The TOGAF Architecture Development Method, usually shortened to the ADM, gives enterprise architects a structured way to move from business drivers and stakeholder concerns to target architectures, transition plans, implementation governance, and continuing change. The current TOGAF Enterprise Architecture Practitioner path based on the TOGAF Standard, 10th Edition focuses on applying that method rather than treating the phases as a sequence to memorize.
The ADM is iterative. Architecture work can revisit earlier decisions when new requirements, constraints, risks, or implementation findings appear. It can also be tailored to the organization’s governance, delivery model, industry, and scope. That flexibility is important because an enterprise transformation, a product-platform redesign, and a focused application modernization effort do not need identical documentation or decision forums.
What remains consistent is the logic: establish capability and principles, define the architecture vision, develop business, information-systems, and technology views, identify solutions and migration choices, govern implementation, and manage architectural change. The method creates traceability between those activities so that an architecture does not become a collection of disconnected diagrams.
Prepare the architecture capability before the first project
The Preliminary work around the ADM establishes how architecture will be practiced. Organizations need principles, governance, roles, methods, tools, repositories, decision rights, and relationships with delivery and portfolio management. Without this capability, each initiative invents its own architecture process and important decisions become dependent on individual architects rather than on an institutional standard.
Tailoring belongs here. Decide which artifacts are mandatory, how approvals work, how architecture integrates with agile or product delivery, what level of detail is appropriate for different change types, and how reusable standards are maintained. Tailoring should reduce unnecessary ceremony while preserving the evidence needed for good decisions.
Architecture principles should be few enough to guide tradeoffs. Principles such as reuse before buy before build, data ownership, security by design, API-first integration, or cloud portability can help teams decide between alternatives, but only if the organization understands when exceptions are allowed. A principle that never changes a decision is merely a slogan.
The current TOGAF Enterprise Architecture Foundation provides the conceptual vocabulary behind this capability. Practitioners then need to apply that vocabulary to real governance, stakeholder, requirements, and transformation problems rather than treating framework terminology as the objective.
Establishing an architecture repository is also part of making the method reusable. Standards, reference architectures, principles, approved technology patterns, decision records, and prior transition lessons should be easy to discover. Reuse does not mean copying an old target into a new problem; it means beginning with institutional knowledge instead of rediscovering settled constraints and proven patterns in every engagement.
Use Phase A to define value, scope, and authority
Architecture Vision work establishes why the effort exists and what success means. Identify sponsors, stakeholders, concerns, business outcomes, scope boundaries, constraints, assumptions, and the initial view of the target. The vision should be specific enough to guide the team but not so detailed that it preempts the analysis that later phases are intended to perform.
Stakeholder analysis is central. Executives may care about investment and strategic outcomes; operations may care about reliability and supportability; security may care about control and risk; product teams may care about delivery speed; regulators may care about evidence and compliance. The architecture must make these concerns visible because many later tradeoffs are really conflicts between stakeholder priorities.
Define the scope across breadth, depth, time, and organizational boundaries. An architecture can cover one capability or a whole enterprise, be conceptual or detailed, focus on a single transition or a multi-year roadmap, and include internal or partner domains. Scope should be justified by the decision the architecture needs to support.
Phase A should also establish approval and working agreements. Clarify who can accept risk, who owns requirements, what governance body will resolve disputes, and how major changes to scope will be controlled. Architecture work loses authority when teams discover late that the people making implementation decisions were never part of the engagement.
Agree on the level of architecture evidence expected at the outset. A small change may need a concise set of views and decisions, while a regulated multi-year transformation may require formal baselines, target states, roadmaps, and conformance records. Proportionality keeps governance credible because teams can see that documentation effort follows risk and decision complexity.
Develop the business architecture before choosing technology
Phase B focuses on the business architecture: capabilities, value streams, organization, processes, information needs, services, and other business structures relevant to the change. This prevents the target from becoming a technology solution in search of a business problem. A cloud migration, ERP program, or data platform initiative still needs to explain which business outcomes improve and which operating model changes are required.
Use baseline and target views selectively. The baseline should be detailed enough to explain the constraints and gaps that matter. Modeling every current process can consume months without changing a decision. The target should describe the future business behavior that technology must enable, including ownership and accountability changes that cannot be solved by systems alone.
Gap analysis compares baseline and target to identify what must be created, changed, retained, or removed. Gaps can include capabilities, roles, processes, information, policies, and governance as well as applications and infrastructure. This makes later work packages more complete because organizational change appears beside technical delivery.
Business transformation often requires deliberate change management. Training, communications, incentives, operating procedures, and ownership may be essential architecture dependencies. Recording them early keeps the target from assuming that people and processes will automatically adapt after a technology deployment.
Shape data and application architecture as connected systems
Phase C addresses information-systems architecture, commonly including data and application architecture. Data architecture considers entities, ownership, lifecycle, quality, integration, security, and the structures needed to support business capabilities. Application architecture considers the systems and services that create, consume, transform, and expose that data.
Do not design the two independently. A target application portfolio that ignores authoritative data sources creates duplicated records and reconciliation problems. A data model that ignores how applications actually use information can become academically clean but operationally impractical. Trace business information needs into both data and application decisions.
Identify systems of record, systems of engagement, integration patterns, shared services, and boundaries where responsibilities change. Rationalization may reveal applications that should be consolidated, retired, replaced, or wrapped. The architecture should explain why a system remains rather than assuming every current application deserves a place in the target.
Nonfunctional requirements are especially important here. Availability, privacy, retention, performance, residency, integration latency, recoverability, and security can change the architecture dramatically. Keep these requirements tied to business concerns so teams understand why a particular data or application pattern is necessary.
Use technology architecture to support the required qualities
Phase D develops the technology architecture: infrastructure services, platforms, networks, runtime environments, identity, security, observability, automation, and other technical foundations needed by the target. The objective is not to list products. It is to define the technology capabilities and standards that make the business, data, and application architecture feasible.
Translate quality requirements into design choices. If the business requires a short recovery time, the architecture may need regional redundancy, replicated data, tested recovery automation, and operational staffing. If latency is critical, network placement and data locality become architectural concerns. If regulated data must remain in a jurisdiction, location and service-selection rules must be explicit.
Architecture should expose constraints and tradeoffs. A highly available design may cost more and be harder to operate. A standardized platform can reduce complexity but limit specialized features. A managed service may reduce operational burden while increasing provider dependency. Document these choices in terms stakeholders can evaluate.
Resilience decisions can be connected to a broader business continuity and disaster recovery strategy. Architecture is stronger when recovery targets, dependencies, people, facilities, and technology are considered together rather than when “DR” is added to an infrastructure diagram at the end.
Turn gaps into solution building blocks in Phase E
Opportunities and Solutions work combines the gaps from earlier phases into candidate work packages and transition architectures. This is the point where the architecture begins to become an executable transformation rather than a target-state description. Group changes that belong together technically, organizationally, or economically.
Identify dependencies between work packages. An application migration may depend on identity modernization, network connectivity, data cleansing, or a new operating model. A transition architecture may be necessary when the final target cannot be reached in one step. These intermediate states should be treated as real architectures because organizations can operate in them for months or years.
Consider implementation options without prematurely turning the architecture into a procurement specification. Build, buy, reuse, retire, rehost, replatform, refactor, or partner decisions should be evaluated against requirements, principles, risk, cost, capability, and time. Architecture provides the criteria that let decision makers compare those options coherently.
Record risks and assumptions as first-class information. A simple risk register can help track uncertainty about funding, skills, vendor capability, migration complexity, data quality, or regulatory approval. Assumptions that prove false often drive more redesign than technical errors.
Sequence change realistically in Migration Planning
Phase F develops the implementation and migration plan. Prioritize work packages by value, dependency, risk, cost, urgency, and organizational capacity. A roadmap should show not only what happens first but why the sequence is credible. If every initiative is listed as high priority, the architecture has not helped the organization choose.
Evaluate transition states for operational viability. A program may need coexistence between old and new applications, temporary integrations, duplicated data flows, or staged user migration. Those states create cost and risk that should be visible in the roadmap. The shortest theoretical path is not always the safest executable path.
Coordinate architecture planning with portfolio and delivery management. Funding cycles, product roadmaps, procurement lead times, regulatory deadlines, and team capacity can constrain the plan. The architecture should influence those decisions while remaining grounded in what the organization can actually deliver.
Define measurable outcomes for major transitions. A milestone such as “data platform complete” is weaker than an outcome such as “three priority domains use governed authoritative data products and retire duplicate feeds.” Measures make it possible to determine whether implementation is moving the enterprise toward the target architecture.
Govern implementation without freezing the design
Phase G connects architecture to delivery through implementation governance. Architecture contracts, conformance reviews, design decisions, standards, and exception processes help ensure that projects remain aligned with agreed outcomes. Governance should focus on material deviations rather than becoming a gate for every engineering choice.
Delivery teams need room to learn. A detailed design may discover constraints that were not visible during architecture work. The right response is not automatic rejection or silent divergence; it is a controlled decision that considers the requirement, design alternative, risk, and effect on the target architecture.
Keep the architecture repository current with decisions that have enterprise value. Reusable patterns, accepted exceptions, technology standards, reference architectures, and lessons from implementation should inform later initiatives. Otherwise every project repeats the same analysis and the architecture function becomes detached from delivery reality.
Architecture governance works best when architects are available during implementation rather than only at review meetings. Early collaboration can resolve a design issue in hours; late conformance review can turn the same issue into rework, delay, or a permanent exception.
Architecture decisions should also have explicit traceability to the concerns they resolve. A decision log can record the alternatives considered, the selected option, the principle or requirement that drove it, and the consequences that stakeholders accepted. This is especially valuable when a later team questions why a seemingly simpler technology was rejected. Without decision traceability, organizations tend to repeat old debates and sometimes reintroduce a risk that was already understood.
Use architecture views to communicate, not to maximize modeling coverage. A capability map may help executives understand investment priorities, a data-flow view may expose privacy and integration issues, and a deployment view may help engineers reason about resilience. The same underlying architecture can be represented differently for different concerns. Modeling detail should be justified by a decision, review, or implementation need.
Manage architectural change as a continuous cycle
Phase H monitors whether the architecture still fits the enterprise. Strategy changes, acquisitions, regulations, product evolution, technical debt, vendor roadmaps, security threats, and delivery findings can all justify a change. The organization needs criteria for deciding whether to make a small controlled update, initiate a new ADM cycle, or revisit the broader target.
Requirements management operates across the ADM rather than as a final phase. Requirements are identified, traced, prioritized, changed, and validated throughout the cycle. When a requirement changes, architects should be able to see which business, data, application, technology, or roadmap decisions are affected.
Do not measure architecture only by documents produced. Useful outcomes include fewer duplicated capabilities, clearer standards, faster decisions, reduced integration complexity, better alignment between investment and strategy, improved resilience, and controlled technology risk. Those outcomes demonstrate whether the method is helping the enterprise change deliberately.
The Open Group certifications provide the formal learning context, but the practical value of the ADM comes from disciplined iteration. It gives architects a shared way to connect stakeholder concerns to requirements, requirements to architectures, architectures to work packages, and implementation evidence back to future change. That traceability is more important than following the phases as a rigid waterfall.