under the target business provider. Then, based on preset indicator extraction rules, key business indicators for evaluating the performance of the business entities are selected from the historical operational data.

[0041] In some embodiments of this application, the aforementioned key business indicators include, but are not limited to: average daily business processing volume, average processing time, customer satisfaction score, resource utilization rate, and business error rate.

[0042] In this application embodiment, the above-mentioned multiple preset business dimensions include at least two of the following dimensions: business processing efficiency dimension, service quality dimension, resource utilization dimension, and risk internal control dimension.

[0043] For example, the resource restructuring device categorizes the extracted key business indicators according to multiple preset business dimensions. These preset business dimensions are predefined classification frameworks used to evaluate the comprehensive capabilities of business entities from different perspectives, and may include, for example, operational efficiency, service quality, resource utilization, and risk control dimensions.

[0044] In this embodiment of the application, by dividing key business indicators into multiple dimensions such as business processing efficiency, service quality, resource utilization, and risk control, a structured, multi-perspective evaluation indicator system is constructed for each business entity, thereby enabling accurate evaluation of the comprehensive score of the business entity.

[0045] For example, in a municipal service system, there are multiple street-level government service centers as business entities. The server extracts key business indicators for each center from the municipal business database for the past quarter, including "average daily number of cases handled at the window," "average processing time for each item," "public satisfaction rate," "self-service terminal usage rate," and "number of errors in business processing." Subsequently, the server categorizes these indicators: "average daily number of cases handled at the window" and "average processing time for each item" are categorized into "operational efficiency dimension"; "public satisfaction rate" is categorized into "service quality dimension"; "self-service terminal usage rate" is categorized into "resource utilization dimension"; and "number of errors in business processing" is categorized into "risk control dimension."

[0046] Step 202: For each business entity, the resource reorganization device obtains the scoring information of each key business indicator for each target business dimension of the business entity, calculates the score information corresponding to each target business dimension of the business entity based on the scoring information, and determines the comprehensive score corresponding to the business entity based on the score information.

[0047] In some embodiments of this application, the resource reorganization device generates scoring information for key business indicators under each business dimension for each business entity. For example, for directly quantifiable indicators (such as processing time), the server converts the raw data into standard scores using a preset standardization function (such as Min-Max normalization or Z-score normalization); for indicators requiring subjective judgment (such as service standardization), the resource reorganization device receives manually input scoring values ​​through an administrator's interface.

[0048] In some embodiments of this application, the resource reorganization device aggregates and calculates the scoring information of all key business indicators under each business dimension to obtain the score information for that business dimension. In some examples, this aggregation calculation adopts a weighted summation method, and the weights can be predefined based on the importance of each indicator to that dimension.

[0049] In some embodiments of this application, the resource reorganization apparatus calculates a comprehensive score for the business entity based on its scores across all business dimensions. Exemplarily, this comprehensive score can be a simple arithmetic mean of the scores for each dimension, or a weighted average that considers the importance of different dimensions.

[0050] For example, when calculating the "operational efficiency" score for a street-level government service center, the server performs a weighted sum of the standardized scores for "average daily number of cases handled at the window" (weight 0.6) and "average processing time for items" (weight 0.4), resulting in a score of 85 for this dimension. Similarly, after calculating the scores for other dimensions, the scores for the four dimensions are averaged (or weighted averaged) to obtain a comprehensive score of 82 for the center.

[0051] Step 203: Based on the comprehensive score corresponding to each business entity among the multiple business entities, the resource reorganization device determines at least one pair of complementary business entities from the multiple business entities that can perform resource reorganization.

[0052] In some embodiments of this application, after obtaining the overall score of all business entities, the resource reorganization apparatus executes a pairing algorithm to identify business entity pairs that have complementary potential in terms of resources.

[0053] It should be noted that the core idea of ​​this algorithm is to systematically pair business entities with higher overall scores with business entities with lower overall scores.

[0054] In some possible implementations, the resource reorganization device sorts all business entities from highest to lowest based on their overall score, and then divides the sorted list in half into high-level and low-level groups. Subsequently, the i-th business entity in the high-level group is paired with the i-th-last business entity in the low-level group, thus forming multiple complementary business entity pairs. This method ensures the structured and comprehensive coverage of the pairings.

[0055] For example, suppose there are 8 government service centers. After ranking them by their comprehensive scores, the top 4 are in the high-scoring group and the bottom 4 are in the low-scoring group. The server pairs the 1st and 8th ranked centers as the first complementary pair, the 2nd and 7th ranked centers as the second complementary pair, and so on.

[0056] Step 204: The resource reorganization device generates a corresponding resource reorganization strategy for each pair of complementary business entities that can be reorganized. The resource reorganization strategy is used to perform resource reorganization on the complementary business pairs.

[0057] In some embodiments of this application, the resource reorganization device generates a customized resource reorganization strategy for each identified pair of complementary business entities, based on the specific performance (i.e., dimension scores) of the two business entities in each business dimension.

[0058] It should be noted that this resource restructuring strategy aims to promote the flow of high-quality resources from advantageous business entities to disadvantaged business entities in order to achieve reasonable resource restructuring.

[0059] In some embodiments of this application, the content of the resource reorganization strategy may include, but is not limited to: short-term personnel exchanges or job rotations, organization of skills training and experience sharing sessions, temporary allocation of specific equipment or technical resources, and promotion of standardized work processes or best practices. For example, the resource reorganization device can use a strategy generation engine to concretize and execute the strategy content, and output it through a management interface or send it to an administrator for confirmation and execution.

[0060] For example, for a successfully paired "Center A" (high-performing group with significant advantages in operational efficiency) and "Center B" (low-performing group with weaknesses in operational efficiency), the generated resource reorganization strategy could include: "Arranging for key business personnel from Center A to undergo two weeks of on-site work guidance at Center B, and organizing employees from Center B to participate in on-the-job training at Center A. Simultaneously, sharing the advanced scheduling tables used by Center A with Center B for trial use."

[0061] The following example illustrates the business resource reorganization method provided in this embodiment through the scenario of optimizing the operation of regional chain retail stores.

[0062] The resource reorganization device retrieves sales, inventory, and personnel data from each store in the database, extracting key business indicators such as "sales area," "average transaction value," "inventory turnover rate," "average sales per employee," and "customer complaint rate." These indicators are then categorized according to pre-defined dimensions: "sales efficiency," "inventory management," and "customer service." The server standardizes and scores each store's indicators, calculating scores for each dimension. For example, when calculating the "sales efficiency" score, the scores for "sales area" and "average transaction value" are weighted. Finally, all dimension scores are aggregated to obtain a comprehensive performance score for each store. The resource reorganization device sorts and groups all stores based on their comprehensive scores, cross-pairing the top 50% of stores with the bottom 50%, identifying complementary pairs such as "Store A (strong sales ability) — Store B (weak sales ability but excellent inventory management)." Finally, after analyzing the specific dimensions and scores of the "Store A - Store B" pair, a resource reorganization strategy was generated: "It is recommended to transfer the senior salesperson of Store A to Store B; at the same time, transfer the senior warehouse management personnel of Store B to Store A."

[0063] The resource reorganization method provided in this application first extracts key business indicators of each business entity from the business database and classifies and integrates them according to preset business dimensions. Next, it obtains indicator scoring information and calculates dimension scores and comprehensive business entity scores through weighted calculations. Finally, based on the comprehensive score ranking, it identifies complementary business entity pairs using pairing rules and executes corresponding resource reorganization strategies. Thus, by establishing a standardized process for indicator collection, scoring calculation, and comprehensive evaluation, the resource allocation process, which originally relied on manual experience analysis, is transformed into an automated data processing process. This enables rapid completion of data collection, scoring calculation, and resource reorganization decisions for multiple business entities. On the one hand, it avoids a large amount of manual data processing and analysis work in traditional methods, significantly improving the efficiency of resource reorganization decisions. On the other hand, by constructing a multi-level indicator system (i.e., key business indicators, business dimensions, and comprehensive scores), it achieves a comprehensive evaluation of business entities, avoiding the one-sidedness of single indicator evaluation. This allows the final comprehensive score to more accurately reflect the true performance of the business entities, providing a reliable decision-making basis for resource reorganization and improving the accuracy of resource allocation.

[0064] In some embodiments of this application, the process of calculating the score information corresponding to each target business dimension of the business entity based on the scoring information of each key business indicator under each target business dimension in step 202 above may include the following step 202a: Step 202a: The resource reorganization device performs a weighted summation of the scoring information of each key business indicator under each target business dimension based on the weights corresponding to each key business indicator under each target business dimension, and obtains the score information corresponding to each target business dimension.

[0065] In some embodiments of this application, the resource reorganization device employs a weighted summation algorithm to aggregate the scoring information of multiple key business indicators under the same business dimension when performing dimensional score calculation. Specifically, the resource reorganization device pre-configures corresponding weight coefficients for each key business indicator under each business dimension, and the weight coefficients characterize the importance of the indicator in its respective business dimension.

[0066] In some embodiments of this application, when performing weighted summation calculations, the standardized score value of each key business indicator is multiplied by its corresponding weight coefficient, and then the weighted results of all indicators under the same dimension are summed. The sum is the score information for that business dimension. This score information is a quantitative value that intuitively reflects the overall performance level of the business entity in that specific dimension.

[0067] For example, when calculating the "Operational Efficiency Dimension" score of a government service center, this dimension includes two key business indicators: "Average Daily Number of Cases Handled at Windows" (with a weight of 0.6) and "Average Processing Time for Items" (with a weight of 0.4). Assuming that through standardization, the center's "Average Daily Number of Cases Handled at Windows" score is 90 points and its "Average Processing Time for Items" score is 80 points, then by weighted summation: 90 * 0.6 + 80 * 0.4 = 86, the center's "Operational Efficiency Dimension" score is 86 points.

[0068] In this embodiment, by introducing weighting coefficients, the final calculated dimension score can more accurately reflect the true strength of the business entity in that dimension, avoiding the evaluation distortion that may be caused by simple averaging, and providing a more reliable and refined data basis for subsequent resource reorganization.

[0069] In some embodiments of this application, the process of determining the comprehensive score corresponding to the business entity based on the scoring information in step 202 above may include the following step 202b: Step 202b: The resource reorganization device performs a weighted summation of the scores corresponding to multiple target business dimensions based on the weights corresponding to each target business dimension to obtain the comprehensive score of the business entity.

[0070] In some embodiments of this application, after obtaining the score information of a business entity in each target business dimension, the resource reorganization device calculates the comprehensive score of the business entity using a weighted summation algorithm. Specifically, the resource reorganization device assigns a weight coefficient to each preset business dimension, which represents the importance of that dimension in the overall business evaluation system.

[0071] In some embodiments of this application, during calculation, the resource reorganization device multiplies the score of each business dimension by its corresponding weight coefficient, and then sums the weighted scores of all dimensions to obtain the comprehensive score of the business entity. This comprehensive score is a single quantitative value used to comprehensively characterize the overall performance level of the business entity, providing a core basis for subsequent business entity ranking and complementary pairing.

[0072] For example, suppose the business dimensions for evaluating a bank branch (business entity) include "Service Quality" (weight 0.4), "Operational Efficiency" (weight 0.35), and "Risk Control" (weight 0.25). The branch scores 92, 85, and 88 points in these three dimensions, respectively. Therefore, its overall score is calculated as: 92 * 0.4 + 85 * 0.35 + 88 * 0.25 = 89.05 points. This score directly reflects the branch's overall performance after considering the importance of each dimension.

[0073] In this embodiment of the application, by assigning weights to different business dimensions and performing weighted summation, the limitation of simply treating the performance of each dimension as the same is avoided. This allows the final comprehensive score to reflect the key business dimensions that are of concern, thereby making subsequent resource reorganization decisions more flexible and in line with actual needs.

[0074] In some embodiments of this application, in conjunction with the above... Figure 1 ,like Figure 2 As shown, step 203 above may include steps 203a to 203c: Step 203a: The resource reorganization device sorts the multiple business entities from highest to lowest score based on the comprehensive score of each business entity.

[0075] Step 203b: The resource reorganization device divides the sorted business entities into a first entity queue and a second entity queue with an equal number of entities.

[0076] The first entity queue contains the top half of the business entities, and the second entity queue contains the bottom half of the business entities.

[0077] Step 203c: The resource reorganization device determines the business entity ranked at position i in the first entity queue and the business entity ranked at position i from the bottom in the second entity queue as a pair of complementary business entities.

[0078] Where i is an integer greater than 1, and i is less than or equal to the sum of the number of business entities in the first entity queue and the number of business entities in the second entity queue.

[0079] In some embodiments of this application, after obtaining the overall scores of all business entities, the resource reorganization apparatus performs a sorting operation to establish a relative performance sequence of the business entities. Specifically, the apparatus uses a sorting algorithm (such as quicksort or heapsort) to sort the overall scores of all business entities in descending order. Exemplarily, after sorting, the resource reorganization apparatus can generate an ordered list of business entities, where each business entity is associated with its unique identifier and corresponding overall score. This ordered list provides a clear input basis for subsequent systematic pairing.

[0080] For example, after evaluating the overall scores of 10 regional sales centers, the resource reorganization device executes a ranking algorithm to generate a list: {Center A: 95 points, Center B: 88 points, Center C: 85 points, ..., Center J: 62 points}. This list clearly shows the sequence of centers from best to those most in need of improvement.

[0081] In some embodiments of this application, after sorting is completed, the resource reorganization device performs a queue partitioning operation. The device first determines the total number N of business entities, and then calculates the half-maximum split point M = N / 2 (if N is odd, it can be configured to round up or down). The resource reorganization device assigns business entities ranked 1st to Mth in the ordered list to a first entity queue, which represents a group with excellent overall performance; and assigns business entities ranked (M+1) to Nth to a second entity queue, which represents a group with significant improvement potential. This partitioning operation ensures comprehensive coverage of subsequent resource pairing and the feasibility of matching at both ends.

[0082] For example, for the above 10 sales centers (N=10, M=5), the device will assign centers ranked 1-5 (center A to center E) to the first entity queue and centers ranked 6-10 (center F to center J) to the second entity queue.

[0083] In some embodiments of this application, the resource reorganization device executes a core complementary pairing algorithm based on two pre-divided queues. The algorithm employs a cross-mapping rule: for i from 1 to M (M being the queue capacity), the business entity at the i-th position in the first entity queue is bound to the business entity at the i-th position from the end in the second entity queue, forming a pair of complementary business entities.

[0084] It should be noted that this pairing logic aims to achieve "highly targeted" resource reallocation: that is, the best-performing entity helps the entity with the greatest potential, the second-best-performing entity helps the entity with the second-greatest potential, and so on. This method ensures that resource reallocation actions can systematically cover all entities that need improvement, and that the intensity of the assistance is commensurate with the difficulty of the improvement.

[0085] In some embodiments of this application, the resource reorganization device may generate a unique pair identifier (Pair ID) for each pair of complementary business entities and record it in a pair mapping table to facilitate subsequent policy generation and progress tracking.

[0086] In this embodiment, by first sorting and equally dividing all entities, and then performing systematic cross-pairing, it is ensured that a high-performing entity and an entity to be improved can form a complementary pair, thereby greatly increasing the accuracy of the subsequent resource reorganization strategy.

[0087] In some embodiments of this application, before determining at least one pair of complementary business entities capable of resource reorganization from multiple business entities in step 203 above, the resource reorganization method provided in this application may further include the following step A1: Step A1: The resource reorganization device establishes a resource attribute profile for each business entity, thus obtaining the resource attribute profile corresponding to each business entity.

[0088] The resource attribute profile includes the skill structure of the human resources of the corresponding business entity and the type and quantity of equipment resources.

[0089] For example, in conjunction with step A1 above, step 203c above may include steps 203c1 and 203c2: Step 203c1: The resource reorganization device verifies whether the resource attributes of the business entity ranked i in the first entity queue and the business entity ranked i from the bottom in the second entity queue match based on their respective resource attribute profiles.

[0090] Step 203c2: When the resource attribute matching degree exceeds the preset threshold, the resource reorganization device determines the business entity ranked at the i-th position in the first entity queue and the business entity ranked at the i-th position from the bottom in the second entity queue as a pair of complementary business entities.

[0091] In some embodiments of this application, before determining complementary business entity pairs, the resource reorganization device first constructs a resource attribute profile for each business entity to achieve more accurate resource matching. Specifically, the device automatically collects and integrates detailed resource data for each business entity by accessing a Human Resources Management System (HRMS), an Asset Management System, and a business operation database.

[0092] For example, a resource attribute profile includes two core dimensions: Human resource skills structure: The resource reorganization device collects and analyzes data such as the job distribution, skills certification, professional qualifications and historical project experience of employees within the business entity to form a structured skills list.

[0093] Equipment resource type and quantity: The resource reorganization device collects information on key equipment, software licenses, special tools and other resources owned by the business entity, and records their type, model, quantity and current utilization rate.

[0094] In some embodiments of this application, after a preliminary pairing is formed (such as the i-th position in the first queue and the i-th position from the end of the second entity queue), the resource reorganization device initiates a resource matching verification process. Specifically, the resource reorganization device obtains the resource attribute profiles of the two business entities in the candidate pairing, performs comparative analysis, and then calculates a quantified resource attribute matching degree based on the comparison results.

[0095] In some embodiments of this application, the resource reorganization apparatus compares the calculated resource attribute matching degree with a preset feasibility threshold. Exemplarily, this threshold can be set and adjusted by a system administrator based on historical reorganization success rates or expert experience.

[0096] For example, if the matching degree is greater than or equal to a preset threshold, the candidate pair is determined to have a feasible complementary basis at the resource level, and is identified as a pair of complementary business entities, and recorded in the final pairing scheme; or, if the matching degree is less than the preset threshold, the pairing is determined to lack practical operational feasibility and will be abandoned. Subsequently, the resource reorganization device can activate a backup pairing strategy, for example, to find another candidate with matching resources for the business entity in the second entity queue in the first entity queue, or to mark it as a case requiring special resource injection for processing.

[0097] In this embodiment of the application, by introducing resource attribute profiling and its matching verification mechanism, resource matching degree verification is added before reorganization, ensuring that the identified complementary entity pairs have an operable resource base in reality, fundamentally improving the feasibility and success rate of the generated resource reorganization strategy, and reducing the waste of implementation costs caused by resource mismatch.

[0098] In some embodiments of this application, in conjunction with the above...Figure 1 ,like Figure 3 As shown, step 204 above may include steps 204a to 204c: Step 204a: For each pair of complementary business entities, the resource reorganization device determines the first business entity located in the first entity queue and the second business entity located in the second entity queue.

[0099] Step 204b: Based on the score information corresponding to each target business dimension of the first business entity, the resource reorganization device determines its advantageous business dimension and allocates the resources corresponding to the advantageous business dimension of the first business entity to the corresponding business area of ​​the second business entity.

[0100] Step 204c: Based on the score information corresponding to each target business dimension of the second business entity, the resource reorganization device determines its advantageous business dimension and configures the resources corresponding to the advantageous business dimension of the second business entity as shared resources with the first business entity.

[0101] In some embodiments of this application, after obtaining a confirmed list of complementary business entity pairs, the resource reorganization device first identifies the roles of the two business entities in each pair.

[0102] In some embodiments of this application, the resource restructuring device analyzes the score information of a first business entity in various target business dimensions to identify its core advantages. Specifically, the resource restructuring device compares the scores of all dimensions of the business entity with preset advantage thresholds, and / or selects one or more dimensions with the highest scores, marking them as advantageous business dimensions.

[0103] In some embodiments of this application, the resource reorganization device executes resource allocation logic. Specifically, based on a preset "dimension-resource" mapping relationship, it determines the key resource types (such as manpower with specific skills, dedicated equipment, or optimization methods) that support the performance of the advantageous business dimension. Then, it generates specific resource allocation instructions to temporarily or permanently allocate this portion of the advantageous resources of the first business entity to the corresponding weakly performing business area in the second business entity. The allocation methods may include personnel secondment, equipment rental, technical guidance, or process sharing.

[0104] For example, the first business entity scores significantly higher than other dimensions in the "Technology R&D Dimension" and exceeds the advantage threshold, thus being identified as having an advantage in that dimension. This advantage relies on its team of "senior algorithm engineers." The resulting resource reorganization strategy could be: "Assign two senior algorithm engineers from the first business entity to the technology R&D department of the second business entity as project support."

[0105] In some embodiments of this application, the resource reorganization apparatus also performs advantage analysis on the second business entity, identifying the relatively better-performing (e.g., scoring the highest in its own dimension, or exceeding the passing threshold) advantageous business dimensions. Then, it executes resource sharing configuration logic. A portion of the resources of the second business entity's advantageous business dimensions are designated as shared resources, allowing the first business entity to apply for and use them when needed, thus establishing a bidirectional resource reorganization relationship.

[0106] In this embodiment of the application, by accurately identifying the strongest aspects and available resources of each business entity based on specific dimensional score information, the rationality and accuracy of the reorganization strategy are ensured, thereby improving the accuracy of subsequent resource reorganization and reducing the blindness and waste of resource allocation.

[0107] In some embodiments of this application, in conjunction with the above... Figure 1 ,like Figure 4 As shown, after step 204 above, the resource reorganization method provided in this application embodiment may further include steps 205 to 207: Step 205: After executing the preset time period following the resource reorganization, the resource reorganization device retrieves new key business indicators for multiple business entities from the business database within the preset time period.

[0108] Step 206: The resource restructuring unit calculates and generates new comprehensive scores for multiple business entities based on the new key business indicators.

[0109] Step 207: The resource reorganization device compares the new comprehensive score with the comprehensive score before resource reorganization. If the increase in the new comprehensive score of the business entities in the second entity queue exceeds the preset threshold and the new comprehensive score of the business entities in the first entity queue does not decrease, the resource reorganization strategy is determined to be effective. Based on the new comprehensive scores of all complementary business entity pairs, the resource reorganization strategy is adaptively adjusted.

[0110] In some embodiments of this application, the resource restructuring device initiates an effectiveness evaluation cycle after the resource restructuring strategy is implemented. For example, the resource restructuring device presets an evaluation time interval (e.g., a quarter or half a year), and automatically triggers a data collection process when this time point is reached. Specifically, the resource restructuring device reconnects to the business database via a data interface to obtain the operational data generated by all participating business entities during the just-concluded evaluation cycle, and extracts a new, complete set of indicator datasets—the new key business indicators—based on the original definitions of key business indicators. This ensures that the data used for effectiveness evaluation is consistent with the data source and scope of the initial evaluation benchmark, guaranteeing the credibility of the comparison.

[0111] For example, the resource restructuring device sets the evaluation cycle to one quarter. At the end of the second quarter, new data on indicators such as "sales per square meter," "average order value," and "inventory turnover rate" for all business entities in the second quarter are automatically retrieved from the database.

[0112] In some embodiments of this application, after obtaining a new dataset of key business indicators, the resource restructuring apparatus completely re-executes the evaluation process described in the embodiments of this application. This includes: classifying the indicators according to the same business dimensions, calculating the score for each business dimension using the same standardization method and weight configuration, and finally using the same comprehensive score calculation model (such as a weighted summation algorithm) as before to calculate a new comprehensive score for each business entity. This new comprehensive score reflects the overall performance level of the business entity after the implementation of the resource restructuring strategy.

[0113] For example, for "Store A" that participated in the restructuring, the resource restructuring device used its new indicator data in the second quarter to recalculate its new comprehensive score of 87 points according to the established three dimensions of "sales efficiency", "inventory management" and "customer service" and their weights, while the comprehensive score before restructuring was 78 points.

[0114] In some embodiments of this application, the resource reorganization device calculates the difference between the old and new comprehensive scores of the second business entity for each complementary business entity pair, i.e., the improvement value. Simultaneously, it checks whether the new comprehensive score of the first business entity has not decreased compared to before reorganization. When the improvement value of the second business entity is greater than a preset improvement threshold and the score of the first business entity has not decreased, it is determined that the resource reorganization strategy for that pair is effective.

[0115] In some embodiments of this application, the preset threshold for improvement is set by the administrator according to business expectations, such as 5 points or 10 points.

[0116] In some embodiments of this application, the resource reorganization device initiates a new round of complementary business entity pair determination process based on the new comprehensive score of all business entities, and forms new and better complementary pairs according to the latest performance, thereby achieving continuous flow and optimization of resources.

[0117] In this embodiment of the application, by introducing a closed loop of "execution-evaluation-adjustment", resource reorganization is upgraded into a continuously operating, self-optimizing intelligent management system. By verifying the effectiveness of its strategies and continuously adjusting and optimizing subsequent actions based on the results, resource allocation can dynamically adapt to changes in the internal and external environment, thereby achieving automation and intelligence in the management process.

[0118] In some embodiments of this application, the process of obtaining the scoring information of each key business indicator for each target business dimension of each business entity in step 202 above may include the following steps 202c to 202e: Step 202c: For each business entity, the resource reorganization device obtains quantitative information of each key business indicator under multiple target business dimensions from the associated business system through the data interface, and converts it into the first score information of each key business indicator through the scoring model.

[0119] Step 202d: The resource reorganization device receives the second scoring information input by the user for each key business indicator through the user operation interface.

[0120] Step 202e: For each key business indicator, the resource reorganization device calculates the weighted average of the first and second scoring information, and uses the weighted average as the scoring information for the corresponding key business indicator.

[0121] In some embodiments of this application, the resource reorganization device communicates with one or more associated business systems (such as Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), Project Management System, etc.) through predefined standardized data interfaces (such as RESTful APIs or database connectors). The resource reorganization device automatically extracts raw quantitative information related to key business indicators from these business systems, such as specific numerical values, percentages, counts, or time data.

[0122] In some embodiments of this application, the resource reorganization device calls a built-in scoring model to process this raw quantitative information. This scoring model includes predefined standardization functions and mapping rules, which transform raw data with different dimensions and magnitudes into comparable standard scores. Commonly used methods include Min-Max normalization (mapping data to a 0-100 score range), Z-score standardization (based on mean and standard deviation), or piecewise function mapping (setting different scores according to different numerical ranges). The transformed result is the first scoring information, which represents the preliminary evaluation result generated based on objective system data.

[0123] For example, when evaluating the "code quality" metric of a software development team, the resource reorganization device obtains the raw value of "defect rate per thousand lines of code" as 1.2% from the code repository system via an interface. The scoring model has a preset rule: a defect rate below 0.5% earns 100 points, 0.5%-1.0% earns 80 points, and 1.0%-2.0% earns 60 points. Accordingly, the scoring model automatically converts this metric for the team into a score of 60, which is then used as its first scoring information.

[0124] In some embodiments of this application, the resource reorganization device may provide a user interface (such as a web management backend or mobile application) through which authorized users (such as managers or domain experts) may input an evaluation score, i.e., second scoring information, for each key business indicator based on their experience, observation and qualitative judgment.

[0125] It should be noted that the user interface clearly displays the list of business entities to be evaluated and their key business metrics. For each metric, the interface provides necessary contextual information (such as metric definition and historical scoring trends) and input controls (such as sliders or numeric input boxes) to guide users in making more accurate judgments. The scoring data submitted by the user is received and securely stored by the device, thus introducing a subjective evaluation mechanism to compensate for the limitations of purely objective data and improve the accuracy of the subsequently generated resource reorganization strategy.

[0126] In some embodiments of this application, after obtaining first scoring information (objective system score) and second scoring information (subjective human score) for the same key business indicator, the resource reorganization device performs a data fusion operation. Exemplarily, the resource reorganization device uses a weighted average algorithm to combine the two scores.

[0127] Specifically, each key business indicator is predefined or dynamically calculated with a weight allocation scheme, including an objective weight (W_objective) and a subjective weight (W_subjective), satisfying W_objective + W_subjective = 1. The final scoring information is calculated according to the following formula (1): Final score = (First score information × W_objective) + (Second score information × W_subjective) (1) It should be noted that weight configuration can be set based on the characteristics of the indicator. For indicators that are easy to quantify and have reliable data sources (such as "number of server failures"), a higher objective weight can be set; for indicators that rely on qualitative judgment (such as "team innovation atmosphere"), a higher subjective weight can be set.

[0128] For example, for the "customer satisfaction" indicator, the first rating information (the satisfaction survey score automatically calculated by the customer service system) is 75 points, and the second rating information (the sales director's experience judgment) is 90 points. The objective weight of this indicator is configured as 0.7, and the subjective weight is 0.3. Then the final rating information is calculated as: (75 × 0.7) + (90 × 0.3) = 79.5 points.

[0129] In this embodiment of the application, by integrating objective data (first scoring information) from the business system and scoring data judged by humans (second scoring information), it is possible to effectively combine objective data and subjective data to score business indicators. This hybrid evaluation mechanism avoids the context and subtle differences that exist in single objective data, and also prevents the inconsistency caused by relying entirely on subjective judgment. As a result, the final scoring information is more comprehensive and balanced, effectively improving the accuracy and reliability of the final output scoring information, and providing higher quality input for subsequent resource reorganization decisions.

[0130] The following uses the scenario of optimizing human resource allocation as an example to illustrate the process of the resource allocation method provided in this application embodiment. Figure 5 As shown, the process of this resource allocation method may include the following steps: Step 11: Extract relevant metrics.

[0131] For example, the resource reorganization device extracts multiple metrics from a large existing set of metrics that are needed to score multiple organizations (i.e., business entities).

[0132] Step 12: Categorize the metrics by dimension.

[0133] For example, the resource reorganization device further classifies the extracted indicators according to the defined dimensions.

[0134] Step 13: Obtain the user's ratings for each metric.

[0135] Step 14: Calculate the scores for each indicator using the scoring model.

[0136] Step 15: Determine the final score of the indicator based on the user-input rating and the rating calculated by the rating model.

[0137] Step 16: Determine the score for each dimension based on the scores of the metrics for each dimension.

[0138] Step 17: Calculate the overall score of the corresponding institution based on the score of each dimension.

[0139] Step 18: Based on the comprehensive score corresponding to each institution, identify at least one pair of complementary institutions from multiple institutions that can perform resource reorganization.

[0140] Step 19: Generate the corresponding resource reorganization strategy for each pair of complementary institutions that can perform resource reorganization.

[0141] The resource reorganization method provided in this application extracts some indicators from the existing massive stock indicators and classifies these indicators by dimension. It scores various manual indicators of the institutions under its jurisdiction, automatically retrieves the indicator scores from the system, and then summarizes the scores of various indicators of the institutions by dimension and calculates the ranking. According to the ranking of the institutions in each dimension, the institutions' performance in each dimension is labeled as "very good", "good", "still needs to work hard", and "needs to be improved". Finally, according to the above labels, the human resources of each institution are redistributed according to the principle of complementarity.

[0142] In this embodiment, extracting indicators greatly narrows the scope of indicators and improves scoring efficiency. Dividing the extracted indicators by dimensions further narrows the scope of labels that need to be applied. Labeling the organization in each dimension with corresponding tags such as "very good," "good," "still needs improvement," and "needs key improvement" allows for a quick and intuitive understanding of the organization's strengths and weaknesses in each dimension. According to the organization's strengths and weaknesses in each dimension, the correctness and efficiency of human resource reorganization and allocation can be ensured, and the goal of improving the overall performance of the organization within the jurisdiction can be achieved quickly and effectively.

[0143] It should be noted that the collection, acquisition, storage, use, processing, transmission, provision and disclosure of user personal information / data involved in the technical solution disclosed in this application all comply with the relevant provisions of national laws and regulations and do not violate public order and good morals.

[0144] It should be noted that the model in this application embodiment is not a model for a specific user and cannot reflect the personal information of a specific user.

[0145] It should be noted that the personal information used in the technical solution of this application is limited to information for which individual consent has been obtained, including but not limited to notifying and reminding users to read the relevant user agreement (notification) and sign the agreement (authorization) which includes the authorization of relevant user information before users use the function.

[0146] Figure 6 This is a schematic diagram of a resource reorganization device provided in an embodiment of this application. Figure 6As shown, the resource reorganization device 600 includes: an acquisition module 601, a processing module 602, and a generation module 603, wherein: the acquisition module 601 is used to acquire multiple key business indicators of multiple business entities of a target business provider from a business database; the processing module 602 is used to classify the multiple key business indicators corresponding to each business entity acquired by the acquisition module according to multiple preset business dimensions to obtain multiple key business indicators of target business dimensions for each business entity; the processing module 602 is also used to acquire the scoring information of each key business indicator of each target business dimension of each business entity for each business entity, calculate the score information corresponding to each target business dimension of the business entity based on the scoring information of each key business indicator of each target business dimension, and determine the comprehensive score corresponding to the business entity based on the score information; the processing module 602 is also used to determine at least one pair of complementary business entities that can be reorganized by execution from the multiple business entities based on the comprehensive score corresponding to each business entity; the generation module 603 is used to generate a corresponding resource reorganization strategy for each pair of complementary business entities that can be reorganized by execution, and the resource reorganization strategy is used to perform resource reorganization on the complementary business pair.

[0147] In some embodiments of this application, the above-mentioned processing module is specifically used to perform weighted summation of the scoring information of each key business indicator under each target business dimension based on the weights corresponding to each key business indicator under each target business dimension, so as to obtain the score information corresponding to each target business dimension.

[0148] In some embodiments of this application, the above-mentioned processing module is specifically used to perform weighted summation of the score information corresponding to multiple target business dimensions based on the weight corresponding to each target business dimension, so as to obtain the comprehensive score of the business entity.

[0149] In some embodiments of this application, the above-described processing module is specifically used to sort the multiple business entities from highest to lowest score based on the comprehensive score of each business entity; divide the sorted multiple business entities into a first entity queue and a second entity queue of equal number; wherein the first entity queue contains the top half of the ranked business entities, and the second entity queue contains the bottom half of the ranked business entities; and determine the business entity ranked i-th in the first entity queue and the business entity ranked i-th from the bottom in the second entity queue as a pair of complementary business entities; wherein i is an integer greater than 1, and i is less than or equal to the sum of the number of business entities in the first entity queue and the number of business entities in the second entity queue.

[0150] In some embodiments of this application, the above-mentioned processing module is further configured to, before determining at least one pair of complementary business entities capable of resource reorganization from multiple business entities, establish a resource attribute profile for each business entity to obtain a resource attribute profile corresponding to each business entity, wherein the resource attribute profile includes the skill structure of the human resources of the corresponding business entity and the type and quantity of equipment resources; the above-mentioned processing module is specifically configured to, based on the resource attribute profiles of the business entity ranked i in the first entity queue and the business entity ranked i from the bottom in the second entity queue, verify whether the resource attributes of the business entity ranked i in the first entity queue and the business entity ranked i from the bottom in the second entity queue match; when the resource attribute matching degree exceeds a preset threshold, the business entity ranked i in the first entity queue and the business entity ranked i from the bottom in the second entity queue are determined as a pair of complementary business entities.

[0151] In some embodiments of this application, the generation module is specifically used to, for each pair of complementary business entities, determine the first business entity located in the first entity queue and the second business entity located in the second entity queue; determine its advantageous business dimension based on the score information corresponding to each target business dimension of the first business entity, and allocate the resources corresponding to the advantageous business dimension of the first business entity to the corresponding business domain of the second business entity; determine its advantageous business dimension based on the score information corresponding to each target business dimension of the second business entity, and configure the resources corresponding to the advantageous business dimension of the second business entity as shared resources with the first business entity.

[0152] In some embodiments of this application, the acquisition module is further configured to generate corresponding resource restructuring strategies for each pair of complementary business entities that can perform resource restructuring, and after a preset time period following the execution of resource restructuring, re-acquire new key business indicators for multiple business entities within the preset time period from the business database; the processing module is further configured to calculate and generate new comprehensive scores for multiple business entities based on the new key business indicators; the processing module is further configured to compare the new comprehensive scores with the comprehensive scores before resource restructuring, and if the increase in the new comprehensive scores of business entities in the second entity queue exceeds a preset threshold, and the new comprehensive scores of business entities in the first entity queue do not decrease, then the resource restructuring strategy is determined to be effective, and the resource restructuring strategy is adaptively adjusted based on the new comprehensive scores of all complementary business entity pairs.

[0153] In some embodiments of this application, the acquisition module is specifically used to acquire, for each business entity, quantitative information of various key business indicators under multiple target business dimensions from the associated business system through a data interface, and convert them into first score information of each key business indicator through a scoring model; receive second score information input by the user for each key business indicator through a user interface; calculate the weighted average of the first score information and the second score information for each key business indicator, and use the weighted average as the score information of the corresponding key business indicator.

[0154] In some embodiments of this application, the aforementioned multiple preset business dimensions include at least two of the following dimensions: business processing efficiency dimension, service quality dimension, resource utilization dimension, and risk and internal control dimension.

[0155] The resource reorganization apparatus provided in this application embodiment can execute the method shown in the above method embodiment. Its implementation principle and beneficial effects can be referred to the relevant description in the method embodiment, and will not be repeated here.

[0156] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 7 As shown, the electronic device 500 includes: a memory 501, a transceiver 502, and at least one processor 503.

[0157] Transceiver 502 is used to interact with other devices to send and receive data. Memory 501 is used to store computer program code, which includes computer instructions. These computer instructions run in the above-described electronic device to implement the method shown in the above-described method embodiments. For example, the memory may include high-speed random access memory (RAM), and may also include non-volatile memory (NVM), such as at least one disk storage device, and may also be a USB flash drive, portable hard drive, read-only memory, disk, or optical disk, etc.

[0158] Processor 503 can be a general-purpose processor, including a Central Processing Unit (CPU), a network processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. Processor 503 can also be other general-purpose processors. The general-purpose processor can be a microprocessor or any conventional processor. For example, in this embodiment, processor 503 can specifically be used to classify multiple key business indicators corresponding to each business entity acquired by the acquisition module according to multiple preset business dimensions to obtain multiple target business dimensions of key business indicators for each business entity.

[0159] The memory 501, transceiver 502, and processor 503 are communicatively connected. For example, the memory 501 and transceiver 502 can be connected to the processor 503 via a system bus and communicate with each other. The system bus can be a peripheral component interconnect (PCI) bus, an extended industry standard architecture (EISA) bus, an industry standard architecture (ISA) bus, etc. The system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the figure, but this does not mean that there is only one bus or one type of bus.

[0160] Optionally, the memory 501 can be either standalone or integrated with the processor 503. When the memory 501 is set up independently, it is connected to the processor 503 via a system bus.

[0161] This application also provides a chip for executing instructions, which is used to execute the resource reorganization method described in the above embodiments.

[0162] This application also provides a computer-readable storage medium storing computer instructions. When these computer instructions are executed by a processor, they are used to implement the technical solution of the resource reorganization method described in the above embodiments. Specifically, when the computer instructions are executed by a processor, the electronic device can perform the technical solution of the resource reorganization method described in the above embodiments.

[0163] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, it can implement the technical solution of the resource reorganization method in the above embodiments. The aforementioned computer-readable storage media can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The computer-readable storage media can be any available medium accessible to a general-purpose or special-purpose computer. An exemplary computer-readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the computer-readable storage medium can also be a component of the processor. The processor and the computer-readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the computer-readable storage medium can exist as discrete components in an electronic control unit or main control device; this application does not limit this.

[0164] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0165] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0166] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0167] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0168] It should be understood that the steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

[0169] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0170] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A resource reorganization method, characterized in that, include: The system retrieves multiple key business metrics of multiple business entities of the target business provider from the business database, and classifies the multiple key business metrics corresponding to each business entity according to multiple preset business dimensions to obtain the key business metrics of multiple target business dimensions of each business entity. For each business entity, obtain the scoring information of each key business indicator for each target business dimension of the business entity, calculate the score information corresponding to each target business dimension of the business entity based on the scoring information of each key business indicator for each target business dimension, and determine the comprehensive score corresponding to the business entity based on the score information. Based on the comprehensive score corresponding to each of the multiple business entities, at least one pair of complementary business entities that can perform resource reorganization is determined from the multiple business entities; For each pair of complementary business entities that can be reorganized, a corresponding resource reorganization strategy is generated, and the resource reorganization strategy is used to reorganize the complementary business pair.

2. The method according to claim 1, characterized in that, The scoring information for each target business dimension of the business entity is calculated based on the scoring information of each key business indicator of each target business dimension, including: Based on the weights corresponding to the key business indicators under each target business dimension, the scoring information of each key business indicator under each target business dimension is weighted and summed to obtain the score information corresponding to each target business dimension.

3. The method according to claim 1, characterized in that, The step of determining the comprehensive score corresponding to the business entity based on the scoring information includes: Based on the weight corresponding to each target business dimension, the scores corresponding to the multiple target business dimensions are weighted and summed to obtain the comprehensive score of the business entity.

4. The method according to claim 1, characterized in that, Based on the comprehensive score corresponding to each of the plurality of business entities, at least one pair of complementary business entities with executable resource reorganization is determined from the plurality of business entities, including: Based on the comprehensive score of each of the multiple business entities, the multiple business entities are sorted from high to low score; The sorted business entities are divided into a first entity queue and a second entity queue with an equal number of entities; wherein, the first entity queue contains the top half of the business entities and the second entity queue contains the bottom half of the business entities. The business entity ranked i in the first entity queue and the business entity ranked i from the bottom in the second entity queue are identified as a pair of complementary business entities; wherein i is an integer greater than 1, and i is less than or equal to the sum of the number of business entities in the first entity queue and the number of business entities in the second entity queue.

5. The method according to claim 1 or 4, characterized in that, Before determining at least one pair of complementary business entity pairs capable of performing resource reorganization from the plurality of business entities, the method further includes: A resource attribute profile is created for each business entity to obtain a resource attribute profile corresponding to each business entity. The resource attribute profile includes the skill structure of the human resources of the corresponding business entity and the type and quantity of equipment resources. The step of determining the business entity ranked i-th in the first entity queue and the business entity ranked i-th from the bottom in the second entity queue as a complementary business entity pair includes: Based on the resource attribute profiles of the business entity ranked i in the first entity queue and the business entity ranked i from the bottom in the second entity queue, verify whether the resource attributes of the business entity ranked i in the first entity queue and the business entity ranked i from the bottom in the second entity queue match. When the resource attribute matching degree exceeds a preset threshold, the business entity ranked at the i-th position in the first entity queue and the business entity ranked at the i-th position from the bottom in the second entity queue are identified as a pair of complementary business entities.

6. The method according to claim 5, characterized in that, The process of generating corresponding resource reorganization strategies for each pair of complementary business entities capable of performing resource reorganization includes: For each pair of complementary business entities, determine the first business entity located in the first entity queue and the second business entity located in the second entity queue. Based on the score information corresponding to each target business dimension of the first business entity, its advantageous business dimension is determined, and the resources corresponding to the advantageous business dimension of the first business entity are allocated to the corresponding business domain of the second business entity. Based on the score information corresponding to each target business dimension of the second business entity, its advantageous business dimensions are determined, and the resources corresponding to the advantageous business dimensions of the second business entity are configured as shared resources with the first business entity.

7. The method according to claim 5, characterized in that, After generating a corresponding resource reorganization strategy for each pair of complementary business entities capable of resource reorganization, the method further includes: After a preset time period following the execution of resource reorganization, new key business indicators for the multiple business entities within the preset time period are retrieved from the business database. Based on the new key business indicators, calculate and generate new comprehensive scores for the multiple business entities; The new comprehensive score is compared with the comprehensive score before resource reorganization. If the increase in the new comprehensive score of the business entities in the second entity queue exceeds a preset threshold, and the new comprehensive score of the business entities in the first entity queue does not decrease, then the resource reorganization strategy is determined to be effective. Based on the new comprehensive scores of all complementary business entity pairs, the resource reorganization strategy is adaptively adjusted.

8. The method according to claim 1, characterized in that, For each business entity, the process of obtaining scoring information for each key business indicator of each target business dimension includes: For each business entity, quantitative information of key business indicators under multiple target business dimensions is obtained from the associated business system through the data interface, and then converted into the first score information of each key business indicator through the scoring model. Receive the second scoring information input by the user for each key business indicator through the user interface; For each key business indicator, a weighted average of the corresponding first and second score information is calculated, and this weighted average is used as the score information for the corresponding key business indicator.

9. The method according to claim 1, characterized in that, The multiple preset business dimensions include at least two of the following dimensions: business processing efficiency, service quality, resource utilization, and risk control.

10. A resource recombination device, characterized in that, include: The module consists of an acquisition module, a processing module, and a generation module, among which: The acquisition module is used to acquire multiple key business indicators of multiple business entities of the target business provider from the business database; The processing module is used to classify the multiple key business indicators corresponding to each business entity acquired by the acquisition module according to multiple preset business dimensions to obtain the key business indicators of multiple target business dimensions of each business entity. The processing module is further configured to, for each business entity, obtain the scoring information of each key business indicator of each target business dimension of the business entity, calculate the score information corresponding to each target business dimension of the business entity based on the scoring information of each key business indicator of each target business dimension, and determine the comprehensive score corresponding to the business entity based on the score information. The processing module is further configured to determine at least one pair of complementary business entities that can perform resource reorganization from the plurality of business entities based on the comprehensive score corresponding to each business entity among the plurality of business entities; The generation module is used to generate a corresponding resource reorganization strategy for each pair of complementary business entities that can be reorganized, and the resource reorganization strategy is used to perform resource reorganization on the complementary business pair.

11. An electronic device, characterized in that, include: A memory and at least one processor; the memory is communicatively connected to the processor; the memory is used to store computer program code, the computer program code including computer instructions; when the processor executes the computer instructions, the electronic device performs the method as described in any one of claims 1-9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, are used to implement the method as described in any one of claims 1-9.

13. A computer program product, characterized in that, When the computer program product is run on a computer / executed by the computer's processor, it implements the method as described in any one of claims 1-9.

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