Digital monitoring of tissue entropy increase and method for continuously de-disordering new tissue

Abstract

The application discloses a kind of organization entropy increase digital monitoring and continuous counter-chaos new quality organization optimization method, belong to organization digital management technical field.Enterprise architecture level, post redundancy, process node, cross-post cooperation, task turnover, internal consumption conflict and research and development efficiency data are collected, through AI organization entropy increase digital quantitative monitoring model and multidimensional weighted algorithm, calculate organization confusion degree, team internal consumption index, process redundancy, decision lag and operation inefficiency, generate organization entropy increase panoramic image and dynamic trend curve;According to the monitoring result positioning entropy increase problem, hierarchical classification executes architecture simplification, level compression, process specification, system iteration and post responsibility boundary clarification;Through normal monitoring, periodic retest, effect review and continuous optimization form steady-state control closed loop, improve the efficiency of scientific and technological organization operation and innovation execution, provide organization support for new quality productivity continuous development.

Description

Technical Field

[0001] This invention belongs to the fields of digital governance of new-quality productivity organizations, intelligent optimization of enterprise architecture, incremental monitoring of organizational entropy, and iterative efficiency improvement of science and technology innovation organizations. Specifically, it involves a new organizational management method that addresses the phenomenon of organizational entropy increase, such as bloated enterprise architecture, chaotic processes, excessive internal friction, and efficiency decline. This method enables digital monitoring of entropy increase index, intelligent analysis, and continuous anti-entropy optimization. It is suitable for scenarios such as organizational architecture management, process system optimization, team efficiency upgrade, and long-term maintenance of scientific and technological innovation vitality in cutting-edge technology innovation enterprises in the information management industry, such as AI intelligent agent research and development, trusted data space, full-domain data governance, and cloud-native architecture. Background Technology

[0002] According to the thermodynamic principle of entropy increase, as an open and complex system, corporate organizations naturally exhibit a tendency towards spontaneous disorder, chaos, and inefficiency, which is a common pain point in the development of science and technology innovation enterprises. With the expansion of R&D teams, the increase in business tracks, and the overlap of innovative projects, traditional corporate organizational management models lack digital monitoring tools and cannot quantify the degree of organizational chaos, internal consumption levels, and operational inefficiencies. In the long run, this easily leads to typical entropy increase problems such as bloated organizational structures, redundant management levels, disordered business processes, overlapping job responsibilities, prominent collaboration barriers, and delayed decision-making.

[0003] Current technologies rely on human experience for organizational restructuring, process streamlining, and architecture optimization, representing a reactive, post-hoc approach. This lacks real-time quantitative perception of organizational entropy increase, dynamic trend analysis, and precise problem identification, making it impossible to predict the evolutionary trends of organizational decline, efficiency degradation, and disorder. Continuous organizational entropy increase directly triggers a chain reaction of problems, including soaring internal friction within teams, declining R&D efficiency, weakened innovation execution, wasted scientific and technological resources, and diminished organizational vitality. This leads to insufficient momentum for new productivity development, slowed innovation iteration, and continuously rising organizational management costs, severely hindering the long-term high-quality, high-efficiency, and high-dynamic development of science and technology enterprises. Currently, the industry lacks a closed-loop technical system that can digitally quantify organizational entropy increase, intelligently identify potential problems, and continuously implement anti-entropy optimization, thus failing to achieve the long-term orderly, efficient, and stable operation of science and technology organizations. Summary of the Invention

[0004] I. Purpose of the invention.

[0005] To address the technical shortcomings of existing science and technology innovation enterprises, such as natural entropy increase, bloated structure, chaotic processes, significant internal friction, efficiency decline, and insufficient innovation vitality, this invention provides a new organizational optimization method for digital monitoring of organizational entropy increase and continuous anti-chaos. By using AI to digitally quantify various core indices of organizational entropy increase, it accurately locates organizational disorder problems, continuously carries out structural simplification, process standardization, and system iteration, effectively combats the natural decline trend of the organization, maintains the orderly and efficient operation of the enterprise organization in the long term, and consolidates the enterprise's technological innovation vitality and healthy new productivity development trend.

[0006] II. Technical Solution.

[0007] To achieve the above-mentioned objectives, the present invention adopts the following technical solution.

[0008] A method for digitally monitoring and continuously optimizing the management of enterprises with bloated architecture, chaotic processes, efficiency decline, and entropy increase index includes the following steps.

[0009] S1. Construct an AI-powered digital quantitative monitoring model for organizational entropy increase. Based on the full volume of big data on enterprise organizational operations, intelligently collect data on architectural hierarchy, job redundancy, process node data, cross-job collaboration, task turnover, internal friction and conflict, and R&D efficiency. Through multi-dimensional weighted algorithms, AI quantitatively calculates core entropy increase values ​​such as organizational disorder, team internal friction index, process redundancy, decision lag, and operational inefficiency. Generate a panoramic portrait of organizational entropy increase and dynamic trend curves to achieve digital, visual, and precise judgment of the disordered state of the organization. The AI-powered organizational entropy increment monitoring model breaks away from the traditional subjective judgment model and constructs a standardized entropy increase evaluation index system. It can capture hidden organizational chaos, potential redundancy problems, and efficiency decline trends in real time, accurately distinguish between normal organizational fluctuations and malignant entropy increase evolution, and achieve early warning, in-process monitoring, and post-event tracing of organizational decline risks.

[0010] S2. Establish an organizational dynamic anti-entropy iteration optimization mechanism. Based on the entropy increment monitoring results, accurately match targeted optimization solutions for different types of entropy increase problems such as bloated enterprise architecture, redundant levels, complex processes, unclear responsibilities, outdated systems, and chaotic collaboration. Continuously streamline redundant organizational structures, reduce ineffective management levels, standardize business innovation processes, iteratively optimize management systems, clarify job responsibility boundaries, and systematically eliminate the root causes of organizational disorder, chaos, and inefficiency. The dynamic anti-entropy optimization mechanism adopts a hierarchical classification and iterative strategy. It focuses on rectifying and optimizing organizational modules with high entropy increase, high internal friction, and low efficiency, while maintaining the steady-state operation of healthy and orderly organizational modules. It avoids a one-size-fits-all rectification model and achieves precise policy implementation, dynamic iteration, and continuous upgrading of organizational optimization.

[0011] S3. Construct a closed loop for the steady and orderly management of the organization. Through routine entropy increase monitoring, periodic anti-entropy optimization, and continuous system iteration, effectively combat the natural entropy increase and disorderly decline trend of the enterprise organization, continuously eliminate organizational redundancy, internal friction barriers, process blockages, and management loopholes, maintain the orderly operation of the enterprise with a streamlined organizational structure, smooth processes, clear responsibilities, efficient collaboration, and rapid decision-making, and completely reverse the trend of continuous decline in organizational effectiveness. The steady-state control closed loop realizes the full-link cycle of "entropy increase monitoring - problem location - precise optimization - effect review - steady-state maintenance" for the organization, so that the enterprise organization is always in a dynamic, orderly and efficient operating state, and avoids the common problems of traditional organizations becoming more bloated and more chaotic as they develop and expand.

[0012] S4. Establish a long-term empowerment system for the vitality of new-type organizations. Relying on a highly efficient organizational system that is continuously optimized to reduce entropy, streamline the entire innovation chain of scientific and technological research and development, patent layout, technology iteration, and digital construction. Continuously reduce internal friction in organizational management, improve innovation execution efficiency, activate team innovation momentum, maintain the company's vigorous technological innovation vitality in the long term, and consolidate the foundation for the company's healthy, sustainable, and high-quality development of new-type productivity.

[0013] The method of this invention is adapted to the organizational governance scenarios of cutting-edge technology innovation enterprises in the information management industry, such as AI intelligent agent research and development, trusted data space construction, full-domain data governance, and cloud-native architecture iteration. It is used for the long-term management and control of science and technology innovation organizations, maintenance of organizational vitality, upgrading of innovation efficiency, and steady development of new quality productivity.

[0014] III. Beneficial Effects.

[0015] Compared with existing technologies, this invention has outstanding novelty, inventiveness and practicality, and improves the patent barrier system for digital management of new quality productivity that fully covers patents No. 14-25.

[0016] First, this invention pioneers an AI-based digital quantitative monitoring technology system for organizational entropy increase in science and technology innovation enterprises. It fills the industry's technological gap in traditional organizational management, which cannot quantify disorder, internal friction index, and inefficient entropy increase. It achieves a fundamental upgrade from subjective experience-based judgment to data-driven precise analysis of organizational disorder.

[0017] Second, this invention constructs a normalized, dynamic, and continuous organizational anti-entropy optimization mechanism to precisely resolve core organizational pain points such as bloated architecture, chaotic processes, ambiguous responsibilities, internal team friction, and declining efficiency, thus completely breaking the natural decline law of enterprise organizations where "expansion equals bloat and development equals chaos".

[0018] Third, this invention enables enterprises to operate in a long-term, stable, orderly, and efficient manner, continuously reducing organizational management costs, internal costs of scientific and technological innovation, and costs of resource waste, comprehensively improving innovation execution efficiency, technology iteration efficiency, and patent output efficiency, and continuously activating the endogenous scientific and technological innovation vitality of enterprises.

[0019] Fourth, this invention forms a complete closed loop with the aforementioned patents 14-24, making up for the core shortcomings in corporate governance, entropy increase control, stable operation, and vitality maintenance. It establishes a full-dimensional new quality productivity patent technology matrix covering resource allocation, risk prevention and control, talent management, team empowerment, project management, competitive barriers, capacity transformation, and organizational optimization, realizing comprehensive digital intelligent management of corporate personnel, finance, materials, affairs, organization, innovation, and growth, forming a new quality development technology system for science and technology innovation enterprises with no blind spots, a complete closed loop, and high barriers. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the overall process of digital monitoring and anti-entropy optimization for entropy increase in this invention.

[0021] Figure 2 This is a diagram of the AI-based organizational entropy multidimensional quantitative monitoring architecture of the present invention.

[0022] Figure 3 This is a schematic diagram illustrating the logic of continuous anti-entropy increase and long-term maintenance of the vitality of new tissues in this invention.

[0023] Abstract and Figure Selection Figure 1 . Detailed Implementation

[0024] The novel organizational optimization method for digital monitoring of organizational entropy increase and continuous anti-chaos disclosed in this invention is suitable for the long-term governance scenarios of science and technology innovation enterprises in the information management industry. The specific implementation steps are as follows.

[0025] First, we launch an AI-powered digital quantitative monitoring model for organizational entropy increase. This model integrates comprehensive data from enterprise operations, team collaboration, process flow, project development, and job performance. It collects core data such as the number of organizational layers, job redundancy rate, process node time, frequency of cross-departmental collaboration conflicts, task turnaround lag rate, number of internal team complaints, and R&D efficiency decay. Through a preset weighted algorithm, it intelligently calculates organizational disorder, internal friction index, process entropy increase, and efficiency decay value, generating a dynamic assessment report on organizational entropy increase. This accurately identifies specific modules and core issues related to organizational bloat, process chaos, and inefficiency.

[0026] Secondly, based on the results of entropy increase monitoring and analysis, a dynamic anti-entropy increase iterative optimization mechanism was launched. This mechanism streamlined the organizational structure and reduced ineffective management levels to address the issue of redundant hierarchical structures; it restructured and innovated business processes, eliminated redundant approval nodes, and broke down collaboration barriers to address the issue of chaotic processes; it refined job responsibilities and clarified the boundaries of division of labor to address the issue of ambiguous authority and responsibility; and iteratively optimized and innovated management systems and improved control standards to address the issue of outdated systems. This approach enabled precise and targeted rectification, systematically eliminating the root causes of disorderly entropy increase within the organization.

[0027] Furthermore, we will construct a closed-loop system for the steady and orderly management of the organization, and set up a monthly and quarterly dual-cycle entropy increase retesting mechanism to continuously track the optimization effect. For modules that have seen a decrease in entropy increase and improved efficiency after rectification, we will maintain steady operation. For modules that have not been rectified and have repeated entropy increases, we will conduct in-depth iterative optimization to continuously combat the natural disorderly decline trend of the enterprise organization and maintain a streamlined, smooth, efficient, and rapid operational state in the long term.

[0028] Finally, relying on an efficient and orderly stable organizational system, we fully empower enterprises in cutting-edge scientific and technological innovation work such as AI intelligent agent R&D, trusted data space construction, full-domain data governance, and cloud-native architecture iteration. This significantly reduces internal organizational friction and management costs, improves the overall efficiency of technological innovation, patent layout, and product iteration, continuously activates the internal vitality of enterprise technological innovation, and maintains a healthy, high-quality, and sustainable new productivity development trend in the long term.

[0029] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for digital monitoring of organizational entropy increase and continuous anti-chaos optimization of novel organizations, characterized in that, It includes the following steps. 2.S1. Construct an AI-powered digital quantitative monitoring model for organizational entropy increase. Based on the full volume of big data on enterprise organizational operations, collect data on architectural hierarchy, job redundancy, process node data, cross-job collaboration, task turnover, internal friction and conflict, and R&D efficiency. Through multi-dimensional weighted algorithms, quantify and calculate organizational disorder, team internal friction index, process redundancy, decision lag, and operational inefficiency to generate a panoramic profile and dynamic trend curve of organizational entropy increase. S2. Establish an organizational dynamic anti-entropy iteration optimization mechanism. Based on the entropy increment monitoring results, match corresponding optimization solutions to address the entropy increase problems of bloated enterprise architecture, redundant levels, complex processes, ambiguous responsibilities, outdated systems, and chaotic collaboration. Implement organizational structure simplification, reduction of ineffective management levels, standardization of business innovation processes, iteration of management systems, and clarification of job responsibility boundaries. S3. Construct a closed loop for the orderly and stable management of the organization, forming a full-link cycle of entropy increase monitoring, problem identification, precise optimization, effect review and steady state maintenance through normalized entropy increase monitoring, periodic anti-entropy optimization and continuous system iteration; S4. Establish a long-term empowerment system for the vitality of new-type organizations. Relying on the efficient organizational system optimized through continuous anti-entropy, streamline the entire innovation chain of scientific and technological research and development, patent layout, technology iteration and digital construction, and continuously reduce internal friction in organizational management and improve innovation execution efficiency.

3. The method for digital monitoring of organizational entropy increase and continuous anti-chaos optimization of novel tissues according to claim 1, characterized in that, The AI-based digital quantitative monitoring model for organizational entropy increase is used to construct a standardized entropy increase evaluation index system and to capture in real time hidden organizational chaos, potential redundancy problems, and performance decline trends.

4. The method for digital monitoring of organizational entropy increase and continuous anti-chaos optimization of new-type organizations according to claim 1, characterized in that, The multi-dimensional weighted algorithm is used to distinguish between normal tissue fluctuations and malignant entropy increase evolution, and to achieve early warning, in-process monitoring and post-event tracing of organizational decay risks.

5. The method for digital monitoring of organizational entropy increase and continuous anti-chaos optimization of new-type organizations according to claim 1, characterized in that, The organizational dynamic anti-entropy iterative optimization mechanism adopts a hierarchical classification iterative strategy to focus on rectifying and optimizing organizational modules with high entropy increase, high internal friction, and low efficiency, while maintaining steady-state operation of healthy and orderly organizational modules.

6. The method for digital monitoring of organizational entropy increase and continuous anti-chaos optimization of new-type organizations according to claim 1, characterized in that, The organizational steady-state orderly management closed loop includes a monthly entropy increase retesting mechanism and a quarterly entropy increase retesting mechanism, which are used to continuously track the optimization effect and conduct in-depth iterative optimization of organizational modules that are not rectified or have repeated entropy increases.

7. The method for digital monitoring of organizational entropy increase and continuous anti-chaos optimization of new-type organizations according to claim 1, characterized in that, The organizational entropy increase panoramic profile and dynamic trend curve are used to locate specific modules and core problems of organizational bloat, chaotic processes, and low efficiency.

8. The method for digital monitoring of organizational entropy increase and continuous anti-chaos optimization of new-type organizations according to claim 1, characterized in that, The method is applicable to organizational governance scenarios for cutting-edge technology innovation enterprises in the information management industry, including AI intelligent agent research and development, trusted data space construction, full-domain data governance, and cloud-native architecture iteration.

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