A service platform for enterprise digital transformation

Abstract

This invention relates to the field of digital platform technology, specifically to a service platform for enterprise digital transformation, comprising: a data acquisition module for collecting operational data of enterprises undergoing transformation; a data processing module for standardizing the operational data of enterprises undergoing transformation; an enterprise operational scenario model construction module for constructing an enterprise operational scenario model based on the standardized operational data of the enterprises undergoing transformation; and a matching and analysis module for matching and analyzing the constructed enterprise operational scenario model with models in a transformation database and outputting analysis results. The enterprise operational scenario model construction module of this invention can construct a model reflecting the actual operating situation of an enterprise, allowing for a more intuitive understanding of its own operating status and existing problems. The matching and analysis module, through comparative analysis, identifies potential opportunities and challenges for enterprise digital transformation. This invention can quickly and efficiently provide enterprises with targeted transformation suggestions and solutions.

Description

Technical Field

[0001] This invention relates to the field of digital platform technology, and more specifically to a service platform for enterprise digital transformation. Background Technology

[0002] Enterprise digital transformation refers to the comprehensive and in-depth transformation and upgrading of a company's or individual's business processes, organizational structure, and cultural philosophy using digital technologies such as big data, cloud computing, and artificial intelligence to achieve a more efficient, intelligent, and flexible operating model. Digital transformation helps companies better understand market demands and customer behavior, thereby responding more quickly to market changes, providing solutions that meet customer expectations, and enhancing the competitiveness of products and services. It reduces human error and wasted time through automation tools and digital processes, improving internal operational efficiency and reducing costs. Simultaneously, it improves efficiency in areas such as supply chain management, logistics, and inventory control. Digital transformation encourages companies 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, companies can interact more closely with customers, meet their individual 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 analytics, artificial intelligence, and the Internet of Things to provide enterprises with a comprehensive solution. However, existing platforms still fall short in terms of analytical efficiency and meeting the personalized needs of enterprises, making it difficult to fully adapt to their specific circumstances and requirements. Summary of the Invention

[0004] (I) Purpose of the Invention

[0005] The purpose of this invention is to provide a digital transformation service platform for enterprises that can improve analysis efficiency and personalization.

[0006] (II) Technical Solution

[0007] To address the above problems, this invention provides an enterprise digital transformation service platform, comprising:

[0008] The data acquisition module is used to collect operational data from companies undergoing transformation.

[0009] The data processing module is used to standardize the operating data of the enterprise to be transformed.

[0010] The enterprise operation scenario model construction module is used to construct an enterprise operation scenario model based on the standardized operating data of the enterprise to be transformed.

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

[0012] In another aspect of the present invention, preferably, the enterprise operation scenario model includes multiple capabilities and multiple criteria, and each capability includes corresponding multiple criteria;

[0013] Based on the standardized operating data of the enterprises to be transformed, a business scenario model is constructed, including:

[0014] Calculate the weights corresponding to multiple capabilities and criteria of the enterprise to be transformed based on its operating data.

[0015] The constructed enterprise operation scenario model and the models in the transformation database are matched and analyzed, and the analysis results are output, including:

[0016] Based on the enterprise characteristics in the operational data of the enterprise to be transformed, the model with the highest similarity to the enterprise to be transformed is matched from the transformation database;

[0017] Calculate the matching value between the model with the highest similarity and the business scenario model of the enterprise to be transformed, corresponding to multiple criteria.

[0018] Based on the matching values ​​corresponding to multiple criteria and the weights corresponding to multiple capabilities and multiple criteria, the overall matching value between the model with the highest similarity and the business scenario model of the enterprise to be transformed is calculated.

[0019] Based on the matching values ​​corresponding to the multiple criteria and the overall matching value, the analysis results are output.

[0020] In another aspect of the present invention, preferably,

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

[0022]

[0023] Among them, C total W' represents the overall match value. j The weight of the j-th capability after normalization is represented by n. j ω represents the number of criteria under the j-th capability. jk Z represents the weight of the k-th criterion under the j-th capability, where n represents the number of capabilities. jk This represents the matching value of the k-th criterion under the j-th capability.

[0024] In another aspect of the present invention, preferably, the matching value corresponding to multiple capabilities and multiple criteria between the model with the highest similarity in the calculation and the business scenario model of the enterprise to be transformed is calculated using the following formula:

[0025]

[0026] Among them, Z jk Z represents the matching value of the k-th criterion under the j-th capability. jk-f Z represents the data for the k-th criterion under the j-th capability of the enterprise to be transformed. jk-m This represents the data for the k-th criterion under the j-th ability of the model with the highest similarity, with a threshold of 10. -7 .

[0027] In another aspect of the present invention, preferably,

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

[0029]

[0030] Where, x jk This represents the raw data under the k-th criterion and the j-th capability, r. jk It is the standardized data under the k-th criterion for the j-th capability, where n is the number of capabilities.

[0031] In another aspect 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 Let n represent the weight of the k-th criterion under the j-th capability. j r represents the number of criteria under the j-th capability. jk It is the standardized data under the k-th criterion for the j-th capability, where n is the number of capabilities.

[0035] In another aspect of the present invention, preferably,

[0036] Calculate the weight corresponding to each ability using the following formula:

[0037]

[0038] Among them, W j W' represents the weight of the j-th ability. jThe weight of the j-th capability after normalization is represented by n. j ω represents the number of criteria under the j-th capability. jk This represents the weight of the k-th criterion under the j-th capability, and n represents the number of capabilities.

[0039] In another aspect of the present invention, preferably,

[0040] Based on the enterprise characteristics in the operational data of the enterprise to be transformed, the models that are most similar to the enterprise to be transformed from the transformation database include:

[0041] The similarity score is calculated using the following formula:

[0042]

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

[0044] Select the model with the highest similarity value Q from all models.

[0045] In another aspect of the present invention, preferably,

[0046] The analysis results output based on the matching values ​​corresponding to the multiple criteria and the overall matching value include:

[0047] Based on the overall matching value and the preset first-level threshold, the stage of the enterprise to be transformed is output;

[0048] Based on the matching values ​​corresponding to the multiple criteria, the weaknesses of the enterprises to be transformed are identified;

[0049] The analysis results are output based on the stage of the enterprise to be transformed and its weaknesses.

[0050] In another aspect of the present invention, preferably, the stages include a primary stage, a growth stage, and a maturity stage;

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

[0052] When the overall matching value is between the lowest and middle thresholds in 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 threshold among the preset first-level thresholds, the enterprise to be transformed is in the mature stage.

[0054] (III) Beneficial Effects

[0055] The above-described technical solution of the present invention has the following beneficial technical effects:

[0056] This invention utilizes a data acquisition module to comprehensively and accurately collect various operational data from enterprises undergoing transformation, ensuring data integrity and real-time performance. The data processing module, through standardization, eliminates differences in data format, units, and quality, providing a unified and comparable data foundation for subsequent analysis. The enterprise operation scenario model construction module builds a model reflecting the enterprise's actual operating situation based on the standardized data, allowing for a more intuitive understanding of its operational status and existing problems, providing strong support for subsequent digital transformation. The matching and analysis module matches the constructed enterprise operation scenario model with models in the transformation database, identifying potential opportunities and challenges for digital transformation through comparative analysis. This matching and analysis process is not only fast and efficient but also provides enterprises with targeted transformation suggestions and solutions. Furthermore, the analysis results help enterprises assess the feasibility and effectiveness of different transformation paths, supporting decision-making. Through intelligent data processing and model analysis, this platform can provide enterprises with customized digital transformation solutions. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the overall structure of one embodiment of the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0059] Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

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

[0061] Example 1

[0062] A digital transformation service platform for enterprises. Figure 1 A schematic diagram of the overall structure of an embodiment of the present invention is shown, as follows. Figure 1 As shown, it includes:

[0063] The data acquisition module is used to collect operational data from the enterprise undergoing transformation. As the starting point of the entire service platform, it is responsible for automatically or manually collecting operational data from various sources. This data may include, but is not limited to, financial data (such as revenue, costs, and profits), operational data (such as production volume, inventory, and sales volume), market data (such as market share and competitor information), customer data (such as customer behavior and satisfaction), and internal process data. In this embodiment, the data acquisition module collects operational data from both the internal and external environments of the enterprise undergoing transformation. Data collection from the external environment utilizes web scraping technology; data collection from the internal environment includes:

[0064] Multiple data collection tables can be preset according to data types;

[0065] The logical relationships between the multiple data collection tables are preset;

[0066] It interfaces with the internal systems of companies undergoing transformation, retrieves the latest data from these systems, and automatically populates the corresponding data collection tables.

[0067] The data processing module is used to standardize the operational data of the enterprises to be transformed. This module standardizes the collected data to ensure consistency and comparability. This includes standardizing data formats, handling missing values, data conversion (such as encoding conversion and unit standardization), and data aggregation and classification.

[0068] The enterprise operation scenario model construction module is used to construct an enterprise operation scenario model based on the standardized operating data of the enterprise to be transformed. This module utilizes the processed data, combined with the enterprise's business logic and industry experience, to construct a model that reflects the actual operating situation of the enterprise. These models may include, but are not limited to, financial models, operational models, and market models, used to simulate and predict the enterprise's performance under different scenarios.

[0069] The matching and analysis module is used to match and analyze the constructed enterprise operation scenario model and the models in the transformation database, and output the analysis results. The matching and analysis module matches the constructed enterprise operation scenario model with the models in the transformation database, and through comparative analysis, identifies the similarities and differences between the enterprise's current operating status and successful transformation cases. Based on these analysis results, personalized transformation suggestions and optimization solutions are provided to the enterprise.

[0070] In this embodiment, a business scenario model is constructed based on the standardized operating data of the enterprise to be transformed, including:

[0071] The enterprise operation scenario model includes multiple capabilities and criteria. These capabilities and criteria are abstracted from various aspects of enterprise operation, such as financial capabilities, market capabilities, and management capabilities. Each capability has a series of specific criteria to measure its strength. In this embodiment, the multiple capabilities include: manufacturing capabilities, management capabilities, basic equipment capabilities, sales capabilities, and development capabilities. Manufacturing capability refers to an enterprise's ability to transform raw materials into finished products or provide services. The criteria for manufacturing capability may include: output value rate, R&D management, production system integration level, and production line automation level. Different types of enterprises have different criteria. For example, an automobile manufacturing enterprise may pay particular attention to the production line automation level and the production system integration level, as these directly affect its large-scale production capacity and product quality consistency. A pharmaceutical enterprise may focus more on R&D management and quality control, as quality assurance during the R&D and production processes of new drugs is crucial. An apparel manufacturing enterprise may value production flexibility and supply chain management, as the rapid changes in the fashion industry require production lines to be quickly adjusted to adapt to new market demands. Management capabilities include digital talent management and digital data management, such as the proportion of digital talent, investment in digital skills training, data integration capabilities, and data analysis capabilities; basic equipment capabilities refer to digital equipment, including network coverage and the degree of equipment digitization; sales capabilities refer to the degree of digitization in sales, including digital marketing and e-commerce operations; development capabilities refer to the enterprise's ability to develop digitally collaboratively, including resource collaboration, supply chain collaboration, and business collaboration.

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

[0073] The weights of various capabilities and criteria corresponding to the enterprise to be transformed are calculated based on the enterprise's operating data. Weight calculation is a crucial step in the evaluation process, as it reflects the importance of different capabilities and criteria in the overall evaluation. Traditional weight calculation methods include inviting industry experts or senior executives to score each capability and criterion and calculating the weights based on the scoring results; or using statistical methods to analyze the operating data, such as extracting key factors and calculating their weights through principal component analysis (PCA) and factor analysis.

[0074] The constructed enterprise operation scenario model and the models in the transformation database are matched and analyzed, and the analysis results are output, including:

[0075] Based on the enterprise characteristics in the operational data of the enterprise to be transformed, the model with the highest similarity to the enterprise to be transformed is matched from the transformation database; based on the enterprise characteristics (such as industry attributes, enterprise size, business model, technological foundation, etc.) in the operational data of the enterprise to be transformed, a search and matching is performed in the transformation database. The transformation database contains multiple preset mature models and enterprise case models that have successfully transformed or are undergoing transformation. Each model describes in detail the enterprise status before and after transformation, transformation path, key success factors, and other information.

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

[0077] Based on the characteristics of the enterprises in the operational data of the enterprises to be transformed, the models that match the enterprises with the highest similarity from the transformation database include:

[0078] The similarity score is calculated using the following formula:

[0079]

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

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

[0082] The matching values ​​of the model with the highest similarity are calculated based on multiple criteria between them and the business 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 business scenario model of the enterprise to be transformed on multiple criteria. Since each capability corresponds to multiple criteria, the matching value of each capability can be obtained through the corresponding matching values ​​of multiple criteria.

[0083] Based on the matching values ​​corresponding to multiple criteria and the weights corresponding to multiple capabilities and multiple criteria, the overall matching value between the model with the highest similarity and the business scenario model of the enterprise to be transformed is calculated.

[0084] Based on the matching values ​​corresponding to the multiple criteria and the overall matching value, output the analysis results. For example, explain the overall matching degree between the model with the highest similarity and the company to be transformed. List the matching value of each criterion and its meaning in detail to help understand in which aspects the two models are similar or different. Based on the analysis results, propose specific transformation suggestions for the company to be transformed. These suggestions may include key areas of transformation, key steps, and expected results. Identify the risks and challenges that may be encountered during the transformation process and propose corresponding countermeasures.

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

[0086]

[0087] Among them, C total W' represents the overall match value. j The weight of the j-th capability after normalization is represented by n. j ω represents the number of criteria under the j-th capability. jk Z represents the weight of the k-th criterion under the j-th capability, where n represents the number of capabilities. jk Let W' represent the matching value of the k-th criterion under the j-th capability. First, the weighted sum of the matching values ​​of all criteria under each capability j is calculated, and then summed over all capabilities to obtain the overall matching value, where W' j The value represents the weight of the j-th capability after normalization, meaning the sum of the weights of all capabilities is 1. By comprehensively considering the weights of multiple capabilities and criteria, as well as their matching values, a comprehensive and quantitative evaluation result is provided for enterprises undergoing transformation. The overall matching value M directly reflects the overall similarity between the enterprise's business scenario model and the model with the highest similarity in the transformation database, providing strong data support for enterprises to formulate transformation strategies.

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

[0089]

[0090] Among them, Z jk Z represents the matching value of the k-th criterion under the j-th capability. jk-f Z represents the data for the k-th criterion under the j-th capability of the enterprise to be transformed. jk-m This represents the data for the k-th criterion under the j-th ability of the model with the highest similarity, with a threshold of 10. -7This is used to avoid situations 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 of several capabilities and criteria corresponding to the enterprise to be transformed involves data standardization using the following formula:

[0092]

[0093] Where, x jk This represents the raw data under the k-th criterion and the j-th capability, r. jk It is the standardized data under the k-th criterion for the j-th capability, where n is the number of capabilities.

[0094] The weights corresponding to each criterion under each capability are calculated using the following formula:

[0095]

[0096] Where, ω jk Let n represent the weight of the k-th criterion under the j-th capability. j r represents the number of criteria under the j-th capability. jk It is the standardized data under the k-th criterion for the j-th capability, where n is the number of capabilities.

[0097] Calculate the weight corresponding to each ability using the following formula:

[0098]

[0099] Among them, W j W' represents the weight of the j-th ability. j The weight of the j-th capability after normalization is represented by n. j ω represents the number of criteria under the j-th capability. jk This 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 assessment result is provided for enterprises undergoing transformation. Based on the data-driven assessment results, enterprises can formulate transformation strategies more scientifically and reduce the bias of subjective judgment.

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

[0101] Based on the matching values ​​corresponding to the multiple criteria and the overall matching value, the output analysis results include:

[0102] Based on the overall matching value and a preset first-level threshold, the stage of the enterprise to be transformed is output. The preset first-level threshold includes a maximum threshold and a minimum threshold. The stage of the enterprise to be transformed is determined by comparing the overall matching value with the preset first-level threshold. These stages typically reflect the maturity or progress of the enterprise in the transformation process.

[0103] The stages include the initial stage, the growth stage, and the maturity stage;

[0104] When the overall matching value is lower than the lowest threshold in the preset first-level threshold, the enterprise to be transformed is in the initial stage; this indicates that the enterprise to be transformed has a large gap with the best practices in the transformation database in multiple capabilities and criteria, and may still be in the initial exploration stage of transformation, requiring a focus on infrastructure construction and capability improvement.

[0105] When the overall matching value is between the lowest and middle thresholds in the first-level threshold, the enterprise to be transformed is in the growth stage; this indicates that the enterprise has made some progress in certain aspects, but still has considerable room for improvement. At this time, the enterprise should continue to strengthen its capabilities while paying attention to key issues and challenges in the transformation process.

[0106] 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. This indicates that the enterprise to be transformed has approached or reached the best practice level in the transformation database in multiple capabilities and criteria, and is in a relatively mature stage. At this time, the enterprise can further consolidate its achievements, explore new transformation directions, or optimize its existing model.

[0107] Based on the matching values ​​corresponding to the multiple criteria, the weaknesses of the enterprises to be transformed are identified. By comparing the matching values ​​under each criterion, it is possible to identify which criteria have low matching values, indicating that the enterprise has significant gaps compared to best practices in these areas. Based on the analysis results of the criterion matching values, and combined with the enterprise's actual situation and business needs, the weaknesses that require key attention are determined.

[0108] The analysis results should be output based on the stage and weaknesses of the company undergoing transformation. This includes a brief description of the company's current transformation stage, its main characteristics, and the challenges it faces. A detailed list of the company's weaknesses should be provided, along with an explanation of their potential impact on the transformation process. Specific improvement suggestions should be proposed based on the company's weaknesses and transformation stage. These suggestions should be actionable and targeted, helping the company effectively improve its transformation outcomes.

[0109] This invention utilizes a data acquisition module to comprehensively and accurately collect various operational data from enterprises undergoing transformation, ensuring data integrity and real-time performance. The data processing module, through standardization, eliminates differences in data format, units, and quality, providing a unified and comparable data foundation for subsequent analysis. The enterprise operation scenario model construction module builds a model reflecting the enterprise's actual operating situation based on the standardized data, allowing for a more intuitive understanding of its operational status and existing problems, providing strong support for subsequent digital transformation. The matching and analysis module matches the constructed enterprise operation scenario model with models in the transformation database, identifying potential opportunities and challenges for digital transformation through comparative analysis. This matching and analysis process is not only fast and efficient but also provides enterprises with targeted transformation suggestions and solutions. Furthermore, the analysis results help enterprises assess the feasibility and effectiveness of different transformation paths, supporting decision-making. Through intelligent data processing and model analysis, this platform can provide enterprises with customized digital transformation solutions.

[0110] It should be understood that the specific embodiments described above are merely illustrative or explanatory of the principles of the invention and do not constitute a limitation thereof. Therefore, any modifications, equivalent substitutions, improvements, etc., made without departing from the spirit and scope of the invention should be included within the protection scope of the invention. Furthermore, the appended claims are intended to cover all variations and modifications falling 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 embodiments thereof. However, these embodiments are merely illustrative and not intended to limit the scope of the invention. The scope of the invention is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of the invention, and all such substitutions and modifications should fall within the scope of the invention.

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

[0113] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A digital transformation service platform for enterprises, characterized in that, include: The data acquisition module is used to collect operational data from companies undergoing transformation. The data processing module is used to standardize the operating data of the enterprise to be transformed. The enterprise operation scenario model construction module is used to construct an enterprise operation scenario model based on the standardized operating data of the enterprise to be transformed. The matching and analysis module is used to match and analyze the constructed enterprise operation scenario model and the model in the transformation database, and output the analysis results. The enterprise operation scenario model includes multiple capabilities and multiple criteria, and each capability includes corresponding multiple criteria. Based on the standardized operating data of the enterprises to be transformed, a business scenario model is constructed, including: The weights of multiple capabilities and criteria corresponding to the enterprise to be transformed are calculated based on the enterprise's operating data. These capabilities include: manufacturing capability, management capability, basic equipment capability, sales capability, and development capability. The constructed enterprise operation scenario model and the models in the transformation database are matched and analyzed, and the analysis results are output, including: Based on the enterprise characteristics in the operational data of the enterprise to be transformed, the model with the highest similarity to the enterprise to be transformed is matched from the transformation database; Calculate the matching value between the model with the highest similarity and the business scenario model of the enterprise to be transformed, based on multiple criteria. Based on the matching values ​​corresponding to multiple criteria and the weights corresponding to multiple capabilities and multiple criteria, the overall matching value between the model with the highest similarity and the business scenario model of the enterprise to be transformed is calculated. Based on the matching values ​​corresponding to the multiple criteria and the overall matching value, the analysis results are output; The weights corresponding to each criterion under each capability are calculated using the following formula: ； in, Let n represent the weight of the k-th criterion under the j-th capability. j r represents the number of criteria under the j-th capability. jk It is the standardized data under the k-th criterion for the j-th capability, where n is the number of capabilities; Calculate the weight corresponding to each ability using the following formula: ； ； Among them, W j This represents the weight of the j-th ability. The weight of the j-th capability after normalization is represented by n. j This represents the number of criteria under the j-th capability. This represents the weight of the k-th criterion under the j-th capability, and n represents the number of capabilities.

2. The enterprise digital transformation service platform according to claim 1, characterized in that, The overall matching value is calculated using the following formula: ； in, Indicates the overall match value. The weight of the j-th capability after normalization is represented by n. j This represents the number of criteria under the j-th capability. Z represents the weight of the k-th criterion under the j-th capability, where n represents the number of capabilities. jk This represents the matching value of the k-th criterion under the j-th capability.

3. The enterprise digital transformation service platform according to claim 1, characterized in that, The matching value between the model with the highest similarity and the business scenario model of the enterprise to be transformed, corresponding to multiple capabilities and multiple criteria, is calculated using the following formula: ； Among them, Z jk Z represents the matching value of the k-th criterion under the j-th capability. jk-f Z represents the data for the k-th criterion under the j-th capability of the enterprise to be transformed. jk-m This represents the data for the k-th criterion under the j-th ability of the model with the highest similarity, with a threshold of 10. -7 .

4. The enterprise digital transformation service platform according to claim 1, characterized in that, The calculation of the weights corresponding to several capabilities and multiple criteria for the enterprise to be transformed includes data standardization using the following formula: ； Where, x jk This represents the raw data under the k-th criterion and the j-th capability, r. jk It is the standardized data under the k-th criterion for the j-th capability, where n is the number of capabilities.

5. The enterprise digital transformation service platform according to claim 1, characterized in that, Based on the enterprise characteristics in the operational data of the enterprise to be transformed, the models that are most similar to the enterprise to be transformed from the transformation database include: The similarity score is calculated using the following formula: ； Where Q represents the similarity value; This represents the average value of various characteristics of the enterprise. X represents the average value of each characteristic of a mature digital transformation model; u Y represents the value of feature u in the enterprise characteristics. u represents the value of feature u in a mature digital transformation model, and v represents the total number of features in a mature digital transformation model; Select the model with the highest similarity value Q from all models.

6. The enterprise digital transformation service platform according to claim 1, characterized in that, The analysis results output based on the matching values ​​corresponding to the multiple criteria and the overall matching value include: Based on the overall matching value and the preset first-level threshold, the stage of the enterprise to be transformed is output; Based on the matching values ​​corresponding to the multiple criteria, the weaknesses of the enterprises to be transformed are identified; The analysis results are output based on the stage of the enterprise to be transformed and its weaknesses.

7. The enterprise digital transformation service platform according to claim 6, characterized in that, The stages include the initial stage, the growth stage, and the maturity stage; When the overall matching value is lower than the lowest threshold in the preset first-level threshold, the enterprise to be transformed is in the initial stage. When the overall matching value is between the lowest and middle thresholds in the first-level threshold, 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.

Images