Supplier service quality assessment management system and method based on dynamic weight optimization

Abstract

The invention provides a supplier service quality assessment management system and method based on dynamic weight optimization, and belongs to the technical field of weight adjustment. The total index module is used for determining quality assessment indexes and sub-indexes thereof according to supplier service contents and contract requirements; the data acquisition module is used for acquiring historical performance data of a target supplier and standardizing the historical performance data to obtain standard performance data; the first scoring module is used for determining a first score of the quality assessment index according to the initial weight of the quality assessment index and the quantification method in combination with the standard performance data; the dynamic weight module is used for generating a weight adjustment strategy according to a business scene of the standard expression data, and obtaining a first weight of the quality assessment index after adjusting an initial weight; and the scoring module is used for calculating a quality assessment score of the target supplier according to the first weight and the first score. The accuracy and the dynamic adaptability of supplier service assessment are improved, and quality assessment and decision support are optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of weight adjustment, and particularly to a supplier service quality assessment and management system and method based on dynamic weight optimization. Background Art

[0002] Currently, with the acceleration of globalization and market competition, enterprises have higher and higher requirements for the selection and management of suppliers. Traditional methods for assessing the service quality of suppliers usually use fixed weights and static indicators for evaluation. However, the assessment indicators for suppliers of IT operation and maintenance services are not perfect. Only a small number of static indicators are used for assessment and management, lacking the efficiency of dynamic assessment during special periods such as application go-live and security incidents, and lacking assessment indicators for security and user experience.

[0003] Therefore, the present invention proposes a supplier service quality assessment and management system and method based on dynamic weight optimization. Summary of the Invention

[0004] The present invention provides a supplier service quality assessment and management system and method based on dynamic weight optimization, which aims to improve the assessment indicators for suppliers of IT operation and maintenance services, accurately quantify the service efficiency and service quality of suppliers through a dynamic weight assessment method, and accurately judge the service results of operation and maintenance suppliers through the quantification results of the cost-output ratio and user experience indicators.

[0005] On the one hand, the present invention provides a supplier service quality assessment and management system based on dynamic weight optimization, including:

[0006] Total Index Module: Determine five types of quality assessment indicators and their sub-indicators for service efficiency, service quality, service cost, service security, and user experience according to the service content of the supplier and the contract requirements;

[0007] Data Acquisition Module: Collect historical performance data of the target supplier and preprocess and standardize it to obtain standard performance data;

[0008] First Scoring Module: Determine the first score of the quality assessment indicator according to the initial weight and quantification method of the quality assessment indicator, in combination with the standard performance data;

[0009] Dynamic Weight Module: Generate a weight adjustment strategy according to the business scenario of the standard performance data, and adjust the initial weight to obtain the first weight of the quality assessment indicator;

[0010] Total Scoring Module: Calculate the quality assessment score of the target supplier according to the first weight and the first score.

[0011] On the other hand, the Total Index Module includes:

[0012] Supplier Unit: Identify the target supplier, obtain the service content and contract requirements of the target supplier, and obtain the management system of the target supplier;

[0013] Assessment Index Unit: Determine five types of quality assessment indexes for service efficiency, service quality, service cost, service safety and user experience, clarify the sub-indexes of the quality assessment indexes based on the service content and contract requirements, add a first index to the quality assessment indexes, and add a second index to the sub-indexes.

[0014] On the other hand, the data collection module includes:

[0015] Data Source Unit: Based on the management system of the target supplier, obtain the data source connection information;

[0016] Collection Unit: Based on the quality assessment indexes and their sub-indexes, define data fields and query dimensions, generate a query statement to collect the historical performance data of the target supplier through the data source;

[0017] Preprocessing Unit: Perform missing value and outlier preprocessing on the historical performance data of any parameter type, specifically:

[0018] Among them, represents the i-th first data of the parameter type, x i+1 represents the (i + 1)-th historical performance data of the parameter type, x i-1 represents the (i - 1)-th historical performance data of the parameter type, x avg represents the mean of the historical performance data of the parameter type, and n represents that there are n historical performance data of the parameter type in total;

[0019] Standardization Unit: Standardize the first data of the parameter type according to statistical methods to obtain the standard performance data of the parameter type.

[0020] On the other hand, the first scoring module includes:

[0021] Sub-index Initial Scoring Unit: Used to obtain the standard performance data corresponding to all sub-indexes of any quality assessment index, and query the corresponding sub-index initial score in the quantization method based on the first index and the second index;

[0022] First Scoring Determination Unit: Based on the initial scores of all sub-indexes of the quality assessment index, obtain the first score of the quality assessment index as:

[0023] Among them, S represents the first score of the quality assessment index, w k represents the initial weight of the quality assessment index, f kRepresents the initial score of the k-th sub-index of the quality assessment index.

[0024] On the other hand, for the dynamic weight module, the business scenario-aware weight adjustment strategy is as follows:

[0025] Increase the weight of the service efficiency dimension by 15%, the weight of the service security dimension by 10%, and decrease the weights of the service quality, user experience, and cost dimensions by 10%, 5%, and 10% respectively;

[0026] When a security vulnerability attack is detected, increase the weight of the service security dimension by 30%, and decrease the weights of the service efficiency, service quality, and user experience dimensions by 10% each;

[0027] During the year-end operation and maintenance planning period, increase the weight of the service cost dimension by 15% and decrease the weight of the service efficiency dimension by 15%;

[0028] In the initial stage of the new system launch, increase the weight of the service quality dimension by 10% and the weight of the user experience dimension by 5%, and decrease the weight of the service efficiency dimension by 15%;

[0029] Based on the business scenario-aware weight adjustment strategy, adjust the initial weight of the corresponding quality assessment index to obtain the first weight.

[0030] On the other hand, the dynamic weight module satisfies the constraint condition: Among them, Y i Represents the first weight of the j-th quality assessment index after dynamic adjustment, and the weight adjustment range of a single dimension does not exceed ±30% of the initial weight.

[0031] On the other hand, the total score module includes:

[0032] Weighted scoring unit: According to the first weight and the first score, calculate the quality assessment score of the target supplier as: Among them, Q represents the quality assessment score of the target supplier, and Y p Represents the first weight of the p-th quality assessment index, and S p Represents the first score of the p-th quality assessment index;

[0033] Rating unit: According to the quality assessment score of the target supplier, match the corresponding level in the preset rating table to obtain the final rating of the target supplier.

[0034] On the other hand, the present invention provides a method for managing the quality assessment of supplier services based on dynamic weight optimization, including:

[0035] Step 1: According to the service content of the supplier and the contract requirements, determine five types of quality assessment indicators and their sub-indicators, namely service efficiency, service quality, service cost, service security, and user experience;

[0036] Step 2: Collect the historical performance data of the target supplier, and preprocess and standardize it to obtain the standard performance data;

[0037] Step 3: Determine the first score of the quality assessment index according to the initial weight and quantification method of the quality assessment index, in combination with the standard performance data;

[0038] Step 4: Generate a weight adjustment strategy according to the business scenario of the standard performance data, and adjust the initial weight to obtain the first weight of the quality assessment index;

[0039] Step 5: Calculate the quality assessment score of the target supplier according to the first weight and the first score.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0041] The present invention provides a supplier service quality assessment management system and method based on dynamic weight optimization, which is used to accurately quantify the service efficiency and service quality of suppliers through a perfect assessment index of IT operation and maintenance service suppliers and an assessment method with dynamic weights, and accurately judge the service results of operation and maintenance suppliers through the quantification results of the cost-output ratio and user experience indicators. Brief Description of the Drawings

[0042] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 It is a schematic structural diagram of a supplier service quality assessment management system based on dynamic weight optimization provided by an embodiment of the present invention;

[0044] Figure 2 It is a schematic flowchart of a supplier service quality assessment management method based on dynamic weight optimization provided by an embodiment of the present invention.

[0045] Figure 3 It is a visualization quantification example diagram of the present invention. Detailed Embodiments

[0046] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts fall within the scope of protection of the present invention.

[0047] Embodiment 1:

[0048] As Figure 1 shown, a supplier service quality assessment and management system based on dynamic weight optimization provided by an embodiment of the present invention includes:

[0049] Total index module: Determine five types of quality assessment indicators and their sub-indicators, namely service efficiency, service quality, service cost, service safety and user experience, according to the service content of the supplier and the contract requirements;

[0050] Data acquisition module: Collect the historical performance data of the target supplier and preprocess and standardize it to obtain the standard performance data;

[0051] First scoring module: Determine the first score of the quality assessment indicators in combination with the standard performance data according to the initial weights and quantification methods of the quality assessment indicators;

[0052] Dynamic weight module: Generate a weight adjustment strategy according to the business scenario of the standard performance data, and obtain the first weight of the quality assessment indicators after adjusting the initial weights;

[0053] Total scoring module: Calculate the quality assessment score of the target supplier according to the first weight and the first score.

[0054] In this embodiment, the supplier refers to a company or organization that provides goods or services, usually a partner of an enterprise or organization, and is responsible for delivering products or services according to the contract requirements.

[0055] In this embodiment, the service content refers to the specific service type or product content provided by the supplier, such as: product quality, delivery date, installation standard, maintenance terms, etc.

[0056] In this embodiment, the contract requirements refer to various specific terms and conditions agreed upon by the supplier and the customer when signing the contract. These requirements are the basis for the supplier to provide services or deliver products, such as: specific descriptions of services or products, delivery time and location, safety requirements for services, etc.

[0057] In this embodiment, service efficiency refers to the ability of a supplier to complete tasks, deliver services or products within the agreed time, and the efficiency of the service is dynamically weighted and quantified through indicators such as the mean time to repair (MTTR), service response timeliness rate, and failure repair compliance rate.

[0058] In this embodiment, service quality reflects the ability of a supplier to solve problems, and the service quality is dynamically weighted and quantified through indicators such as the fault recurrence rate, change success rate, and vulnerability repair rate.

[0059] In this embodiment, service cost refers to all the expenses incurred by a supplier in the process of providing services. Based on the quantified service efficiency and service quality data, and according to the signed service level agreement, the input-output ratio is evaluated.

[0060] In this embodiment, user experience refers to the overall feeling and satisfaction obtained by a customer during the interaction with the services or products provided by a supplier, and the user experience of the service is quantified through indicators such as the user satisfaction index and service contribution index.

[0061] In this embodiment, service security refers to whether the services provided by a supplier can ensure the security of customer data, information, and assets during the entire delivery process, and the security of the service is quantified through indicators such as security incidents and vulnerability repair rate.

[0062] In this embodiment, quality assessment indicators are key factors used to measure the comprehensive performance of a supplier when providing services.

[0063] In this embodiment, sub-indicators are specific quantitative indicators used to measure the performance of each quality assessment indicator (service efficiency, service quality, service cost, service security, user experience), including: fault recurrence rate, change success rate, vulnerability repair rate, user satisfaction index, service contribution index, etc.

[0064] In this embodiment, historical performance data refers to the actual data shown by a target supplier in the past period of time based on different quality assessment indicators (such as service efficiency, service quality, service cost, service security, user experience).

[0065] In this embodiment, preprocessing standardization refers to the preliminary processing of the historical performance data of a target supplier in the data collection module to ensure that these data can be compared and analyzed according to a unified standard.

[0066] In this embodiment, standard performance data refers to the historical performance data of a target supplier after passing through the data collection module and preprocessing standardization.

[0067] In this embodiment, the initial weight refers to the preset proportion of the quality assessment indicators before dynamic adjustment, including: service efficiency (initial weight 30%), service quality (initial weight 25%), service cost (initial weight 20%), safety (initial weight 15%), and user experience (initial weight 10%).

[0068] In this embodiment, the quantification method refers to how to convert each quality assessment indicator (such as service efficiency, service quality, service cost, service safety, and user experience, etc.) into specific numerical values through certain mathematical or statistical means. For example, for the service efficiency quality assessment indicator, the specific score values for the sub - indicators are as follows: Average fault repair time (40 points):

[0069] Σ(Single - fault recovery time) / Total number of faults;

[0070] When the average fault repair time <= 70% of the protocol time, the score is: 40 points;

[0071] When 70% of the protocol time < average fault repair time <= 80% of the protocol time, the score is: 30 points;

[0072] When 80% of the protocol time < average fault repair time <= 90% of the protocol time, the score is: 20 points;

[0073] When 90% of the protocol time < average fault repair time <= the protocol time, the score is: 10 points;

[0074] When the average fault repair time > the protocol time, the score is: 0 points;

[0075] Service response timeliness rate (30 points):

[0076] Number of faults with timely response / Total number of system faults × 100%;

[0077] When the service response timeliness rate >= 90%, the score is: 30 points;

[0078] When the service response timeliness rate >= 80%, the score is: 20 points;

[0079] When the service response timeliness rate >= 70%, the score is: 10 points;

[0080] When the service response timeliness rate < 70%, the score is: 0 points;

[0081] Fault repair compliance rate (30 points):

[0082] Number of faults repaired on time / Total number of system faults × 100%;

[0083] When the fault repair compliance rate >= 90%, the score is: 30 points;

[0084] When the failure repair compliance rate >= 80%, the score is: 20 points;

[0085] When the failure repair compliance rate >= 70%, the score is: 10 points;

[0086] When the failure repair compliance rate < 70%, the score is: 0 points;

[0087] In this embodiment, the first scoring refers to the initial scores of each indicator calculated based on the standard performance data of the target supplier and the initial weights of the quality assessment indicators in the initial stage of the scoring process.

[0088] In this embodiment, the business scenario refers to a specific business environment, such as: detecting a security vulnerability attack, in the initial stage of a new system going online, etc.

[0089] In this embodiment, the first weight is the result of adjusting the initial weight in combination with the business scenario weight adjustment strategy.

[0090] In this embodiment, the weight adjustment strategy is a method generated by the dynamic weight module based on the standard performance data and the business scenario, used to adjust the initial weight. For example, during the year-end operation and maintenance planning period, increase the weight of the service cost dimension by 15% and decrease the weight of the service efficiency dimension by 15%.

[0091] In this embodiment, the quality assessment score

[0092] The working principle and beneficial effects of the above technical solution are: By dynamically adjusting the weights and the quantitative scoring method, optimizing the quality assessment of suppliers, ensuring accurate and flexible scoring, adapting to different business scenarios, improving the efficiency of supplier management, and promoting supply chain optimization and long-term cooperation relationships.

[0093] Embodiment 2:

[0094] Based on the above Embodiment 1, the total indicator module includes:

[0095] Supplier unit: Identify the target supplier, obtain the service content and contract requirements of the target supplier, and obtain the management system of the target supplier;

[0096] Assessment indicator unit: Determine five types of quality assessment indicators for service efficiency, service quality, service cost, service security, and user experience, and clarify the sub-indicators of the quality assessment indicators based on the service content and contract requirements, add a first index to the quality assessment indicators, and add a second index to the sub-indicators.

[0097] In this embodiment, the management system refers to a tool platform for monitoring, managing, and evaluating aspects such as supplier behavior, service quality, and contract execution.

[0098] In this embodiment, the first index is a tool for classifying, coding, and identifying quality assessment indicators.

[0099] In this embodiment, the second index is a tool for more refined classification and identification of sub-indicators of quality assessment indicators.

[0100] The working principle and beneficial effects of the above technical solution are as follows: By clarifying the supplier and service content, setting quality assessment indicators and sub-indicators in combination with contract requirements, and adding indexes to them, it ensures that the assessment criteria are clear and systematic, which helps to improve the accuracy of supplier evaluation and management efficiency.

[0101] Embodiment 3:

[0102] Based on the above Embodiment 2, the data acquisition module includes:

[0103] Data source unit: Based on the management system of the target supplier, obtain data source connection information;

[0104] Collection unit: Based on the quality assessment indicators and their sub-indicators, define data fields and query dimensions, and generate a query statement to collect the historical performance data of the target supplier through the data source;

[0105] Preprocessing unit: Perform preprocessing of missing values and outliers on the historical performance data of any parameter type, specifically:

[0106] Among them, represents the i-th first data of the parameter type, x i+1 represents the (i + 1)-th historical performance data of the parameter type, x i-1 represents the (i - 1)-th historical performance data of the parameter type, x avg represents the average value of the historical performance data of the parameter type, and n represents that there are n historical performance data of the parameter type in total;

[0107] Standardization unit: Standardize the first data of the parameter type according to statistical methods to obtain the standard performance data of the parameter type.

[0108] In this embodiment, the data source connection information refers to various configurations and information required to connect to an external data source, including: IP, port number, database name, etc.

[0109] In this embodiment, the query statement is to extract the historical performance data of the target supplier and perform screening and summarization according to the defined fields and query dimensions.

[0110] In this embodiment, the missing value refers to that some data items in the data set are not recorded, collected, or calculated, and are manifested as "null value" or "no value".

[0111] In this embodiment, an outlier refers to a value in a dataset that significantly deviates from other data points.

[0112] In this embodiment, the statistical method is through statistical indicators, including: mean, variance, median, etc. For example: Among them, z0 i1 represents the i1-th standard performance data of the parameter type, z i1 represents the i1-th first data of the parameter type, μ represents the mean of the parameter type, and σ represents the standard deviation of the parameter type.

[0113] The working principle and beneficial effects of the above technical solution are: By collecting and preprocessing the historical performance data of the target supplier, dealing with missing values and outliers, and standardizing, the accuracy and consistency of the data are ensured, providing a reliable basis for subsequent scoring and evaluation, and improving the scientificity and fairness of supplier assessment.

[0114] Example 4:

[0115] Based on the above Example 2, the first scoring module includes:

[0116] Sub-index initial scoring unit: used to obtain the standard performance data corresponding to all sub-indices of any quality assessment indicator, and query the corresponding sub-index initial score in the quantization method based on the first index and the second index;

[0117] First scoring determination unit: Based on the initial scores of all sub-indices of the quality assessment indicator, the first score of the quality assessment indicator is obtained as:

[0118] Among them, S represents the first score of the quality assessment indicator, w k represents the initial weight of the quality assessment indicator, f k represents the initial score of the k-th sub-index of the quality assessment indicator.

[0119] In this embodiment, the initial score refers to the preliminary score assigned to each sub-index based on certain standard performance data and corresponding quantization methods when quantifying the quality assessment indicator. For example: the initial score of the user satisfaction index is 50 points, the initial score of the security incident repair rate is 50 points, and the initial score of the vulnerability repair rate is 50 points.

[0120] In this embodiment, the explanation of the relevant sub-index is: The mean time to repair (MTTR) represents the average time taken to repair a system failure from occurrence, calculated by (Σ (single failure recovery time) / total number of failures). When the value of MTTR is less than or equal to the time agreed in the service level agreement (SLA), the service quality of the supplier is qualified; otherwise, it is unqualified.

[0121] A Service Level Agreement (SLA) represents a formal contract between a service provider and a customer, clearly defining the quality standards, performance metrics, and the responsibilities and obligations of both parties. An SLA typically includes key metrics such as service availability, response time, and fault resolution time, and specifies the compensation measures in case the agreed-upon standards are not met. Through the SLA, the customer can ensure that the service quality meets expectations, while the service provider can clarify service goals and reduce disputes.

[0122] The service response timeliness rate represents the ratio of responses to system failures within a specified time (e.g., 15 minutes), calculated as (the number of faults with timely responses / the total number of system faults × 100%). When the system is in the peak business period, this weight is automatically increased by 5 - 15%.

[0123] The fault repair compliance rate represents the ratio of repairs to system failures within a specified time (e.g., 45 minutes), calculated as (the number of faults repaired on time / the total number of system faults × 100%). When the system is in the peak business period, this weight is automatically increased by 15 - 30%.

[0124] The fault recurrence rate represents the ratio of the recurrence of the same type of fault points on the same device within 30 days after repair, calculated as (the number of devices with repeated faults / the total number of faulty devices × 100%). When the recurrence rate is greater than 5%, the service quality of the service provider is unqualified; otherwise, it is qualified.

[0125] The change success rate represents the ratio of successful configuration change operations at one time, calculated as (the number of successful changes / the total number of changes × 100%). When the change success rate is less than 10%, it indicates that the service quality of the service provider is unqualified; otherwise, it is qualified.

[0126] The vulnerability repair rate represents the repair ratio of high - risk vulnerabilities within the time specified in the SLA.

[0127] The security incident repair rate represents the repair ratio of security incidents that occurred within the time specified in the SLA.

[0128] The user satisfaction index represents the comprehensive evaluation of the service quality of the service provider by end - users. It is obtained from the immediate evaluation after service completion (accounting for 60%) and the quarterly questionnaire survey score (accounting for 40%).

[0129] The service contribution degree represents the comprehensive evaluation of the service contribution of the service provider. It is obtained by integrating the service catalog contribution degree of the faults repaired by the service provider (accounting for 50%) and the service agreement level contribution degree (accounting for 50%).

[0130] User roles can be divided into three types: service providers, rule administrators, and end - users. Among them:

[0131] Service provider: Responsible for providing IT fault repair services and signing service level agreements (SLAs) with end users.

[0132] Rule administrator: Responsible for operations such as creating, modifying, starting, stopping, uploading, destroying rules for quantifying service efficiency and service quality, and setting dynamic weights.

[0133] End user: Responsible for discovering and submitting IT fault problems.

[0134] The working principle and beneficial effects of the above technical solution are: Through the technical acquisition solution, the data standard of the sub-standard index according to the index is obtained, and combined with the initial data and initial scores and weights, the first score of each quality assessment index calculated by the weight is calculated, providing an accurate basis for the final score. Subsequently, the weight adjustment and scoring improve the scientific nature of the supplier assessment.

[0135] Example 5:

[0136] Based on the above Example 1, for the dynamic weight module, the business scenario perception weight adjustment strategy is:

[0137] Increase the weight of the service efficiency dimension by 15%, the weight of the service security dimension by 10%, and reduce the weights of the service quality, user experience, and cost dimensions by 10%, 5%, and 10% respectively;

[0138] When a security vulnerability attack is detected, increase the weight of the service security dimension by 30%, and reduce the weights of the service efficiency, service quality, and user experience dimensions by 10% each;

[0139] During the year-end operation and maintenance planning period, increase the weight of the service cost dimension by 15% and reduce the weight of the service efficiency dimension by 15%;

[0140] In the initial stage of the new system launch, increase the weight of the service quality dimension by 10% and the weight of the user experience dimension by 5%, and reduce the weight of the service efficiency dimension by 15%;

[0141] Based on the business scenario perception weight adjustment strategy, adjust the initial weight of the corresponding quality assessment index to obtain the first weight.

[0142] The working principle and beneficial effects of the above technical solution are: By dynamically adjusting the weights of each dimension according to different business scenarios, flexibly responding to the demand changes in different stages, optimizing service assessment, improving the accuracy and response ability of supplier management, and ensuring that the assessment results are more in line with the actual situation and goals.

[0143] Example 6:

[0144] Based on the above Example 1, the dynamic weight module satisfies the constraint conditions: Among them, Y i represents the first weight of the j-th quality assessment index after dynamic adjustment, and the weight adjustment range of a single dimension does not exceed ±30% of the initial weight.

[0145] In this embodiment, the dimension refers to different aspects or indicators used to evaluate and quantify service quality.

[0146] The working principle and beneficial effects of the above technical solution are: by dynamically adjusting the weights of each quality assessment index, ensuring that the weight adjustment range of a single dimension does not exceed ±30% of the initial value, while ensuring flexibility, avoiding excessive adjustment, and improving the stability of weight adjustment and the reliability of assessment results.

[0147] Embodiment 7:

[0148] Based on the above Embodiment 5, the total score module includes:

[0149] Weighted scoring unit: According to the first weight and the first score, calculate the quality assessment score of the target supplier as: Among them, Q represents the quality assessment score of the target supplier, and Y p represents the first weight of the p-th quality assessment index, and S p represents the first score of the p-th quality assessment index;

[0150] Rating unit: According to the quality assessment score of the target supplier, match the corresponding level in the preset rating table to obtain the final rating of the target supplier.

[0151] In this embodiment, the preset rating table refers to a pre-defined table used to convert the quality assessment score of the target supplier into a specific rating.

[0152] In this embodiment, the level refers to a specific grade assigned to the target supplier according to its quality assessment score.

[0153] In this embodiment, the visual quantitative example is Figure 3 as shown.

[0154] In this embodiment, the final rating is determined according to the quality assessment score of the target supplier, and the score is converted into a grade according to a set of preset rating tables.

[0155] The working principle and beneficial effects of the above technical solution are: through the weighted scoring and rating units, calculate the quality assessment score of the target supplier according to the first weight and score, and perform the final rating through the preset rating table, ensuring the fairness and transparency of the scoring process, providing accurate supplier evaluation results, and helping to optimize supplier management.

[0156] Example 8:

[0157] As Figure 2 shown, a method for evaluating and managing the service quality of suppliers based on dynamic weight optimization provided by an embodiment of the present invention includes:

[0158] Step 1: Determine five types of quality assessment indicators and their sub-indicators, namely service efficiency, service quality, service cost, service security, and user experience, according to the service content of the supplier and the contract requirements;

[0159] Step 2: Collect the historical performance data of the target supplier and preprocess and standardize it to obtain the standard performance data;

[0160] Step 3: Determine the first score of the quality assessment indicators according to the initial weights and quantification methods of the quality assessment indicators and in combination with the standard performance data;

[0161] Step 4: Generate a weight adjustment strategy according to the business scenario of the standard performance data, and obtain the first weight of the quality assessment indicators after adjusting the initial weights;

[0162] Step 5: Calculate the quality assessment score of the target supplier according to the first weight and the first score.

[0163] The working principle and beneficial effects of the above technical solution are: By dynamically adjusting the weights and quantification scoring methods, the quality assessment of suppliers is optimized, ensuring accurate and flexible scoring, adapting to different business scenarios, improving the efficiency of supplier management, and promoting supply chain optimization and long-term cooperative relationships.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A supplier service quality assessment and management system based on dynamic weight optimization, characterized in that Including: Total Index Module: Determine five types of quality assessment indicators and their sub-indicators for service efficiency, service quality, service cost, service security, and user experience according to the supplier service content and contract requirements; Data Collection Module: Collect historical performance data of the target supplier and preprocess and standardize it to obtain standard performance data; First Scoring Module: Determine the first score of the quality assessment indicators according to the initial weights and quantification methods of the quality assessment indicators, in combination with the standard performance data; Dynamic Weight Module: Generate a weight adjustment strategy according to the business scenario of the standard performance data, and adjust the initial weight to obtain the first weight of the quality assessment indicators; Total Scoring Module: Calculate the quality assessment score of the target supplier according to the first weight and the first score.

2. The supplier service quality assessment and management system based on dynamic weight optimization according to claim 1, wherein, Total Index Module, including: Supplier Unit: Identify the target supplier, obtain the service content and contract requirements of the target supplier, and obtain the management system of the target supplier; Assessment Indicator Unit: Determine five types of quality assessment indicators for service efficiency, service quality, service cost, service security, and user experience, and clarify the sub-indicators of the quality assessment indicators based on the service content and contract requirements, add a first index to the quality assessment indicators, and add a second index to the sub-indicators.

3. The supplier service quality assessment and management system based on dynamic weight optimization according to claim 2, wherein Data Collection Module, including: Data Source Unit: Obtain data source connection information based on the management system of the target supplier; Collection Unit: Define data fields and query dimensions based on the quality assessment indicators and their sub-indicators, generate a query statement, and collect historical performance data of the target supplier through the data source; Preprocessing Unit: Perform missing value and outlier preprocessing on the historical performance data of any parameter type, specifically: Among them, represents the i-th first data of the parameter type, x i+1 represents the (i + 1)-th historical performance data of the parameter type, x i-1 represents the (i - 1)-th historical performance data of the parameter type, x avg represents the mean of the historical performance data of the parameter type, and n represents that there are n historical performance data of the parameter type; Standardization Unit: Standardize the first data of the parameter type according to statistical methods to obtain the standard performance data of the parameter type.

4. The supplier service quality assessment and management system based on dynamic weight optimization according to claim 2, characterized in that First Scoring Module, including: Sub-indicator Initial Scoring Unit: Used to obtain the standard performance data corresponding to all sub-indicators of any quality assessment indicator, and query the corresponding sub-indicator initial scores based on the first index and the second index in the quantification method; First Score Determination Unit: Based on the initial scores of all sub-indicators of the quality assessment indicator, the first score of the quality assessment indicator is obtained as: Among them, S represents the first score of the quality assessment index, w k represents the initial weight of the quality assessment index, f k represents the initial score of the k-th sub-index of the quality assessment index.

5. The supplier service quality assessment and management system based on dynamic weight optimization according to claim 1, characterized in that For the Dynamic Weight Module, the business scenario-aware weight adjustment strategy is: Increase the weight of the service efficiency dimension by 15%, the weight of the service security dimension by 10%, and reduce the weights of the service quality, user experience, and cost dimensions by 10%, 5%, and 10% respectively; When a security vulnerability attack is detected, increase the weight of the service security dimension by 30%, and reduce the weights of the service efficiency, service quality, and user experience dimensions by 10% respectively; During the year-end operation and maintenance planning period, increase the weight of the service cost dimension by 15% and reduce the weight of the service efficiency dimension by 15%; In the initial stage of the new system launch, increase the weight of the service quality dimension by 10% and the weight of the user experience dimension by 5%, and reduce the weight of the service efficiency dimension by 15%; Based on the business scenario-aware weight adjustment strategy, adjust the initial weight of the corresponding quality assessment indicator to obtain the first weight.

6. The supplier service quality assessment and management system based on dynamic weight optimization according to claim 1, characterized in that The dynamic weight module satisfies the following constraint condition: where Y i represents the first weight of the j-th quality assessment index after dynamic adjustment, and the weight adjustment range of a single dimension does not exceed ±30% of the initial weight.

7. The supplier service quality assessment and management system based on dynamic weight optimization according to claim 5, characterized in that The Total Scoring Module, including: Weighted scoring unit: Calculate the quality assessment score of the target supplier according to the first weight and the first score as follows: where Q represents the quality assessment score of the target supplier, and Y p represents the first weight of the p-th quality assessment indicator, and S p represents the first score of the p-th quality assessment indicator; Rating unit: According to the quality assessment score of the target supplier, match the corresponding level in the preset rating form to obtain the final rating of the target supplier.

8. A method for evaluating and managing the service quality of suppliers based on dynamic weight optimization, which is applied to a system for evaluating and managing the service quality of suppliers based on dynamic weight optimization as described in any one of claims 1-7, and is characterized in that, Including: Step 1: Determine five types of quality assessment indicators and their sub-indicators, namely service efficiency, service quality, service cost, service safety, and user experience, according to the service content of the supplier and the contract requirements. Step 2: Collect the historical performance data of the target supplier and preprocess and standardize it to obtain the standard performance data. Step 3: Determine the first score of the quality assessment indicator according to the initial weight and quantification method of the quality assessment indicator, in combination with the standard performance data. Step 4: Generate a weight adjustment strategy according to the business scenario of the standard performance data, and adjust the initial weight to obtain the first weight of the quality assessment indicator. Step 5: Calculate the quality assessment score of the target supplier according to the first weight and the first score.

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