Evaluation method and system for enterprise digital transformation

Abstract

The invention provides an enterprise digital transformation evaluation method and system, and the method comprises the steps: obtaining scores of a plurality of enterprises in a target industry in an evaluation domain, and obtaining a score set of the evaluation domain; calculating a correlation coefficient between the evaluation domains according to the score set; if the target correlation coefficient exists, fusing the evaluation domains corresponding to at least one target correlation coefficient to obtain an evaluation domain group; obtaining evaluation indexes of the unfused evaluation domains to obtain a first evaluation index set, obtaining evaluation indexes of the evaluation domains contained in the evaluation domain group to obtain a second evaluation index set, and setting weights for the evaluation indexes in the second evaluation index set; calculating a first maturity score and a second maturity score of the evaluated enterprise; and generating a maturity evaluation result according to the first maturity score and the second maturity score. According to the invention, the evaluation accuracy of enterprise digital transformation is improved.

Description

Technical Field

[0001] The present application relates to the field of digital transformation technology, and in particular to an evaluation method and system for enterprise digital transformation. Background Art

[0002] With the rapid development of digital technologies such as cloud computing, big data, artificial intelligence, the Internet of Things, and blockchain, as well as changes in market demand in various industries, many companies are actively exploring digital transformation to integrate their original businesses with digital technologies, innovate, and achieve the transformation requirements for corporate performance growth and sustainable development.

[0003] Digital transformation is a long-term transformation process, and the maturity evaluation of digital transformation of enterprises is an important means to measure the digital transformation of enterprises. In related technologies, the maturity evaluation of digital transformation of enterprises usually determines the evaluation indicators through expert scoring, determines the indicator scores through questionnaires, and determines the maturity of digital transformation of enterprises based on the indicator scores. The evaluation results are greatly affected by subjective factors and lack accuracy. Summary of the invention

[0004] In order to improve the accuracy of the evaluation of enterprise digital transformation, the present application provides an evaluation method and system for enterprise digital transformation.

[0005] In a first aspect, the present application provides a method for evaluating the digital transformation of an enterprise, the method comprising:

[0006] Obtaining scores of multiple enterprises in a target industry in an evaluation domain to obtain a score set of the evaluation domain, wherein the target industry is the industry corresponding to the evaluated enterprise;

[0007] Calculating the correlation coefficient between the evaluation domains according to the score set;

[0008] If there is a target correlation coefficient, at least one evaluation domain corresponding to the target correlation coefficient is merged to obtain an evaluation domain group, wherein the target correlation coefficient is a correlation coefficient that meets a preset range;

[0009] Obtaining evaluation indicators of unfused evaluation domains to obtain a first evaluation indicator set, obtaining evaluation indicators of evaluation domains included in the evaluation domain group to obtain a second evaluation indicator set, and setting weights for evaluation indicators in the second evaluation indicator set;

[0010] Calculating a first maturity score of the evaluated enterprise according to a first indicator value of the evaluation indicator of the evaluated enterprise in the first evaluation indicator set, and calculating a second maturity score of the evaluated enterprise according to a second indicator value and a weight of the evaluation indicator of the evaluated enterprise in the second evaluation indicator set;

[0011] A maturity evaluation result is generated according to the first maturity score and the second maturity score.

[0012] In some embodiments, the step of fusing the evaluation domains corresponding to at least one of the target correlation coefficients to obtain an evaluation domain group includes:

[0013] When there are multiple target correlation coefficients, determining whether the multiple target correlation coefficients correspond to overlapping evaluation domains;

[0014] If there are no corresponding overlapping evaluation domains, the evaluation domains corresponding to the multiple target correlation coefficients are merged respectively to obtain multiple evaluation domain groups;

[0015] If there are corresponding overlapping evaluation domains, the evaluation domains corresponding to the target correlation coefficients are fused in descending order of the correlation coefficients until the correlation coefficients between the unfused evaluation domains are not the target correlation coefficients.

[0016] In some embodiments, setting weights for the evaluation indicators in the second evaluation indicator set includes:

[0017] In the second evaluation indicator set, the evaluation indicators of one evaluation domain are set with a first weight, and the remaining evaluation indicators are set with a second weight, and the second weight is greater than the first weight.

[0018] In some embodiments, setting weights for the evaluation indicators in the second evaluation indicator set includes:

[0019] Obtaining the priority of the evaluation domain corresponding to the target industry;

[0020] In the second evaluation indicator set, the evaluation indicators of the evaluation domain with a high priority are set with a first weight, and the remaining evaluation indicators are set with a second weight, and the second weight is greater than the first weight.

[0021] In some embodiments, generating a maturity evaluation result according to the first maturity score and the second maturity score includes:

[0022] The average maturity score of the evaluated enterprise in all evaluation domains is calculated according to the first maturity score and the second maturity score, and the maturity of the evaluated enterprise is determined according to the maturity score range corresponding to the average maturity score.

[0023] In some embodiments, generating a maturity evaluation result according to the first maturity score and the second maturity score includes:

[0024] The first maturity score and the second maturity score are weightedly summed to obtain an average maturity score of the evaluated enterprise in all evaluation domains, and the maturity of the evaluated enterprise is determined according to a maturity score range corresponding to the average maturity score.

[0025] In some embodiments, generating a maturity evaluation result according to the first maturity score and the second maturity score includes:

[0026] The maturity score variance of the evaluated enterprise in all evaluation domains is calculated according to the first maturity score and the second maturity score, and the maturity of the evaluated enterprise is determined according to the maturity variance range corresponding to the maturity score variance.

[0027] In a second aspect, the present application provides an evaluation system for enterprise digital transformation, which is characterized by including:

[0028] An evaluation domain scoring module is used to obtain the scores of multiple enterprises in a target industry in an evaluation domain, and obtain a score set of the evaluation domain, wherein the target industry is the industry corresponding to the evaluated enterprise;

[0029] An evaluation domain association analysis module, used to calculate the correlation coefficient between the evaluation domains according to the score set;

[0030] An evaluation domain fusion module, used for fusing at least one evaluation domain corresponding to a target correlation coefficient to obtain an evaluation domain group when there is a target correlation coefficient, wherein the target correlation coefficient is a correlation coefficient that meets a preset range;

[0031] An evaluation indicator setting module, used to obtain evaluation indicators of unfused evaluation domains to obtain a first evaluation indicator set, obtain evaluation indicators of evaluation domains included in the evaluation domain group to obtain a second evaluation indicator set, and set weights for evaluation indicators in the second evaluation indicator set;

[0032] An evaluation domain score calculation module, used to calculate a first maturity score of the evaluated enterprise according to a first indicator value of the evaluation indicator of the evaluated enterprise in the first evaluation indicator set, and to calculate a second maturity score of the evaluated enterprise according to a second indicator value and a weight of the evaluation indicator of the evaluated enterprise in the second evaluation indicator set;

[0033] The maturity output module is used to generate a maturity evaluation result according to the first maturity score and the second maturity score.

[0034] In some embodiments, the maturity output module is used to perform weighted summation of the first maturity score and the second maturity score to obtain an average maturity score of the evaluated enterprise in all evaluation domains, and determine the maturity of the evaluated enterprise based on a maturity score range corresponding to the average maturity score.

[0035] In some embodiments, the maturity output module is used to calculate the maturity score variance of the evaluated enterprise in all evaluation domains based on the first maturity score and the second maturity score, and determine the maturity of the evaluated enterprise based on the maturity variance range corresponding to the maturity score variance.

[0036] The beneficial effects of the enterprise digital transformation evaluation method and system provided in this application include:

[0037] When conducting a digital transformation evaluation on an evaluated enterprise, the embodiment of the present application determines an evaluation domain group corresponding to the target industry based on the scores of multiple enterprises in the target industry of the evaluated enterprise in the evaluation domain, and sets weights for the evaluation indicators of the evaluation domains it contains, so that the evaluation domain group can better reflect the industry characteristics of the target industry compared with the evaluation domains it contains, thereby improving the automation of the digital transformation evaluation of the evaluated enterprise and achieving higher accuracy of the evaluation results based on the first maturity score of the evaluated enterprise in the unintegrated evaluation domain and the second maturity score in the evaluation domain group. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the implementation methods in the embodiments of the present application or the related technologies, the following is a brief introduction to the drawings required for use in the embodiments or the related technology descriptions. Obviously, the drawings described below are some embodiments of the present application, and a person skilled in the art can also obtain other drawings based on these drawings.

[0039] Figure 1 A flowchart of an evaluation method for enterprise digital transformation according to some embodiments is exemplarily shown in FIG.

[0040] Figure 2 Schematic diagram of an evaluation domain model according to some embodiments is exemplarily shown in FIG.

[0041] Figure 3 exemplarily shows a flow chart of an evaluation domain classification method according to some embodiments;

[0042] Figure 4 A schematic diagram of a flow chart of an evaluation domain fusion method according to some embodiments is exemplarily shown in FIG.

[0043] Figure 5A flowchart of a method for setting weights of evaluation indicators according to some embodiments is exemplarily shown in FIG.

[0044] Figure 6 exemplarily shows a structural diagram of an evaluation system for enterprise digital transformation according to some embodiments;

[0045] Figure 7 exemplarily shows a schematic diagram of the structure of an evaluation domain scoring module according to some embodiments;

[0046] Figure 8 exemplarily shows a structural schematic diagram of an evaluation domain fusion module according to some embodiments;

[0047] Fig. 9 exemplarily shows a structural schematic diagram of an evaluation index setting module according to some embodiments;

[0048] Fig.10 The structure diagram of the evaluation system for enterprise digital transformation according to other embodiments is exemplified in FIG. DETAILED DESCRIPTION

[0049] In order to make the purpose and implementation method of the present application clearer, the exemplary implementation method of the present application will be clearly and completely described below in conjunction with the drawings in the exemplary embodiments of the present application. Obviously, the described exemplary embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0050] It should be noted that the brief description of terms in this application is only for the convenience of understanding the embodiments described below, and is not intended to limit the embodiments of this application. Unless otherwise specified, these terms should be understood according to their common and usual meanings.

[0051] The terms "first", "second", "third", etc. in the specification and claims of this application and the above drawings are used to distinguish similar or similar objects or entities, and do not necessarily mean to limit a specific order or sequence, unless otherwise noted. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances.

[0052] The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover but not exclude inclusion, for example, a product or device comprising a list of components is not necessarily limited to all the components expressly listed but may include other components not expressly listed or inherent to such product or device.

[0053] In some embodiments, the evaluation of enterprise digital transformation includes a maturity evaluation, which can be used to determine the development stage of the enterprise digital transformation, such as the first stage, the second stage, the third stage, etc., where the maturity of the second stage is higher than that of the first stage, the maturity of the third stage is higher than that of the second stage, and so on.

[0054] In some embodiments, maturity evaluation can be used to determine the maturity level of the enterprise's digital transformation, such as the first level, the second level, the third level, etc., where the maturity of the second level is higher than the first level, the maturity of the third level is higher than the second level, and so on.

[0055] In order to evaluate the maturity of enterprise digital transformation, the present application embodiment provides an evaluation method for enterprise digital transformation, see Figure 1 , the method may include the following steps:

[0056] Step S101: Obtain scores of multiple enterprises in a target industry in an evaluation domain to obtain a score set of the evaluation domain, wherein the target industry is the industry corresponding to the evaluated enterprise.

[0057] In some embodiments, enterprises in different industries have different industry characteristics when conducting digital transformation. For example, enterprises in industry A may have simpler and more mature digital transformation in some areas, and more complex and less mature digital transformation in other areas, while enterprises in industry B may have the opposite.

[0058] In order to accurately evaluate the digital transformation of the evaluated enterprise, the industry corresponding to an evaluated enterprise, that is, the industry in which the evaluated enterprise is located, can be determined as the target industry, and the digital transformation data of multiple enterprises in the target industry can be analyzed, wherein these enterprises can be called sample enterprises. According to the analysis results of the digital transformation data of multiple enterprises in the target industry, data representing the industry characteristics of the target industry are obtained, and then based on the data representing the industry characteristics of the target industry, the digital transformation of the evaluated enterprise is evaluated, and the evaluation results of the digital transformation of the evaluated enterprise are obtained, which can improve the evaluation accuracy of the digital transformation of the evaluated enterprise.

[0059] In some embodiments, an evaluation domain model may be pre-constructed. The evaluation domain model includes multiple evaluation domains, which are pre-set evaluation fields for evaluating the maturity of digital transformation.

[0060] For example, see Figure 2 , is a schematic diagram of an evaluation domain model according to some embodiments, such as Figure 2As shown, the evaluation domain model may include a first-level evaluation domain 200 and a second-level evaluation domain 300. Among them, the first-level evaluation domain 200 is a comprehensive field for evaluating digital transformation, which may include a development strategy evaluation domain, a new capability evaluation domain, a systematic solution evaluation domain, a governance system evaluation domain, and a business innovation transformation evaluation domain. The second-level evaluation domain 300 is a subdivision of the first-level evaluation domain 200. For example, the development strategy evaluation domain can be subdivided into a competitive cooperation advantage evaluation domain, a business scenario evaluation domain, and a value model evaluation domain. In an embodiment of the present application, the maturity of the evaluated enterprise can be evaluated based on the second-level evaluation domain 300.

[0061] In some embodiments, for a target industry, multiple evaluation domains may be pre-set, such as Figure 2 The secondary evaluation domain 300 in the evaluation domain measures the maturity of enterprises in the industry in different dimensions of digital transformation. For sample enterprises, their digital transformation data can be obtained, and the digital transformation data can include their scores in each evaluation domain. The higher the score of a sample enterprise in an evaluation domain, the higher the maturity of the digital transformation of the sample enterprise in the evaluation domain.

[0062] In some embodiments, the scores of sample enterprises in each evaluation domain can be obtained through the Delphi method. The Delphi method is also called the expert opinion method. This method uses multiple rounds of surveys to obtain the scores of sample enterprises in each evaluation domain by experts. After repeated consultation, induction, and modification, the scores of the sample enterprises by experts with high consistency are finally summarized as the prediction results. The prediction results obtained by this method are widely representative and relatively reliable.

[0063] In some embodiments, the scores of the sample enterprises in each evaluation domain may also be obtained by other methods. For example, the data of the specified type of each sample enterprise in the evaluation domain may be normalized and analyzed to obtain the scores of each sample enterprise in the evaluation domain. For one evaluation domain, one or more specified types of data may be predetermined. If multiple specified types of data are determined, the different types of data may be normalized and analyzed respectively, and the normalized data may be weighted and summed to obtain the scores of the sample enterprises in the evaluation domain. For different evaluation domains, different specified types of data may be predetermined to generate scores in the evaluation domain.

[0064] In some embodiments, after a maturity assessment of a digital transformation is initiated for an evaluated enterprise, the scores of sample enterprises in the industry of the evaluated enterprise in each evaluation domain can be obtained, and a score set for each evaluation domain can be generated, where the elements in the score set are the scores of each sample enterprise in the evaluation domain.

[0065] Exemplarily, the value range of the score P of each evaluation domain is: 0≤P≤10. Taking the number of sample enterprises in the target industry as 5, the score set P1 of the competitive cooperation advantage evaluation domain is: P1=[6,6,5,4,4], the score set P2 of the business scenario evaluation domain is: P2=[3,5,3,6,5], and so on, the score sets of each secondary evaluation domain 300 are obtained: P1, P2, ..., P22.

[0066] Step S102: Calculate the correlation coefficient between the evaluation domains according to the score set.

[0067] In some embodiments, for a target industry, the evaluation domains may have a certain correlation in the maturity of digital transformation, and the correlation is related to the characteristics of the industry. For example, for industry A, the first evaluation domain and the second evaluation domain have a certain correlation, and for industry B, the first evaluation domain and the third evaluation domain have a certain correlation.

[0068] After obtaining the score set of the target industry in each evaluation domain, the correlation coefficient between the evaluation domains can be calculated based on the score set. For two evaluation domains, if the absolute value of the correlation coefficient is large, it means that the correlation between the two evaluation domains in terms of the maturity of digital transformation is strong; if the absolute value of the correlation coefficient is small, it means that the correlation between the two evaluation domains in terms of the maturity of digital transformation is weak.

[0069] In some embodiments, the correlation coefficient may be a Pearson correlation coefficient. For two evaluation domains, the Pearson correlation coefficient between the score sets of the two evaluation domains is calculated to determine whether the two evaluation domains have a strong correlation. The value range of the Pearson correlation coefficient is between -1 and 1, where 1 represents a perfect positive correlation, -1 represents a perfect negative correlation, and 0 represents no linear correlation.

[0070] For example, the Pearson correlation coefficient can be represented by ρ, ρ 1-2 represents the Pearson correlation coefficient between the competitive cooperation advantage evaluation domain and the business scenario evaluation domain, ρ 1-3 Represents the Pearson correlation coefficient between the competitive cooperation advantage evaluation domain and the value model evaluation domain.

[0071] In some embodiments, for two evaluation domains, the correlation coefficient may also be calculated by other methods. For example, a nonlinear correlation coefficient between two score sets, such as an eta coefficient, may also be calculated.

[0072] Step S103: If there is a target correlation coefficient, at least one evaluation domain corresponding to the target correlation coefficient is merged to obtain an evaluation domain group, and the target correlation coefficient is a correlation coefficient that meets a preset range.

[0073] In some embodiments, the preset range may be greater than the first threshold or less than the second threshold. For example, the first threshold may be 0.9 and the second threshold may be -0.9. The correlation coefficient that meets the preset range is determined as the target correlation coefficient.

[0074] In some embodiments, after calculating all correlation coefficients between an evaluation domain and other evaluation domains, the evaluation domain may be classified. Figure 3 , is a flowchart of an evaluation domain classification method according to some embodiments, such as Figure 3 As shown, the method may include the following steps:

[0075] Step S201: Obtain all correlation coefficients corresponding to the evaluation domain.

[0076] In some embodiments, if the total number of evaluation domains is N, the number of all correlation coefficients corresponding to one evaluation domain is N-1.

[0077] Step S202: Determine whether there is at least one correlation coefficient in the evaluation domain within a preset range.

[0078] In some embodiments, for an evaluation domain, it may be determined whether each corresponding correlation coefficient is within a preset range.

[0079] Step S203: If it does not exist, determine the evaluation domain as an independent evaluation domain.

[0080] In some embodiments, for an evaluation domain, if each of its corresponding correlation coefficients is not within a preset range, it indicates that the correlation relationship between the evaluation domain and other evaluation domains is weak, and the evaluation domain can be determined as an independent evaluation domain.

[0081] Step S203: If it exists, determine the evaluation domain as a non-independent evaluation domain.

[0082] In some embodiments, for an evaluation domain, if at least one correlation coefficient corresponding to the evaluation domain is within a preset range, it indicates that the evaluation domain has a strong correlation with at least one evaluation domain, and the evaluation domain can be determined as a non-independent evaluation domain.

[0083] For different target industries, due to different industry characteristics, Figure 2 The evaluation domain model shown may result in different independent evaluation domains and different non-independent evaluation domains. Therefore, some non-independent evaluation domains can be fused to obtain an evaluation domain group. In subsequent steps, the evaluation domain group can replace the evaluation domains contained in the evaluation domain group to control the final evaluation results, which can fully reflect the characteristics of the industry and improve the accuracy of the evaluation results.

[0084] See also Figure 4 , is a flowchart of an evaluation domain fusion method according to some embodiments, such as Figure 4 As shown, the method may include the following steps:

[0085] Step S301: when there are multiple target correlation coefficients, determine whether the multiple target correlation coefficients correspond to overlapping evaluation domains.

[0086] In some embodiments, if the number of target correlation coefficients calculated in step S103 is 1, the evaluation domains corresponding to the target correlation coefficient may be fused to generate an evaluation domain group, and the evaluation domains corresponding to other correlation coefficients are not fused.

[0087] In some embodiments, if the number of target correlation coefficients calculated in step S103 is multiple, the evaluation domains corresponding to these target correlation coefficients can be traversed, and if one of the evaluation domains corresponding to a target correlation coefficient is also one of the evaluation domains corresponding to another target correlation coefficient, then it is determined that the two target correlation coefficients correspond to overlapping evaluation domains. If one of the evaluation domains corresponding to a target correlation coefficient is not one of the evaluation domains corresponding to the remaining target correlation coefficients, then it is determined that the target correlation coefficient and the remaining target correlation coefficients do not correspond to overlapping evaluation domains.

[0088] Step S302: If there are no corresponding overlapping evaluation domains, the evaluation domains corresponding to the plurality of target correlation coefficients are merged respectively to obtain a plurality of evaluation domain groups.

[0089] In some embodiments, if any two target correlation coefficients do not correspond to overlapping evaluation domains, the evaluation domains corresponding to the target correlation coefficients may be fused separately to obtain multiple evaluation domain groups.

[0090] Step S303: If there are corresponding overlapping evaluation domains, the evaluation domains corresponding to the target correlation coefficients are merged in descending order of the correlation coefficients until the correlation coefficients between the unfused evaluation domains are not the target correlation coefficients.

[0091] In some embodiments, if two of the target correlation coefficients correspond to overlapping evaluation domains, the target correlation coefficients can be sorted, and then the evaluation domains corresponding to the largest target correlation coefficients are fused to obtain an evaluation domain group. At this time, the unfused evaluation domains will not include the evaluation domains in the evaluation domain group. For the unfused evaluation domains, the evaluation domains corresponding to the current largest target correlation coefficients are fused to obtain a new evaluation domain group. At this time, the unfused evaluation domains will not include the evaluation domains in the new evaluation domain group. And so on, until the correlation coefficients between the unfused evaluation domains are not the target correlation coefficients.

[0092] Step S104: obtaining evaluation indicators of unfused evaluation domains to obtain a first evaluation indicator set, obtaining evaluation indicators of evaluation domains included in the evaluation domain group to obtain a second evaluation indicator set, and setting weights for evaluation indicators in the second evaluation indicator set.

[0093] In some embodiments, for different evaluation domains, evaluation indicators for evaluating the maturity of digital transformation can be pre-set in the evaluation domains.

[0094] In some embodiments, if an evaluation domain is an independent evaluation domain, the set of evaluation indicators of the evaluation domain is called a first evaluation indicator set.

[0095] In some embodiments, if an evaluation domain and other evaluation domains constitute an evaluation domain group, the evaluation indicators of the evaluation domains constituting the evaluation domain group constitute the second evaluation indicator set. For example, the first evaluation domain and the second evaluation domain constitute an evaluation domain group, and the evaluation indicators of the first evaluation domain and the evaluation indicators of the second evaluation domain constitute the second evaluation indicator set.

[0096] When determining the maturity of the digital transformation of the evaluated enterprise, it is necessary to integrate the evaluation results of multiple evaluation domains to obtain the final evaluation result. In order to make the final evaluation result more reflect the characteristics of the industry, the embodiment of the present application aggregates the evaluation indicators of multiple evaluation domains of the evaluation domain group into a second evaluation indicator set, so that the evaluation domain group is used as a new evaluation domain to replace the evaluation domain included in the evaluation domain group to control the final evaluation result, which can improve the accuracy of the evaluation result.

[0097] In some embodiments, in order to distinguish the roles of evaluation indicators of different evaluation domains in the second evaluation indicator set in maturity evaluation, weights may be set for the evaluation indicators in the second evaluation indicator set.

[0098] For example, the priority of the evaluation domain of each industry can be set in advance according to the industry characteristics of each industry, and the evaluation indicators in the second evaluation indicator set are weighted based on the priority. Figure 5 , is a flow chart of a method for setting weights of evaluation indicators according to some embodiments, such as Figure 5 As shown, the method may include the following steps:

[0099] Step S401: Obtain the priority of the evaluation domain corresponding to the target industry.

[0100] In some embodiments, after the second evaluation indicator set is generated, the priority of the evaluation domain corresponding to the preset target industry can be obtained.

[0101] Step S402: In the second evaluation indicator set, the evaluation indicators of the evaluation domain with a high priority are set with a first weight, and the remaining evaluation indicators are set with a second weight, and the second weight is greater than the first weight.

[0102] In some embodiments, for a second evaluation indicator set, the evaluation indicators of the evaluation domain with a high priority may be set to a first weight, and the evaluation indicators of the evaluation domain with a low priority may be set to a second weight, and the second weight may be greater than the first weight.

[0103] For example, for the target industry corresponding to the evaluated enterprise, the business scenario evaluation domain and the business digitalization evaluation domain constitute an evaluation domain group, wherein the evaluation indicators of the business scenario evaluation domain include the business scenario digitization rate and the business scenario modeling rate, and the evaluation indicators of the business digitalization evaluation domain include the R&D business digitization rate, the R&D business modeling rate, the R&D cycle shortening rate, and the R&D cost reduction rate. Since in this target industry, the priority of the business digitalization evaluation domain is higher than that of the business scenario evaluation domain, the business scenario digitization rate and the business scenario modeling rate are set to the first weight, and the R&D business digitization rate, the R&D business modeling rate, the R&D cycle shortening rate, and the R&D cost reduction rate are set to the second weight.

[0104] Exemplarily, in order to improve the efficiency of setting weights, a general priority order of evaluation domains can be pre-set for each industry. After obtaining the second set of evaluation indicators, the evaluation indicators of one of the evaluation domains are set to a first weight according to the priority order, and the remaining evaluation indicators are set to a second weight, and the second weight is greater than the first weight.

[0105] Step S105: Calculate the first maturity score of the evaluated enterprise according to the first indicator value of the evaluation indicator of the evaluated enterprise in the first evaluation indicator set, and calculate the second maturity score of the evaluated enterprise according to the second indicator value and weight of the evaluation indicator of the evaluated enterprise in the second evaluation indicator set.

[0106] In some embodiments, a corresponding indicator value calculation formula may be pre-set for each evaluation indicator. For the evaluated enterprise, the enterprise transformation data corresponding to each indicator value calculation formula may be obtained, and the indicator value of each evaluation indicator may be calculated according to the indicator value calculation formula.

[0107] After obtaining the index value of each evaluation index in a first evaluation index set, the first maturity score S1 of the evaluation domain can be calculated according to the average value of the scores of all evaluation indexes in the first evaluation index set. The calculation formula is as follows:

[0108]

[0109] Among them, α i1is the first indicator value, i1 represents the evaluation indicator in the first evaluation indicator set, and n1 represents the number of evaluation indicators in the evaluation domain.

[0110] After obtaining the index value of each evaluation index in a second evaluation index set, the second maturity score S2 of the evaluated enterprise in the evaluation domain group can be obtained by weighted summing all the evaluation indexes in the second evaluation index set and then taking the average value. The calculation formula is as follows:

[0111]

[0112] Where a is the first weight, b is the second weight, the range of a and b is 0 to 1, and the sum of a and b is 1, i2 represents the evaluation index with the first weight, i3 represents the evaluation index with the second weight, α i2 is the second indicator value of the evaluation indicator with the first weight, n2 represents the number of evaluation indicators with the first weight, α i3 is the second indicator value of the evaluation indicator with the second weight, and n3 represents the number of evaluation indicators with the second weight.

[0113] Step S106: Generate a maturity evaluation result according to the first maturity score and the second maturity score.

[0114] In some embodiments, for the evaluated enterprise, the average of the first maturity score of each independent evaluation domain and the second maturity score of the evaluation domain group may be calculated to obtain the average maturity score of the evaluated enterprise in all evaluation domains. The calculation formula is as follows:

[0115]

[0116] Among them, n m It represents the number of all evaluation domains before fusion, p1 represents independent evaluation domains, m1 represents the number of independent evaluation domains, p2 represents evaluation domain groups, and m2 represents the number of evaluation domain groups.

[0117] The maturity of the evaluated enterprise is determined based on the maturity score range corresponding to the maturity average score. Different maturity score ranges correspond to different maturity levels. The maturity level of the evaluated enterprise is obtained based on the maturity average score.

[0118] In some embodiments, for the evaluated enterprise, the average value of the weighted sum of the first maturity score of each independent evaluation domain and the second maturity score of the evaluation domain group may be calculated to obtain the average maturity score of the evaluated enterprise in all evaluation domains. The calculation formula is as follows:

[0119]

[0120] Among them, c is the third weight, d is the fourth weight, the range of c and d is 0 to 1, and the sum of c and d is 1.

[0121] In some embodiments, when there is no evaluation domain group for the target industry, the value of c is 1 and the value of d is 0.

[0122] In some embodiments, when there is an evaluation domain group in the target industry, the value of c is smaller than the value of d, so that the calculated average maturity score can better reflect the industry characteristics and has higher accuracy.

[0123] The maturity of the evaluated enterprise is determined based on the maturity score range corresponding to the maturity average score. Different maturity score ranges correspond to different maturity levels. The maturity level of the evaluated enterprise is obtained based on the maturity average score.

[0124] In some embodiments, for the evaluated enterprise, the maturity score variance of the evaluated enterprise in all evaluation domains can be calculated based on all the first maturity scores and the second maturity scores, and the maturity of the evaluated enterprise can be determined based on the maturity variance range corresponding to the maturity score variance. Different maturity variance ranges correspond to different development stages, and the development stage of the digital transformation of the evaluated enterprise can be obtained based on the maturity variance range.

[0125] It can be seen from the above embodiments that when the embodiment of the present application conducts a digital transformation evaluation on the evaluated enterprise, the independent evaluation domain and evaluation domain group corresponding to the target industry are determined according to the scores of multiple enterprises in the target industry of the evaluated enterprise in the evaluation domain, wherein, for the evaluation domain group, weights are set for the evaluation indicators of the evaluation domains it contains, so that the evaluation domain group can better reflect the industry characteristics of the target industry than the evaluation domains it contains, thereby improving the automation of the digital transformation evaluation of the evaluated enterprise based on the first maturity score of the evaluated enterprise in the independent evaluation domain and the second maturity score in the evaluation domain group, and the accuracy of the evaluation results is relatively high.

[0126] See also Figure 6 The embodiment of the present application also provides an evaluation system for enterprise digital transformation, which is used to realize the automated evaluation of enterprise digital transformation, such as Figure 6 As shown, the evaluation system may include the following functional modules:

[0127] The evaluation domain scoring module 501 is used to obtain the scores of multiple enterprises in the target industry in the evaluation domain to obtain a score set of the evaluation domain.

[0128] In some embodiments, the evaluation domain scoring module 501 may be provided with a plurality of evaluation units, each of which corresponds to an evaluation domain, and is used to obtain the evaluation domain score of a sample enterprise in a target industry in one of the evaluation domains. Figure 7The evaluation domain scoring module may include a competitive cooperation advantage unit, a business scenario unit...a digital business cultivation unit.

[0129] An evaluation domain correlation analysis module 502 is used to calculate correlation coefficients between multiple evaluation domains based on a score set;

[0130] The evaluation domain fusion module 503 is used to fuse at least one evaluation domain corresponding to the target correlation coefficient to obtain an evaluation domain group when there is a target correlation coefficient, and the target correlation coefficient is a correlation coefficient that meets a preset range.

[0131] In some embodiments, see Figure 8 The evaluation domain fusion module 503 may include an evaluation domain classification unit and an evaluation domain group management unit. The evaluation domain classification unit is used to divide the evaluation domain into independent evaluation domains and non-independent evaluation domains according to the correlation coefficient; the evaluation domain group management unit is used to fuse the non-independent evaluation domains into the evaluation domain group according to the correlation coefficient.

[0132] The evaluation index setting module 504 is used to obtain the evaluation index of the unfused evaluation domain to obtain a first evaluation index set, obtain the evaluation index of the evaluation domain included in the evaluation domain group to obtain a second evaluation index set, and set weights for the evaluation indexes in the second evaluation index set.

[0133] In some embodiments, see Fig. 9 The evaluation index setting module 504 may include an evaluation domain index setting unit and an evaluation domain group index setting unit. The evaluation domain index setting unit is used to calculate the index value of the evaluation index of the unfused evaluation domain; the evaluation domain group index setting unit is used to set the weight of the evaluation index in the evaluation domain group and calculate the index value of the evaluation index in the evaluation domain group.

[0134] The evaluation domain score calculation module 505 is used to calculate the first maturity score of the evaluated enterprise according to the first indicator value of the evaluation indicator of the evaluated enterprise in the first evaluation indicator set, and to calculate the second maturity score of the evaluated enterprise according to the second indicator value and weight of the evaluation indicator of the evaluated enterprise in the second evaluation indicator set.

[0135] The maturity output module 506 is used to generate a maturity evaluation result according to the first maturity score and the second maturity score.

[0136] See also Fig.10 , the embodiment of the present application also provides another enterprise digital transformation evaluation system, which is used to realize the automated evaluation of enterprise digital transformation, such as Fig.10 As shown, the evaluation system may include the following functional modules:

[0137] Evaluation domain management module 601, used to set Figure 2 The evaluation domain model shown obtains the scores of multiple enterprises in the target industry in the evaluation domain to obtain a score set of the evaluation domain.

[0138] The evaluation domain group management module 602 is used to implement the functions of the evaluation domain association analysis module 502 and the evaluation domain fusion module 503 .

[0139] The evaluation index management module 603 is used to set the evaluation index of each evaluation domain and realize the functions of the evaluation index setting module 504 and the evaluation domain score calculation module 505.

[0140] The maturity evaluation and reporting module 604 is used to implement the functions of the maturity output module 506 and output report information on digital transformation. The report information may include information on evaluation domains or evaluation domain groups whose maturity scores are lower than a preset score threshold, so as to indicate the deficiencies of the evaluated enterprise in the digital transformation process.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0142] For the convenience of explanation, the above description has been made in conjunction with specific embodiments. However, the above exemplary discussion is not intended to be exhaustive or limit the embodiments to the specific forms disclosed above. Based on the above teachings, various modifications and variations can be obtained. The selection and description of the above embodiments are to better explain the principles and practical applications, so that those skilled in the art can better use the embodiments and various different variations of the embodiments suitable for specific use considerations.

Claims

1. A method for evaluating enterprise digital transformation, characterized in that: include: Obtaining scores of multiple enterprises in a target industry in an evaluation domain to obtain a score set of the evaluation domain, wherein the target industry is the industry corresponding to the evaluated enterprise; Calculating the correlation coefficient between the evaluation domains according to the score set; If there is a target correlation coefficient, at least one evaluation domain corresponding to the target correlation coefficient is merged to obtain an evaluation domain group, wherein the target correlation coefficient is a correlation coefficient that meets a preset range; Obtaining evaluation indicators of unfused evaluation domains to obtain a first evaluation indicator set, obtaining evaluation indicators of evaluation domains included in the evaluation domain group to obtain a second evaluation indicator set, and setting weights for evaluation indicators in the second evaluation indicator set; Calculating a first maturity score of the evaluated enterprise according to a first indicator value of the evaluation indicator of the evaluated enterprise in the first evaluation indicator set, and calculating a second maturity score of the evaluated enterprise according to a second indicator value and a weight of the evaluation indicator of the evaluated enterprise in the second evaluation indicator set; A maturity evaluation result is generated according to the first maturity score and the second maturity score.

2. The evaluation method for enterprise digital transformation according to claim 1 is characterized in that: The step of fusing the evaluation domains corresponding to at least one of the target correlation coefficients to obtain an evaluation domain group includes: When there are multiple target correlation coefficients, determining whether the multiple target correlation coefficients correspond to overlapping evaluation domains; If there are no corresponding overlapping evaluation domains, the evaluation domains corresponding to the multiple target correlation coefficients are merged respectively to obtain multiple evaluation domain groups; If there are corresponding overlapping evaluation domains, the evaluation domains corresponding to the target correlation coefficients are fused in descending order of the correlation coefficients until the correlation coefficients between the unfused evaluation domains are not the target correlation coefficients.

3. The evaluation method for enterprise digital transformation according to claim 1 is characterized in that: The step of setting weights for the evaluation indicators in the second evaluation indicator set includes: In the second evaluation indicator set, the evaluation indicators of one evaluation domain are set with a first weight, and the remaining evaluation indicators are set with a second weight, and the second weight is greater than the first weight.

4. The evaluation method for enterprise digital transformation according to claim 1 is characterized in that: The step of setting weights for the evaluation indicators in the second evaluation indicator set includes: Obtaining the priority of the evaluation domain corresponding to the target industry; In the second evaluation indicator set, the evaluation indicators of the evaluation domain with a high priority are set with a first weight, and the remaining evaluation indicators are set with a second weight, and the second weight is greater than the first weight.

5. The enterprise digital transformation evaluation method according to claim 1 is characterized in that: Generating a maturity evaluation result according to the first maturity score and the second maturity score includes: The average maturity score of the evaluated enterprise in all evaluation domains is calculated according to the first maturity score and the second maturity score, and the maturity of the evaluated enterprise is determined according to the maturity score range corresponding to the average maturity score.

6. The evaluation method for enterprise digital transformation according to claim 1 is characterized in that: Generating a maturity evaluation result according to the first maturity score and the second maturity score includes: The first maturity score and the second maturity score are weightedly summed to obtain an average maturity score of the evaluated enterprise in all evaluation domains, and the maturity of the evaluated enterprise is determined according to a maturity score range corresponding to the average maturity score.

7. The enterprise digital transformation evaluation method according to claim 1 is characterized in that: Generating a maturity evaluation result according to the first maturity score and the second maturity score includes: The maturity score variance of the evaluated enterprise in all evaluation domains is calculated according to the first maturity score and the second maturity score, and the maturity of the evaluated enterprise is determined according to the maturity variance range corresponding to the maturity score variance.

8. An evaluation system for enterprise digital transformation, characterized in that: include: An evaluation domain scoring module is used to obtain the scores of multiple enterprises in a target industry in an evaluation domain, and obtain a score set of the evaluation domain, wherein the target industry is the industry corresponding to the evaluated enterprise; An evaluation domain association analysis module, used to calculate the correlation coefficient between the evaluation domains according to the score set; An evaluation domain fusion module, used for fusing at least one evaluation domain corresponding to a target correlation coefficient to obtain an evaluation domain group when there is a target correlation coefficient, wherein the target correlation coefficient is a correlation coefficient that meets a preset range; An evaluation indicator setting module, used to obtain evaluation indicators of unfused evaluation domains to obtain a first evaluation indicator set, obtain evaluation indicators of evaluation domains included in the evaluation domain group to obtain a second evaluation indicator set, and set weights for evaluation indicators in the second evaluation indicator set; An evaluation domain score calculation module, used to calculate a first maturity score of the evaluated enterprise according to a first indicator value of the evaluation indicator of the evaluated enterprise in the first evaluation indicator set, and to calculate a second maturity score of the evaluated enterprise according to a second indicator value and a weight of the evaluation indicator of the evaluated enterprise in the second evaluation indicator set; The maturity output module is used to generate a maturity evaluation result according to the first maturity score and the second maturity score.

9. The enterprise digital transformation evaluation system according to claim 8, characterized in that: The maturity output module is used to perform weighted summation of the first maturity score and the second maturity score to obtain an average maturity score of the evaluated enterprise in all evaluation domains, and determine the maturity of the evaluated enterprise according to a maturity score range corresponding to the average maturity score.

10. The enterprise digital transformation evaluation system according to claim 8, characterized in that: The maturity output module is used to calculate the maturity score variance of the evaluated enterprise in all evaluation domains according to the first maturity score and the second maturity score, and determine the maturity of the evaluated enterprise according to the maturity variance range corresponding to the maturity score variance.

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