Enterprise architecture is about business outcomes, value assessment, definition and realization through effective delivery and deployment. It covers many aspects overlapping with ITSM practices in terms of services management and operations, though not limited to technology management.
Per the ITIL framework, ITSM best practices are grouped in 5 core perspectives:
- Service strategy
- Service design
- Service transition
- Service operation
- Continuous service improvement
First and foremost, enterprise architecture is about forward-looking and continuous business alignment, towards effective data governance and business transformation.
Enterprise architecture: driving how data contributes to value creation
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.
Data governance fosters effective and efficient process usage and delivery management
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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Building and continuously aligning the operating model is a mandatory exercise to maximise effectiveness and embed continuous learning and improvement, considering the required adjustments to design, build, test, and deploy the solution and associated change:
- Delivery model: what is the solution and associated service, how they will be packaged and delivered?
- Engagement model: how will the team engage with the business and IT stakeholders to deliver the solution?
- Commercial model: how much is the solution proposed for and will be the total cost of ownership, and how products and services are commercially bundled?