BAT - Summary of Business Architecture

Need for transformation and digital mastery: without transformation, even leading companies have risk. Digital mastery: Important, digital masters are 26% more profitable, but rare: - Many fail to develop adequate Architecture. - Many fail to develop a clear business vision aligned with di...

Need for transformation and digital mastery: without transformation, even leading companies have risk. Digital mastery: Important, digital masters are 26% more profitable, but rare: - Many fail to develop adequate Architecture. - Many fail to develop a clear business vision aligned with digital technologies. How to manage transformation: - Manage current capabilities. - Adjust your architecture depending on the transformation. - Implement the transformation. The problem: - Mapping takes a lot of resources. - Mapping and understanding the architecture is very difficult. Why architecture is important: - Modern firms are complex and IT is everywhere. - Digital transformation is mandatory, but complex. - Having a well-defined business architecture ensures that new technologies are integrated effectively, supporting strategic goals and enabling precise transformations. 4 foundational elements of business architecture: 1: IT strategy: Understanding the objectives and how IT supports them. Strategy is based on unique activities to offer a value proposition. Successful strategies are focused and require trade-offs. - Different orders: - First order: Consistency - precise vision - Second order: Reinforcement - echo with other industries or services - Third order: Optimization - Efficient coordination and information exchange. - Porter's 5 forces: - Rivalry among competitors - Threat to new entrants - Treat to substitutes - Bargaining power of suppliers - Bargaining power of buyers - Analyzing business angle (mission and vision) - How their aspiration align with their strategy - Uber and Volkswagen might have the same vision (to provide transport) but have a different strategic path. - Evaluating strategic positioning: - Cost-based strategy: volkswagen (incubent), is focused on efficiency and scale, customers price sensitive and technology used to lower cost. - Differentiation based strategy: Uber (new entrant) uses unique offerings that customers value. They often use advanced technologies or knowledge to create a premium product. - Assessing Operating Models (Integration and Standardization): This step evaluates how processes and systems are managed across business units. 2: Business IT capabilities: Capabilities represent what a business must excel at to deliver value and achieve goals. They are unique values that enable an organization to deliver value and achieve goals. - Importance: - Foundation of operational model: Capabilities underpin how an organization operates and creates value. - Structured understanding: They help map and assess how different components of a business work together. - 3 types of business capabilities: - Core: Essential functions directly tied to the primary mission of the organization. - Supporting: Facilitate or enhance the core capabilities but do not directly add value. - Differentiating: Provide an advantage and set the organization apart. - 4 ways to use business capabilities: - Capability mapping: Visiolize different capabilities and how they relate to each other. - Strategic alignment: Combine capabilities and strategic objectives to align with business goals. - identification of strengths/weaknesses: identify strengths to leverage areas of improvement. - Agility and adaption: use capabilities to adapt quickly to changing market conditions. 3: value stream: what delivers value to the customer? When using it it must be visualized and continuously improved. - importance: - Structured view: they offer clear visualization of how organization creates, delivers and captures value. - process optimization: Value streams help identify inefficiencies, bottlenecks, and opportunities for improvement. - 4 key components: - Value-adding activities: directly contribute to value of the customer - Support activities: Facilitate value delivery but do not directly add value - Inputs and outputs: Include resources, information, and deliverables at each stage of the value stream. - Customers and stakeholders: the people who benefit from value delivery. 4: IT processes: tasks and workflows needed to execute capabilities and produce output. - Importance: - Enhances efficiency: streamlines tasks ensures faster execution and reduces costs. - Consistency: Standardized processes deliver consistent outcomes and improve reliability. - Scalability: a good business process can scale. - Accountability: Clearly defines roles and responsibilities, avoiding overlaps or gaps. 4 ways to use business processes: - Mapping processes: visualize each step to identify bottlenecks. - Business process mining: Use data-driven techniques to analyze existing processes and uncover optimization opportunities. - Optimization and automation: Streamline processes to reduce redundant tasks or delays. - Continuous monitoring: regularly evaluate processes for improvement opportunities.  TOGAF: The Open Group Architecture Framework: framework designed to help organizations structure, manage, and implement enterprise architecture (EA). It provides methodologies and tools to align business goals with IT infrastructure and processes, ultimately supporting digital transformation and improving efficiency. - Key components: - Architecture development method (ADM): step-by-step approach to create, implement, and manage architecture that aligns with organizational goals and transformation needs. - Architecture Content Framework: Storage framework of all outputs generated by the ADM process. - Enterprise Continuum: A classification system for organizing architectural artifacts, ranging from generic to highly specific solutions, facilitating reuse and adaptation. - Architecture Capability Framework: Ensures the organization has the structures, processes, and tools required to develop and sustain enterprise architecture. - Why TOGAF: - Consistency: - Agility: - Collaboration - Scalability: - Phases in ADM: Preliminary Phase Preparation, initiation, and customization of the TOGAF process. A. Architecture Vision Define scope, key stakeholders, and gain stakeholder buy-in Setting the Foundations for the vision. B. Business Architecture Define workflows and strategies to align with the architecture Building the Architecture vision. C. Information Systems Define logical and physical data models supporting the vision. D. Technology Specify hardware, software, and infrastructure to implement Architecture the vision. E. Opportunities & Create a roadmap for iterations and projects to meet the Planning the Transition Solutions vision. F. Migration Planning Prioritize projects based on cost, risk, and business value. G. Implementation Define acceptance criteria and ensure alignment with the Oversight and Adaptation Governance architecture. H. Change Management Manage risks and changes during implementation of the vision. 5 levels of IT-enabled business transformation: outlines the increasing potential of IT in transforming organizations. - Localized Exploitation: using IT to solve isolated issues within a specific function or department. - Internal Integration: Enhances organizational efficiency by integrating IT systems and business processes across departments - Business Process Redesign: Involves fundamental rethinking and redesigning of business processes to fully leverage IT capabilities - Business Network Redesign: Redesigns the relationships and interactions between multiple organizations within a business network using IT. - Business Scope Redefinition: Uses IT to redefine the company’s role in the market and its relationships within the extended business network. CONTINUE?!?!??!?! Sesh 2: Iceberg model: - visible layer (what people see): actions and behaviors are outcomes of organizational behaviour, often visible for stakeholders, and measurable trough performance. - Hidden layers: - Values: principles and priorities that guide decisions. - Believes: Assumptions held as truths about the organization or its environment. - Worldview: Deep-seated perspectives and attitudes that define how individuals interpret the world. - The right mindset: Organizational change is only sustainable if it aligns with and shifts the deeper, hidden layers of the iceberg. Actions alone are insufficient without addressing the underlying mindset. 5 key principals for successful organizational transformation: - Visionary leadership: Goal: Inspire and mobilize the organization towards a unified vision. - Clear communication: Goal: Build trust and ensure consistent understanding of the transformation. - Stakeholder engagement: Goal: Foster collaboration and ensure stakeholder support for the transformation. - 3 Examples: - From one to many to many: transitioning communication and engagement from one-on-one interactions to a network-based approach. - Agile Manifesto at Philips: Demonstrating principles like collaboration over processes and tools, fostering a mindset where customer collaboration and adaptability are prioritized to align all stakeholders with organizational goals. - Philips Team Blenders: identify key players and influencers within and outside the organization. - Strategic planning: Goal: Provide a clear, actionable framework to guide the organization through transformation while aligning teams and resources to achieve defined objectives. - 5 Key practices: - Define objectives: Clearly outline what success looks like. - Design a roadmap: break the transformation into actionable phases, with milestones. - allocate resources: Distribute human, financial, and technological resources efficiently to support the roadmap. - Engage stakeholders: involve key leaders and decision-makers to ensure alignment. - Monitor progress: regularly review performance metrics and adjust strategies. - 5 Examples: - Philips CBM Map (Component Business Model): - Building One IT Architecture at Philips: - The Philips Business System (PBS): - Agile Transformation Roadmap at Philips: - Agile Center of Excellence at Philips: - Cultural alignment: Goal: Build a culture that embraces change and innovation, creating an environment where teams thrive and align with the transformation objectives. - 3 key practices: - Foster a growth mindset: Encourage teams to view challenges as opportunities for learning and innovation. - Embrace diversity: Leverage diverse perspectives to create innovative solutions and improve decision-making.  - Promote continuous improvement: Encourage teams to view challenges as opportunities for learning and innovation. 4 stages of digital transformation according to the multidimensional journey: - Mechanization: The introduction of basic machinery for process automation (e.g., early analog cameras). - Digitization: The shift from analog to digital tools and technologies (e.g., digital cameras). - Integration: Connecting digital technologies into cohesive solutions that improve functionality and customer experience (e.g., smartphones with cameras). - Building an ecosystem: create ecosystems to share the photos. Pathway of the digital revolution: - Analog to digital: - Single function to multi-function integration: - system to system-of-systems: Progressing from standalone systems to interconnected ecosystems that provide unified solutions. Digital technologies: - Wide data: continuous monitoring over time. - Deep data: more detailed information - Dense data: Big data pattern recognition Digital transformation shifts organizations from focusing on isolated products to delivering integrated solutions through a convergence of products, services, and software within ecosystems. 3 key takeaways: - Multidimensionality: Digital transformation requires orchestrating changes across technology, culture, and business processes. - Integration as a Goal: Moving from simple systems to interconnected ecosystems is critical for sustaining transformation - Ecosystem Value: Success hinges on collaboration among diverse stakeholders to create comprehensive, customer-centric solutions. CASE: Digital Oncology: Driving "Next-Generation" Care Through Data and AI Integration - Goal: Delivering "Next-Generation" Care: provide accessible and affordable care for patients while enhancing efficiency. - 4 Challenges and solutions: - fragmented data - centralized data storage - Rapid growth of data - Cloud-based storage - Limited AI Infrastructure - Integrated AI Platforms - Limited Learning From Real-World Data - Single Source of Truth - 3 AI Integration in Oncology Workflows - Radiology and Radiotherapy: - Triage with Large Language Models (LLMs): - Decision Support (ACTIN Platform): - 4 AI-Driven Decision Support Workflow: - Accessing Medical Data: - Structuring Data: - Treatment Decision Support: - Creating Reports: - Benefits of AI Integration in Oncology: - Efficiency Gains: Reduces manual processing time (e.g., triage or lesion reporting). - Accuracy Improvements: Enhances precision in radiology and treatment recommendations. - Scalability: Supports treating more patients without increasing resource demands.  - Personalized Care: Combines real-world data with advanced analytics to tailor treatment plans. Sesh 3: Zachman Framework: Overview and Explanation: - 5 Rows: Stakeholder Perspectives Each row represents the perspective of a different stakeholder or role in the organization: - Contextual (Planner): High-level view focusing on the enterprise's goals and environment. - Conceptual (Owner): The business owner’s perspective, focusing on business needs and processes. - Logical (Designer): A logical design perspective, translating business needs into system requirements. - Physical (Builder): The implementer's view, specifying the physical implementation of the system. - Detailed (Programmer): A technical perspective focusing on operational details and programming specifics. - 6 Columns (horizontal): Architectural Aspects Each column represents a fundamental question about the system or enterprise: - Why (Motivation): The reasons or goals driving the architecture. - How (Function): The processes or methods needed to achieve the goals. - What (Data): The information or data necessary for the processes. - Who (People): The stakeholders or actors involved in the system. - Where (Network): The locations or infrastructure where the processes will occur. - When (Time): The timing or sequencing of processes and events. - Steps to Fill the Cells: - Identify the Scope: Begin by determining the overall transformation or system being analyzed. - Analyze Stakeholders: Consider the viewpoint of each stakeholder for the rows, from planners to programmers. - Ask the Right Questions: Use the six fundamental questions (Why, How, What, Who, Where, When) for each perspective to define the specific details for each cell. - Gather Input: Collaborate with relevant teams (e.g., business analysts, architects, engineers) to ensure comprehensive and accurate input. - Document Artifacts: Populate each cell with the appropriate models, documents, or insights (e.g., strategy plans, process models, data schemas). - For example: - Planner’s Perspective + Why (Motivation): Articulate the high-level goals and strategy driving the transformation. - Programmer’s Perspective + What (Data): Define the actual data structures used in the functioning system. - Key Features and Applications - Holistic View: The framework ensures that all aspects of the enterprise are considered, reducing the risk of overlooked elements. - Stakeholder Alignment: By representing multiple perspectives, it helps align technical implementations with business needs and strategies. - Flexibility: It is non-prescriptive, meaning it doesn’t mandate specific methodologies or tools, allowing organizations to adapt it to their needs. - Structured Transformation: It is particularly useful in guiding digital transformations, as it provides a comprehensive way to analyze and design systems. Common mistakes in transformations: - People:  - Team Cohesion Matters: Motivation, ability, and team dynamics are critical for productivity. - Adding More People: May decrease productivity due to mismanagement or lack of integration. - Process: - Fuzzy Front End: Lack of clarity in early stages leads to wasted time and inefficiencies. - Forecast Failures: Poor scheduling, risk management, and outsourcing lead to project derailments. - Products: - Overloading Features: Excessive requirements increase complexity and risk of failure. - Over-Diversification: Too many simultaneous IT projects dilute focus and increase risks. - technology: - Overestimating Tech: Believing new technologies will solve all problems leads to misplaced reliance. - Mid-Project Changes: Switching technologies midway is risky and destabilizing. Success in transformations: Transformation is challenging but achievable with strategic alignment, adaptability, and a focus on customer needs. CASE: SAP: Closed -> open source software Sesh 4: 4 Elements of modern business architecture: - Information and data architecture: Map data architecture - Technology architecture: Map tech architecture - Business agility and innovation: Use agile and understand technology architecture - Digital strategy: Embrace digital vision Technology architecture: - Hardware: - Software: - Network: 3 Technologie requirements: - Online user interface:  - Storage requirements: - Performance requirements: 2 netflix examples: - Simple architecture: - Complex architecture: 5 types of Data process architecture: - Data sources: Raw data enters the system through diverse channels - Data integration: The initial processing stage - Data management: A critical stage - Data analytics: The transformation stage - Insights generation: 3 types of architecture levels: - Conceptual model: High-level framework aligning data organization with business objectives. - Key elements: User profile and behavior, content catalogs and characteristics, user activity patterns and technical data infrastructure. - Purpose: Guides strategic decision-making, Directs feature development and Aligns data usage with business goals - Limitations: Lacks process details, Missing data specifications and No entity relationship details - Logical model: Framework detailing relationships between data entities and specific business needs. - Key elements: Entity relationships, Data flow patterns, Business requirement mapping, System interconnections - Purpose: Identifies specific data needs, Maps data relationships, Structures information flow. - Limitations: - Lacks database specifications and Missing technical implementation details - Physical model: Detailed technical implementation including database schemas and data structures. - Key elements: Database schemas, Column specifications, Data types and Storage requirements - Purpose: Provides implementation blueprint, Defines technical requirements and Enables system development Business Agility: represents a modern organizational approach to rapid change and adaptation. At its core, it's about maintaining forward momentum while transforming, much like a rugby team moving forward while passing the ball between players. 4 frameworks: - Scrum represents the foundational agile approach, focusing on team-based project management. Like a rugby team, it emphasizes quick, coordinated movements and adaptability. Teams work in sprints, regularly reviewing and adjusting their approach. - Kanban provides visual organization of work, helping teams track progress and manage workflows effectively. Think of it as a dynamic dashboard showing what's being worked on, what's coming up, and what's completed. - Lean methodology emphasizes efficiency and value creation with minimal waste. It's about streamlining processes while maintaining quality and effectiveness. - Additional frameworks like SAFe (Scaled Agile Framework), Design Thinking, and DevOps complement these core approaches, each adding specific tools for different organizational needs. S-curve: represents a technology's lifecycle. - 3 types: - Technology level s-curve: y= technology process, x= respective time  - Market level s-curve: y= market growth x=market adoption of a specific product - Jumping the s-curve: New technologies (based on entirely different approaches) replace older ones, representing a leap in performance. Timing the transition is critical. Early adoption risks wasted resources, while late adoption risks falling behind competitors. - 3 phases: - Early Development Stage: - Breakthrough Acceleration: - Maturity and Diminishing Returns: - Example: hard drive: - First Technology:Incremental improvements to ferrite-head/oxide disks enabled smaller, more precise drives. - Second Technology: Thin-film photolithography displaced ferrite-heads for better performance and efficiency (1979–1990). - Third Technology: Magneto-resistive heads further enhanced storage capabilities. - Fourth Technology: solid-state drives (SSD) revolutionized data storage with speed and reliability. - Difficulties transitioning the s-curve: - Fundamental dilemma: it always feels more economical to protect old businesses than to feed new ones. - Improving current technology: Increasing the current performance of the established business. - new technologies: Might result in gains in performance for untested products in minor clients. 6 rules for effective forecasting: - Uncertainty Mapping (Cone of uncertainty): assign/estimate probabilities of uncertain events. y= Different markets, x= time. Like a weather forecast cone, broader predictions become necessary as you look further ahead. - Look for the s-curve: Understanding that most technologies follow this pattern helps predict development stages. - Embrace the things that don't fit: past events allow you to draw and predict the evolution of technology or market, but failure to identify points might lead to wrong forecasts. - Flexible thinking: maintain strong opinions weakly, if new evidence emerges you have to be ready to adjust.  - Look back twice as far as you look forworth: - Know when not to make a forecast: Forecasting deals with predicting the future, which is inherently uncertain. This rule reminds forecasters to acknowledge that no prediction can be entirely accurate. Overconfidence in a forecast can lead to poor decisions if unexpected changes occur. Recognizing uncertainty helps manage expectations and allows for better adaptability Sesh 5 Business process modeling: (bpm): optimize business processes to make an organization more efficient and capable of adapting to an ever-changing environment. 6 steps: - Process Identification: Recognize and define key business processes within the organization. - Process Discovery: Document the "as-is" state of processes, often using visual tools like process flow diagrams. - Process Analysis: Evaluate existing processes to identify inefficiencies, bottlenecks, or redundancies. - Process Redesign: Propose and model improved "to-be" processes based on the analysis. - Process Implementation: Execute the redesigned processes in the operational environment. - Process Monitoring: Continuously monitor and measure performance to ensure conformance and identify areas for improvement. Process mining: gives the actual real-time process of the company at any stage as they seek to automate/optimize. BPMN (Business Process Model Notation): BPMN is a standardized visual modeling language used to map and communicate business processes clearly. - Events: Represent triggers (e.g., start, intermediate, or end of a process). - Example: A customer placing an order (start event). - Activities: Tasks or work performed in the process. - Example: Preparing pizza. - Gateways: Decision points that determine different process flows (e.g., "Yes/No" decisions). - Flows: Arrows showing the sequence of tasks or events in the process. Sesh 6 Digital mastery is the ability to integrate digital capabilities (technology, operations, and business models) with leadership capabilities (vision, governance, and cultural alignment) to achieve sustained business transformation. - Digital Capabilities - Focus: - operational excellence - customer engagement - innovative business models driven by digital technologies. - Examples include leveraging data analytics, cloud computing, and automation to enhance processes and deliver value. - Leadership Capabilities - Focus: - Vision & governance - IT-business relationship - Leadership culture - Leadership ensures alignment across silos, mobilizes teams, and nurtures a culture of continuous innovation. Framework: The Digital Transformation Playbook - Framing: Build awareness of digital opportunities and threats Key activities: \ - Assess digital maturity - kKnow your starting point and create a vision - Ensure the team is aligned around it. - Focusing Investment: translate your vision into an actionable roadmap. Key activities: - Build cross-silo governance structures - Put in place the funding for transformation. - Mobilizing the Organization: Engage employees and foster a culture of innovation. Key activities: - Communicate a clear ambition for transformation - Encourage new behaviors that support innovation - Build momentum through quick wins and sustained engagement - Sustaining the Transition: Ensure long-term success by embedding transformation into the organization. Key activities: - Align incentives and rewards to support digital goals. - Build foundational digital skills across the workforce. - Monitor progress and iterate based on measurable outcomes. Six IT Decisions Your IT People Shouldn’t Make (Leadership Capabilities) - How Much Should We Spend on IT? - Which Business Processes Should Receive our IT Dollars? - Which IT Capabilities Need to Be Companywide? - How Good Do IT Services Need to Be? - What Security and Privacy Risks Will We Accept? - Whom Do We Blame If an IT Initiative Fails? Implications and Best Practices - Business Ownership of IT Decisions: Senior management must lead strategic IT decisions to align technology with business goals. IT executives should serve as advisors, not sole decision-makers. - Collaboration Between Business and IT: Establish clear communication channels between IT leaders and business units to align priorities and define accountability. - Clear Metrics and Accountability: For each IT initiative, set measurable goals (e.g., ROI, user adoption rates) and assign accountability to business leaders and IT teams as appropriate. - Iterative and Adaptive Approach: IT decisions, especially in dynamic areas like digital capabilities and technology adoption, should be revisited periodically as business needs evolve. Digital Capabilities and Predictive Analytics: Driving Proactive Decision-Making. A key enabler of digital capabilities is predictive analytics, which leverages historical data, statistical algorithms, and machine learning to forecast future trends and outcomes. - Role of Predictive Analytics in Digital Capabilities - Personalization and Customer Experience - Operational Optimization - Enhancing Decision-Making - Fraud Detection and Risk Mitigation - Advantages of Predictive Analytics: - Improved Forecast Accuracy: Reduces uncertainty and enhances strategic planning. - Proactive Problem Solving: Addresses potential risks before they escalate. - Competitive Advantage: Early adoption enables differentiation in fast-changing industries. - Challenges in Predictive Analytics: - Data Dependency: High-quality, comprehensive data is essential for accurate predictions. - Cultural Resistance: Adopting a data-driven culture requires overcoming traditional mindsets and silos. - Complex Implementation: Skilled professionals, robust infrastructure, and ongoing validation are necessary for success. Technology Adoption and Predictive Analytics: Predictive analytics exemplifies the broader shift toward technology adoption. However, embedding predictive forecasting into business processes requires deliberate planning and cultural adaptation: - Investment Decisions: Senior management must align technology investments with strategic goals. - Decision Applications: Predictive analytics is particularly impactful in areas like human resources, client acquisition, supply chain management, and service design. - Balancing Human and Machine Inputs: Predictive tools augment decision-making but still require human oversight to provide context, ethical judgment, and nuanced understanding. Hybrid Forecasting: Merging Human and Algorithmic Insights: Predictive forecasting thrives when combined with human expertise. A hybrid approach leverages the strengths of both:  - Human Forecasts: Capture nuanced trends, qualitative insights, and emerging patterns. - Algorithmic Forecasts: Process large-scale data and historical patterns with precision. - Blended Model - Sesh 7 Sustainability Assurance in the Digital Age: The landscape of business assurance and reporting is undergoing a dramatic transformation, particularly in the realm of sustainability. As organizations face increasing pressure to demonstrate their environmental and social impact. - Assurance At its core, assurance is about building trust through independent verification. This process involves three key players working in concert: - Service Organizations providing the information - Auditors like KPMG verifying the data - User Organizations relying on the verified information - Scope: has expanded far beyond traditional financial audits to include various forms of assurance engagements, from algorithmic systems to behavioral assessments and ESG metrics. - The CSRD Revolution: The Corporate Sustainability Reporting Directive represents a watershed moment in corporate reporting. It introduces a phased approach: - 2024: Large public-interest entities lead the way - 2025: Other large companies join the mandate - 2026: Listed SMEs become part of the framework - The Reality of Implementation: Organizations currently find themselves at 3 different stages of maturity: - Starting Point: Minimal Compliance Today's reality for many organizations involves manual processes, Excel-based reporting, and fragmented data sources. It's a starting point that highlights the gap between current capabilities and future requirements. - The Journey: Transition State Organizations are beginning to implement standardized policies, develop control frameworks, and introduce basic automation. This middle ground represents the challenging but necessary evolution toward better reporting. - The Vision: Future State The goal is to achieve integrated reporting systems with automated controls, real-time data access, and centralized ESG data models. This represents the ideal state where sustainability reporting becomes as robust as financial reporting. - Technology as the Enabler: Success in this transformation requires a sophisticated technology infrastructure: - Cloud-based applications managing ESG data - Robust validation systems ensuring data quality - Seamless integration with business processes - Comprehensive compliance frameworks :)