A water supply enterprise digital transformation method based on a togaf framework

Abstract

The application provides a water supply enterprise digital transformation method based on a TOGAF framework, which comprises the following steps: adopting the TOGAF framework to sort out business processes of a water supply enterprise, obtaining a business process list, constructing a CRE business architecture framework, the CRE business architecture framework comprising a water vein overall planning layer, a water network hub layer and a water intelligence engine layer, obtaining a basic business architecture, constructing a customer demand list, associating demand entries of the customer demand list to corresponding process nodes of a three-level process set, generating a transmission path according to a dependency relationship between nodes and data flow conversion logic, obtaining an end-to-end business process view, constructing a three-dimensional value evaluation model, forming a target business architecture, designing an application architecture based on the target business architecture and a double-engine architecture framework, designing a data architecture based on a target application architecture blueprint, designing a technical architecture based on the target application architecture blueprint and the data architecture, and providing a scientific basis for digital transformation of the water supply enterprise.

Description

Technical Field

[0001] This application relates to the field of digital transformation technology, and in particular to a digital transformation method for water supply enterprises based on the TOGAF framework. Background Technology

[0002] Water supply companies face challenges in their digital transformation, including low operational efficiency, severe data silos, lagging technological updates, and resource waste, urgently requiring comprehensive improvement through systemic restructuring. Currently, business architecture design primarily employs either the POS (Plan-Operation-Support) or OES (Operation-Enable-Support) approach. The former emphasizes the leading role of strategic management and is suitable for flow-oriented companies; the latter focuses on processes that create value for customers and is more suitable for project-based operations. However, the business characteristics of traditional water supply companies require both strategic and planning guidance and continuous business expansion to meet market demands, making it difficult to achieve an ideal business architecture design by simply relying on POS or OES methods.

[0003] While TOGAF, as a comprehensive enterprise architecture framework, offers guidance covering strategic planning and business process design, it lacks specific tools and support for tightly integrating strategic management with business processes, especially for organizations that rely on strategic planning and continuously expand their operations, such as water supply companies. TOGAF's strength lies in its adaptability to different industry needs and its support for all aspects from strategy to execution; however, it was not specifically built for rigid business architectures and derivative business architectures. This means that when facing the complex needs of specific industries, such as the operational inefficiencies and data silos encountered by water supply companies during digital transformation, relying solely on TOGAF may not be sufficient to meet all their requirements. Summary of the Invention

[0004] Therefore, the purpose of this application is to propose a digital transformation method for water supply enterprises based on the TOGAF framework, providing a scientific basis for the digital transformation of water supply enterprises.

[0005] To achieve the above objectives, this application proposes a digital transformation method for water supply enterprises based on the TOGAF framework, including:

[0006] The TOGAF framework was used to analyze the business processes of water supply companies, resulting in a business process list. The business process list includes, from top to bottom, a first-level process set, a second-level process set, a third-level process set, and a final-level process set.

[0007] Construct a CRE business architecture framework, which includes a water vein coordination layer, a water network hub layer, and a water intelligence engine layer; map the three-level process sets to the corresponding layers in the CRE business architecture framework to obtain the basic business architecture.

[0008] Construct a customer requirement list, associate the requirement items in the customer requirement list with the corresponding process nodes of the three-level process set, generate a transmission path based on the dependencies between the nodes and the data flow logic, and obtain an end-to-end business process view;

[0009] A three-dimensional value assessment model is constructed, and the actual execution data of each process node is collected. The actual execution data is compared with the corresponding assessment indicators of the three-dimensional value assessment model, and the process nodes that do not meet the standards are marked. The process nodes that do not meet the standards are then optimized to form the target business architecture.

[0010] Based on the target business architecture and the construction of the dual-engine intelligent transformation architecture framework, the application architecture is designed to obtain the target application architecture blueprint. The dual-engine intelligent transformation architecture framework includes a strategic engine and an intelligent engine. The strategic engine is used to transform the enterprise's strategic goals into application system planning requirements, and the intelligent engine is used to integrate artificial intelligence technology platform components to generate intelligent application design schemes.

[0011] Based on the target application architecture blueprint, design a data architecture, construct a water supply industry data model and data dictionary corresponding to the business entities in the target application architecture blueprint, determine the relationship between each business entity, and deploy a unified data platform, which includes an IoT data access module, a real-time stream processing module, and a historical data storage module.

[0012] Based on the target application architecture blueprint and data architecture design, a technical infrastructure system is constructed, comprising an interaction layer, a platform layer, and a facility layer. The interaction layer is configured with a unified enterprise portal to integrate the access points for business entities in the target application architecture blueprint. The platform layer includes a technical support platform and a data platform. The technical support platform supports the operational logic and service calls of the business entities. The data platform carries the data model, data dictionary, and unified data platform. The facility layer includes server resources, network resources, storage resources, and security protection components.

[0013] In some implementations, the CRE business architecture framework includes a water vein coordination layer comprising a strategic planning module and a business ecosystem module. The strategic planning module is used to receive policy instructions from higher authorities and decompose them into executable task items, while the business ecosystem module is used to maintain the cooperative relationship status with external service providers.

[0014] The water network central layer includes rigid process lines and flexible process lines. The rigid process lines are planning-driven business processes, and the flexible process lines are market-driven business processes.

[0015] The water intelligence engine layer includes an execution module, a prediction module, and a support module. The execution module is used for seamless connection between field equipment and data sources and for issuing commands. The prediction module is used to provide predictive data for operational decisions. The support module is used to generate business optimization solutions to support the operational decisions of the water network central layer.

[0016] In some implementations, the construction of the customer requirements list includes:

[0017] A multi-dimensional hierarchical system of stakeholders for water supply enterprises is adopted, which divides the stakeholders into two categories: internal customers and external customers. The internal and external customers are further divided into levels to form a customer classification model.

[0018] Obtain the demand text at the end level of the customer classification model, and standardize the demand text to obtain multiple demand items.

[0019] Based on the customer classification model, the required items are tagged and grouped to obtain a customer requirement list.

[0020] In some implementations, associating the requirement items of the customer requirement list with the corresponding process nodes of the three-level process set, and generating a transmission path based on the dependencies between the nodes and the data flow logic to obtain an end-to-end business process view includes:

[0021] The requirement items are associated with the corresponding process nodes of the three-level process set to determine the start node, intermediate processing node and end node involved in the implementation of the requirement items;

[0022] Based on the dependencies between nodes and the data flow logic, a transmission path is generated and embedded into the CRE business architecture framework to obtain an end-to-end process view from the submission of customer requirements to the fulfillment of those requirements.

[0023] In the end-to-end process view, the switching points between rigid process lines and flexible process lines are identified. The switching points are configured to automatically determine whether to enter the value-added service process branch based on the type of customer needs.

[0024] Configure a unique identifier, processing time limit threshold, and responsible person role code for each process node.

[0025] In some implementations, the construction of the three-dimensional value assessment model includes:

[0026] The three-dimensional value assessment model includes a coordination layer dimension, a central layer dimension, and an engine layer dimension, which correspond to the water vein coordination layer, the water network central layer, and the water intelligence engine layer of the CRE business architecture framework, respectively. The coordination layer dimension, the central layer dimension, and the engine layer dimension each correspond to a set of preset assessment indicators.

[0027] In some implementations, the overall planning layer dimension, the central layer dimension, and the engine layer dimension each correspond to a set of preset evaluation indicators, including:

[0028] The evaluation indicators corresponding to the overall planning level include compliance audit pass rate, cross-departmental collaboration efficiency, policy task completion rate, and ecosystem partner coverage rate;

[0029] The evaluation indicators corresponding to the central layer include water supply guarantee rate, pipeline leakage rate, process flow time, approval process time ratio, emergency handling time, value-added service coverage rate, and customer demand response speed.

[0030] The evaluation metrics for the engine layer include interface expansion speed, prediction model accuracy, decision support adoption rate, and the proportion of new technology applications.

[0031] In some implementations, the step of collecting actual execution data from each process node, comparing the actual execution data with the corresponding evaluation indicators of the three-dimensional value assessment model, and marking nodes that fail to meet the standards includes:

[0032] Extract actual execution data corresponding to each evaluation indicator from the existing information platform;

[0033] The actual execution data is collected according to the unique identifier of the process node, and mapped at the field level with the evaluation index under the dimension to which the node belongs.

[0034] The collected actual execution data is compared with the preset evaluation index threshold range; if the actual execution data exceeds the threshold range, the process node is marked as a non-compliant node.

[0035] In some implementations, marking the process node as a non-compliant node includes:

[0036] Determine the level of the non-compliant node within the CRE business architecture framework, and obtain the corresponding level weight value based on the level it belongs to;

[0037] Calculate the deviation of the evaluation index associated with the non-compliant node, where the deviation is the percentage of relative deviation between the actual execution data and the preset threshold;

[0038] Obtain all demand items associated with the non-compliant node, and determine the corresponding demand item weight value according to the end level of the customer classification model in the customer demand list.

[0039] The hierarchical weight value, deviation degree, and requirement item weight value are combined and calculated to obtain the score of the non-compliant node;

[0040] If the score is greater than or equal to the preset score threshold, then the non-compliant node is included in the optimization queue.

[0041] In some implementations, after designing the technical architecture based on the target application architecture blueprint and data architecture, the following further steps are included:

[0042] The system architecture for safeguarding data includes an intelligent security defense system, a comprehensive data governance system, and a digital transformation governance system. The intelligent security defense system comprises a technology-in-depth defense layer, a management and control framework layer, and a continuous improvement mechanism layer. The comprehensive data governance system includes modules for data governance organization, data standards system, data quality management, data security management, and data lifecycle management. The digital transformation governance system includes an organizational capability building mechanism, a process control innovation mechanism, and a continuous optimization engine.

[0043] This application provides a digital transformation method for water supply enterprises based on the TOGAF framework. By constructing a CRE business architecture framework comprising a water system coordination layer, a water network central layer, and a water intelligence engine layer, it accurately maps three levels of business processes to their corresponding levels, effectively solving the problem of the disconnect between the business architecture and the characteristics of the water supply industry in traditional TOGAF implementations. Simultaneously, by associating requirement items in the customer requirement list with process nodes and generating an end-to-end business process view, it ensures that digital transformation is always customer-value-oriented. Differentiated evaluation indicators are set for each of the three CRE layers, and non-compliant nodes are automatically marked based on actual execution data. Furthermore, an optimized priority scoring mechanism integrating three factors—layer weight value, indicator deviation, and requirement item weight—is introduced to avoid wasting resources on low-value processes and significantly improve governance efficiency.

[0044] In the application architecture design, the strategic engine transforms enterprise goals into system requirements, the intelligent engine integrates AI platform components to generate intelligent application solutions, and the data architecture builds a unified data platform and industry data models, connecting IoT, real-time streams and historical data to provide a high-quality data foundation for prediction, execution and support modules. Through the collaborative design of an intelligent security defense system, a full-element data governance system and a digital transformation governance system, the sustainable advancement of digital transformation is ensured from the dimensions of security protection, data quality and organizational mechanisms, thereby improving the system's stability, compliance and long-term evolution capabilities.

[0045] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0046] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0047] Figure 1 A framework diagram of a digital transformation method for water supply enterprises based on the TOGAF framework provided in this application embodiment;

[0048] Figure 2 A schematic diagram of a digital transformation method for water supply enterprises based on the TOGAF framework, provided as an embodiment of this application;

[0049] Figure 3 This is a framework diagram of the customer classification model provided in the embodiments of this application;

[0050] Figure 4 This is an end-to-end process view of the water meter batch replacement process provided in the embodiments of this application;

[0051] Figure 5 This is a framework diagram of the dual-engine intelligent transformation architecture provided in the embodiments of this application. Detailed Implementation

[0052] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0053] The following describes a method for digital transformation of water supply enterprises based on the TOGAF framework, with reference to the accompanying drawings.

[0054] This embodiment discloses a digital transformation method for water supply enterprises based on the TOGAF framework. It combines the TOGAF framework with the concepts of existing POS and OES methods to propose a novel digital transformation approach. This approach considers the characteristics of water supply enterprises, including diversified external customers, complex and large internal group organizational structures, and high requirements for the confidentiality and security of data and information systems. Figure 1As shown. In digital transformation projects, the strategic level drives the business architecture through policy guidance and receives feedback from the business architecture to optimize its direction. Here, "Aqua" represents water and is often used as a prefix in water supply company terminology. To effectively promote the implementation of digital transformation plans, the 4A+ architecture (Business Architecture (BA), Data Architecture (DA), Application Architecture (AA), Technical Architecture (TA), and Support System Architecture (SSA)) forms a closely interconnected whole. The business architecture not only drives and supports the application architecture but also empowers the data architecture; there is a two-way feedback relationship between the application architecture and the technical architecture, with both depending on and supporting each other. Similarly, the demand and support relationship between the data architecture and the technical architecture ensures that data needs are met and implemented. The support system architecture, as the foundational layer, ensures the stable operation and mutual collaboration of each architectural layer. This embodiment, based on the TOGAF framework, innovatively redesigns the business architecture according to the strategic plan and business needs of the water supply company, enabling it to respond to strategic guidance and flexibly expand to adapt to market changes, thereby achieving an ideal business architecture design, promoting the smooth implementation of digital transformation, and achieving the expected results.

[0055] like Figure 2 As shown, a digital transformation method for water supply enterprises based on the TOGAF framework includes the following steps.

[0056] Step S101: Use the TOGAF framework to sort out the business processes of the water supply company and obtain a business process list. The business process list includes, from top to bottom, a first-level process set, a second-level process set, a third-level process set, and a final-level process set.

[0057] As an implementation method, business process checklists typically categorize existing business processes according to their hierarchical structure. This includes the names of first-, second-, third-, and final-level processes, the responsible departments, process inputs, outputs, descriptions of key activities, existing problems, and their digitalization status. For water supply companies, taking the first-level process of pipeline network operation as an example, its second-level processes include: pipeline network strategy and planning, pipeline network lifecycle management, pipeline network resource monitoring and optimization, operation, maintenance and scheduling, water supply installation, secondary water supply management, abnormal fault management, meter management, pipeline network ancillary facility management, and audit management—a total of 10 second-level processes. These second-level processes are further subdivided into several third-level and final-level processes. The purpose of conducting checklist analysis is to inventory processes and provide a foundation for subsequent business process analysis.

[0058] Step S102: Construct the CRE business architecture framework. The CRE business architecture framework includes the water vein coordination layer, the water network hub layer, and the water intelligence engine layer. Map the three-level process sets to the corresponding layers in the CRE business architecture framework to obtain the basic business architecture.

[0059] In the CRE business architecture framework, the Water Network Coordination Layer includes a strategic planning module and a business ecosystem module. The strategic planning module receives policy instructions from higher authorities and breaks them down into executable tasks. The business ecosystem module maintains the cooperative relationship with external service providers. The Water Network Central Layer includes rigid and flexible process lines. The rigid process lines are plan-driven business processes, while the flexible process lines are market-driven business processes. The Water Intelligence Engine Layer includes an execution module, a prediction module, and a support module. The execution module is used for seamless connection between field equipment and data sources and for issuing instructions. The prediction module provides predictive data for operational decisions. The support module generates business optimization solutions to support the operational decisions of the Water Network Central Layer.

[0060] Water supply enterprises possess a dual nature: they rely on policy and planning while simultaneously needing to continuously expand their business ecosystem to meet their survival needs. The business architecture design must fully consider this contradiction and seek a balanced path. Therefore, a new business framework is needed to align with their business characteristics and expansion requirements. Based on the actual strategic and business development needs of water supply enterprises, a creative CRE architecture system is proposed. This architecture consists of three layers, from top to bottom: The Water Supply Coordination Layer's main function is to coordinate policy planning and the water supply business ecosystem, achieving overall balance and regulation, emphasizing the symbiotic relationship between "policy and planning dominance" and "market-driven innovation." The Water Network Hub Layer's main function is the operation and resource allocation of the main water supply chain. Based on the symbiotic relationship between planning and the market in the Water Supply Coordination Layer, a dual-cycle process system of "basic guarantee + value-added services" is constructed: the rigid process line represents planning-driven business, including water supply and dispatching; the flexible process line represents market-driven business, using customer needs insights to promote the extension of ecosystem services, forming a value feedback loop. The main functions of the Water Intelligence Engine layer are to provide technical support, drive innovation, and continuously optimize and expand to support and empower the realization of core businesses. The characteristics of the above business architecture are: dual-ring drive, reflecting both the leading role of the water supply company's strategic plan and the market demand for continuously expanding the water supply business ecosystem; inner ring: policy directives → rigid processes → public welfare security; outer ring: market demand → flexible processes → ecosystem expansion; three-layer penetration: the overall planning layer's strategy and plans provide legitimacy endorsement, the central layer's core operations and resource allocation create fundamental value, and the engine layer's continuous empowerment enables and supports value realization.

[0061] Step S103: Construct a customer requirement list, associate the requirement items in the customer requirement list with the corresponding process nodes of the three-level process set, generate a transmission path based on the dependencies between nodes and the data flow logic, and obtain an end-to-end business process view; including.

[0062] Step S103.1: Adopt the multi-dimensional hierarchical system of stakeholders of water supply enterprises, divide stakeholders into two categories: internal customers and external customers, and further subdivide the internal and external customers into levels to form a customer classification model.

[0063] Step S103.2: Obtain the demand text at the end level of the customer classification model, and standardize the demand text to obtain demand items. There are multiple demand items.

[0064] Step S103.3: Based on the customer classification model, the demand items are tagged and collected to obtain a customer demand list.

[0065] Step S103.4: Associate the requirement item with the corresponding process node of the three-level process set, and determine the start node, intermediate processing node and end node involved in the implementation of the requirement item.

[0066] Step S103.5: Generate a transmission path based on the dependencies between nodes and the data flow logic, and embed the path into the CRE business architecture framework to obtain an end-to-end process view from the submission of customer requirements to the fulfillment of those requirements.

[0067] Step S103.6: In the end-to-end process view, mark the switching point between rigid process lines and flexible process lines. The switching point is configured to automatically determine whether to enter the value-added service process branch based on the customer's demand type.

[0068] As an implementation approach, the water network central layer is divided into rigid and flexible process lines. Rigid process lines correspond to policy-mandated, regulatory-constrained, or basic guarantee-related businesses, with fixed process paths and unskippable approval nodes. Flexible process lines correspond to market-responsive, customer-customized, or value-added service-related businesses, with dynamically combinable processes and selectable nodes. When constructing the end-to-end business process view, the system sets switching points at the nodes of the water network central layer, achieving organic synergy between policy rigidity and market flexibility at the process level under the constraints of the CRE architecture.

[0069] Step S103.7: Configure a unique identifier, processing time limit threshold, and responsible person role code for each process node.

[0070] After the business list is compiled, the challenge in business architecture is how to extract end-to-end processes from the complex business components of an enterprise, ensuring a focus on core and key businesses without omissions. Currently, mainstream end-to-end process extraction methods include the Y-model and V-model, which offer theoretical frameworks for end-to-end process analysis, but lack a clear starting point. Therefore, this paper proposes a method that can quickly extract end-to-end business processes while ensuring coverage of core businesses and minimizing omissions. Its core idea is based on a customer value anchoring mechanism, using customer demand architecture modeling to reconstruct the business process value stream and construct a multi-dimensional, hierarchical stakeholder system. Figure 3The model establishes a multi-level customer classification system with two categories (internal and external customers) to ensure the identification of all stakeholders in the water supply company, directly determining the comprehensiveness of the end-to-end process. Customer needs penetration analysis and structured modeling: Abandoning the traditional approach of extracting end-to-end processes based on departmental functions or business scope, this model starts with different types of customers, deeply exploring their needs for water supply services to form a customer needs list. Business process value stream reconstruction: Based on the customer needs list, following the logic from need identification to need fulfillment, and adhering to the principle that only processes that create value need end-to-end process extraction, the end-to-end process extraction work is carried out in conjunction with the process list. This two-way drive from the customer needs side and the business supply side overcomes the limitations of traditional single-dimensional analysis; the customer classification model framework established through stakeholder analysis provides direction and guidance for water supply companies to conduct customer classification; and it provides an effective method and means for comprehensively extracting end-to-end processes.

[0071] As one implementation method, such as Figure 4 As shown, the end-to-end process for batch replacement of expired water meters is an example. This process primarily targets water users. The starting point is developing a replacement plan by screening expired water meters, and the ending point is archiving the replacement data. In this process, the replacement plan falls under the water supply management layer. Replacing expired meters is mandated by national law and is a social responsibility that water supply companies must fulfill, not subject to market competition. During the replacement process, the meter appointment process uses big data analytics to analyze users' water usage habits and recommend suitable replacement times, avoiding customer waiting and wasted trips for staff. The formulation and execution of supply guarantee measures require model calculations to provide reasonable scheduling schemes or water supply measures, mitigating the impact of meter replacement work on users' normal lives. These are all solutions provided by the Water Intelligence Engine layer and executed by the central water supply network layer. This process consists of 23 final-level processes. Each activity in each final-level process is equipped with a process node, and each process node has a unique identification code.

[0072] Step S104: Construct a three-dimensional value assessment model, collect actual execution data of each process node, compare the actual execution data with the corresponding assessment indicators of the three-dimensional value assessment model, mark the process nodes that do not meet the standards, and optimize the process nodes that do not meet the standards to form the target business architecture.

[0073] The three-dimensional value assessment model includes the overall planning layer, the central layer, and the engine layer, which correspond to the water vein planning layer, the water network central layer, and the water intelligence engine layer of the CRE business architecture framework, respectively. The overall planning layer, the central layer, and the engine layer each correspond to a set of preset assessment indicators.

[0074] As one implementation approach, the evaluation indicators corresponding to the overall planning layer include compliance audit pass rate, cross-departmental collaboration efficiency, policy task completion rate, and ecosystem partner coverage rate; the evaluation indicators corresponding to the central layer include water supply security rate, pipeline leakage rate, process flow time, approval process time ratio, emergency handling time, value-added service coverage rate, and customer demand response speed; the evaluation indicators corresponding to the engine layer include interface expansion speed, prediction model accuracy, decision support adoption rate, and new technology application ratio.

[0075] The value orientation of the overall planning layer is compliance, achievability of strategic goals, coordination effectiveness, and innovation-driven value. The value orientation of the central layer is ultra-large capacity, market response agility, lightweight design, and operational efficiency. The value orientation of the engine layer is technical support adaptability, innovation-driven capability, and cross-layer collaboration capability. Evaluation indicators are determined based on the value orientation of the above three dimensions.

[0076] Step S104.1: Extract the actual execution data corresponding to each evaluation indicator from the existing information platform.

[0077] As one implementation method, data sources include internal audit reports, regulatory agency inspection results, OA systems, project management platforms, policy management systems, supplier management systems, customer management systems, and work order systems.

[0078] Step S104.2: Collect the actual execution data according to the unique identifier of the process node, and map it at the field level with the evaluation index of the dimension to which the node belongs.

[0079] Step S104.3: Compare the collected actual execution data with the preset evaluation index threshold range; if the actual execution data exceeds the threshold range, mark the process node as a non-compliant node.

[0080] Step S104.4: Determine the level of the non-compliant node in the CRE business architecture framework, and obtain the corresponding level weight value according to the level.

[0081] Step S104.5: Calculate the deviation of the evaluation index associated with the non-compliant node. The deviation is the percentage of relative deviation between the actual execution data and the preset threshold.

[0082] Step S104.6: Obtain one or more requirement items associated with the non-compliant node, and determine the corresponding requirement item weight value according to the end level of the customer classification model in the customer requirement list.

[0083] Step S104.7: Combine the hierarchical weight value, deviation degree and requirement item weight value to calculate the score of the non-compliant node.

[0084] Step S104.8: If the score is greater than or equal to the preset score threshold, then the non-compliant node is included in the queue to be optimized.

[0085] After completing the process architecture design and end-to-end process refinement, it's crucial to quickly focus on optimizing critical and problematic processes. For core business processes, establish a method that fully leverages time information / time logs for analysis to identify bottleneck processes and prioritize their optimization. For the CRE architecture framework, propose a three-dimensional value assessment model and suggested evaluation metrics. By selecting appropriate evaluation metrics and performing weighted calculations, problematic processes can be identified, and it's possible to focus on which dimensions of the process require optimization.

[0086] Step S105: Based on the target business architecture and the dual-engine architecture framework, design the application architecture to obtain the target application architecture blueprint. The dual-engine intelligent transformation architecture framework includes a strategic engine and an intelligent engine. The strategic engine is used to transform the enterprise's strategic goals into application system planning requirements, and the intelligent engine is used to integrate artificial intelligence technology platform components to generate intelligent application design solutions.

[0087] Driven by strategy and guided by business logic, the logic of application system and business architecture mapping relationship analysis is used to establish the application architecture. Optimization of the application architecture is then achieved by leveraging technology to empower applications and allowing applications to feed back into the business. In the traditional practice of the TOGAF architecture framework, application architecture design follows a strict business-driven paradigm. This involves establishing a business capability-application system mapping matrix, analyzing baseline and target architectures, and ultimately forming an application architecture blueprint that is strategically consistent. Facing the wave of digital transformation, such as... Figure 5 As shown, the dual-engine intelligent transformation architecture framework is constructed. Its core idea is to maintain the guiding role of strategic business objectives in application architecture design, while establishing an artificial intelligence technology platform as an enabler for architectural innovation. Through the injection of new architectural components such as machine learning pipelines and intelligent decision engines, a virtuous cycle of technology feeding back into business is achieved. The dual-core power of the strategic engine (driven by corporate strategy) and the intelligent engine (driven by AI technology) echoes the innovation paradigm of "business-technology two-way empowerment." It highlights the intelligent evolution path of AI empowerment (rather than traditional informatization), which includes the dual meaning of continuous architectural evolution and business breakthrough transformation. Ultimately, it forms a two-way empowerment mechanism between business architecture and application architecture: on the one hand, it drives the construction and iteration of application systems through digital modeling of business processes, realizing the stable support of application systems for business processes; on the other hand, it uses the intelligent application system empowered by AI to feed back into business process reengineering, forming a closed-loop evolution of "data insight-intelligent decision-making-process reshaping," achieving an exponential improvement in operational efficiency and customer service experience.

[0088] Traditional leakage management follows a "fault response" process: leak detection – reporting – repair. However, leveraging new technologies and equipment such as IoT devices, big data analytics, and hydraulic models, a "predictive maintenance" process has been established: leakage prediction – prioritization and notification to affected parties – on-site maintenance. This shortens response time, reduces maintenance costs, and minimizes customer impact. Furthermore, data analysis from smart water meters is enabling water supply companies to develop new businesses such as smart elderly care.

[0089] Step S106: Design a data architecture based on the target application architecture blueprint, construct a water supply industry data model and data dictionary corresponding to the business entities in the target application architecture blueprint, determine the relationships between the business entities, and deploy a unified data platform. The unified data platform includes an IoT data access module, a real-time stream processing module, and a historical data storage module.

[0090] Data architecture design primarily encompasses two aspects: data model design and data dictionary design, considered from both static and dynamic perspectives. The static aspect includes data model definition, master data identification, analysis and modeling of shared data and all business-related object data; the dynamic aspect mainly involves the management and governance of the entire data lifecycle. A data model and data dictionary closely aligned with the characteristics of the water supply industry are designed to accurately define the connotation of data and its interrelationships, laying a solid foundation for data application. The unified data platform includes an IoT data access module for collecting actual execution data, a real-time stream processing module for real-time processing, and a historical data storage module for storage. Integrating cutting-edge IoT technologies with big data processing capabilities, an efficient and intelligent data platform is constructed to achieve real-time collection, secure storage, and in-depth analysis of data throughout the entire water supply process, improving the timeliness and insight of data processing. A data governance framework is established to ensure data quality and security.

[0091] Step S107: Based on the target application architecture blueprint and data architecture, design the technical architecture and build a technical infrastructure system including an interaction layer, a platform layer, and a facility layer. The interaction layer is configured with a unified enterprise portal to integrate the access points of business entities in the target application architecture blueprint. The platform layer includes a technical support platform and a data platform. The technical support platform is used to support the operation logic and service calls of the business entities. The data platform is used to carry data models, data dictionaries, and a unified data platform. The facility layer includes server resources, network resources, storage resources, and security protection components.

[0092] The interaction layer integrates various application systems within the application architecture by building a unified enterprise portal. It provides personalized, single sign-on functionality, aggregates content from various information sources, and serves as the host for the information system's presentation layer. The platform layer includes the construction of a technical support platform and a data platform. The technical platform provides general technologies to support the construction of application systems and ensures system compatibility and scalability; the data platform provides a series of components for the data architecture technical implementation. The infrastructure layer includes the design of components such as server resources, storage resources, network resources, server operating systems, and security systems. Under the premise of security and controllability, it strives to achieve reasonable allocation and optimized sharing of resources.

[0093] Step S108: Construct the security system architecture, which includes an intelligent security defense system, a full-element data governance system, and a digital transformation governance system. The intelligent security defense system includes a technology-in-depth defense layer, a management and control framework layer, and a continuous improvement mechanism layer. The full-element data governance system includes modules for data governance organization, data standard system, data quality management, data security management, and data lifecycle management. The digital transformation governance system includes an organizational capability building mechanism, a process control innovation mechanism, and a continuous optimization engine.

[0094] Under the TOGAF framework, the traditional 4A architecture, due to insufficient endogenous evolution capabilities and a lack of resilient governance design, struggles to adapt to the core challenges of the water supply industry, including complex organizational hierarchies, diverse business constraints (such as cross-regional scheduling and collaboration), and strong data security risks. To address these issues, in addition to building a technology stack for system iteration, institutional innovation is also a powerful supporting means. The security defense system within the assurance system safeguards the risk resistance of the technological foundation; the data governance system ensures data credibility and compliance, protecting data-driven business operations; and the transformation governance system provides systematic guarantees for the implementation of the 4A architecture through institutional constraints, process embedding, and dynamic compliance mechanisms. Ultimately, this achieves a three-dimensional alignment of business objectives, technological implementation, and governance effectiveness, ensuring the smooth implementation of digital transformation for water supply enterprises.

[0095] This application provides a digital transformation method for water supply enterprises based on the TOGAF framework. By constructing a CRE business architecture framework comprising a water network management layer, a water network central layer, and a water intelligence engine layer, and accurately mapping the three-tiered business processes to their corresponding layers, it effectively solves the problem of the business architecture being disconnected from the characteristics of the water supply industry in traditional TOGAF implementations. Simultaneously, by associating the requirements in the customer requirement list with process nodes and generating an end-to-end business process view, it ensures that digital transformation is always customer-value-oriented. Differentiated evaluation indicators are set for each of the three CRE layers, and non-compliant nodes are automatically marked based on actual execution data. Furthermore, an optimized priority scoring mechanism integrating three factors—layer weight value, indicator deviation, and requirement item weight—is introduced to avoid wasting resources on low-value processes and significantly improve governance efficiency.

[0096] In the application architecture design, the strategic engine transforms enterprise goals into system requirements, the intelligent engine integrates AI platform components to generate intelligent application solutions, and the data architecture builds a unified data platform and industry data models, connecting IoT, real-time streams and historical data to provide a high-quality data foundation for prediction, execution and support modules. Through the collaborative design of an intelligent security defense system, a full-element data governance system and a digital transformation governance system, the sustainable advancement of digital transformation is ensured from the dimensions of security protection, data quality and organizational mechanisms, thereby improving the system's stability, compliance and long-term evolution capabilities.

[0097] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0098] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0099] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0100] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0101] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0102] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0103] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0104] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0105] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0106] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0107] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A digital transformation method for water supply enterprises based on the TOGAF framework, characterized in that, Includes the following steps: The TOGAF framework was used to analyze the business processes of water supply companies, resulting in a business process list. The business process list includes, from top to bottom, a first-level process set, a second-level process set, a third-level process set, and a final-level process set. A CRE business architecture framework is constructed, which includes a water vein coordination layer, a water network hub layer, and a water intelligence engine layer. The three-level process sets are mapped to the corresponding layers in the CRE business architecture framework to obtain the basic business architecture. The water network coordination layer includes a strategic planning module and a business ecosystem module. The strategic planning module receives policy instructions from higher-level authorities and breaks them down into executable tasks. The business ecosystem module maintains cooperative relationships with external service providers. The water network central layer includes rigid and flexible process lines. The rigid process lines are plan-driven business processes, while the flexible process lines are market-driven business processes. The water intelligence engine layer includes an execution module, a prediction module, and a support module. The execution module handles seamless integration between field equipment and data sources and issues instructions. The prediction module provides predictive data for operational decisions. The support module generates business optimization solutions to support the operational decisions of the water network central layer. Construct a customer requirement list, associate the requirement items in the customer requirement list with the corresponding process nodes of the three-level process set, generate a transmission path based on the dependencies between the nodes and the data flow logic, and obtain an end-to-end business process view; A three-dimensional value assessment model is constructed, and the actual execution data of each process node is collected. The actual execution data is compared with the corresponding assessment indicators of the three-dimensional value assessment model, and the process nodes that do not meet the standards are marked. The process nodes that do not meet the standards are then optimized to form the target business architecture. Based on the target business architecture and the dual-engine intelligent transformation architecture framework, the application architecture is designed to obtain the target application architecture blueprint. The dual-engine intelligent transformation architecture framework includes a strategic engine and an intelligent engine. The strategic engine is used to transform the enterprise's strategic goals into application system planning requirements, and the intelligent engine is used to integrate artificial intelligence technology platform components to generate intelligent application design schemes. Based on the target application architecture blueprint, design a data architecture, construct a water supply industry data model and data dictionary corresponding to the business entities in the target application architecture blueprint, determine the relationship between each business entity, and deploy a unified data platform, which includes an IoT data access module, a real-time stream processing module, and a historical data storage module. Based on the target application architecture blueprint and data architecture design, a technical infrastructure system is constructed, comprising an interaction layer, a platform layer, and a facility layer. The interaction layer is configured with a unified enterprise portal to integrate the access points for business entities in the target application architecture blueprint. The platform layer includes a technical support platform and a data platform. The technical support platform supports the operational logic and service calls of the business entities. The data platform carries the data model, data dictionary, and unified data platform. The facility layer includes server resources, network resources, storage resources, and security protection components.

2. The method for digital transformation of water supply enterprises based on the TOGAF framework according to claim 1, characterized in that, The process of building a customer needs list includes: A multi-dimensional hierarchical system of stakeholders for water supply enterprises is adopted, which divides the stakeholders into two categories: internal customers and external customers. The internal and external customers are further divided into levels to form a customer classification model. Obtain the demand text at the end level of the customer classification model, and standardize the demand text to obtain multiple demand items. Based on the customer classification model, the required items are tagged and grouped to obtain a customer requirement list.

3. The method for digital transformation of water supply enterprises based on the TOGAF framework according to claim 2, characterized in that, The step of associating the requirement items of the customer requirement list with the corresponding process nodes of the three-level process set, generating a transmission path based on the dependencies between the nodes and the data flow logic, and obtaining an end-to-end business process view includes: The requirement items are associated with the corresponding process nodes of the three-level process set to determine the start node, intermediate processing node and end node involved in the implementation of the requirement items; Based on the dependencies between nodes and the data flow logic, a transmission path is generated and embedded into the CRE business architecture framework to obtain an end-to-end process view from the submission of customer requirements to the fulfillment of those requirements. In the end-to-end process view, the switching points between rigid and flexible process lines are identified. The switching points are configured to automatically determine whether to enter the value-added service process branch based on the type of customer needs. Configure a unique identifier, processing time limit threshold, and responsible person role code for each process node.

4. The method for digital transformation of water supply enterprises based on the TOGAF framework according to claim 3, characterized in that, The construction of the three-dimensional value assessment model includes: The three-dimensional value assessment model includes a coordination layer dimension, a central layer dimension, and an engine layer dimension, which correspond to the water vein coordination layer, the water network central layer, and the water intelligence engine layer of the CRE business architecture framework, respectively. The coordination layer dimension, the central layer dimension, and the engine layer dimension each correspond to a set of preset assessment indicators.

5. The method for digital transformation of water supply enterprises based on the TOGAF framework according to claim 4, characterized in that, The overall planning layer, central layer, and engine layer dimensions each correspond to a set of preset evaluation indicators, including: The evaluation indicators corresponding to the overall planning level include compliance audit pass rate, cross-departmental collaboration efficiency, policy task completion rate, and ecosystem partner coverage rate; The evaluation indicators corresponding to the central layer include water supply guarantee rate, pipeline leakage rate, process flow time, approval process time ratio, emergency handling time, value-added service coverage rate, and customer demand response speed. The evaluation metrics for the engine layer include interface expansion speed, prediction model accuracy, decision support adoption rate, and the proportion of new technology applications.

6. The method for digital transformation of water supply enterprises based on the TOGAF framework according to claim 5, characterized in that, The process of collecting actual execution data from each process node, comparing the actual execution data with the corresponding evaluation indicators of the three-dimensional value assessment model, and marking process nodes that fail to meet the standards includes: Extract actual execution data corresponding to each evaluation indicator from the existing information platform; The actual execution data is collected according to the unique identifier of the process node, and mapped at the field level with the evaluation index under the dimension to which the node belongs. The collected actual execution data is compared with the preset evaluation index threshold range; if the actual execution data exceeds the threshold range, the process node is marked as a non-compliant node.

7. A method for digital transformation of water supply enterprises based on the TOGAF framework according to claim 6, characterized in that, After marking the process node as a non-compliant node, the following steps are included: Determine the level of the non-compliant node in the CRE business architecture framework and obtain the level weight value corresponding to the level. Calculate the deviation of the evaluation index associated with the non-compliant node, where the deviation is the percentage of relative deviation between the actual execution data and the preset threshold; Obtain all demand items associated with the non-compliant node, and determine the corresponding demand item weight value according to the end level of the customer classification model in the customer demand list. The hierarchical weight value, deviation degree, and requirement item weight value are combined and calculated to obtain the score of the non-compliant node; If the score is greater than or equal to the preset score threshold, then the non-compliant node is included in the queue to be optimized.

8. The method for digital transformation of water supply enterprises based on the TOGAF framework according to claim 1, characterized in that, The technical architecture design based on the target application architecture blueprint and data architecture also includes: The system architecture for safeguarding data includes an intelligent security defense system, a comprehensive data governance system, and a digital transformation governance system. The intelligent security defense system comprises a technology-in-depth defense layer, a management and control framework layer, and a continuous improvement mechanism layer. The comprehensive data governance system includes modules for data governance organization, data standards system, data quality management, data security management, and data lifecycle management. The digital transformation governance system includes an organizational capability building mechanism, a process control innovation mechanism, and a continuous optimization engine.

Images