Enterprise digital transformation full life cycle management and control method and system

Abstract

The invention relates to the technical field of digital transformation management, in particular to an enterprise digital transformation full life cycle management and control method and system, which are applied to a target enterprise, and the method comprises the following steps: carrying out digital transformation demand analysis and planning on the target enterprise, and customizing a digital transformation scheme for the target enterprise; carrying out resource aggregation and collaborative optimization; constructing a data-driven decision support system for the target enterprise; constructing a digital security and compliance guarantee mechanism for the target enterprise; and on the basis of the digital transformation scheme, enterprise digital transformation full-life-cycle management and control are carried out on the target enterprise through the decision support system. According to the method, a digital transformation scheme is customized for an enterprise, full-life-cycle management and control are carried out on the enterprise, the transformation progress and the evaluation effect are monitored in real time, the strategy is flexibly adjusted, uncertainty and risks in the transformation process are effectively handled, and smooth implementation of a transformation target is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of digital transformation management, and specifically to a method and system for managing and controlling the entire life cycle of enterprise digital transformation. Background Art

[0003] In the journey of digital transformation, Qihang Enterprises face many unique challenges and urgent needs. On the one hand, their transformation is not only about technological innovation, but also involves innovation in organizational structure, reconstruction of business processes and improvement of employee skills. On the other hand, as a small-scale, high-risk startup, it is particularly difficult for Qihang Enterprises to promote comprehensive digital transformation with limited resources. Therefore, accurate control and effective guidance of the transformation process are crucial. More urgently, in a market environment with rapid iteration and fierce competition, Qihang Enterprises urgently need a set of systematic, full-life cycle digital transformation control strategies to ensure the smooth progress of the transformation process and the steady development of the enterprise.

[0004] Unfortunately, most of the mainstream digital transformation solutions on the market today focus on large, mature companies, ignoring the unique needs of start-ups, especially those in high-risk, high-return fields. These standardized, macro solutions are difficult to accurately match the actual needs of start-ups during the transformation process, limiting the effectiveness and potential of their digital transformation. In view of the rapid market changes, resource constraints, and technological innovation needs faced by start-ups, it is particularly urgent to develop a set of tailor-made digital transformation management methods that can effectively respond to their transformation challenges. Existing solutions fail to fully consider the particularities of such companies and lack targeted implementation plans. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for the full life cycle management of enterprise digital transformation in order to solve at least one of the above-mentioned technical problems. Combined with the characteristics of Qihang Enterprise, it starts from innovation-driven, resource aggregation, risk management, market response and other aspects to provide a comprehensive solution covering the entire process of enterprise digital transformation.

[0006] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0007] A method for managing and controlling the entire life cycle of enterprise digital transformation, applied to a target enterprise, includes the following steps:

[0008] Conduct digital transformation demand analysis and planning for the target enterprise, and customize a digital transformation plan for the target enterprise;

[0009] Conduct resource aggregation and collaborative optimization;

[0010] Building a data-driven decision support system for the target enterprise;

[0011] Establish digital security and compliance assurance mechanisms for the target enterprises;

[0012] Based on the digital transformation plan, the target enterprise is managed and controlled throughout its digital transformation life cycle through the decision support system.

[0013] Furthermore, the digital transformation needs analysis and planning are conducted for the target enterprise, including:

[0014] Collect basic enterprise data, analyze the basic enterprise data using artificial intelligence and big data analysis tools, and obtain the current status of the enterprise;

[0015] Obtain enterprise transformation demand information, and customize the digital transformation plan for the target enterprise based on the enterprise transformation demand information and the current status of the enterprise.

[0016] Further, the enterprise transformation demand information includes enterprise vision information and market demand information; and / or,

[0017] Obtaining the current status of the enterprise includes:

[0018] Collecting basic data of the target enterprise based on the existing information system of the target enterprise;

[0019] Based on the big data platform, the basic data of the enterprise is processed and analyzed to obtain the problems and bottlenecks of the target enterprise.

[0020] Furthermore, resource aggregation and collaborative optimization are carried out, including:

[0021] Build a sharing platform and assign permissions to each enterprise user on the sharing platform;

[0022] Integrate internal and external resources of the enterprise into the shared platform and process the data of the shared platform;

[0023] The data of the sharing platform is opened to each enterprise user according to the authority of the enterprise user on the sharing platform.

[0024] Furthermore, a sharing platform is constructed and permissions of each enterprise user on the sharing platform are allocated, including:

[0025] Building the shared platform based on a microservice architecture;

[0026] Using data encryption technology to protect the data stored and transmitted on the sharing platform;

[0027] Role-based permission management and data access control technology allocates permissions to each enterprise user on the sharing platform.

[0028] Furthermore, a data-driven decision support system is constructed for the target enterprise, including:

[0029] Select a management system suitable for the digital transformation needs of the target enterprise based on the type of enterprise, and build the decision support system based on big data and artificial intelligence technology;

[0030] Collect and analyze key data in the target enterprise's operations in real time, and generate various management reports based on the key data;

[0031] The various management reports are pushed to the managers in real time to assist the managers in making management decisions.

[0032] Furthermore, the target enterprise is managed and controlled throughout its digital transformation life cycle, including:

[0033] Divide the digital transformation program into multiple management stages;

[0034] Build a full-process digital management and control platform for the target enterprise, and monitor the key indicators of each management stage in real time through the full-process digital management and control platform;

[0035] Based on data visualization technology, the key indicators are processed to obtain a visualization dashboard in real time, and the visualization dashboard is displayed to managers through the full-process digital management and control platform;

[0036] Obtain the stage goals corresponding to the current management stage, and manage the digital transformation plan based on the visualization dashboard and the stage goals.

[0037] Furthermore, the management stage includes a demand analysis stage, a planning stage, a resource integration stage, an implementation stage, an evaluation stage, and an optimization stage;

[0038] If the current management stage is the assessment stage, the technical means used include:

[0039] Construct an evaluation model based on multi-dimensional weighted scoring;

[0040] Use multivariate statistical methods such as regression analysis and factor analysis to evaluate the contribution of each key indicator to the final effect during the transformation process; optimize the evaluation model based on the contribution of each key indicator to the final effect;

[0041] Generate a comprehensive evaluation report based on the optimized evaluation model and real-time data during the enterprise's digital transformation process.

[0042] Furthermore, the target enterprise is managed and controlled throughout its digital transformation life cycle, including: risk monitoring of the target enterprise according to the digital transformation plan; specifically,

[0043] Based on the risk characteristics of the target enterprise, a risk prediction model and emergency response mechanism are constructed;

[0044] Acquire real-time data during the enterprise's digital transformation process, and obtain risk prediction results based on the real-time data and the risk prediction model;

[0045] Based on the risk prediction results and the emergency response mechanism, a response plan is provided to the manager to assist the manager in making management decisions.

[0046] A full life cycle management and control system for enterprise digital transformation, applied to target enterprises, including:

[0047] A digital transformation planning module is used to analyze and plan the digital transformation needs of the target enterprise and customize a digital transformation plan for the target enterprise;

[0048] Resource integration and collaborative management module, used for resource aggregation and collaborative optimization;

[0049] A decision support system building module, used to build a data-driven decision support system for the target enterprise;

[0050] A security assurance mechanism building module, used to build a digital security and compliance assurance mechanism for the target enterprise;

[0051] A management and control module is used to perform full life cycle management and control of the target enterprise's digital transformation through the decision support system based on the digital transformation plan.

[0052] The beneficial effects of the present invention are:

[0053] Customized demand analysis and transformation planning: In view of the particularity of Qihang enterprises, the present invention provides accurate demand analysis and customized transformation planning to ensure that enterprises can clearly define innovation goals and technical paths and reduce the risk of transformation failure in an environment of limited resources and market uncertainty.

[0054] Flexible resource integration and external collaboration: Through cloud platform and big data technology, the present invention realizes dynamic integration and collaboration of internal and external resources, enhances the technological innovation capability of enterprises, solves resource bottleneck problems, and provides all-round support for digital transformation.

[0055] Data-driven precise decision support: Using artificial intelligence and machine learning technologies, the present invention provides precise decision support based on multi-dimensional data, helping enterprises make scientific decisions in complex markets and high-risk technological innovations, and improving the success rate of transformation.

[0056] Full life cycle management and risk monitoring: This invention proposes a full life cycle management and control solution, covering the entire process from planning to evaluation, and designs an emergency response mechanism based on risk warning to ensure that the enterprise always maintains flexibility and stability during the transformation process and significantly reduces transformation risks.

[0057] The present invention provides a comprehensive, systematic and flexible solution for the digital transformation of Qihang Enterprise, significantly improving the transformation efficiency and success rate and reducing the transformation risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A flow chart of a method for managing and controlling the entire life cycle of enterprise digital transformation according to an implementation of the present invention;

[0059] Figure 2 This is a structural diagram of an enterprise digital transformation full life cycle management and control system according to an implementation method of the present invention. DETAILED DESCRIPTION

[0060] The content of the present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only to enable those skilled in the art to better understand and thus implement the content of the present invention, rather than implying any limitation on the scope of the present invention.

[0061] As used herein, the term “including” and variations thereof are to be interpreted as open-ended terms meaning “including, but not limited to.” The term “based on” is to be interpreted as “based, at least in part, on.” The terms “one embodiment” and “an embodiment” are to be interpreted as “at least one embodiment.”

[0062] Embodiment 1

[0063] Figure 1 This is a flow chart of a method for managing and controlling the entire life cycle of enterprise digital transformation in accordance with an embodiment of the present invention. Figure 1 As shown, according to an embodiment of the present invention, a method for managing and controlling the entire life cycle of enterprise digital transformation is applied to a target enterprise, and includes the following steps:

[0064] Step S10, analyzing and planning the digital transformation needs of the target enterprise, and customizing a digital transformation plan for the target enterprise;

[0065] Step S20, performing resource aggregation and collaborative optimization;

[0066] Step S30, building a data-driven decision support system for the target enterprise;

[0067] Step S40, building a digital security and compliance assurance mechanism for the target enterprise;

[0068] Step S50: Based on the digital transformation plan, the target enterprise is managed and controlled throughout its digital transformation life cycle through a decision support system.

[0069] In this embodiment, a method for the full life cycle management and control of enterprise digital transformation is proposed. The method is implemented for the target enterprise, aiming to comprehensively guide and optimize its digital transformation process, from demand analysis and planning to full life cycle management and control, forming a complete transformation process. In step S10, data collection and analysis are carried out on the target enterprise, and the basic data of the target enterprise is deeply mined through big data technology to identify the problems and bottlenecks faced by the enterprise in the process of digital transformation. Artificial intelligence is used to assist planning, combined with industry reports, technology trends and successful cases, and artificial intelligence technology is used to extract and integrate information to tailor digital transformation plans for target enterprises. In step S20, internal and external resources of the enterprise are integrated, including technology, talents, funds, etc., and resource utilization efficiency is improved through collaborative management. In step S30, a decision support system is built for the target enterprise based on big data and artificial intelligence technology, and the enterprise operation data is analyzed in real time to provide strategic decision support for the management, helping the enterprise to respond quickly to market changes. In step S40, a comprehensive digital security and compliance guarantee mechanism is established for the digital transformation needs of the target enterprise to ensure data security and compliance during the transformation process. In step S50, the target enterprise is managed throughout its digital transformation life cycle, from transformation initiation to technology development, resource integration, market promotion, and transformation evaluation and continuous optimization, covering all stages of digital transformation. Real-time monitoring, progress management, and effect evaluation are used to ensure the achievement of transformation goals, and strategies are adjusted according to actual conditions to effectively deal with uncertainties and risks.

[0070] The present invention tailors digital transformation solutions for enterprises through in-depth demand analysis and planning, and efficient resource collaboration; builds a data-driven decision support system to ensure that management can make accurate decisions based on real-time data, and establishes a comprehensive digital security and compliance assurance mechanism; through full life cycle management and control, real-time monitoring of transformation progress, evaluation of effects, and flexible adjustment of strategies, it effectively responds to uncertainties and risks in the transformation process, and ensures the smooth realization of transformation goals.

[0071] According to one embodiment of the present invention, step S10 includes:

[0072] Step S102, collecting basic enterprise data, analyzing the basic enterprise data using artificial intelligence and big data analysis tools, and obtaining the current status of the enterprise;

[0073] Preferably, obtaining the current status of the enterprise includes:

[0074] Collect basic enterprise data based on the target enterprise's existing information system;

[0075] Based on the big data platform, the basic data of the enterprise is processed and analyzed to obtain the problems and bottlenecks of the target enterprise.

[0076] Step S104, obtaining enterprise transformation demand information, and customizing a digital transformation plan for the target enterprise based on the enterprise transformation demand information and the enterprise's current status.

[0077] Preferably, the enterprise transformation demand information includes enterprise vision information and market demand information.

[0078] Enterprise vision information refers to the internal needs of the target enterprise. Ways to obtain enterprise vision information include but are not limited to: collecting specific needs of the enterprise for digital transformation through questionnaires, employee interviews, customer feedback, etc.;

[0079] Market demand information is the objective transformation demand information of the target enterprise, including but not limited to: industry reports, industry technology trends and industry cases.

[0080] In this embodiment, the content of step S10 is explained in detail, specifically including: first, by collecting basic enterprise data and conducting in-depth analysis of these data with the help of artificial intelligence and big data analysis tools, the current operating status, existing problems and bottlenecks of the target enterprise can be accurately obtained; then, the enterprise vision information is collected through questionnaires, employee interviews, customer feedback, etc., and at the same time, market demand information such as industry reports, technology trends and success stories is combined to fully grasp the subjective and objective transformation needs of the enterprise; finally, based on the current status and transformation needs information of the enterprise, a digital transformation plan that is in line with the enterprise's vision and meets market demand is customized. The plan covers key contents such as technology innovation direction, organizational structure adjustment, and market positioning, aiming to ensure that the digital transformation is closely connected with the strategic goals of the enterprise, and lay a solid foundation for the enterprise's digital transformation.

[0081] This invention combines artificial intelligence and big data analysis to accurately diagnose the current status of the enterprise and discover bottleneck problems; and based on the comprehensively collected transformation needs, it customizes a digital transformation plan that is highly consistent with the enterprise's strategic goals, providing strong support for the enterprise's transformation.

[0082] According to one embodiment of the present invention, step S20 includes:

[0083] Step S202, building a sharing platform and allocating permissions on the sharing platform to each enterprise user;

[0084] Step S204, integrating internal and external resources of the enterprise into the sharing platform, and processing the data of the sharing platform;

[0085] Step S206, opening the data on the sharing platform to each enterprise user according to their authority on the sharing platform.

[0086] In this embodiment, the content of step S20 is described in detail, specifically including: building a sharing platform and allocating enterprise user permissions, integrating internal and external resources of the enterprise into the sharing platform and performing data processing, and opening shared data to enterprise users according to permissions. Through this mechanism, internal and external resources such as funds, technology, talents and equipment of the enterprise can be efficiently integrated to form a flexible and collaborative sharing platform. This sharing platform not only supports information sharing, collaborative work and cross-departmental cooperation among various departments of the enterprise, improves work efficiency and reduces communication costs, but also adopts advanced technologies such as data desensitization, role-based permission management (RBAC) and attribute-based access control (ABAC) to ensure the security and compliance of user privacy data, achieve a balance between data sharing and privacy protection, and provide solid technical support for the optimization of the overall operation of the enterprise.

[0087] According to one embodiment of the present invention, step S202 includes:

[0088] Build a shared platform based on microservice architecture;

[0089] Use data encryption technology to protect data stored and transmitted on the shared platform;

[0090] Role-based permission management and data access control technology allocates permissions to each enterprise user on the sharing platform.

[0091] In this implementation, the content of step S202 is further limited. Specifically, a sharing platform is built through a microservice architecture, and data encryption technology is used to fully protect the data stored and transmitted on the sharing platform. At the same time, role-based permission management and fine data access control technology are used to allocate reasonable access rights to each enterprise user on the sharing platform. The sharing platform supports a multi-tenant mode, ensuring that each user can work safely and efficiently in an independent virtual space, achieving effective isolation and strict security management of data, and providing a solid technical guarantee for multi-party data sharing and access management.

[0092] The present invention builds a sharing platform through a microservice architecture to achieve comprehensive data encryption and fine permission management, ensuring data security and efficient sharing in a multi-tenant mode.

[0093] According to one embodiment of the present invention, step S30 includes:

[0094] Step S302: Select a management system suitable for the digital transformation needs of the target enterprise according to the type of the target enterprise, and build a decision support system based on big data and artificial intelligence technology;

[0095] Step S304, collecting and analyzing key data in the target enterprise's operations in real time, and generating various management reports based on the key data;

[0096] Step S306: Push various management reports to managers in real time to assist them in making management decisions.

[0097] In this embodiment, the content of step S30 is further introduced in detail. In response to the needs of enterprise digital transformation, a suitable management system is first selected according to the type of target enterprise, and an advanced data-driven decision support system is built based on big data and artificial intelligence technology. The decision support system can collect and analyze the key data of the target enterprise in the operation process in real time, and then generate various detailed management reports. These reports not only cover traditional financial indicators, but also incorporate diversified information such as the evaluation of technological innovation and feasibility analysis of market expansion. By pushing these reports to managers in real time, the decision support system can assist management in making more accurate and scientific management decisions.

[0098] The present invention builds a data-driven decision support system, collects and analyzes key data in real time, generates diversified management reports, assists management in making accurate and scientific decisions, and promotes the successful digital transformation of enterprises.

[0099] According to one embodiment of the present invention, step S50 includes:

[0100] Step S502, dividing the digital transformation plan into multiple management stages;

[0101] Preferably, the management stage includes the demand analysis stage, planning stage, resource integration stage, implementation stage, evaluation stage, and optimization stage;

[0102] Step S504, building a full-process digital management and control platform for the target enterprise, and monitoring the key indicators of each management stage in real time through the full-process digital management and control platform;

[0103] Step S506: Based on data visualization technology, key indicators are processed to obtain a visualization dashboard in real time, and the visualization dashboard is displayed to managers through the full-process digital management and control platform;

[0104] Step S508, obtain the stage goals corresponding to the current management stage, and manage the digital transformation plan based on the visualization dashboard and the stage goals.

[0105] For example, if the current management stage is the evaluation stage, the technical means used include:

[0106] Step 1: Construct an evaluation model based on multi-dimensional weighted scoring;

[0107] Step 2: Use multivariate statistical methods such as regression analysis and factor analysis to evaluate the contribution of each key indicator to the final effect during the transformation process; optimize the evaluation model based on the contribution of each key indicator to the final effect;

[0108] Step three: Generate a comprehensive evaluation report based on the optimized evaluation model and real-time data during the enterprise's digital transformation process.

[0109] In this implementation, first of all, according to the digital transformation needs of enterprises, the digital transformation plan is subdivided into multiple management stages such as demand analysis, planning, resource integration, implementation, evaluation and optimization. Subsequently, a full-process digital management and control platform is built to monitor the key indicators of each stage in real time, and use data visualization technology to generate a visual dashboard for intuitive display to managers. For example, in the evaluation stage, by constructing an evaluation model based on multi-dimensional weighted scoring, combined with multivariate statistical methods such as regression analysis and factor analysis, the contribution of key indicators to the transformation effect is dynamically evaluated, and the evaluation model is optimized accordingly. Finally, based on the optimized model and real-time data, a comprehensive evaluation report is generated to provide decision makers with an accurate and scientific basis to ensure that every link in the entire life cycle of digital transformation can be efficiently executed as planned, continuously optimized, and promote the success of transformation.

[0110] The present invention subdivides the digital transformation plan into multiple management stages, builds a full-process digital management and control platform, monitors key indicators in real time and uses data visualization technology to assist decision-making. In particular, in the evaluation stage, a multi-dimensional weighted scoring model and multivariate statistical methods are used to optimize the evaluation, provide accurate basis for decision makers, ensure efficient execution and continuous optimization of digital transformation, and promote successful transformation.

[0111] According to an embodiment of the present invention, step S50 includes: performing risk monitoring on the target enterprise according to the digital transformation plan; specifically,

[0112] Based on the risk characteristics of the target enterprise, build a risk prediction model and emergency response mechanism;

[0113] Obtain real-time data during the enterprise's digital transformation process, and obtain risk prediction results based on real-time data and risk prediction models;

[0114] Based on risk prediction results and emergency response mechanisms, response plans are provided to managers to assist them in making management decisions.

[0115] In this embodiment, step S50 includes risk monitoring during the digital transformation of the target enterprise, building a risk prediction model and emergency response mechanism by combining the risk characteristics of the enterprise, collecting and analyzing data during the transformation process in real time to obtain risk prediction results, and providing managers with response plans based on these results and emergency response mechanisms to assist them in making accurate decisions.

[0116] The risk prediction model is constructed by using big data analysis and machine learning models. The risks predicted by the risk prediction model include but are not limited to: market risk, technical risk, financial risk, etc. By integrating the enterprise's operating data, market data, R&D data and other multi-source information, various risks are quantitatively evaluated and risk levels are automatically generated. For example, different risk thresholds are set, and the current risk stage is judged based on the risk threshold. Different emergency response mechanisms are adopted at different risk stages. According to the corresponding emergency response mechanisms, response plans are provided to managers to assist managers in making management decisions. In view of the risk characteristics of Qihang enterprises (such as enterprises involved in core technology fields such as artificial intelligence, quantum information, and biomedicine), advanced data analysis technology is used for market forecasting and technology evaluation, real-time tracking of technology research and development progress, and risk forecasting and return analysis combined with multi-dimensional data. Not only traditional financial indicators are considered, but also technology innovation evaluation and market expansion feasibility analysis are integrated, so as to provide enterprises with all-round decision-making support, significantly improve the probability of successful transformation, and reduce the risk of failure of technological innovation.

[0117] The present invention designs a highly customized digital transformation plan by accurately analyzing the business status, technical capabilities, industry characteristics and market demand of the starting enterprise (target enterprise). It can provide the enterprise with a phased and detailed transformation roadmap, help the enterprise clarify its innovation goals and technical paths, avoid strategic deviations caused by market uncertainties, and ensure that the enterprise gains a competitive advantage in an uncertain market environment.

[0118] The present invention flexibly integrates internal and external resources and quickly obtains support in technology, capital, talent, etc. with limited resources. This resource integration mechanism enhances the company's technological innovation capabilities, reduces resource bottlenecks in the transformation process, provides all-round support for the company's digital transformation, and improves the efficiency and sustainability of the transformation.

[0119] The present invention adopts advanced data analysis technology based on artificial intelligence and machine learning to conduct accurate market forecasts and technical evaluations on the core technology fields of Qihang Enterprises; it tracks the progress of technological research and development in real time, combines multi-dimensional data for risk forecasting and return analysis, and provides all-round decision-making support for management, which significantly improves the probability of successful transformation and reduces the risks brought about by technological innovation failures.

[0120] The present invention provides a full life cycle management and control solution for the digital transformation of enterprises, covering every link in the entire transformation process from the planning and implementation of digital transformation to the later evaluation and optimization; by real-time monitoring of the transformation progress, resource input, technological innovation results, etc. of enterprises at different stages, the transformation strategy can be dynamically adjusted. In addition, in combination with the risk characteristics of Qihang Enterprise, the present invention specially designs an emergency response mechanism based on risk warning to ensure that enterprises always maintain flexibility in a highly uncertain market, significantly improve the success rate of transformation, and reduce the negative impact caused by market fluctuations or technological innovation failures.

[0121] Embodiment 2

[0122] According to an embodiment of the present invention, a method for managing and controlling the entire life cycle of enterprise digital transformation includes the following steps:

[0123] Step S100: digital transformation needs analysis and planning; including:

[0124] Step S110, collect basic enterprise data, analyze the basic enterprise data with artificial intelligence and big data analysis tools, and obtain the current status of the enterprise; specifically,

[0125] Step S112, collecting basic enterprise data based on the enterprise's existing information system;

[0126] Among them, the company's existing information systems include but are not limited to: ERP, CRM, SCM, production monitoring system; the company's basic data include but are not limited to: financial data, production data, market data, customer feedback, employee capabilities, organizational structure, management model, business process, technology application;

[0127] Step S114, processing and analyzing the basic data of the enterprise based on the big data platform to obtain the problems and bottlenecks existing in the enterprise.

[0128] Among them, big data platforms include but are not limited to: Hadoop, Spark;

[0129] Process and analyze basic enterprise data, including: cleaning, processing and mining data.

[0130] Through cluster analysis, association rule mining, trend analysis and other methods of historical data, we can discover the problems and bottlenecks in the digital transformation of enterprises.

[0131] Step S120, obtaining enterprise transformation demand information, and customizing a digital transformation plan for the enterprise based on the enterprise transformation demand information and enterprise basic data; specifically,

[0132] Step S122, obtaining enterprise transformation demand information, the enterprise transformation demand information including: enterprise vision information and market demand information;

[0133] Among them, obtaining enterprise vision information includes but is not limited to: collecting specific needs of the enterprise's digital transformation through questionnaires, employee interviews, customer feedback, etc.;

[0134] Market demand information includes but is not limited to: industry reports, industry technology trends and industry cases;

[0135] Step S124, based on the enterprise transformation demand information and enterprise basic data, using machine learning and natural language processing (NLP) technology to customize a digital transformation plan for the enterprise;

[0136] Among them, the digital transformation plan includes digital transformation planning documents including strategic goals, implementation paths, key technology selection, budget estimates, etc.

[0137] Step S200, resource aggregation and collaborative optimization; including:

[0138] Step S210, constructing a sharing platform and assigning permissions to each enterprise user on the sharing platform; specifically,

[0139] Step S212, building a sharing platform based on the microservice architecture;

[0140] Step S214, using data encryption technology to protect the data stored and transmitted on the sharing platform;

[0141] Among them, data encryption technologies include: AES encryption, TLS transmission encryption;

[0142] Step S216, role-based authority management (RBAC) and data access control technology (such as attribute-based access control, ABAC) are used to allocate permissions to each enterprise user on the sharing platform;

[0143] Step S220, integrating the internal and external resources of the enterprise into the sharing platform, and processing the data of the sharing platform; specifically,

[0144] Step S222, integrating internal and external resources of the enterprise into the sharing platform; internal and external resources of the enterprise include but are not limited to: human resources, technical resources, and financial resources;

[0145] The data connection between the sharing platform and the third-party system adopts API interface;

[0146] Step S224, optimizing the data of the sharing platform based on the demand forecasting and resource allocation model of machine learning;

[0147] Step S226, ensuring data compliance and transparency of the sharing platform through blockchain technology;

[0148] Step S230, opening the data of the sharing platform to each enterprise user according to the authority of the enterprise user on the sharing platform.

[0149] By building a shared platform, we can achieve efficient aggregation and collaborative optimization of internal and external enterprise resources, and ensure a balance between data sharing and privacy protection among different business departments and users.

[0150] Step S300, building a data-driven decision support system for the target enterprise; including:

[0151] Step S310, selecting a management system suitable for the enterprise's digital transformation needs according to the enterprise type, and building a data-driven decision support system based on big data and artificial intelligence technology;

[0152] Step S320, collecting and analyzing key data in enterprise operations in real time, and generating various management reports based on the key data;

[0153] Among them, key data include but are not limited to: market dynamics, customer feedback, and technology research and development progress;

[0154] Step S330, push various management reports to managers in real time to assist managers in making management decisions.

[0155] Step S400, building a digital security and compliance assurance mechanism;

[0156] Under the premise of complying with relevant national laws and regulations, a multi-level security mechanism is established to ensure effective protection of sensitive data and core technologies during the transformation process through technical means such as data encryption, identity authentication, and access control. It ensures that Qihang enterprises can meet regulatory requirements during the digital transformation process and avoid legal risks caused by technological innovation. The construction of this security mechanism needs to be formulated in combination with the specific situation of the enterprise, and the most suitable mechanism for the enterprise to be digitally transformed should be selected from the existing security mechanisms, and adaptive modifications should be made according to the actual conditions of the enterprise.

[0157] Step S500, performing full life cycle management and control of enterprise digital transformation; including:

[0158] Step S510, dividing the digital transformation plan into multiple management stages;

[0159] The management stages include but are not limited to: demand analysis stage, planning stage, resource integration stage, implementation stage, evaluation stage, and optimization stage; the specific management stages are divided according to the goals and tasks of the enterprise's digital transformation, and each management stage includes a variety of corresponding key indicators.

[0160] Step S520, building a full-process digital management and control platform, and monitoring the key indicators of each management stage in real time through the full-process digital management and control platform;

[0161] Among them, the full-process digital management and control platform supports technologies such as big data analysis, artificial intelligence-assisted decision-making, and intelligent scheduling to ensure efficient operation of each link.

[0162] Step S530: Based on data visualization technology, various key indicators are processed to obtain a visualization dashboard in real time, and the visualization dashboard is displayed to managers through the full-process digital management and control platform;

[0163] Real-time visual dashboards can help management understand various key indicators in the transformation process in a timely manner and respond quickly.

[0164] Step S540, obtaining the stage goal corresponding to the current management stage, and managing the digital transformation plan based on the real-time visual dashboard and the stage goal;

[0165] The technical means used in each management stage are different, including but not limited to data monitoring, resource scheduling, and technical support; specifically,

[0166] If the current management stage is the evaluation stage, the technical means used include:

[0167] Step 1: Construct an evaluation model based on multi-dimensional weighted scoring;

[0168] This evaluation model involves multiple dimensions such as digital infrastructure construction, strategic planning implementation, and innovation capabilities, and the weight of each dimension is determined through weighted evaluation methods (such as AHP and entropy method).

[0169] Step 2: Use multivariate statistical methods such as regression analysis and factor analysis to evaluate the contribution of each factor to the final effect during the transformation process; optimize the evaluation model based on the contribution of each factor to the final effect;

[0170] The factors (key indicators) used for reference in the optimization of the evaluation model include but are not limited to: digital infrastructure, strategic planning completion, business process optimization, and customer satisfaction;

[0171] Step three: Generate a comprehensive evaluation report based on the optimized evaluation model and real-time data during the enterprise's digital transformation process.

[0172] Through the full-process digital management and control platform, key indicators of each management stage (including various business operation data, market data, etc.) are continuously collected for real-time monitoring and feedback. Based on real-time data feedback, the system can automatically adjust the weight and indicator settings of the evaluation model to ensure the timeliness and accuracy of the evaluation results. Combined with the scores of each dimension, an evaluation report is automatically generated to provide a basis for decision-making.

[0173] If the current management stage is the optimization stage, the technical means used include:

[0174] Based on the comprehensive evaluation report and data from the shared platform, the shortcomings of the current digital transformation plan were discovered, and the content of the digital transformation plan was further optimized and adjusted.

[0175] This invention significantly optimizes the digital transformation strategy of Qihang Enterprises, and accurately meets the unique needs of start-up and high-risk enterprises. Through flexible resource allocation, real-time data-driven decision-making and comprehensive security and compliance guarantees, it greatly improves the efficiency and accuracy of transformation, and paves an efficient, robust and adaptable digital development path for such enterprises.

[0176] This paper deeply analyzes the business status, technical capabilities, industry characteristics and market demand of Qihang Enterprise, and designs a highly customized planning plan for its pain points and challenges in the transformation process. With the help of real-time research and data analysis, the plan provides enterprises with a phased and refined transformation roadmap, clarifies innovation goals and technology implementation paths, and effectively avoids strategic deviations caused by market uncertainty. This tailor-made planning strategy ensures that enterprises maintain their competitive advantage in turbulent markets and flexibly respond to various unexpected changes.

[0177] Embodiment 3

[0178] Figure 2 This is a structural diagram of the enterprise digital transformation full life cycle management and control system in one embodiment of the present invention. Figure 2 As shown, according to an embodiment of the present invention, a full life cycle management and control system for enterprise digital transformation is applied to a target enterprise, including:

[0179] The digital transformation planning module 10 is used to analyze and plan the digital transformation needs of the target enterprise and customize the digital transformation plan for the target enterprise;

[0180] Resource integration and collaborative management module 20, used for resource aggregation and collaborative optimization;

[0181] A decision support system building module 30, used to build a data-driven decision support system for a target enterprise;

[0182] A security assurance mechanism building module 40 is used to build a digital security and compliance assurance mechanism for the target enterprise;

[0183] The management and control module 50 is used to manage the entire life cycle of the digital transformation of the target enterprise through a decision support system based on the digital transformation plan.

[0184] In this embodiment, the digital transformation planning module 10 is the starting point of the enterprise digital transformation full life cycle management and control system, and is specially designed for the start-up enterprise to tailor a digital transformation plan. This module plans a scientific and practical transformation path for the enterprise by deeply analyzing the enterprise's current situation, technical foundation, market demand, resource conditions and competitive situation. The resource integration and collaborative management module 20 is used to achieve efficient aggregation and collaborative utilization of resources, aiming to help start-up enterprises maximize the use of limited resources in digital transformation. In view of the actual situation of tight enterprise resources, this module implements the following key functions: Use big data analysis and AI technology to promote the effective integration of external resources. Build a cross-departmental information sharing platform to improve collaborative efficiency. Real-time monitoring of internal resource usage, identification and optimization of inefficient resource usage links, and improvement of overall resource utilization efficiency. The decision support system construction module 30 is used to create a data-driven decision support system for the enterprise, integrate and analyze the enterprise's full life cycle data, including operating conditions, technological progress and market feedback, and provide a comprehensive enterprise view for management. The security mechanism construction module 40 is used to build a digital security and compliance guarantee mechanism for the target enterprise. This module implements a multi-level security strategy, using core technical means such as data encryption, identity authentication and access control to protect the company's sensitive data and core technologies. At the same time, it takes into account the requirements of national laws and regulations, helping companies to meet regulatory standards and avoid legal risks during the transformation period. Control module 50 monitors the entire chain of enterprise technology research and development to ensure that technological innovation is completed on time and with high quality, and in line with market demand. It serves Qihang companies to ensure the smooth advancement of technology from conception to marketization. Use historical data and machine learning models (such as SVM, neural networks) combined with market trends to predict the prospects of technological innovation. Use big data and text mining technology (NLP) to analyze industry news, academic papers, patents, etc., and gain insight into the direction of technological innovation. Integrate real-time data and expert feedback to continuously improve the accuracy and foresight of the prediction model. According to the progress of research and development and the status of corporate resources, intelligently allocate resources to ensure that they match technical needs.

[0185] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0186] Embodiment 4

[0187] A new material company was selected as one of the first companies to start the journey. It focuses on the research and development and production of high-performance composite materials. The company is undergoing digital transformation to improve production efficiency, research and development capabilities, and market response speed. In this context, the full life cycle management method and system for digital transformation of enterprises of the present invention will bring significant improvements and benefits to the company. The following is an example of how the company applies the present invention:

[0188] 1. Customized digital transformation solutions

[0189] First, a comprehensive diagnosis was conducted on the new material enterprise, analyzing its existing production process, R&D management, market layout and financial status. Through data collection and analysis, the system found that the enterprise had problems with uneven resource allocation in the technology R&D stage, bottlenecks with low automation in the production process, slow market response, and a long conversion cycle for R&D results.

[0190] In response to these problems, a digital transformation roadmap was developed for enterprises, suggesting that they first implement smart manufacturing upgrades to improve the level of automation; secondly, accelerate the digital management of R&D, and introduce big data and artificial intelligence technologies to support R&D decision-making; finally, build a cloud-based supply chain collaboration platform to enhance market responsiveness.

[0191] Set phased goals based on the digital transformation plan:

[0192] The transformation goals are divided into three stages:

[0193] In the first phase, we will realize the intelligent upgrade of the production process and complete the construction of the digital production line.

[0194] In the second phase, the R&D process will be digitized and AI algorithms will be used to assist in material development.

[0195] The third stage is to build a full-chain supply chain management platform to achieve rapid response to customer needs.

[0196] 2. Resource integration and collaborative management

[0197] Through real-time market analysis, we help new material companies find opportunities to cooperate with leading scientific research institutions and obtain more technical support; and promote relevant government support policies to help companies obtain tax exemptions and R&D funding support.

[0198] Within the enterprise, it helps R&D, production, sales and other departments to achieve information sharing and process collaboration. For example, the latest material development progress of the R&D department can be directly synchronized to the production department, helping the production department to adjust the production line configuration in time to avoid waste of production capacity.

[0199] The system monitors the usage of production resources (such as equipment usage, raw material inventory) and R&D resources (such as R&D personnel input, laboratory resources, etc.) in real time, and automatically generates resource utilization efficiency reports to help management identify waste and bottlenecks in a timely manner.

[0200] 3. Manage the entire life cycle of digital transformation of enterprises through decision support systems

[0201] R&D progress monitoring includes: systematic monitoring of the progress of new material R&D projects, automatic generation of R&D progress reports through integrated R&D data (such as experimental data, production data, market feedback, etc.), helping management to adjust the R&D direction in a timely manner and ensure that the R&D plan is completed on schedule.

[0202] Evaluation of technological innovation, including: The company is developing a new high-strength composite material, and based on historical data and market demand forecasts, the market potential of the technology is evaluated. Based on market feedback and peer competition, the R&D team is provided with suggestions on material performance improvement, cost control and production process optimization to ensure the market adaptability of technological innovation.

[0203] Allocate R&D resources, including: automatically recommending resources from other departments (such as production technicians, equipment, etc.) when the R&D team faces technical difficulties, and suggesting increasing support for key technology R&D personnel to improve R&D efficiency.

[0204] Real-time risk monitoring, including: During the production process, if the system detects the risk of raw material price fluctuations, especially the supply of certain key raw materials may be affected by policy changes, the system will immediately issue an early warning and remind the procurement department to make procurement decisions in advance to ensure a stable supply chain.

[0205] Conduct risk assessment and early warning, including: for the research and development stage of new materials, the system uses big data analysis to predict bottlenecks that may be encountered in the technology research and development process, and warns the research and development team of technical difficulties that may be encountered, suggesting the need for technical breakthroughs.

[0206] The activation of the emergency response mechanism includes: when production quality problems that may occur during the material production process are discovered, the system can immediately activate the emergency response mechanism, automatically push relevant operation manuals to production line operators, and adjust the production process through automated equipment to prevent the large-scale production of defective products.

[0207] Analyze global data, including: the system aggregates data from production, R&D, sales and marketing to help management understand the overall operation of the company in real time. For example, by analyzing the operation data of the production line and market sales data, the system can determine whether the market demand for a new material exceeds the production capacity and recommend increasing production or adjusting the production plan.

[0208] Forecasting technology trends, including: combining the development trends of global materials science to predict innovative achievements that may subvert existing materials technology in the future, and providing companies with guidance and suggestions on the direction of technology research and development based on cutting-edge industry dynamics to ensure that the company's research and development is always at the forefront of technological innovation.

[0209] Market and financial analysis, including: providing management with detailed market forecasts through in-depth analysis of sales data, helping companies determine the competitiveness of new materials in different markets, and providing financial forecasts and capital allocation recommendations.

[0210] In the process of applying the full life cycle management and control system of enterprise digital transformation, it is continuously evaluated and optimized, specifically:

[0211] Conduct phased evaluations, including: The system conducts phased evaluations on the transformation process of new material enterprises. For example, after the first phase of intelligent manufacturing upgrades, the system evaluated that production efficiency increased by 20% and equipment failure rate decreased by 15%. Through these evaluation results, the system provides data support for the second phase of digital research and development.

[0212] Make optimization suggestions, including: based on the transformation effect evaluation, systematically make optimization suggestions to the management, such as increasing the training of R&D personnel in the second phase to improve R&D efficiency; at the same time, it is recommended to reduce production costs by increasing the degree of automation to further enhance competitiveness.

[0213] The continuous improvement mechanism of the system includes: the system summarizes lessons learned based on the transformation effects of each stage of the enterprise, and continuously improves the transformation strategy through the data feedback mechanism. For example, after discovering that certain links (such as material research and development) require stronger market driving force, the system will automatically adjust the research and development direction to ensure that the enterprise can keep pace with market demand in digital transformation.

[0214] By using the enterprise digital transformation full life cycle management and control method and system of the present invention, the enterprise can not only improve production efficiency and optimize R&D processes, but also better manage external resources and respond to risks. The data-driven decision support and real-time risk monitoring provided by the system enable enterprises to achieve the expected transformation goals at a faster speed and in an efficient manner during the high-risk, high-tech digital transformation process. At the same time, through continuous evaluation and optimization, it ensures that each stage of the transformation process is closely connected with market demand and technological development trends, thereby enhancing the core competitiveness of the enterprise.

[0215] The present invention realizes effective control over the entire process of digital transformation of Qihang Enterprise through innovative designs such as customized demand analysis, flexible resource integration, accurate data-driven decision support, and full life cycle management. Through these differentiated technological innovations, the present invention can help Qihang Enterprise to improve transformation efficiency and reduce the risk of failure through digital means when facing the high-risk and high-uncertainty market environment in the field of emerging technologies, and ultimately achieve sustainable innovative development.

[0216] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the present application.

[0217] It should be understood that the size of the serial numbers of each step in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

Claims

1. A method for managing and controlling the entire life cycle of enterprise digital transformation, applied to a target enterprise, characterized in that: The following steps are involved: Conduct digital transformation demand analysis and planning for the target enterprise, and customize a digital transformation plan for the target enterprise; Conduct resource aggregation and collaborative optimization; Building a data-driven decision support system for the target enterprise; Establish digital security and compliance assurance mechanisms for the target enterprises; Based on the digital transformation plan, the target enterprise is managed and controlled throughout its digital transformation life cycle through the decision support system.

2. The enterprise digital transformation full life cycle management and control method according to claim 1 is characterized in that: Conduct digital transformation needs analysis and planning for the target enterprise, including: Collect basic enterprise data, analyze the basic enterprise data using artificial intelligence and big data analysis tools, and obtain the current status of the enterprise; Obtain enterprise transformation demand information, and customize the digital transformation plan for the target enterprise based on the enterprise transformation demand information and the current status of the enterprise.

3. The enterprise digital transformation full life cycle management and control method according to claim 2 is characterized by: The enterprise transformation demand information includes enterprise vision information and market demand information; and / or, Obtaining the current status of the enterprise includes: Collecting basic data of the target enterprise based on the existing information system of the target enterprise; Based on the big data platform, the basic data of the enterprise is processed and analyzed to obtain the problems and bottlenecks of the target enterprise.

4. The enterprise digital transformation full life cycle management and control method according to claim 1 is characterized in that: Conduct resource aggregation and collaborative optimization, including: Build a sharing platform and assign permissions to each enterprise user on the sharing platform; Integrate internal and external resources of the enterprise into the shared platform and process the data of the shared platform; The data of the sharing platform is opened to each enterprise user according to the authority of the enterprise user on the sharing platform.

5. The enterprise digital transformation full life cycle management and control method according to claim 4 is characterized in that: Build a sharing platform and assign permissions to each enterprise user on the sharing platform, including: Building the sharing platform based on microservice architecture; Using data encryption technology to protect the data stored and transmitted on the sharing platform; Role-based permission management and data access control technology allocates permissions to each enterprise user on the sharing platform.

6. The enterprise digital transformation full life cycle management and control method according to claim 1 is characterized in that: Build a data-driven decision support system for the target enterprise, including: Select a management system suitable for the digital transformation needs of the target enterprise based on the type of enterprise, and build the decision support system based on big data and artificial intelligence technology; Collect and analyze key data in the target enterprise's operations in real time, and generate various management reports based on the key data; The various management reports are pushed to the managers in real time to assist the managers in making management decisions.

7. The enterprise digital transformation full life cycle management and control method according to claim 1 is characterized in that: Conduct full life cycle management and control of the target enterprise’s digital transformation, including: Divide the digital transformation program into multiple management stages; Build a full-process digital management and control platform for the target enterprise, and monitor the key indicators of each management stage in real time through the full-process digital management and control platform; Based on data visualization technology, the key indicators are processed to obtain a visualization dashboard in real time, and the visualization dashboard is displayed to managers through the full-process digital management and control platform; Obtain the stage goals corresponding to the current management stage, and manage the digital transformation plan based on the visualization dashboard and the stage goals.

8. The enterprise digital transformation full life cycle management and control method according to claim 7 is characterized by: The management stages include demand analysis stage, planning stage, resource integration stage, implementation stage, evaluation stage, and optimization stage; If the current management stage is the assessment stage, the technical means used include: Construct an evaluation model based on multi-dimensional weighted scoring; Use multivariate statistical methods such as regression analysis and factor analysis to evaluate the contribution of each key indicator to the final effect during the transformation process; optimize the evaluation model based on the contribution of each key indicator to the final effect; Generate a comprehensive evaluation report based on the optimized evaluation model and real-time data during the enterprise's digital transformation process.

9. The enterprise digital transformation full life cycle management and control method according to claim 1 is characterized in that: Conduct full life cycle management and control of the target enterprise's digital transformation, including: monitoring the risks of the target enterprise according to the digital transformation plan; specifically, Based on the risk characteristics of the target enterprise, a risk prediction model and emergency response mechanism are constructed; Acquire real-time data during the enterprise's digital transformation process, and obtain risk prediction results based on the real-time data and the risk prediction model; Based on the risk prediction results and the emergency response mechanism, a response plan is provided to the manager to assist the manager in making management decisions.

10. A full life cycle management and control system for enterprise digital transformation, applied to target enterprises, characterized by: include: A digital transformation planning module is used to analyze and plan the digital transformation needs of the target enterprise and customize a digital transformation plan for the target enterprise; Resource integration and collaborative management module, used for resource aggregation and collaborative optimization; A decision support system building module, used to build a data-driven decision support system for the target enterprise; A security assurance mechanism building module, used to build a digital security and compliance assurance mechanism for the target enterprise; A management and control module is used to perform full life cycle management and control of the target enterprise's digital transformation through the decision support system based on the digital transformation plan.

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