Enterprise digital transformation service platform

Abstract

The invention relates to the technical field of digital platforms, in particular to an enterprise digital transformation service platform, which comprises a data acquisition module used for acquiring operation data of an enterprise to be transformed; the data processing module is used for carrying out standardization processing on the operation data of the to-be-transformed enterprise; the enterprise operation scene model construction module is used for constructing an enterprise operation scene model according to the standardized operation data of the to-be-transformed enterprise; and the matching and analyzing module is used for matching and analyzing the constructed enterprise operation scene model and the model in the transformation database and outputting an analysis result. The enterprise operation scene model construction module can construct a model reflecting the actual operation condition of an enterprise, the operation condition and existing problems of the enterprise can be known more visually, and the matching and analysis module finds out potential opportunities and challenges of digital transformation of the enterprise through comparative analysis. According to the method, targeted transformation suggestions and schemes can be quickly and efficiently provided for enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of digital platforms, and particularly to an enterprise digital transformation service platform. Background Art

[0002] Enterprise digital transformation refers to the comprehensive and in-depth transformation and upgrading of an enterprise's or individual's business processes, organizational structure, cultural concepts, etc. by using digital technologies such as big data, cloud computing, and artificial intelligence to achieve a more efficient, intelligent, and flexible operation mode. Digital transformation can help enterprises better understand market demands and customer behaviors, so as to respond to market changes faster, provide solutions that meet customer expectations, and enhance the competitiveness of products and services. Reduce human errors and time waste through automated tools and digital processes, improve internal operation efficiency, and reduce costs. At the same time, improve the efficiency in aspects such as supply chain management, logistics, and inventory control. Digital transformation encourages enterprises to innovate, adopt new technologies and digital tools, develop new products, services, and business models, and create new business opportunities. Through digital channels and mobile applications, enterprises can interact more closely with customers, meet their individualized needs, and provide convenient and personalized services.

[0003] Enterprise digital transformation service platforms integrate various digital tools and technologies such as cloud computing, big data analysis, artificial intelligence, and the Internet of Things to provide enterprises with a package of solutions. Existing platforms still have deficiencies in analysis efficiency and meeting the personalized needs of enterprises, and it is difficult to fully adapt to the specific situations and needs of enterprises. Summary of the Invention

[0004] (1) Object of the Invention

[0005] The object of the present invention is to provide an enterprise digital transformation service platform that can improve analysis efficiency and personalization degree.

[0006] (2) Technical Solution

[0007] To solve the above problems, the present invention provides an enterprise digital transformation service platform, including:

[0008] A data collection module, which is used to collect the business data of the enterprise to be transformed;

[0009] A data processing module, which is used to perform standardization processing on the business data of the enterprise to be transformed;

[0010] An enterprise business scenario model construction module, which is used to construct an enterprise business scenario model according to the standardized business data of the enterprise to be transformed;

[0011] A matching and analysis module, which is used to match, analyze the constructed enterprise operation scenario model and the model in the transformation database, and output the analysis result.

[0012] On the other hand, preferably, the enterprise operation scenario model includes multiple capabilities and multiple criteria, and each of the capabilities includes a corresponding plurality of criteria;

[0013] Constructing an enterprise operation scenario model according to the operation data of the enterprise to be transformed after the standardized processing, including:

[0014] Calculating the weights corresponding to a plurality of capabilities and a plurality of criteria corresponding to the enterprise to be transformed according to the operation data of the enterprise to be transformed;

[0015] Matching, analyzing the constructed enterprise operation scenario model and the model in the transformation database, and outputting the analysis result, including:

[0016] Matching the model with the highest similarity to the enterprise to be transformed from the transformation database according to the enterprise characteristics in the operation data of the enterprise to be transformed;

[0017] Calculating the matching values corresponding to a plurality of criteria between the model with the highest similarity and the enterprise operation scenario model of the enterprise to be transformed;

[0018] Calculating the overall matching value between the model with the highest similarity and the enterprise operation scenario model of the enterprise to be transformed according to the matching values corresponding to a plurality of criteria and the weights corresponding to a plurality of capabilities and a plurality of criteria;

[0019] Outputting the analysis result according to the matching values corresponding to the plurality of criteria and the overall matching value.

[0020] On the other hand, preferably,

[0021] The overall matching value is calculated using the following formula:

[0022]

[0023] where C total represents the overall matching value, W' j represents the weight of the jth capability after normalization processing, n j represents the number of criteria under the jth capability, ω jk represents the weight of the kth criterion under the jth capability, n represents the number of capabilities, Z jk represents the matching value of the kth criterion under the jth capability.

[0024] On the other hand of the present invention, preferably, the matching values corresponding to multiple capabilities and multiple criteria between the model with the highest calculated similarity and the business scenario model of the enterprise to be transformed are calculated using the following formula:

[0025]

[0026] where Z jk represents the k-th criterion matching value under the j-th capability, Z jk-f represents the data of the k-th criterion under the j-th capability of the enterprise to be transformed, Z jk-m represents the data of the k-th criterion under the j-th capability of the model with the highest calculated similarity, and threshold is 10 -7 .

[0027] On the other hand of the present invention, preferably,

[0028] The weights corresponding to several capabilities and multiple criteria of the enterprise to be transformed include data standardization using the following formula:

[0029]

[0030] where x jk represents the original data under the k-th criterion under the j-th capability, r jk is the data after standardization under the k-th criterion under the j-th capability, and n is the number of capabilities.

[0031] On the other hand of the present invention, preferably,

[0032] The weights corresponding to each criterion under each capability are calculated using the following formula:

[0033]

[0034] where ω jk represents the weight of the k-th criterion under the j-th capability, n j represents the number of criteria under the j-th capability, r jk is the data after standardization under the k-th criterion under the j-th capability, and n is the number of capabilities.

[0035] On the other hand of the present invention, preferably,

[0036] The weights corresponding to each capability are calculated using the following formula:

[0037]

[0038] where W j represents the weight of the j-th capability, W' jRepresents the weight of the j-th ability after normalization, n j Represents the number of criteria under the j-th ability, ω jk Represents the weight of the k-th criterion under the j-th ability, and n represents the number of abilities.

[0039] On the other hand, preferably,

[0040] Matching the model with the highest similarity to the enterprise to be transformed from the transformation database according to the enterprise characteristics in the operation data of the enterprise to be transformed includes:

[0041] Calculating the similarity value using the following formula:

[0042]

[0043] Where Q represents the similarity value; Represents the average value of each enterprise characteristic, Represents the average value of each characteristic of the mature digital transformation model; X u Represents the value of characteristic u in the enterprise characteristics, Y u Represents the value of characteristic u in the mature digital transformation model, and v represents the total number of characteristics of the mature digital transformation model;

[0044] Selecting the model with the largest similarity value Q from all models.

[0045] On the other hand, preferably,

[0046] Outputting the analysis result according to the matching values corresponding to the multiple criteria and the overall matching value includes:

[0047] Outputting the stage of the enterprise to be transformed according to the overall matching value and a preset first-level threshold;

[0048] Identifying the weak points of the enterprise to be transformed according to the matching values corresponding to the multiple criteria;

[0049] Outputting the analysis result according to the stage and the weak points of the enterprise to be transformed.

[0050] On the other hand, preferably, the stage includes the primary stage, the growth stage, and the mature stage;

[0051] When the overall matching value is lower than the lowest threshold of the preset first-level threshold, the enterprise to be transformed is in the primary stage;

[0052] When the overall matching value is between the lowest threshold and the medium threshold of the first-level threshold, the enterprise to be transformed is in the growth stage;

[0053] When the overall matching value is higher than the highest value among the preset first-level thresholds, the enterprise to be transformed is in the mature stage.

[0054] (III) Beneficial effects

[0055] The above technical solutions of the present invention have the following beneficial technical effects:

[0056] Through the data collection module, the present invention can comprehensively and accurately collect various business data of the enterprise to be transformed, ensuring the integrity and real-time nature of the data. Through standardization processing, the data processing module eliminates differences in data format, unit, quality, etc., providing a unified and comparable data basis for subsequent analysis. The enterprise business scenario model construction module can construct a model reflecting the actual business situation of the enterprise based on the standardized data, enabling a more intuitive understanding of its own business situation and existing problems, and providing strong support for subsequent digital transformation. The matching and analysis module matches the constructed enterprise business scenario model with the models in the transformation database, and through comparative analysis, identifies potential opportunities and challenges for the enterprise's digital transformation. This matching and analysis process is not only fast and efficient, but also can quickly provide targeted transformation suggestions and solutions for the enterprise. At the same time, the analysis results can also help the enterprise evaluate the feasibility and effectiveness of different transformation paths, providing support for decision-making. Through intelligent data processing and model analysis, the platform can provide customized digital transformation solutions for the enterprise. Brief description of the drawings

[0057] Figure 1 It is a schematic diagram of the overall structure of an embodiment of the present invention. Detailed implementation manners

[0058] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the specific implementation manners and with reference to the accompanying drawings. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In addition, in the following descriptions, the descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present invention.

[0059] Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0060] In addition, the technical features involved in different implementation manners of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0061] Embodiment 1

[0062] An enterprise digital transformation service platformFigure 1 The overall structural schematic diagram of an embodiment of the present invention is shown. As Figure 1 shown, it includes:

[0063] A data acquisition module, which is used to acquire the business data of the enterprise to be transformed; the data acquisition module is the starting point of the entire service platform and is responsible for automatically or manually collecting the business data of the enterprise to be transformed from various sources. These data may include but are not limited to financial data (such as revenue, cost, profit), operation data (such as production volume, inventory, sales volume), market data (such as market share, competitor information), customer data (such as customer behavior, satisfaction), and internal process data, etc. In this embodiment, the data acquisition module acquiring the business data of the enterprise to be transformed includes acquiring the enterprise business data from the internal and external environments of the enterprise to be transformed; acquiring the business data of the enterprise to be transformed from the external environment by using web crawler technology; acquiring the business data of the enterprise to be transformed from the internal of the enterprise to be transformed includes:

[0064] Presetting multiple data acquisition tables according to the data type;

[0065] Presetting the logical relationship between the multiple data acquisition tables;

[0066] Docking with the interface of the internal system of the enterprise to be transformed, scraping the latest data from the enterprise internal system, and automatically filling it into the corresponding data acquisition tables.

[0067] A data processing module, which is used to perform standardized processing on the business data of the enterprise to be transformed; the data processing module performs standardized processing on the acquired data to ensure the consistency and comparability of the data. This includes unifying the data format, processing data missing values, data conversion (such as encoding conversion, unit unification), and data aggregation and classification, etc.;

[0068] An enterprise business scenario model construction module, which is used to construct an enterprise business scenario model according to the standardized business data of the enterprise to be transformed; this module uses the processed data, combines the enterprise business logic and industry experience, and constructs a model that reflects the actual business situation of the enterprise. These models may include but are not limited to financial models, operation models, market models, etc., and are used to simulate and predict the performance of the enterprise in different situations.

[0069] A matching and analysis module, which is used to match, analyze the constructed enterprise business scenario model and the models in the transformation database, and output the analysis results. The matching and analysis module matches the constructed enterprise business scenario model with the models in the transformation database, and finds out the similarities and differences between the current business state of the enterprise and successful transformation cases through comparative analysis. Based on these analysis results, personalized transformation suggestions and optimization solutions are provided for the enterprise.

[0070] In this embodiment, an enterprise operation scenario model is constructed based on the operation data of the enterprise to be transformed after the standardization process, including:

[0071] The enterprise operation scenario model includes multiple capabilities and multiple criteria; these capabilities and criteria are abstracted from multiple aspects of enterprise operation, such as financial capabilities, market capabilities, management capabilities, etc. Under each capability, there will be a series of specific criteria to measure the strength of this capability. In this embodiment, the multiple capabilities include: manufacturing capability, management capability, infrastructure capability, sales capability, and development capability; The manufacturing capability refers to the ability of an enterprise to convert raw materials into finished products or provide services. The multiple criteria included in the manufacturing capability may include: output value rate, R & D management, production system integration degree, production line automation level, etc.; Different types of enterprises have different criteria. For example, for an automobile manufacturing enterprise, it may particularly focus on the production line automation level and the production system integration degree, because this directly affects its large-scale production capacity and the consistency of product quality. A pharmaceutical enterprise may pay more attention to R & D management and quality control, because the R & D of new drugs and quality assurance in the production process are crucial to it. While a clothing manufacturing enterprise may value production flexibility and supply chain management more, because the rapid changes in the fashion industry require the production line to be able to adjust quickly to meet new market demands. The management capability includes digital talent management, digital data management, etc., such as the proportion of digital talents, investment in digital skills training, data integration ability or data analysis ability, etc.; The infrastructure capability refers to digital equipment, including network coverage rate, equipment digitalization degree, etc.; The sales capability refers to the degree of digitalization in sales, including digital marketing, e-commerce operation, etc.; The development capability refers to the ability of the enterprise's digital collaborative development, including resource collaboration, supply chain collaboration, business collaboration, etc.;

[0072] Each of the said capabilities includes a corresponding multiple criteria;

[0073] Calculate the weights corresponding to the multiple capabilities and multiple criteria of the enterprise to be transformed according to the operation data of the enterprise to be transformed; Weight calculation is a very crucial step in the evaluation process, which reflects the importance degree of different capabilities and criteria in the overall evaluation. Traditional weight calculation methods include inviting industry experts or enterprise internal executives to score each capability and criterion, and calculating the weights according to the scoring results; Using statistical methods to analyze the operation data, such as extracting key factors and calculating weights through methods such as principal component analysis (PCA), factor analysis, etc.;

[0074] Match, analyze, and output the analysis results for the constructed enterprise operation scenario model and the model in the transformation database, including:

[0075] Match the model with the highest similarity to the enterprise to be transformed from the transformation database according to the enterprise characteristics in the operation data of the enterprise to be transformed; search and match in the transformation database according to the enterprise characteristics (such as industry attributes, enterprise scale, business model, technical foundation, etc.) in the operation data of the enterprise to be transformed. The transformation database contains multiple preset mature models and enterprise case models that have been successfully transformed or are in the process of transformation. Each model details information such as the enterprise status before and after transformation, the transformation path, and the key success factors;

[0076] In one embodiment of the present invention, further,

[0077] Matching the model with the highest similarity to the enterprise to be transformed from the transformation database according to the enterprise characteristics in the operation data of the enterprise to be transformed includes:

[0078] Calculate the similarity value using the following formula:

[0079]

[0080] where Q represents the similarity value; represents the average value of each enterprise characteristic, represents the average value of each characteristic of the mature digital transformation model; X u represents the value of feature u in the enterprise characteristics, Y u represents the value of feature u in the mature digital transformation model, and v represents the total number of features of the mature digital transformation model;

[0081] Select the model with the largest similarity value Q from all models.

[0082] Calculate the matching values corresponding to multiple criteria between the model with the highest matching similarity and the operation scenario model of the enterprise to be transformed; after determining the model with the highest similarity, the next step is to calculate the matching values of this model and the operation scenario model of the enterprise to be transformed on multiple criteria. Since each ability corresponds to multiple criteria, the matching value of each ability can be obtained through the corresponding matching values of multiple criteria,

[0083] Calculate the overall matching value between the model with the highest matching similarity and the operation scenario model of the enterprise to be transformed according to the matching values corresponding to multiple criteria and the weights corresponding to multiple abilities and multiple criteria;

[0084] Output the analysis result based on the matching values corresponding to the multiple criteria and the overall matching value. For example, illustrate the overall matching degree between the model with the highest similarity and the enterprise to be transformed. List in detail the matching values of each criterion and their meanings to help understand in which aspects the two models are similar or different. Based on the analysis result, propose specific transformation suggestions for the enterprise to be transformed. These suggestions can include key areas of transformation, key steps, expected effects, etc. Point out the possible risks and challenges encountered during the transformation process and propose corresponding countermeasures.

[0085] In one embodiment of the present invention, further, the overall matching value is calculated using the following formula:

[0086]

[0087] Wherein, C total represents the overall matching value, W' j represents the weight of the j-th ability after normalization, n j represents the number of criteria under the j-th ability, ω jk represents the weight of the k-th criterion under the j-th ability, n represents the number of abilities, Z jk represents the matching value of the k-th criterion under the j-th ability. First, calculate the sum of the weighted matching values of all criteria under each ability j, and sum over all abilities to finally obtain the overall matching value. Among them, W' j represents the weight of the j-th ability after normalization, which means that the sum of the weights of all abilities is 1. By comprehensively considering the weights of multiple abilities and criteria and their matching values, a comprehensive and quantitative evaluation result is provided for the enterprise to be transformed. The magnitude of the overall matching value M directly reflects the overall similarity degree between the business scenario model of the enterprise to be transformed and the model with the highest similarity in the transformation database, providing strong data support for the enterprise to formulate transformation strategies.

[0088] In one embodiment of the present invention, further, the matching values corresponding to the multiple abilities and multiple criteria between the model with the highest matching similarity and the business scenario model of the enterprise to be transformed are calculated using the following formula:

[0089]

[0090] Wherein, Z jk represents the matching value of the k-th criterion under the j-th ability, Z jk-f represents the data of the k-th criterion under the j-th ability of the enterprise to be transformed, Z jk-m represents the data of the k-th criterion under the j-th ability of the model with the highest matching similarity, and threshold is 10 -7, which is used to avoid the situation where the denominator is zero or too small, and can be adjusted according to the actual situation to control the sensitivity of the matching value.

[0091] Calculating the weights corresponding to several capabilities and multiple criteria of the enterprise to be transformed includes normalizing the data using the following formula:

[0092]

[0093] where x jk represents the original data under the k-th criterion of the j-th capability, and r jk is the normalized data under the k-th criterion of the j-th capability, and n is the number of capabilities.

[0094] Calculate the weights corresponding to each criterion under each capability using the following formula:

[0095]

[0096] where ω jk represents the weight of the k-th criterion under the j-th capability, n j represents the number of criteria under the j-th capability, and r jk is the normalized data under the k-th criterion of the j-th capability, and n is the number of capabilities.

[0097] Calculate the weights corresponding to each capability using the following formula:

[0098]

[0099] where W j represents the weight of the j-th capability, and W' j represents the weight of the j-th capability after normalization processing, n j represents the number of criteria under the j-th capability, and ω jk represents the weight of the k-th criterion under the j-th capability, and n represents the number of capabilities. By comprehensively considering the weights and matching values of multiple capabilities and criteria, a comprehensive and quantitative evaluation result is provided for the enterprise to be transformed. Based on the data-based evaluation result, the enterprise can formulate a transformation strategy more scientifically and reduce the deviation of subjective judgment.

[0100] In an embodiment of the present invention, further,

[0101] According to the matching values corresponding to the multiple criteria and the overall matching value, the output analysis result includes:

[0102] Output the stage of the enterprise to be transformed according to the overall matching value and the preset first-level thresholds. The preset first-level thresholds include the highest threshold and the lowest threshold. Compare the overall matching value with the preset first-level thresholds to determine the stage of the enterprise to be transformed. These stages usually reflect the maturity or progress of the enterprise in the transformation process;

[0103] The stages include the primary stage, the growth stage, and the mature stage;

[0104] When the overall matching value is lower than the lowest threshold of the preset first-level thresholds, the enterprise to be transformed is in the primary stage; it indicates that there are significant gaps between the enterprise to be transformed and the best practices in the transformation database in terms of multiple capabilities and criteria, and it may still be in the initial exploration stage of transformation, and it is necessary to focus on infrastructure construction and capacity improvement;

[0105] When the overall matching value is between the lowest threshold and the medium threshold of the first-level thresholds, the enterprise to be transformed is in the growth stage; it shows that the enterprise to be transformed has made certain progress in some aspects, but there is still a large room for improvement. At this time, the enterprise should continue to strengthen capacity building while paying attention to the key issues and challenges in the transformation process;

[0106] When the overall matching value is higher than the highest threshold of the preset first-level thresholds, the enterprise to be transformed is in the mature stage. It indicates that the enterprise to be transformed has approached or reached the best practice level in the transformation database in terms of multiple capabilities and criteria and is in a relatively mature stage. At this time, the enterprise can further consolidate the results, explore new transformation directions or optimize the existing models.

[0107] Identify the weak points of the enterprise to be transformed according to the matching values corresponding to the multiple criteria; by comparing the matching values under each criterion, it is possible to identify which criteria have lower matching values, that is, there are significant gaps between the enterprise in these aspects and the best practices. According to the analysis results of the criterion matching values, combined with the actual situation and business needs of the enterprise, determine the weak points that need to be focused on.

[0108] Output the analysis results according to the stage of the enterprise to be transformed and the weak points. Briefly describe the transformation stage the enterprise is in, as well as the main characteristics and challenges of this stage. List in detail the weak points of the enterprise and explain the possible impacts of these weak points on the transformation process. Put forward specific improvement suggestions for the weak points and transformation stage of the enterprise. These suggestions should be operable and targeted, and can help the enterprise effectively improve the transformation effect, etc.

[0109] Through the data acquisition module, the present invention can comprehensively and accurately collect various business data of the enterprise to be transformed, ensuring the integrity and real-time nature of the data. The data processing module eliminates differences in data format, unit, quality, etc. through standardized processing, providing a unified and comparable data basis for subsequent analysis. The enterprise business scenario model construction module can construct a model reflecting the actual business situation of the enterprise based on the standardized data, enabling a more intuitive understanding of its own business conditions and existing problems, and providing strong support for subsequent digital transformation. The matching and analysis module matches the constructed enterprise business scenario model with the models in the transformation database, and through comparative analysis, identifies potential opportunities and challenges for the enterprise's digital transformation. This matching and analysis process is not only fast and efficient but also can quickly provide targeted transformation suggestions and solutions for the enterprise. At the same time, the analysis results can also help the enterprise evaluate the feasibility and effects of different transformation paths, providing support for decision-making. Through intelligent data processing and model analysis, this platform can provide customized digital transformation solutions for the enterprise.

[0110] It should be understood that the above specific embodiments of the present invention are only for illustrative or explanatory purposes of the principle of the present invention and do not constitute a limitation to the present invention. Therefore, any modifications, equivalent replacements, improvements, etc. made without departing from the spirit and scope of the present invention shall be included within the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all variations and modifications that fall within the scope and boundaries of the appended claims or equivalent forms of such scope and boundaries.

[0111] The present invention has been described above with reference to the embodiments of the present invention. However, these embodiments are only for illustrative purposes and not for limiting the scope of the present invention. The scope of the present invention is defined by the appended claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art can make various substitutions and modifications, and all these substitutions and modifications should fall within the scope of the present invention.

[0112] Although the embodiments of the present invention have been described in detail, it should be understood that various changes, substitutions, and alterations can be made to the embodiments of the present invention without departing from the spirit and scope of the present invention.

[0113] Obviously, the above embodiments are only examples for clear illustration and not limitations to the embodiments. For those of ordinary skill in the art, other different forms of changes or alterations can be made based on the above description. It is not necessary and impossible to enumerate all the embodiments here. And the obvious changes or alterations derived therefrom are still within the protection scope of the present invention.

Claims

1. An enterprise digital transformation service platform, characterized in that, Including: A data collection module for collecting the business data of the enterprise to be transformed; A data processing module for performing standardization processing on the business data of the enterprise to be transformed; An enterprise business scenario model construction module for constructing an enterprise business scenario model according to the standardized business data of the enterprise to be transformed; A matching and analysis module for matching, analyzing the constructed enterprise business scenario model and the models in the transformation database, and outputting an analysis result.

2. The enterprise digital transformation service platform according to claim 1, wherein The enterprise business scenario model includes multiple capabilities and multiple criteria, and each of the capabilities includes corresponding multiple criteria; Constructing an enterprise business scenario model according to the standardized business data of the enterprise to be transformed includes: Calculating weights corresponding to multiple capabilities and multiple criteria corresponding to the enterprise to be transformed according to the business data of the enterprise to be transformed; Matching, analyzing the constructed enterprise business scenario model and the models in the transformation database, and outputting an analysis result includes: Matching the model with the highest similarity to the enterprise to be transformed from the transformation database according to the enterprise characteristics in the business data of the enterprise to be transformed; Calculating the matching values corresponding to multiple criteria between the model with the highest similarity and the enterprise business scenario model of the enterprise to be transformed; Calculating the overall matching value between the model with the highest similarity and the enterprise business scenario model of the enterprise to be transformed according to the matching values corresponding to multiple criteria and the weights corresponding to multiple capabilities and multiple criteria; Outputting an analysis result according to the matching values corresponding to the multiple criteria and the overall matching value.

3. The enterprise digital transformation service platform according to claim 2, wherein The overall matching value is calculated using the following formula: Among them, C total represents the overall matching value, W j ' represents the weight of the j-th ability after normalization, n j represents the number of criteria under the j-th ability, ω jk represents the weight of the k-th criterion under the j-th ability, n represents the number of abilities, Z jk represents the matching value of the k-th criterion under the j-th ability.

4. The enterprise digital transformation service platform according to claim 2, wherein, The calculation of the matching values corresponding to multiple capabilities and multiple criteria between the model with the highest similarity and the enterprise business scenario model of the enterprise to be transformed is calculated using the following formula: Among them, Z jk represents the k-th criterion matching value under the j-th ability, and Z jk-f represents the data of the k-th criterion under the j-th ability of the enterprise to be transformed. Z jk-m represents the data of the k-th criterion under the j-th ability of the model with the highest matching similarity. The threshold is 10 -7 .

5. The enterprise digital transformation service platform according to claim 2, wherein The calculation of the weights corresponding to several capabilities and multiple criteria corresponding to the enterprise to be transformed includes performing data standardization using the following formula: Among them, x jk represents the original data under the k-th criterion of the j-th ability, r jk is the data after standardization under the k-th criterion of the j-th ability, and n is the number of abilities.

6. The enterprise digital transformation service platform according to claim 5, wherein The weights corresponding to each criterion under each capability are calculated using the following formula: Among them, ω jk represents the weight of the k-th criterion under the j-th ability, and n j represents the number of criteria under the j-th ability, and r jk is the data after standardization under the k-th criterion under the j-th ability, and n is the number of abilities.

7. The enterprise digital transformation service platform according to claim 6, wherein The weights corresponding to each capability are calculated using the following formula: Among them, W j represents the weight of the j-th ability, and W j ' represents the weight of the j-th ability after normalization. n j represents the number of criteria under the j-th ability, and ω jk represents the weight of the k-th criterion under the j-th ability. n represents the number of abilities.

8. The enterprise digital transformation service platform according to claim 2, wherein Matching the model with the highest similarity to the enterprise to be transformed from the transformation database according to the enterprise characteristics in the business data of the enterprise to be transformed includes: Calculating the similarity value using the following formula: Among them, Q represents the similarity value; represents the average value of each feature of the enterprise, represents the average value of each feature of a mature digital transformation model; X u represents the value of feature u in the enterprise features, Y u represents the value of feature u in a mature digital transformation model, and v represents the total number of features of the mature digital transformation model; Screening out the model with the largest similarity value Q from all models.

9. The enterprise digital transformation service platform according to claim 2, wherein Outputting an analysis result according to the matching values corresponding to the multiple criteria and the overall matching value includes: Outputting the stage of the enterprise to be transformed according to the overall matching value and a preset primary threshold; Identifying the weak points of the enterprise to be transformed according to the matching values corresponding to the multiple criteria; Output the analysis result according to the stage of the enterprise to be transformed and the weakness points.

10. The enterprise digital transformation service platform according to claim 9, wherein The stage includes the primary stage, the growth stage, and the mature stage; When the overall matching value is lower than the lowest threshold among the preset first-level thresholds, the enterprise to be transformed is in the primary stage; When the overall matching value is between the lowest threshold and the medium threshold among the first-level thresholds, the enterprise to be transformed is in the growth stage; When the overall matching value is higher than the highest threshold among the preset first-level thresholds, the enterprise to be transformed is in the mature stage.

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