Enterprise architecture focuses on achieving business outcomes and value realization through effective solution definition and deployment. It encompasses various aspects, including services management and operations, but is not limited to technology management.
In alignment with the ITIL framework, ITSM best practices are classified into five core perspectives:
- Service strategy
- Service design
- Service transition
- Service operation
- Continuous service improvement
At its core, enterprise architecture is about continuous business alignment and forward-looking planning towards effective data governance and business transformation.
Enterprise architecture: driving how data create value
Nightingale (2009) introduced the 7 principles of enterprise architecture thinking to guide organizations towards achieving sustainable transformation:
- Adopt a holistic approach to enterprise transformation
- Identify relevant stakeholders and determine their value propositions
- Focus on enterprise effectiveness before efficiency
- Address internal and external enterprise interdependencies
- Ensure stability and flow within and across the enterprise
- Cultivate leadership to support and drive enterprise behaviors
- Emphasize organizational learning
Enterprise architecture principle: focus on effectiveness before efficiency.
Effective data governance fosters better ways of working
Enterprise architecture: 9-block value grid
Performing product development and operational maturity assessment, identifying opportunities for improvement, critical success factors and associated metrics
Building capability and enterprise data alignment with stakeholder map, defining and driving data governance, managing capability implications across business functions
Defining value statements based on expected change, aligning digitalisation and integration roadmaps, from education to data migration, archiving and decommissioning strategies
Building the business value realisation strategy, linking to the capability implementation roadmap to address current and future imperatives, pain point and risk mitigations
Master Data Strategy
Driving single source and single version of truth clarity, identifying configuration items, building data continuity and linkages across enterprise platforms and system interfaces
Assessing how the business operates, internally across teams and with the supply chain, defining how the change will affect current operations and how value will be realised
Defining product modularity, driving platformisation, mapping business processes and capabilities, improving knowledge capitalisation and standardisation and talent development
Understanding capability and improvement requirements, mapping user stories and business processes across functions, defining change roadmaps and deployment strategies
Assessing change assumptions and interdependencies, mapping prioritization decisions, building awareness, initiating transformation governance and tracking effectiveness
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To maximize effectiveness and embed continuous learning and improvement, it is essential to build and continuously align the operating model. This involves considering the following questions in relation to the solution design, build, test, and deployment, as well as associated changes:
- Delivery model: What is the proposed solution and associated service? How will they be packaged and delivered?
- Engagement model: How will the team engage with business and IT stakeholders to deliver the solution?
- Commercial model: How much will the solution cost, and what will be the total cost of ownership? How are products and services commercially bundled?