A quantitative method, device and electronic equipment for evaluating information technology service capability

Abstract

The present application relates to the field of quantitative evaluation, and discloses a quantitative method, device and electronic device for evaluating information technology service capabilities. The method includes: determining the weight value of each indicator in a preset indicator system architecture; wherein the preset indicator system architecture includes subjective indicators and objective indicators; determining an importance value set for identifying the importance of the evaluator based on the initial scores of all subjective indicators, and determining an importance value ranking set, and determining the final score of each subjective indicator based on the importance value set, the importance value ranking set and the preset percentage value; determining the final score of each objective indicator through a preset objective indicator evaluation model based on the initial score of each objective indicator; determining the information technology service capability evaluation value based on the weight value of each indicator and the final score of each indicator. Extracting the scores of the main evaluators and scientifically synthesizing the evaluation results can effectively eliminate the interference of human factors and improve the robustness of the evaluation results.

Description

Technical Field

[0001] The present application relates to the field of quantitative evaluation technology, and in particular to an information technology service capability evaluation quantitative method, device, computer program product, storage medium and electronic device. Background Art

[0002] The purpose of the background technology description provided here is to give an overall background of the present application. The statements in this section merely provide background related to the present application and do not necessarily constitute prior art.

[0003] Information technology services refer to business activities that provide technical services to clients by utilizing computing resources, storage resources, network resources, data resources, security resources, management resources, technical resources, and software resources. They are the core force leading scientific and technological innovation and driving economic and social transformation and development, and play an important role in digital transformation.

[0004] With the innovation of technology and service models, it continues to become the engine of the new era. For technology service providers, information technology services are the core value of enterprise business value-added. By continuously improving service capabilities, economic benefits and enterprise value growth can be achieved. For information technology service customers, information technology services can help customers achieve digital transformation and upgrades, optimize work processes and operational management, reduce management costs, and improve the quality and efficiency of products and services.

[0005] At the same time, information technology services can enhance the innovation of user technology products, improve the market competitiveness of products and services, expand sales channels and enhance the core competitiveness of enterprises. In addition, information technology services can also promote the optimization of user experience and the improvement of service quality.

[0006] In addition, in the field of information security, information technology services continue to promote the closed-loop optimization of security technology revolution and security management. The application of information technology services in the digital transformation of enterprises has gradually become a trend in all walks of life, and it has become an industry consensus to improve the effect of digital transformation through information technology services. In view of this, information technology services play an important role and significance for the healthy development and capacity improvement of various industries.

[0007] However, in the process of application and development, due to the advanced technology and innovative service model, information technology services have a series of problems in organizational management, business operations, technical operation and maintenance, technology research and development, security, service response, service availability, and service reliability. At the same time, information technology services lack unified cognition in terms of technical capabilities and management levels, resulting in non-standard and immature technical services, and the inability to effectively quantify information technology service capabilities, which seriously affects the healthy development of the industry and the market. As an effective means of effective supervision and auditing of services, information technology service capability assessment has become an important tool for continuously promoting the transformation and upgrading of the digital economy, standardizing the service market, and optimizing service organizations. It can provide a methodology for the healthy development and iterative optimization of the service system. Summary of the invention

[0008] In view of the above problems, the present application proposes a quantitative method, device, computer program product, storage medium and electronic device for evaluating information technology service capabilities. A basic indicator system structure for information technology service evaluation is disclosed, which divides the evaluation indicators into subjective indicators and objective indicators. Specifically, the evaluation method adopts a quantitative method, and uses the analytic hierarchy process (AHP) to determine the indicator weights between each dimension and each level, including the weights between subjective factor indicators and objective indicators. The scoring of subjective indicators is quantified in the form of scoring by evaluators, and the objective indicators are based on the quantitative results of actual evaluation. Innovative cost-based indicator quantification methods and benefit-based indicator quantification methods based on Logistic functions are constructed, and quantification is performed in combination with the threshold requirements of each indicator. In the AHP expert weight synthesis link, the judgment matrix correlation measurement based on the Spearman rank correlation coefficient is used to form a group decision algorithm for fusion scoring.

[0009] In a first aspect of the present application, a quantitative method for evaluating information technology service capabilities is provided, the method comprising:

[0010] Determine the weight value of each indicator in the preset indicator system architecture; wherein the preset indicator system architecture includes multiple subjective indicators and multiple objective indicators;

[0011] Determine an importance value set for identifying the importance of the evaluator according to the initial scores of all subjective indicators, determine an importance value ranking set according to the importance value set, and determine the final score of each subjective indicator according to the importance value set, the importance value ranking set and a preset percentage value; wherein the initial score of the subjective indicator is obtained by a first preset method;

[0012] Determining the final score of each objective indicator through a preset objective indicator evaluation model according to the initial score of each objective indicator; wherein the initial score of the objective indicator is obtained through a second preset method;

[0013] The information technology service capability assessment value is determined based on the weight value of each indicator and the final score of each indicator.

[0014] Furthermore, the preset objective indicator evaluation model includes a cost-based evaluation model and a benefit-based evaluation model; the final score of each objective indicator is determined by the preset objective indicator evaluation model, including:

[0015] Determine the indicator type of the objective indicator; wherein the indicator type includes cost-based indicators and benefit-based indicators;

[0016] In the case where the indicator type is a cost-based indicator, the final score of the objective indicator is determined by the cost-based evaluation model;

[0017] When the indicator type is a benefit-type indicator, the final score of the objective indicator is determined by the benefit-type evaluation model.

[0018] Furthermore, the determination of a ranking set for identifying the importance of the evaluators according to the initial scores of all subjective indicators includes:

[0019] Generate an initial scoring matrix based on the initial scores of all subjective indicators; wherein the rows of the initial scoring matrix represent indicators, and the columns of the initial scoring matrix represent the scores of the evaluators;

[0020] Determine the median of each row of the initial scoring matrix and generate a median vector of the initial scoring matrix;

[0021] According to the initial scoring matrix, respectively determine the column vector corresponding to each evaluator;

[0022] Determine the importance value of each evaluator according to the column vector corresponding to each evaluator and the median vector;

[0023] The rank corresponding to each evaluator is determined according to the importance value of each evaluator, and the rank corresponding to each evaluator is stored in a set to generate a rank set identifying the importance of the evaluator.

[0024] Furthermore, the importance value of the evaluator is determined by the following formula:

[0025]

[0026] Among them, I a is the importance value of the ath evaluator, A is the index set of the columns of the initial rating matrix, dc ais the center distance of the column vector corresponding to the a-th evaluator, dc i is the center distance of the column vector corresponding to the i-th evaluator; where the center distance is determined by the following formula:

[0027]

[0028] Among them, dc a is the center distance of the column vector corresponding to the a-th evaluator, V a is the column vector corresponding to the a-th evaluator, V i is the column vector corresponding to the i-th evaluator, V c is the median vector.

[0029] Furthermore, determining the final score of each subjective indicator according to the ranking set and the preset percentage value includes:

[0030]

[0031] Where j is the serial number of the subjective indicator in the preset indicator system architecture; I a is the importance value of the ath evaluator; S ja is the initial score of the ath evaluator on the jth subjective indicator in the preset indicator system architecture; SU j is the final score of the jth subjective indicator in the preset indicator system architecture; AN rat is the set of ratio importance evaluators, AN rat Determined by the following formula based on the preset percentage value:

[0032] I={I i |i∈A}

[0033] AN rat =R(1:y)

[0034]

[0035] Among them, I is a set of importance values; A is a set of indexes of the columns of the initial rating matrix; rat is a preset percentage value; R is a set of importance value rankings corresponding to I; y is the number of evaluators in I whose cumulative importance values ​​are not less than rat; R(1:y) is a set of serial numbers corresponding to the first y evaluators in I; i is a position index of an element in I; j is a position index of an element in R, and k is the upper limit of j.

[0036] Furthermore, the determining of the weight value of each indicator in the preset indicator system architecture includes:

[0037] For any indicator with sub-indicators in the preset indicator system architecture, a judgment matrix for determining the weight of each sub-indicator is generated according to the sub-indicators of the indicator; wherein the order of the judgment matrix is ​​equal to the number of sub-indicators, and the value of each element in the judgment matrix represents the ratio of the importance between the sub-indicator corresponding to the corresponding row index and the column index;

[0038] issuing a scoring reminder so that a plurality of experts can provide feedback on the judgment matrix by filling in values ​​for the judgment matrix respectively; wherein the value of each element in the judgment matrix is ​​determined by a preset scaling method;

[0039] For any judgment matrix that has passed the consistency test and is fed back by an expert, the initial weight value of each sub-indicator is determined according to the value of the element in the judgment matrix, wherein the initial weight value is the weight value determined for the sub-indicator by the expert who fed back the judgment matrix;

[0040] Determine the weight value of each expert based on the judgment matrix that has passed the consistency test and is fed back by all evaluators;

[0041] For any sub-indicator, the final weight value of the sub-indicator is determined according to the weight values ​​of each expert and the initial weight value of the sub-indicator determined by each expert, and the final weight value is used as the weight value of the sub-indicator.

[0042] Furthermore, after determining the value of each element in the judgment matrix, it also includes:

[0043] Determine the maximum eigenvalue of the judgment matrix based on the values ​​of each element in the judgment matrix determined by the experts;

[0044] Determining a consistency index according to the maximum eigenvalue and the order of the judgment matrix, and determining a consistency ratio of the judgment matrix according to the consistency index;

[0045] When the consistency ratio does not satisfy a preset consistency condition, a correction reminder message is issued, so that the expert corrects the value of the element in the judgment matrix according to the correction reminder message;

[0046] When the consistency ratio meets the preset consistency condition, it is determined that the judgment matrix fed back by the expert passes the consistency test.

[0047] Furthermore, the step of determining the weight value includes:

[0048] Taking the judgment matrix fed back by the current expert as a benchmark judgment matrix, determining the rank correlation values ​​between the benchmark judgment matrix and the judgment matrices fed back by other experts respectively, and generating a correlation matrix according to all the rank correlation values;

[0049] According to the correlation matrix, the weight value is determined by the following formula:

[0050]

[0051] Among them, w i is the weight of the ith expert, the number of rows and columns of the correlation matrix are both p, x ij Represents the j-th column element in the i-th row of the correlation matrix.

[0052] Furthermore, the judgment matrix fed back by the current expert is used as a reference judgment matrix, and the rank correlation values ​​between the reference judgment matrix and the judgment matrices fed back by other experts are determined respectively, including:

[0053] Extract the elements not including the main diagonal from each judgment matrix in row priority order, and generate the judgment matrix vector corresponding to each judgment matrix;

[0054] According to the value of each element in the judgment matrix vector, the elements in the judgment matrix vector are sorted in descending order, and the rank vectors corresponding to each judgment matrix are generated according to the judgment matrix vectors sorted in descending order;

[0055] According to the rank vector corresponding to the reference judgment matrix, the rank correlation values ​​between the rank vector corresponding to the reference judgment matrix and the rank vectors corresponding to other judgment matrices are determined respectively; wherein the rank correlation value is determined by the following formula:

[0056]

[0057] n=m 2 -m

[0058] Among them, x ij is the rank correlation value between the rank vector corresponding to the judgment matrix i and the rank vector corresponding to the judgment matrix j, d ijk is the difference between the rank at position k in the rank vector corresponding to the judgment matrix i and the rank at position k in the rank vector corresponding to the judgment matrix j, and m is the number of rows of the judgment matrix i.

[0059] Optionally, generate a rank vector corresponding to each judgment matrix. Extract the elements in the area without the main diagonal in the judgment matrix according to row priority to form a judgment matrix vector, and judge the ranks corresponding to the elements of the matrix vector to form a rank vector, wherein the value of each element in the rank vector is the rank of the elements in the area without the main diagonal in the corresponding judgment matrix, which is expanded in descending order according to row priority; then, according to the rank vector corresponding to the benchmark judgment matrix, determine the rank correlation values ​​between the rank vectors corresponding to other judgment matrices.

[0060] Furthermore, the step of determining the weight value of the indicator includes:

[0061]

[0062] Among them, winf a is the weight value of the ath indicator, g is the number of experts, w i is the weight of the i-th expert, win ia is the initial weight value of the feedback from the ith expert for the ath indicator.

[0063] A second aspect of the present application provides an information technology service capability evaluation and quantification device, the device comprising:

[0064] A weight determination module, used to determine the weight value of each indicator in a preset indicator system architecture; wherein the preset indicator system architecture includes multiple subjective indicators and multiple objective indicators;

[0065] A subjective indicator score determination module, used to determine an importance value set for identifying the importance of an evaluator based on the initial scores of all subjective indicators, determine an importance value ranking set based on the importance value set, and determine a final score of each subjective indicator based on the importance value set, the importance value ranking set and a preset percentage value; wherein the initial score of the subjective indicator is obtained by a first preset method;

[0066] An objective indicator score determination module, used to determine the final score of each objective indicator through a preset objective indicator evaluation model according to the initial score of each objective indicator; wherein the initial score of the objective indicator is obtained through a second preset method;

[0067] The service capability determination module is used to determine the information technology service capability evaluation value based on the weight value of each indicator and the final score of each indicator.

[0068] According to a third aspect of the present application, a computer-readable storage medium is provided, wherein a computer program stored in the computer-readable storage medium can be executed by one or more processors to implement the steps of the method described above.

[0069] The fourth aspect of the present application provides an electronic device, including a memory and one or more processors, wherein the memory stores a computer program, the memory and the one or more processors are communicatively connected to each other, and when the computer program is executed by the one or more processors, the steps of the method described above are implemented.

[0070] According to a fifth aspect of the present application, a computer program product is provided, wherein the computer program product comprises a computer program or instructions, and when the computer program or instructions are executed by a processor, the steps of the method described above are implemented.

[0071] Compared with the prior art, the advantages or beneficial effects of the technical solution of the present application include:

[0072] (1) It can support the scientificity and rationality of IT service capability assessment and promote the healthy development of the IT service industry and market;

[0073] (2) It proposes an evaluation method that scientifically integrates subjective and objective indicators, which can promote the effectiveness and scientificity of the evaluation;

[0074] (3) The proposed comprehensive evaluation and quantitative method can promote the integration of subjective cognition and objective data;

[0075] (4) Extracting the scores of the main evaluators and scientifically synthesizing the evaluation results can effectively eliminate the interference of human factors and improve the robustness of the evaluation results;

[0076] (5) Using improved mathematical models, scaling objective indicators and removing dimensional interference can standardize scoring;

[0077] (6) An expert weighting method is proposed based on the rank correlation matrix. The weight generation is more scientific and can improve the stability of the evaluation.

[0078] (7) The concept and method of ratio importance are proposed, which can improve the credibility of the synthesis of scoring results from multiple evaluators.

[0079] Furthermore, the information technology service capability assessment quantification subsystem that executes the method disclosed in the present application has the advantages of low operation complexity and good user experience because it sets up operation interfaces corresponding to different groups of people respectively and sets corresponding function options separately according to the user's specific operation permissions in the operation interfaces corresponding to different groups of people. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in the relevant field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0081] It should also be noted that, for the convenience of description, only the parts related to the present disclosure are shown in the drawings. The drawings constituting a part of the specification of this application are used to provide a further understanding of the present application. The illustrative embodiments and their descriptions in this application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0082] Figure 1 A flowchart of a quantitative method for evaluating information technology service capabilities provided in an embodiment of the present application;

[0083] Figure 2A schematic diagram of a preset indicator system architecture provided in an embodiment of the present application;

[0084] Figure 3 A flowchart of another information technology service capability evaluation and quantification method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0085] The following will describe the implementation methods of the present application in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present application applies technical means to solve technical problems and achieve corresponding technical effects can be fully understood and implemented accordingly. The embodiments of the present application and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the protection scope of the present application.

[0086] It should be clear that the embodiments described below are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by technicians in the relevant field without making creative work are within the scope of protection of the present application.

[0087] Specifically, the present application proposes an information technology service capability evaluation method that integrates subjective and objective quantitative models. A basic indicator system architecture for information technology service evaluation is disclosed, which divides the evaluation indicators into subjective indicators and objective indicators. The evaluation method adopts a quantitative method, and uses the Analytic Hierarchy Process (AHP) to determine the indicator weights between each dimension and each level, including the weights between subjective factor indicators and objective indicators. The scoring of subjective indicators can be quantified in the form of scoring by evaluators, and objective indicators can be based on the quantitative results of actual evaluation. Innovative cost-based indicator quantification methods and benefit-based indicator quantification methods based on Logistic functions are constructed, and quantification is performed in combination with the threshold requirements of each indicator. In the AHP expert weight fusion link, the judgment matrix correlation measurement based on the Spearman rank correlation coefficient is used to form a group decision algorithm for fusion scoring.

[0088] Embodiment 1

[0089] This embodiment provides a method for evaluating and quantifying information technology service capabilities. The method can be integrated into relevant management systems of an enterprise (e.g., enterprise management system, information service system, etc.), or an information technology service capability evaluation and quantification subsystem that executes the method can be integrated into relevant management systems of an enterprise.

[0090] In this embodiment, the personnel are divided into three categories, including experts, evaluators and testers. Experts are mainly responsible for applying the improved AHP method to compare the importance of indicators at all levels of each dimension, and completing indicator weighting by forming a judgment matrix and combining group decision-making; evaluators are mainly responsible for evaluating and scoring the subjective indicators of leaf nodes; and testers are mainly responsible for testing the objective indicators of leaf nodes and obtaining the measured values.

[0091] Furthermore, for experts, evaluators and testers, different operating permissions can be granted to different groups of people in the relevant management system, and corresponding operation interfaces can be set up for different groups of people so that different groups of people can operate in their respective operation interfaces; in the operation interfaces corresponding to different groups of people, corresponding function options can be set separately according to the specific operation permissions of users. Therefore, it has the advantages of reducing the complexity of operation and improving the user experience.

[0092] Figure 1 A flowchart of a quantitative method for evaluating information technology service capabilities provided in an embodiment of the present application, such as Figure 1 As shown, the method disclosed in this embodiment includes the following steps:

[0093] Step 110: Determine the weight value of each indicator in the preset indicator system architecture; wherein the preset indicator system architecture includes multiple subjective indicators and multiple objective indicators.

[0094] Among them, a preset indicator system architecture is saved in the relevant management system, and managers with relevant operation permissions can modify or update the preset indicator system architecture. At the same time, the relevant management system also supports the evaluation and quantification of information technology service capabilities based on other indicator system architectures, and the indicator system architectures do not affect each other.

[0095] Optionally, the preset indicator system architecture can refer to Figure 2 ,This application evaluates the subjectivity and objectivity of evidence collection based on the content of ,indicators in each dimension, and divides the indicator types into two categories: ,subjective indicators and objective indicators.

[0096] Specifically, the entire indicator system is based on the two dimensions of subjective indicators and objective indicators to develop graded indicators for information technology service capability indicators. The indicators of leaf nodes are not expanded here, and only corresponding explanations are given when evaluators score and synthesize the leaf node indicators.

[0097] In this embodiment, the analytic hierarchy process (AHP) is used to determine the weights of indicators between various dimensions and levels, and improvements are given in terms of expert group decision-making.

[0098] Optionally, relevant function buttons can be set in the operation interface for each group of people to perform relevant operations. For example, a weight determination button is set in the operation interface to send a weight determination reminder to each expert in the expert group, so that each expert can feedback the judgment matrix used to determine the weight as soon as possible.

[0099] The weight of the indicator can be determined by constructing a judgment matrix, and the judgment matrix is ​​given by each expert in the expert group. The construction method of the judgment matrix A composed of n indicators is to determine the importance of each indicator to the target by comparing the n indicators with each other. The element value of A can be determined by the matrix judgment standard. For example: 1-9 scaling method, and the matrix meets the requirements of positive reciprocal matrix. If scalability is considered, the scale value range can be appropriately expanded. The following Table 1 is an example of the 1-9 scaling method of the judgment matrix element:

[0100] Table 1 Judgment matrix element 1-9 scale value table

[0101]

[0102]

[0103] For example, when the importance of x is between "x and y are equally important" and "x is slightly more important than y", its value can be set to 2; when the importance of x is between "x is very important than y" and "x is extremely important than y", its value can be set to 8.

[0104] In some embodiments, determining the weight value of each indicator in the preset indicator system architecture includes:

[0105] For any indicator with sub-indicators in the preset indicator system architecture, a judgment matrix for determining the weight of each sub-indicator is generated according to the sub-indicators of the indicator; wherein the order of the judgment matrix is ​​equal to the number of sub-indicators, and the value of each element in the judgment matrix represents the ratio of the importance between the sub-indicator corresponding to the corresponding row index and the column index;

[0106] issuing a scoring reminder so that a plurality of experts can provide feedback on the judgment matrix by filling in values ​​for the judgment matrix respectively; wherein the value of each element in the judgment matrix is ​​determined by a preset scaling method;

[0107] For any judgment matrix that has passed the consistency test and is fed back by an expert, the initial weight value of each sub-indicator is determined according to the value of the element in the judgment matrix, wherein the initial weight value is the weight value determined for the sub-indicator by the expert who fed back the judgment matrix;

[0108] Determine the weight value of each expert based on the judgment matrix that has passed the consistency test and is fed back by all evaluators;

[0109] For any sub-indicator, the final weight value of the sub-indicator is determined according to the weight values ​​of each expert and the initial weight value of the sub-indicator determined by each expert, and the final weight value is used as the weight value of the sub-indicator.

[0110] In some embodiments, after determining the value of each element in the judgment matrix, the method further includes:

[0111] Determine the maximum eigenvalue of the judgment matrix based on the values ​​of each element in the judgment matrix determined by the experts;

[0112] Determining a consistency index according to the maximum eigenvalue and the order of the judgment matrix, and determining a consistency ratio of the judgment matrix according to the consistency index;

[0113] When the consistency ratio does not satisfy a preset consistency condition, a correction reminder message is issued, so that the expert corrects the value of the element in the judgment matrix according to the correction reminder message;

[0114] When the consistency ratio meets the preset consistency condition, it is determined that the judgment matrix fed back by the expert passes the consistency test.

[0115] Optionally, a scoring button is set in the operation interface for issuing scoring reminders; a judgment button is set in the operation interface for determining whether the judgment matrix of the feedback can pass the consistency check; a corresponding reminder logic can also be set for issuing correction reminder messages; a reminder button can also be set in the operation interface, and when the reminder button is clicked, it is used to actively issue correction reminder messages to experts who have not yet had time to perform correction processing.

[0116] Since the judgment matrix is ​​a positive reciprocal matrix, the following steps are taken to calculate the maximum eigenvalue of the judgment matrix:

[0117] First, calculate the weight value:

[0118] Normalize the judgment matrix by column (dividing each element by the sum of its column), then add up the normalized columns (summing up by row), and finally divide each element of the vector obtained by addition by n to obtain the weight vector.

[0119]

[0120] Among them, w i is the weight of the ith indicator or requirement.

[0121] Then, the maximum eigenvalue of the judgment matrix is ​​calculated by the following formula:

[0122]

[0123] Among them, λmax is the maximum eigenvalue of the judgment matrix.

[0124] After determining the maximum eigenvalue, in order to verify the logical rationality, it is necessary to perform a consistency check on the judgment matrix. The specific test steps are as follows:

[0125] First, calculate the consistency index CI:

[0126]

[0127] Among them, λ max is the maximum eigenvalue of the judgment matrix A, and n is the matrix order.

[0128] Then, the consistency ratio CR is calculated by the following formula:

[0129]

[0130] Among them, RI is the average random consistency index, which can be obtained by querying the following Table 2.

[0131] Table 2 Correspondence between matrix order and average random consistency index

[0132] Matrix order RI 1 0 2 0 3 0.58 4 0.90 5 1.12 6 1.24 7 1.32 8 1.41 9 1.45 10 1.49 11 1.51 12 1.54 13 1.56 14 1.58 15 1.59

[0133] It should be noted that when the order of the judgment matrix is ​​greater than 15, the following method can be used to calculate RI. Assuming that the order of the judgment matrix is ​​n, the steps of calculating RI may include: the first step, for each element in the n-order judgment matrix, randomly select from 1, 2, ..., 9 and 1 / 2, ..., 1 / 9, a total of 17 numbers, according to the average probability, to form an n-order pairwise comparison matrix A; the second step, calculate the consistency index CI of the judgment matrix A; the third step, repeat the operation multiple times to generate a sufficient number of n-order random judgment matrix samples (such as 1000 samples) and calculate the consistency index of each sample, and finally calculate the arithmetic mean of the consistency indexes of multiple samples, which is RI.

[0134] Finally, make a consistency judgment:

[0135] When CR < 0.1, the consistency of the judgment matrix is ​​considered acceptable.

[0136] When CR≥0.1, the judgment matrix does not meet the consistency requirements. It is necessary to correct the judgment matrix, recalculate CR and make judgments until the consistency requirements of the matrix are met.

[0137] In this embodiment, the weight generation between the evaluation indicators of each dimension (i.e., each unit) at each level needs to be judged separately by the expert group. The experts compare the weights of the indicators of each unit to form a judgment matrix. If the judgment matrix does not pass the aforementioned consistency test, the experts need to make corresponding adjustments to the elements in the judgment matrix, and after passing the consistency test, the corresponding unit indicator weights are generated. In this way, each expert corresponds to a unit indicator weight vector. At this time, the weights of each expert need to be calculated, so as to form the final weight of the indicator item in a weighted sum manner.

[0138] By calculating the correlation coefficients between expert judgment matrices, a judgment matrix correlation coefficient matrix is ​​formed, and then the weights of each judgment matrix in the overall judgment matrix set are calculated. Since the elements in the judgment matrix are scale values ​​defined by the AHP method and belong to hierarchical data, they can be regarded as non-continuous and non-Gaussian, and outliers have a greater impact on correlation analysis. Therefore, when comparing the correlation of two matrices, the Spearman's Rank Correlation rank correlation coefficient can be used to measure the correlation between matrices, which can be applied to evaluation scenarios and has a certain tolerance for outliers.

[0139] In some embodiments, the step of determining the weight value comprises:

[0140] Taking the judgment matrix fed back by the current expert as a benchmark judgment matrix, determining the rank correlation values ​​between the benchmark judgment matrix and the judgment matrices fed back by other experts respectively, and generating a correlation matrix according to all the rank correlation values;

[0141] According to the correlation matrix, the weight value is determined by the following formula:

[0142]

[0143] Among them, w i is the weight of the ith expert, the number of rows and columns of the correlation matrix are both p (i.e., the number of experts), x ij represents the jth column element in the i-th row of the correlation matrix. w i =1 / p.

[0144] In some embodiments, the method of using the judgment matrix fed back by the current expert as a reference judgment matrix and determining the rank correlation values ​​between the reference judgment matrix and the judgment matrices fed back by other experts respectively includes:

[0145] Extract the elements not including the main diagonal from each judgment matrix in row priority order, and generate the judgment matrix vector corresponding to each judgment matrix;

[0146] According to the value of each element in the judgment matrix vector, the elements in the judgment matrix vector are sorted in descending order, and the rank vectors corresponding to each judgment matrix are generated according to the judgment matrix vectors sorted in descending order;

[0147] According to the rank vector corresponding to the reference judgment matrix, the rank correlation values ​​between the rank vector corresponding to the reference judgment matrix and the rank vectors corresponding to other judgment matrices are determined respectively; wherein the rank correlation value is determined by the following formula:

[0148]

[0149] n=m 2 -m

[0150] Among them, x ij is the rank correlation value between the rank vector corresponding to the judgment matrix i and the rank vector corresponding to the judgment matrix j, d ijk is the difference between the rank at position k in the rank vector corresponding to the judgment matrix i and the rank at position k in the rank vector corresponding to the judgment matrix j, and m is the number of rows of the judgment matrix i.

[0151] Optionally, the correlation of the judgment matrices formed by the experts can be measured by the following process:

[0152] Extract the elements of each judgment matrix that do not contain the main diagonal in row priority order (for example, extract the first row first, then the second row, and so on), and generate the judgment matrix vector corresponding to each judgment matrix; sort the elements in the judgment matrix vector in descending order, and determine the rank of each corresponding element. A rank of 1 means that the value of the matrix element is the largest in the area that does not contain the main diagonal, and a larger relative rank means that the value of the matrix element is relatively small in the area that does not contain the main diagonal. If the values ​​of multiple elements are the same, then the average of the sorting positions is taken as the rank of each element.

[0153] Based on the correlation values ​​of each judgment matrix and other judgment matrices determined above, a judgment matrix correlation matrix A is formed, wherein each element in A represents the correlation between the judgment matrix of the corresponding row index and the judgment matrix of the corresponding column index.

[0154] In some embodiments, the step of determining the weight value of the indicator includes:

[0155]

[0156] Among them, winf a is the weight value of the ath indicator, g is the number of experts, w i is the weight of the i-th expert, win ia is the initial weight value of the feedback from the ith expert for the ath indicator.

[0157] Step 120: determine an importance value set for identifying the importance of the evaluator based on the initial scores of all subjective indicators, determine an importance value ranking set based on the importance value set, and determine the final score of each subjective indicator based on the importance value set, the importance value ranking set and a preset percentage value; wherein the initial score of the subjective indicator is obtained by a first preset method.

[0158] Optionally, a subjective indicator scoring button is set in the operation interface to issue a subjective indicator scoring reminder.

[0159] Optionally, the initial scoring of the subjective indicators can be obtained by means of document review, material spot check, personnel interview, system evaluation, etc. The first preset method can also be determined according to actual needs.

[0160] In some embodiments, determining a ranking set for identifying the importance of evaluators based on the initial scores of all subjective indicators includes:

[0161] Generate an initial scoring matrix based on the initial scores of all subjective indicators; wherein the rows of the initial scoring matrix represent indicators, and the columns of the initial scoring matrix represent the scores of the evaluators;

[0162] Determine the median of each row of the initial scoring matrix and generate a median vector of the initial scoring matrix;

[0163] According to the initial scoring matrix, respectively determine the column vector corresponding to each evaluator;

[0164] Determine the importance value of each evaluator according to the column vector corresponding to each evaluator and the median vector;

[0165] The rank corresponding to each evaluator is determined according to the importance value of each evaluator, and the rank corresponding to each evaluator is stored in a set to generate a rank set identifying the importance of the evaluator.

[0166] Optionally, if the initial scoring matrix is ​​presented in table form, reference may be made to Table 3 below.

[0167] Table 3 Initial scoring matrix

[0168] Evaluator 1 Evaluator 2 Evaluator 3 … Evaluator Indicator 1 2 3 3 … 3 Indicator 2 6 6 5 … 6 Indicator 3 8 7 8 … 7 Indicator 4 7 7 8 … 8 … … … … … … Index m 8 6 7 … 8

[0169] For subjective indicators, at the leaf nodes of the indicator system, evaluators will give subjective scores to the indicator evaluation results of each leaf node based on the technical requirements of the indicators and their own evaluation experience, thus forming an initial score for the subjective indicator.

[0170] A score matrix (m×n) is generated based on the scoring results of each evaluator, where m is the number of all evaluation indicators of the leaf node and n is the number of evaluators.

[0171] In the score matrix, the median of each row is calculated to form an m×1 vector, which is defined as the column median vector of the score matrix, denoted by V c .

[0172] Calculate the column vectors and V in the score matrix c The center distance can be quantified by Euclidean distance, Manhattan distance, Chebyshev distance, cosine distance, Minkowski distance, etc., and each distance is normalized:

[0173]

[0174] Among them, dc a is the center distance of the column vector corresponding to the a-th evaluator, V a is the column vector corresponding to the a-th evaluator, V i is the column vector corresponding to the i-th evaluator, A is the set of serial numbers of all evaluators (1, 2, 3…, the serial number of the first evaluator can be 1, the serial number of the second evaluator can be 2, and so on), V c is the median vector.

[0175] In addition, when When, dc a =1 / u, where u is the number of evaluators.

[0176] In some embodiments, the importance value of the assessor is determined by the following formula:

[0177]

[0178] Among them, I a is the importance value of the ath evaluator, A is the set of serial numbers of all evaluators, that is, the index set of the columns of the initial scoring matrix, dc a is the center distance of the column vector corresponding to the a-th evaluator, dc i is the center distance of the column vector corresponding to the i-th evaluator. The value of i is the serial number of the evaluator, such as: the first evaluator, the second evaluator, etc. In addition, when When, dc a =1 / u, where u is the number of evaluators.

[0179] An importance value set is generated according to the importance values ​​of all evaluators, denoted as I, where Ia is the importance value of the a-th evaluator (which can be understood as a weight).

[0180] The ranks of the elements in I are counted in descending order to form an importance value rank set R (for example, if the fifth evaluator's rank is 1 and the fifth evaluator's serial number is 5, then the first element in the set R is 5, R(1)=5; if the third evaluator's rank is 2 and the third evaluator's serial number is 3, then the second element in the set R is 3, R(2)=3).

[0181] The ranks of the importance of evaluators are selected in R in turn to form subsets ANx of the rank set. ANx means that the subset is composed of the first x elements in R. The ratio of the sum of the importance values ​​of the evaluators with the corresponding rank of ANx to the sum of the importance values ​​of all evaluators is called the importance of the x main evaluators.

[0182] Here, AN rat For example, AN rat is the rat ratio importance assessor index set, which can be determined by the following formula:

[0183] I={I i |i∈A}

[0184] AN rat =R(1:y)

[0185]

[0186] Among them, I is a set of importance values; A is a set of indexes of the columns of the initial rating matrix; rat is a preset percentage value; R is a set of importance value rankings corresponding to I; y is the number of evaluators in I whose cumulative importance values ​​are not less than rat; R(1:y) is a set of serial numbers corresponding to the first y evaluators in I; i is a position index of an element in I; j is a position index of an element in R, and k is the upper limit of j.

[0187] For example, the rat value is set to 80%, that is, the scores of the evaluators whose cumulative importance is not less than 80% are counted. First, the number of evaluators is determined according to the rat (for example, there are 10 evaluators, and the cumulative importance of the 10 evaluators is 100%. Assume that the cumulative importance of the first 8 evaluators is 90%, the cumulative importance of the first 6 evaluators is 82%, and the cumulative importance of the first 5 evaluators is 79%; then the minimum number not less than the rat is 6, that is, the determined y value is 6.), and then the serial number of the corresponding evaluator is determined according to the set I and the set R, and finally the score of each evaluator is determined according to the serial number of each evaluator.

[0188] In some embodiments, determining the final score of each subjective indicator according to the ranking set and the preset percentage value includes:

[0189]

[0190] Where j is the serial number of the subjective indicator in the preset indicator system architecture; I a is the importance value of the ath evaluator; S ja is the initial score of the ath evaluator on the jth subjective indicator in the preset indicator system architecture; SU j It is the final score of the jth subjective indicator in the preset indicator system architecture.

[0191] It should be noted that the value range of rat is [0,1], and the specific value of rat can be set according to actual needs.

[0192] In summary, the evaluation score synthesis based on ratio importance can be performed in the following steps:

[0193] (1) For each subjective indicator in the preset indicator system architecture, the scores of each evaluator are counted, with the score interval being [0, 1], and a score matrix is ​​generated;

[0194] (2) According to the score matrix, calculate the median vector V in turn c and importance value set I;

[0195] (3) Determine An according to the given rat rat ;

[0196] (4) For the unit indicators of the leaf nodes, the scores of each indicator are synthesized by determining the calculation formula of the final score of the subjective indicator.

[0197] Step 130: Determine the final score of each objective indicator according to the initial score of each objective indicator through a preset objective indicator evaluation model; wherein the initial score of the objective indicator is obtained through a second preset method.

[0198] Optionally, an objective indicator scoring button is set in the operation interface to issue an objective indicator scoring reminder.

[0199] Optionally, the initial scoring of the objective indicators mainly adopts benchmark testing, system testing, document review, system review, etc. to obtain the evaluation results. The second preset method can also be determined according to actual needs.

[0200] In some embodiments, the preset objective indicator evaluation model includes a cost-based evaluation model and a benefit-based evaluation model; the final score of each objective indicator is determined by the preset objective indicator evaluation model, including:

[0201] Determine the indicator type of the objective indicator; wherein the indicator type includes cost-based indicators and benefit-based indicators;

[0202] In the case where the indicator type is a cost-based indicator, the final score of the objective indicator is determined by the cost-based evaluation model;

[0203] When the indicator type is a benefit-type indicator, the final score of the objective indicator is determined by the benefit-type evaluation model.

[0204] Optionally, the cost-based evaluation model includes:

[0205]

[0206] The Logistic function is customized to form a cost-based indicator quantification model (related indicators such as service responsiveness indicators, etc.). The model manually sets the test threshold thc of the relevant objective indicators, x is the input of the measured value of the corresponding indicator, fc is the score corresponding to the threshold thc, the value range of fc is (0,1), and Ac is the shape parameter of the Logistic function, with a value range of (0,+∞). Among them, thc, fc and Ac can all be set manually based on experience. The model input and output are negatively correlated. sorec(x) is the quantified value of the cost-based indicator with the measured value x, and the interval is (0,1). If x is not input, sorec(x)=0.

[0207] Optionally, the benefit-based evaluation model includes:

[0208]

[0209] The Logistic function is customized to form a benefit-type indicator quantification model (related indicators such as service concurrency indicators, etc.). The model manually sets the test threshold thb of the relevant objective test indicators, x is the input of the measured value of the corresponding indicator, and fb is the score corresponding to the threshold thb. The value range of fb is (0,1), and Ab is the shape parameter of the Logistic function, with a value range of (0,+∞). Among them, thb, fb and Ab can all be set manually based on experience. The model input and output are positively correlated. soreb(x) is the quantified value of the benefit-type indicator with the measured value x, and the interval is (0,1). If x is not input, soreb(x)=0.

[0210] Step 140: Determine the information technology service capability evaluation value based on the weight value of each indicator and the final score of each indicator.

[0211] Optionally, an evaluation and scoring button is provided in the operation interface to determine the information technology service capability evaluation value based on the weight value of each indicator and the final score of each indicator.

[0212] Specifically, according to the preset indicator system architecture, the weighted score of each unit is calculated starting from the leaf node to obtain the score of the upper node; and so on, through the weighted sum method, the node scores of the corresponding hierarchical dimensions are deduced and calculated one by one to the upper layer of the indicator tree, and finally the score result of the root node "evaluation quantification" is obtained, which is the quantitative result of the output evaluation of a set of information technology service systems.

[0213] Optionally, a related display page can be developed, and the evaluation and quantification results can be displayed in the display interface. An export button can also be set in the operation interface to output the evaluation and quantification results to other external systems that communicate with it; when used in combination with related intelligent hardware, the evaluation and quantification results can also be exported through the related interfaces of the intelligent hardware (for example, USB interface, Type C interface, Bluetooth module or NFC communication module, etc.).

[0214] At the same time, in order to facilitate understanding of the technical solution of this application, you can also refer to Figure 3 , Figure 3 A flowchart of another information technology service capability evaluation and quantification method provided in an embodiment of the present application.

[0215] Embodiment 2

[0216] This embodiment provides an information technology service capability evaluation and quantification device. This device embodiment can be used to execute the method embodiment of this application. For details not disclosed in this device embodiment, please refer to the method embodiment of this application. The device disclosed in this embodiment includes:

[0217] A weight determination module, used to determine the weight value of each indicator in a preset indicator system architecture; wherein the preset indicator system architecture includes multiple subjective indicators and multiple objective indicators;

[0218] A subjective indicator score determination module, used to determine an importance value set for identifying the importance of an evaluator based on the initial scores of all subjective indicators, determine an importance value ranking set based on the importance value set, and determine a final score of each subjective indicator based on the importance value set, the importance value ranking set and a preset percentage value; wherein the initial score of the subjective indicator is obtained by a first preset method;

[0219] An objective indicator score determination module, used to determine the final score of each objective indicator through a preset objective indicator evaluation model according to the initial score of each objective indicator; wherein the initial score of the objective indicator is obtained through a second preset method;

[0220] The service capability determination module is used to determine the information technology service capability evaluation value based on the weight value of each indicator and the final score of each indicator.

[0221] It should be understood by those skilled in the art that the above modules or steps of the present application can be implemented by a general-purpose computing device, and they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices. Optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation.

[0222] Technical personnel in the relevant field can clearly understand that, for the convenience and simplicity of description, the specific working process of each module in the information technology service capability assessment and quantification device can refer to the corresponding process in the aforementioned method embodiment, and this embodiment will not be repeated here.

[0223] It can be understood that each module in the information technology service capability assessment and quantification device can also be integrated separately into the relevant management system of the enterprise (for example, the enterprise management system, the information service system, etc.), and the information technology service capability assessment and quantification subsystem integrated in the relevant management system can also perform corresponding data processing according to the modules as described above.

[0224] Embodiment 3

[0225] This embodiment provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps in the above method embodiment can be implemented, and this embodiment will not be repeated here.

[0226] Among them, the computer-readable storage medium may also include computer programs, data files, data structures, etc. alone, or include a combination thereof. The computer-readable storage medium or computer program may be specifically designed and understood by a technician in the field of computer software, or the computer-readable storage medium may be known and available to a technician in the field of computer software. Examples of computer-readable storage media include: magnetic media, such as hard disks, floppy disks, and tapes; optical media, such as CDROM disks and DVDs; magneto-optical media, such as optical disks; and hardware devices, specifically configured to store and execute computer programs, such as read-only memory (ROM), random access memory (RAM), flash memory; or servers, app application stores, etc. Examples of computer programs include machine code (e.g., code generated by a compiler) and files containing high-level code, which can be executed by a computer using an interpreter. The described hardware device may be configured to be used as one or more software modules to perform the operations and methods described above, and vice versa. In addition, the computer-readable storage medium may be distributed in a networked computer system, and program code or computer programs may be stored and executed in a decentralized manner.

[0227] Embodiment 4

[0228] This embodiment provides a computer program product. The computer program product includes a computer program or instructions, and when the computer program or instructions are executed by a processor, all or part of the steps of the method in the above method embodiment are implemented, and this embodiment will not be repeated here.

[0229] Further, the computer program product may include one or more computer executable components configured to perform the embodiments when the program is run; the computer program product may also include a computer program tangibly contained on a readable medium, the computer program including program code for performing any method in the embodiments of the present disclosure. In such an embodiment, the computer program may be downloaded and installed from a network through a communication portion, and / or installed from a removable medium.

[0230] Embodiment 5

[0231] This embodiment provides an electronic device, which may include: one or more processors, a memory, a multimedia component, an input / output (I / O) interface, and a communication component.

[0232] One or more processors are used to execute all or part of the steps in the above method embodiments. The memory is used to store various types of data, which may include instructions of any application or method in the electronic device, and data related to the application.

[0233] One or more processors may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and are used to execute the method in the aforementioned method embodiment.

[0234] The memory can be implemented by any type of volatile or non-volatile storage device or a combination of them, 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.

[0235] The multimedia component may include a screen and an audio component, the screen may be a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signal may be further stored in a memory or sent via a communication component. The audio component also includes at least one speaker for outputting audio signals.

[0236] The I / O interface provides an interface between one or more processors and other interface modules, which may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons.

[0237] The communication component is used for wired or wireless communication between the electronic device and other devices. Wired communication includes communication through network ports, serial ports, etc.; wireless communication includes: Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, 5G, or one or a combination of them.

[0238] In addition, it should be understood that the method or device disclosed in the embodiments provided in the present application can also be implemented in other ways. The method or device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the methods and devices according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a computer program segment or a part of a computer program, and the module, computer program segment or a part of a computer program contains one or more computer programs for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings, and can actually be executed in parallel. They can also be executed in the opposite order sometimes, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of dedicated hardware and computer programs.

[0239] In this application, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements that are inherent to such process, method, article, or apparatus. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, device or equipment including the elements; if there is a description of "first", "second", etc., it is only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features; in the description of this application, unless otherwise specified, the terms "multiple" and "multiple" mean at least two; if there is a description of a server, it should be noted that the server can be an independent physical server or terminal, or a server cluster composed of multiple physical servers, or a cloud server that can provide basic cloud computing services such as cloud servers, cloud databases, cloud storage and CDN; if there is a description of a smart terminal or mobile device in this application, it should be noted that the smart terminal or mobile device can be a mobile phone, a tablet computer, a smart watch, a netbook, a wearable electronic device, a personal digital assistant (PDA), an augmented reality technology device (AR), a virtual reality device (VR), a smart TV, a smart speaker, a personal computer (PC), a tablet computer, a smart phone, a smart TV, a smart speaker, a smart phone ... Computer, referred to as PC), etc., but not limited to this, the present application does not specifically limit the specific form of the smart terminal or mobile device.

[0240] Finally, it should be noted that, in the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "an example" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0241] Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary, and the contents described are only embodiments adopted for the convenience of understanding the present application, and are not intended to limit the present application. Any technician in the technical field to which the present application belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present application, but the scope of protection of the present application shall still be based on the scope defined in the attached claims.

Claims

1. A quantitative method for evaluating information technology service capabilities, characterized in that: The method comprises: Determine the weight value of each indicator in the preset indicator system architecture; wherein the preset indicator system architecture includes multiple subjective indicators and multiple objective indicators; the determining the weight value of each indicator in the preset indicator system architecture includes: For any indicator with sub-indicators in the preset indicator system architecture, a judgment matrix for determining the weight of each sub-indicator is generated according to the sub-indicators of the indicator; wherein the order of the judgment matrix is ​​equal to the number of sub-indicators, and the value of each element in the judgment matrix represents the ratio of the importance between the sub-indicator corresponding to the corresponding row index and the column index; issuing a scoring reminder so that a plurality of experts can provide feedback on the judgment matrix by filling in values ​​for the judgment matrix respectively; wherein the value of each element in the judgment matrix is ​​determined by a preset scaling method; For any judgment matrix that has passed the consistency test and is fed back by an expert, the initial weight value of each sub-indicator is determined according to the value of the element in the judgment matrix, wherein the initial weight value is the weight value determined for the sub-indicator by the expert who fed back the judgment matrix; Determine the weight value of each expert based on the judgment matrix that has passed the consistency test and is fed back by all evaluators; For any sub-indicator, the final weight value of the sub-indicator is determined according to the weight values ​​of each expert and the initial weight value of the sub-indicator determined by each expert, and the final weight value is used as the weight value of the sub-indicator; Determine an importance value set for identifying the importance of the evaluator according to the initial scores of all subjective indicators, determine an importance value ranking set according to the importance value set, and determine the final score of each subjective indicator according to the importance value set, the importance value ranking set and a preset percentage value; wherein the initial score of the subjective indicator is obtained by a first preset method; Determining the final score of each objective indicator through a preset objective indicator evaluation model according to the initial score of each objective indicator; wherein the initial score of the objective indicator is obtained through a second preset method; Determine the information technology service capability assessment value based on the weight value of each indicator and the final score of each indicator; Among them, the subjective indicators involve: personnel support, organizational management, business operations, technical operation and maintenance, technology research and development, security assurance and resource support; the objective indicators involve: service reliability, service responsiveness, service availability, service level achievement rate, service continuity, service satisfaction, incident closure rate, data persistence, service concurrency, resource efficiency and fault recovery efficiency.

2. The information technology service capability evaluation and quantification method according to claim 1 is characterized in that: The preset objective indicator evaluation model includes a cost evaluation model and a benefit evaluation model; the final score of each objective indicator is determined by the preset objective indicator evaluation model, including: Determine the indicator type of the objective indicator; wherein the indicator type includes cost-based indicators and benefit-based indicators; In the case where the indicator type is a cost-based indicator, the final score of the objective indicator is determined by the cost-based evaluation model; When the indicator type is a benefit-type indicator, the final score of the objective indicator is determined by the benefit-type evaluation model.

3. The information technology service capability evaluation and quantification method according to claim 1 is characterized in that: The ranking set for identifying the importance of the evaluator is determined based on the initial scores of all subjective indicators, including: Generate an initial scoring matrix based on the initial scores of all subjective indicators; wherein the rows of the initial scoring matrix represent indicators, and the columns of the initial scoring matrix represent the scores of the evaluators; Determine the median of each row of the initial scoring matrix and generate a median vector of the initial scoring matrix; According to the initial scoring matrix, respectively determine the column vector corresponding to each evaluator; Determine the importance value of each evaluator according to the column vector corresponding to each evaluator and the median vector; The rank corresponding to each evaluator is determined according to the importance value of each evaluator, and the rank corresponding to each evaluator is stored in a set to generate a rank set identifying the importance of the evaluator.

4. The information technology service capability evaluation and quantification method according to claim 3 is characterized in that: The importance value of the assessor is determined by the following formula: Among them, I a is the importance value of the ath evaluator, A is the index set of the columns of the initial rating matrix, dc a is the center distance of the column vector corresponding to the a-th evaluator, dc i is the center distance of the column vector corresponding to the i-th evaluator; where the center distance is determined by the following formula: Among them, dc a is the center distance of the column vector corresponding to the a-th evaluator, V a is the column vector corresponding to the a-th evaluator, V i is the column vector corresponding to the i-th evaluator, V c is the median vector.

5. The information technology service capability evaluation and quantification method according to claim 1 is characterized in that: Determining the final score of each subjective indicator according to the importance value set, the importance value ranking set and the preset percentage value includes: Where j is the serial number of the subjective indicator in the preset indicator system architecture; I a is the importance value of the ath evaluator; S ja is the initial score of the ath evaluator on the jth subjective indicator in the preset indicator system architecture; SU j is the final score of the jth subjective indicator in the preset indicator system architecture; AN rat is the set of ratio importance evaluators, AN rat Determined by the following formula based on the preset percentage value: Among them, I is a set of importance values; A is a set of indexes of the columns of the initial rating matrix; rat is a preset percentage value; R is a set of importance value ranks corresponding to I; y is the number of evaluators in I whose cumulative importance values ​​are not less than rat; R(1:y) is a set of ordinal sequences corresponding to the first y evaluators in I; i is a position index of an element in I; j is a position index of an element in R, and k is the upper limit of j.

6. The information technology service capability evaluation and quantification method according to claim 1 is characterized in that: After determining the value of each element in the judgment matrix, the method further includes: Determine the maximum eigenvalue of the judgment matrix based on the values ​​of each element in the judgment matrix determined by the experts; Determining a consistency index according to the maximum eigenvalue and the order of the judgment matrix, and determining a consistency ratio of the judgment matrix according to the consistency index; When the consistency ratio does not satisfy a preset consistency condition, a correction reminder message is issued, so that the expert corrects the value of the element in the judgment matrix according to the correction reminder message; When the consistency ratio meets the preset consistency condition, it is determined that the judgment matrix fed back by the expert passes the consistency test.

7. The information technology service capability evaluation and quantification method according to claim 1 is characterized in that: The step of determining the weight value comprises: Taking the judgment matrix fed back by the current expert as a benchmark judgment matrix, determining the rank correlation values ​​between the benchmark judgment matrix and the judgment matrices fed back by other experts respectively, and generating a correlation matrix according to all the rank correlation values; According to the correlation matrix, the weight value is determined by the following formula: Among them, w i is the weight of the ith expert, the number of rows and columns of the correlation matrix are both p, x ij Represents the j-th column element in the i-th row of the correlation matrix.

8. The information technology service capability evaluation and quantification method according to claim 7 is characterized in that: The method of using the judgment matrix fed back by the current expert as a reference judgment matrix and determining the rank correlation values ​​between the reference judgment matrix and the judgment matrices fed back by other experts respectively includes: Extract the elements not including the main diagonal from each judgment matrix in row priority order, and generate the judgment matrix vector corresponding to each judgment matrix; According to the value of each element in the judgment matrix vector, the elements in the judgment matrix vector are sorted in descending order, and the rank vectors corresponding to each judgment matrix are generated according to the judgment matrix vectors sorted in descending order; According to the rank vector corresponding to the reference judgment matrix, the rank correlation values ​​between the rank vector corresponding to the reference judgment matrix and the rank vectors corresponding to other judgment matrices are determined respectively; wherein the rank correlation value is determined by the following formula: Among them, x ij is the rank correlation value between the rank vector corresponding to the judgment matrix i and the rank vector corresponding to the judgment matrix j, d ijk is the difference between the rank at position k in the rank vector corresponding to the judgment matrix i and the rank at position k in the rank vector corresponding to the judgment matrix j, m is the number of rows of the judgment matrix i, and n is a constant.

9. The information technology service capability evaluation and quantification method according to claim 7 is characterized in that: The steps to determine the weight value of the indicator include: Among them, winf a is the weight value of the ath indicator, g is the number of experts, w i is the weight of the i-th expert, win ia is the initial weight value of the feedback from the ith expert for the ath indicator.

10. An information technology service capability evaluation and quantification device, characterized in that: include: A weight determination module is used to determine the weight value of each indicator in a preset indicator system architecture; wherein the preset indicator system architecture includes multiple subjective indicators and multiple objective indicators; the weight value of each indicator in the preset indicator system architecture is determined, including: For any indicator with sub-indicators in the preset indicator system architecture, a judgment matrix for determining the weight of each sub-indicator is generated according to the sub-indicators of the indicator; wherein the order of the judgment matrix is ​​equal to the number of sub-indicators, and the value of each element in the judgment matrix represents the ratio of the importance between the sub-indicator corresponding to the corresponding row index and the column index; issuing a scoring reminder so that a plurality of experts can provide feedback on the judgment matrix by filling in values ​​for the judgment matrix respectively; wherein the value of each element in the judgment matrix is ​​determined by a preset scaling method; For any judgment matrix that has passed the consistency test and is fed back by an expert, the initial weight value of each sub-indicator is determined according to the value of the element in the judgment matrix, wherein the initial weight value is the weight value determined for the sub-indicator by the expert who fed back the judgment matrix; Determine the weight value of each expert based on the judgment matrix that has passed the consistency test and is fed back by all evaluators; For any sub-indicator, the final weight value of the sub-indicator is determined according to the weight values ​​of each expert and the initial weight value of the sub-indicator determined by each expert, and the final weight value is used as the weight value of the sub-indicator; A subjective indicator score determination module, used to determine an importance value set for identifying the importance of an evaluator based on the initial scores of all subjective indicators, determine an importance value ranking set based on the importance value set, and determine a final score of each subjective indicator based on the importance value set, the importance value ranking set and a preset percentage value; wherein the initial score of the subjective indicator is obtained by a first preset method; An objective indicator score determination module, used to determine the final score of each objective indicator through a preset objective indicator evaluation model according to the initial score of each objective indicator; wherein the initial score of the objective indicator is obtained through a second preset method; A service capability determination module is used to determine the information technology service capability evaluation value based on the weight value of each indicator and the final score of each indicator; Among them, the subjective indicators involve: personnel support, organizational management, business operations, technical operation and maintenance, technology research and development, security assurance and resource support; the objective indicators involve: service reliability, service responsiveness, service availability, service level achievement rate, service continuity, service satisfaction, incident closure rate, data persistence, service concurrency, resource efficiency and fault recovery efficiency.

11. A computer program product, comprising a computer program or instructions, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, characterized in that: The computer program stored in the computer-readable storage medium, when executed by one or more processors, implements the steps of the method according to any one of claims 1 to 9.

13. An electronic device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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