Enterprise innovation ability optimization model based on digital technology and application thereof

Abstract

The invention discloses an enterprise innovation capability optimization model based on a digital technology and application thereof, belongs to the technical field of enterprise innovation management and digital technology application, and integrates the technologies of data management, big data analysis, AI prediction, digital collaboration and the like, so that an enterprise can quickly respond to market and personalized user needs, and the enterprise innovation capability is optimized. And the product innovation and competitiveness are improved. Through the Internet of Things and an online platform, an enterprise can accurately capture market trends and user preferences; big data and an AI algorithm assist in deep insight and decision making; a digital platform and cloud computing promote remote cooperation; smart tags and language processing optimize knowledge management. 3D printing and VR accelerate product development, and a user community promotes user participation. The security is guaranteed by multi-factor authentication and regular auditing, and an organization culture and continuous learning mechanism ensures that an enterprise adapts to changes. The model not only enhances innovation, but also provides the advantage of sustainable development, and is the key of digital transformation.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of enterprise innovation management and digital technology application, and specifically relates to an enterprise innovation capability optimization model based on digital technology and application thereof. BACKGROUND

[0002] With the rapid development of globalization and information technology, enterprises are facing increasingly fierce market competition. In this context, enterprise innovation capability has become one of the key factors for them to gain competitive advantage. Innovation capability not only includes the ability to develop new products, but also the ability to improve production processes, business model innovation, and quickly respond to market changes. Currently, many enterprises rely on traditional market research and product development processes to drive innovation. These processes are usually linear, rigid and slow, making it difficult to adapt to the rapid changes in the market and the individualization of consumer demand. In addition, the knowledge resources within an enterprise are often scattered among different departments and individuals, lacking effective integration and management mechanisms, resulting in the potential of knowledge resources not being fully utilized.

[0003] With the development of digital technologies such as big data, artificial intelligence (AI), and Internet of Things (IoT), enterprises have the opportunity to collect and analyze large amounts of data through these technologies to better understand market demand and user behavior, thereby optimizing the innovation process. However, existing solutions do not provide a comprehensive framework or model that can fully utilize these digital technologies to improve enterprise innovation capability. Therefore, there is a technical problem of how to design a model that can integrate and utilize digital technologies to optimize data collection, analysis, knowledge management, and innovation strategy formulation in enterprises to improve innovation efficiency and effectiveness. To this end, we propose an enterprise innovation capability optimization model based on digital technology and its application to solve the above-mentioned problems. SUMMARY

[0004] The purpose of the present application is to provide an enterprise innovation capability optimization model based on digital technology and its application to solve the problems mentioned in the background.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solution: An enterprise innovation capability optimization model based on digital technology, characterized by comprising the following steps:

[0006] a) Data collection and management: Collect data on market trends, customer preferences, and product performance through the use of IoT devices, online platforms, and internal information systems;

[0007] b) Data analysis: Use big data analysis tools and techniques to analyze the collected data to identify patterns and trends;

[0008] c) Innovation Strategy Formulation: Develop innovative strategies including new product development, business process improvement, etc., based on data analysis results;

[0009] d) Digital Platform Development: Create digital platforms to facilitate internal and external collaboration;

[0010] e) Knowledge Management: Integrate and manage internal and external knowledge resources to improve innovation efficiency;

[0011] f) Rapid Prototyping and Iterative Development: Use digital tools for product design and improvement;

[0012] g) User Engagement and Feedback: Collect user feedback through digital channels to improve products;

[0013] h) Security and Privacy Protection: Ensure data security and user privacy;

[0014] i) Organizational Culture and Structure Adjustment: Establish an organizational culture that adapts to digital transformation;

[0015] j) Continuous Learning and Updating: Regularly evaluate and update digital tools and processes.

[0016] Preferably, the data analysis in step b) further includes predictive analysis and decision support using artificial intelligence algorithms.

[0017] Preferably, the innovation strategy formulation step in step c) includes simulation and risk assessment using software tools, and further includes using interactive visual dashboards to present analysis results and strategy effect predictions.

[0018] Preferably, the digital platform development step in step d) includes building cloud computing environments and mobile applications to support remote collaboration, and also includes developing a collaboration suite that integrates messaging, file sharing, and video conferencing functions.

[0019] Preferably, the rapid prototyping and iterative development step in step f) includes using 3D printing technology and virtual reality (VR) simulation, and also includes configuring interfaces and tools for collecting user feedback to integrate user opinions immediately during prototype testing.

[0020] Preferably, the security and privacy protection step in step h) includes implementing encryption measures and multi-factor authentication mechanisms, and further includes conducting regular security audits and vulnerability scans to prevent data breaches.

[0021] Preferably, the continuous learning and updating step in step j) includes setting up a dedicated team to monitor industry trends and regularly train employees, and also includes establishing an internal online learning platform to provide courses and seminars on the latest digital technologies and innovative methods.

[0022] Preferably, the knowledge management in step e) includes building an enterprise knowledge base that employs intelligent tagging systems and semantic search technologies to improve information retrieval efficiency.

[0023] Preferably, the knowledge management step further includes automatically classifying and tagging key knowledge assets using natural language processing (NLP) techniques for quick identification and sharing of relevant content.

[0024] Preferably, the user engagement and feedback in step g) is achieved by setting up an interactive user community that provides personalized recommendations based on user history data and allows users to participate in the early stages of product design.

[0025] Compared with the prior art, the beneficial effects of the present application are:

[0026] This model integrates data collection and management, big data analysis, artificial intelligence prediction, digital platform collaboration, knowledge resource integration, rapid prototyping, user participation, security and privacy protection, organizational culture adjustment, and continuous learning, enabling enterprises to more effectively respond to market changes, individualize user needs, and improve the innovation and competitiveness of products and services.

[0027] By collecting market and user data through IoT devices and online platforms, enterprises can more accurately capture market dynamics and customer preferences. Using big data analysis and artificial intelligence algorithms, enterprises can gain insights into patterns and trends in the data, making more accurate predictions and decision-making. The construction of digital platforms and the application of cloud computing environments promote internal and external collaboration and improve remote work efficiency. Effective implementation of knowledge management, especially the use of intelligent tagging systems and natural language processing techniques, improves information retrieval efficiency and facilitates the quick identification and sharing of key knowledge assets.

[0028] In addition, rapid prototyping tools such as 3D printing and virtual reality simulation accelerate the product development process, and the establishment of user communities promotes user participation and feedback, making product design more market-oriented. In terms of security and privacy, multi-factor authentication and regular security audits provide a strong protective wall for enterprise data. At the same time, the adaptive adjustment of organizational culture and the establishment of continuous learning mechanisms ensure that enterprises can continue to progress and adapt to changing market and technological environments.

[0029] In summary, this model not only enhances the innovation capabilities of enterprises, but also provides a sustainable competitive advantage for enterprises, and is an important helper for enterprises on the road of digital transformation. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 The step diagram of the present application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort fall within the protection scope of the present application.

[0032] Please refer to Figure 1 The present application provides an enterprise innovation capability optimization model based on digital technology, characterized by comprising the following steps:

[0033] a) Data collection and management: Collect data on market trends, customer preferences, and product performance through IoT devices, online platforms, and internal information systems;

[0034] b) Data analysis: Use big data analysis tools and techniques to analyze the collected data to identify patterns and trends;

[0035] c) Innovation strategy formulation: Formulate innovation strategies including new product development, business process improvement, etc. based on data analysis results;

[0036] d) Digital platform construction: Create a digital platform to facilitate internal and external collaboration;

[0037] e) Knowledge management: Integrate and manage internal and external knowledge resources to improve innovation efficiency;

[0038] f) Rapid prototyping and iterative development: Use digital tools for product design and improvement;

[0039] g) User participation and feedback: Obtain user feedback through digital channels to improve products;

[0040] h) Security and privacy protection: Ensure data security and user privacy;

[0041] i) Organizational culture and structure adjustment: Establish an organizational culture that adapts to digital transformation;

[0042] j) Continuous learning and updating: Regularly evaluate and update digital tools and processes.

[0043] The data analysis in step b) further includes using artificial intelligence algorithms for predictive analysis and decision support.

[0044] The innovation strategy formulation step in step c) includes using software tools for simulation and risk assessment, and further includes using interactive visual dashboards to display analysis results and strategy effect predictions.

[0045] Wherein the digital platform building step of step d) includes constructing a cloud computing environment and mobile applications to support remote collaboration, and also includes developing a collaboration suite that integrates messaging, file sharing, and video conferencing functions.

[0046] Wherein the rapid prototyping and iterative development step of step f) includes using 3D printing technology and virtual reality (VR) simulation, and also includes configuring interfaces and tools for collecting user feedback to integrate user opinions immediately during the prototype testing phase.

[0047] Wherein the security and privacy protection step of step h) includes implementing encryption measures and multi-factor authentication mechanisms, and further includes conducting regular security audits and vulnerability scans to prevent data breaches.

[0048] Wherein the continuous learning and updating step of step j) includes setting up a dedicated team to monitor industry trends and regularly train employees, and also includes establishing an internal online learning platform that provides courses and seminars on the latest digital technologies and innovative methods.

[0049] Wherein the knowledge management of step e) includes building an enterprise knowledge base that uses intelligent tagging systems and semantic search technology to improve information retrieval efficiency.

[0050] Wherein the knowledge management step further includes using natural language processing (NLP) technology to automatically classify and tag key knowledge assets, so as to quickly identify and share relevant content.

[0051] Wherein the user engagement and feedback of step g) is achieved by setting up an interactive user community that provides personalized recommendations based on user historical data and allows users to participate in the early stages of product design.

[0052] Further,

[0053] The beneficial effects of data collection and management: Through the integration of Internet of Things devices, online platforms, and internal information systems, key information such as market trends, customer preferences, and product performance can be comprehensively captured. This provides real-time and accurate data support for enterprises, making the decision-making process more scientific and efficient, and also enhancing the enterprise's response speed and sensitivity to market changes.

[0054] The beneficial effects of data analysis: The application of big data analysis tools and technologies can extract valuable information from a large amount of complex data and identify patterns and trends. This not only helps enterprises discover potential market opportunities, but also optimizes products and services and improves operational efficiency. Combined with artificial intelligence algorithms, it further improves prediction accuracy and decision quality.

[0055] Benefits of innovation strategy development: By utilizing advanced software tools for simulation and risk assessment, businesses can more effectively plan new product development and business process improvement strategies. Interactive visual dashboards provide a clear and transparent view of the analysis results, improving the feasibility of decision-making.

[0056] Benefits of digital platform development: The constructed cloud computing environment and mobile applications facilitate collaboration among team members, regardless of their location, enabling efficient information sharing and teamwork, which greatly improves project progress and remote work efficiency.

[0057] Benefits of knowledge management: By establishing an intelligent enterprise knowledge base, using intelligent tagging systems and semantic search technology, businesses can more efficiently manage and retrieve knowledge resources. Natural language processing technology further helps to automatically classify and tag key knowledge assets, accelerating knowledge sharing and reuse.

[0058] Benefits of rapid prototyping and iterative development: The introduction of 3D printing and virtual reality (VR) simulation technology enables businesses to quickly turn design concepts into tangible prototypes and make timely adjustments based on user feedback. This significantly shortens the product development cycle, improving the timeliness and market adaptability of product launches.

[0059] Benefits of user engagement and feedback: Establishing an interactive user community not only strengthens user interaction but also provides personalized recommendations by analyzing and utilizing user data, allowing users to directly participate in product design. This sense of participation and customized service significantly improves user satisfaction and brand loyalty.

[0060] Benefits of security and privacy protection: By implementing encryption measures and multi-factor authentication mechanisms, as well as regular security audits and vulnerability scans, businesses can effectively prevent sensitive data from being leaked and misused. This safeguards the interests of businesses and users, while maintaining the reputation and legal compliance of the enterprise.

[0061] Benefits of organizational culture and structure adjustment: As digital transformation deepens, businesses need to establish an organizational culture that promotes flexibility and innovative thinking among employees. Adjusting the organizational structure helps to quickly adapt to market changes and improve the overall agility and execution of the organization.

[0062] Benefits of continuous learning and updating: By monitoring industry trends, regularly training employees, and establishing online learning platforms, businesses can ensure that the team continuously updates their knowledge and skills. A culture of continuous learning helps businesses maintain long-term competitiveness and adapt to changing market and technological requirements.

[0063] Working principle and use process of the invention:

[0064] The operation process of the digital technology-based enterprise innovation capability optimization model starts with data collection and management, collects data on market trends, customer preferences and product performance through the deployment of Internet of Things devices, online platforms and internal information systems, then analyzes the collected data using big data analysis tools and technologies to identify patterns and trends in the data, and uses artificial intelligence algorithms for predictive analysis and decision support, followed by innovation strategy development steps that combine data analysis results, use software tools for simulation and risk assessment, and display analysis results and strategy effect predictions through interactive visual dashboards, to facilitate internal and external collaboration, build digital platforms including cloud computing environments and mobile applications, and develop collaboration suites integrated with messaging, file sharing and video conferencing capabilities, knowledge management steps integrate and manage internal and external knowledge resources, use intelligent tagging systems and semantic search technologies to improve information retrieval efficiency, and use natural language processing technologies to automatically classify and tag key knowledge assets, rapid prototyping and iterative development steps use 3D printing technology and virtual reality simulation to configure interfaces and tools to integrate user feedback immediately during the prototype testing phase, user participation and feedback are achieved through the establishment of an interactive user community, personalized recommendations are provided and users are involved in the early stages of product design, security and privacy protection steps implement encryption measures and multi-factor authentication mechanisms, and conduct regular security audits and vulnerability scans, organizational culture and structure adjustment steps establish an organizational culture that adapts to digital transformation, and continuous learning and updating include monitoring industry trends, regularly training employees and establishing online learning platforms, through this series of interconnected steps, enterprises can comprehensively improve their innovation efficiency and market competitiveness.

[0065] The electronic components and modules used in the summary of the invention can be commonly used parts that can achieve the specific functions in the case, and the specific models and sizes can be selected and adjusted according to actual needs.

[0066] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above examples, and the above examples and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A digital technology-based enterprise innovation capability optimization model, characterized by the following steps: a) Data collection and management: Collect data on market trends, customer preferences, and product performance through IoT devices, online platforms, and internal information systems; b) Data analysis: Analyze the collected data using big data analysis tools and techniques to identify patterns and trends; c) Innovation strategy formulation: Formulate an innovation strategy including new product development, business process improvement, etc. based on data analysis results; d) Digital platform construction: Create a digital platform to facilitate internal and external collaboration; e) Knowledge management: Integrate and manage internal and external knowledge resources to improve innovation efficiency; f) Rapid prototyping and iterative development: Use digital tools for product design and improvement; g) User engagement and feedback: Obtain user feedback through digital channels to improve products; h) Security and privacy protection: Ensure data security and user privacy; i) Organizational culture and structure adjustment: Establish an organizational culture that adapts to digital transformation; j) Continuous learning and updating: Regularly evaluate and update digital tools and processes.

2. The enterprise innovation capability optimization model based on digital technology according to claim 1, characterized in that: The data analysis in step b) further includes using artificial intelligence algorithms for predictive analysis and decision support.

3. The enterprise innovation capability optimization model based on digital technology according to claim 2, characterized in that: The innovation strategy formulation step in step c) includes using software tools for simulation and risk assessment, and further includes using interactive visual dashboards to display analysis results and strategy effect predictions.

4. The enterprise innovation capability optimization model based on digital technology according to claim 3, characterized in that: The digital platform construction step in step d) includes building cloud computing environments and mobile applications to support remote collaboration, and also includes developing a collaboration suite that integrates messaging, file sharing, and video conferencing functions.

5. The enterprise innovation capability optimization model based on digital technology according to claim 4, characterized in that: The rapid prototyping and iterative development step in step f) includes using 3D printing technology and virtual reality (VR) simulation, and also includes configuring interfaces and tools for collecting user feedback to integrate user opinions immediately during the prototype testing phase.

6. The enterprise innovation capability optimization model based on digital technology according to claim 5, characterized in that: The security and privacy protection step in step h) includes implementing encryption measures and multi-factor authentication mechanisms, and further includes conducting regular security audits and vulnerability scans to prevent data breaches.

7. The enterprise innovation capability optimization model based on digital technology according to claim 6, characterized in that: The continuous learning and updating step in step j) includes setting up a dedicated team to monitor industry trends and regularly train employees, and also includes establishing an internal online learning platform that provides courses and seminars on the latest digital technologies and innovation methods.

8. The enterprise innovation capability optimization model based on digital technology according to claim 7, characterized in that: The knowledge management in step e) includes building an enterprise knowledge base that uses intelligent tagging systems and semantic search technology to improve information retrieval efficiency.

9. The enterprise innovation capability optimization model based on digital technology according to claim 8, characterized in that: The knowledge management step further includes using natural language processing (NLP) technology to automatically classify and tag key knowledge assets for quick identification and sharing of relevant content.

10. The enterprise innovation capability optimization model based on digital technology according to claim 9, characterized in that: The user engagement and feedback in step g) is achieved by setting up an interactive user community that provides personalized recommendations based on user historical data and allows users to participate in the early stages of product design.

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