The term Enterprise Architecture (EA) is appearing more frequently in boardrooms and IT roadmaps, yet even within Japanese manufacturing companies, many IT departments still lack a structured understanding of what EA actually entails. As someone working in an EA role and supporting Japanese manufacturers with EA proposals and guidance, I continue to see a significant gap between the promise of EA and how it is practiced on the ground.
In this article, I will unpack the essence of EA based on TOGAF from three angles, with a focus on practical application in manufacturing and large enterprises:
In a follow‑up article, I will connect these concepts to “EA Methodology in SAP” and discuss how to apply EA on SAP‑centric landscapes in real projects.
TOGAF defines Enterprise Architecture as a structured approach for designing and governing an organization’s business and IT with consistent structures, principles, and roadmaps, in order to systematically define and manage “how the enterprise creates value.” Two points are critical here for practitioners:
Even the most compelling business initiatives fail to scale if the required IT capabilities are missing; organizations are forced into manual workarounds, struggle to keep pace with market and customer change, and eventually erode their competitive edge.
On the other hand, trying to roll out every strategic initiative company‑wide at once leads to massive up‑front investments, rising risk and governance overhead, and longer lead times before tangible results appear.
TOGAF addresses these challenges by recommending smaller, incremental execution units and an iterative approach to planning and governance rather than one‑shot, big‑bang designs.
EA is therefore not a one‑time architecture blueprint, but an ongoing capability to evolve the enterprise structure in a controlled and repeatable way.
When asked to “design the architecture of the entire enterprise,” many organizations struggle to know where to start.
TOGAF tackles this by splitting EA into four architecture domains and defining a consistent development approach across them:
By designing and managing these four domains together, enterprises can maintain end‑to‑end traceability from strategy through business processes and systems down to infrastructure (“strategy → process → system → infrastructure”).
At a practical level, EA work typically follows these high‑level steps:
TOGAF structures these steps as an iterative process called the Architecture Development Method (ADM).
The next section outlines what makes ADM particularly powerful in real‑world EA work.
At the heart of TOGAF is the Architecture Development Method (ADM), an iterative cycle that defines how to design and update EA over time. The main ADM phases are:
Excerpt and edited from the TOGAF website The Open Group Architecture Framework Version 8.1.1 ADM Reference
By continuously cycling through these phases, ADM embeds EA into the organization as an ongoing capability instead of a one‑off project. Among the many elements of ADM, three areas are especially critical in practice:
Even when TO‑BE architectures are well designed, EA remains a “paper tiger” if execution responsibilities and decision rights are unclear.
To avoid ending up with broad conceptual agreement but no concrete action (“everyone agrees in principle, but nobody owns the specifics”), it is essential to design stakeholder roles and governance structures in the early phases of EA.
For each improvement domain and initiative, EA must clarify how value will be generated and in what sequence. Without top management involvement and explicit approval of priorities, initiatives rarely move beyond the slide deck, especially given limited investment capacity; EA should make transparent “where to start and in what order to harvest benefits.”
If organizations complete only the first ADM cycle and stop updating EA as conditions change, their architecture quickly diverges from reality.
This reduces the effectiveness of planned initiatives and increases the risk of misaligned investments; by continuously revisiting EA in response to market and customer dynamics, organizations can keep executing context‑appropriate initiatives over time.
Beyond ADM, TOGAF defines several components that support day‑to‑day EA work. Key elements include:
These components ensure EA is not just a set of diagrams but an organizational capability that can be defined, executed, and governed consistently. I will break each of these down in more detail in separate, dedicated articles.
Put simply, the value of EA and TOGAF lies in “closing the gap between business strategy and IT, and building an enterprise structure that can adapt to continuous change.” Representative benefits include:new.
The latest TOGAF standard (including the TOGAF Standard, 10th Edition) positions EA as an enabler of the “agile enterprise.” Here, “agile enterprise” does not only refer to agile development practices such as sprints, but to an organization that can continuously design, deliver, and evolve its enterprise architecture in small increments.
TOGAF guides organizations to break down strategic, segment, and capability architectures into manageable units and deliver them iteratively—often aligned to agile delivery cycles—so that enterprises can respond quickly to business change while preserving overall coherence. From this, it is clear that both speed of response and sustainability of change are at the core of EA’s intent.
TOGAF uses the term “enterprise agility” to describe a target state in which organizations become more customer‑ and product‑centric, more efficient, and more compliant while simultaneously increasing their ability to respond to change. TOGAF highlights the following characteristics of enterprise agility:
The final point—“Respect for people”—captures a key philosophical aspect of TOGAF that often resonates strongly with practitioners: enterprise architecture is not only about technology and processes, but also about creating an environment where people can contribute and adapt effectively.
In recent years, a growing number of vendors have introduced tools to support EA practices. SAP, for example, acquired LeanIX—a leader in enterprise architecture management (EAM)—and now offers it as a core platform for managing EA across complex landscapes.
Without a dedicated EA platform and relying instead on manual approaches (for example, spreadsheets and slide decks), organizations quickly encounter issues such as:leanix+1
Because governance and continuity are the keys to successful EA, IT tools that enable systematic, long‑term management of EA information have become essential. I will cover concrete usage patterns and integration with SAP and other platforms in a future article.
EA is gaining renewed attention because digital transformation, cloud adoption, AI initiatives, and legacy modernization are all happening simultaneously, making it essential to design and govern business and IT as an integrated whole. Below are six particularly important perspectives.
Fragmented, department‑level DX initiatives are no longer sufficient; enterprises must design and prioritize transformations across the entire portfolio. EA visualizes strategy, processes, applications, data, and infrastructure in a single blueprint and makes it explainable “what to invest in, and in what order.”
Multi‑cloud, SaaS, and API‑driven integration have turned application landscapes into living, evolving organisms; uncoordinated adoption leads to silos and technical debt. EA uses standard architectures and reference models to guide cloud/SaaS selection and integration patterns, thereby controlling complexity and cost.
Replacing core systems in a single big‑bang is risky; most enterprises now seek stepwise modernization that keeps legacy systems running while moving toward target architectures. EA supports this by inventorying current assets, analyzing dependencies, designing target architectures, and defining migration steps that bridge legacy and modern platforms.
Proof‑of‑concepts for generative AI and analytics have become easy to spin up, but scaling them safely and with proper governance remains a major challenge. EA designs the supporting data architecture, model deployment patterns, responsibility boundaries, and risk management structures required to upgrade AI from one‑off experiments to sustained enterprise capabilities.
Recent studies and case examples show that EA is increasingly recognized not just as an IT control function but as a strategic driver of growth and innovation. With AI‑enabled scenario planning and digital twin capabilities embedded in EA tools, EA is starting to accelerate both the speed and quality of executive decision‑making.
Supply chain disruptions, regulatory tightening, and cyber risks are amplifying threats to business continuity. EA clarifies which processes, systems, and data are critical, what alternatives and recovery patterns exist, and provides the foundation for designing resilient enterprise structures.new.
This article has explored Enterprise Architecture (EA) and TOGAF with a focus on how they help organizations become more resilient to change:
In the next EA article, I will introduce real‑world EA examples and discuss how SAP’s EA Methodology relates to TOGAF, with a focus on turning “EA as theory” into “EA you can actually use on the ground.”
For more insights on SAP, please also check out the following articles:
•LieberLieber Software: Volkswagen accelerates with Enterprise Architect
Volkswagen accelerates with Enterprise Architect < LieberLieber
•Enterprise Architecture in Toyota Automotive
Enterprise Architecture in Toyota Automotive | PDF | Enterprise Architecture | Business
•The new shape of IT at Volkswagen
A program of change for Volkswagen Group IT | Article | Automotive Manufacturing Solutions
•Vintage – Architecture On Demand’s Post
Building a Mature Enterprise Architecture Practice: The Toyota Story | Vintage – Architecture On Demand
•Group Management Report
Information Technology – Volkswagen Group Annual Report 2024
•Volkswagen’s digital transformation gathers speed
Volkswagen’s digital transformation gathers speed | Volkswagen Newsroom
•How EA benefits Volkswagen of America: a case study
How EA benefits Volkswagen of America: a case study | Samuel Holcman posted on the topic | LinkedIn
•CARIAD’s Unified Data Platform: A Data Streaming Automotive Success Story Behind Volkswagen’s Software-Defined Vehicles
CARIAD’s Unified Data Platform: A Data Streaming Automotive Success Story Behind Volkswagen’s Software-Defined Vehicles – Kai Waehner
•Toyota accelerates digital transformation with SAP S/4HANA upgrades
Toyota accelerates digital transformation
•Toyota shifts into overdrive: Developing an AI platform for enhanced manufacturing efficiency
How Toyota is revolutionizing manufacturing with AI | Google Cloud Blog
•The Value of Enterprise Architecture by Tony Brown
Admiral.doc
•Toyota Credit Canada Inc.
Toyota Credit Canada Case Study
•The Toyota bZ4X was the best-selling car in Norway for October
The Toyota bZ4X was the best-selling car in Norway for October : r/electricvehicles
•トヨタの成長を支えるITの革新
トヨタの成長を支えるITの革新:手本はクルマの開発(1/3 ページ) – ITmedia エンタープライズ
•トヨタvs中国EV】競争軸は「知能化」へ/トヨタも中国EVも勝ち組/2035年の世界シェア/中国EVの4分類/BYDの苦難とジーリーの躍進/ファーウェイの戦略/
(6) 【トヨタvs中国EV】競争軸は「知能化」へ/トヨタも中国EVも勝ち組/2035年の世界シェア/中国EVの4分類/BYDの苦難とジーリーの躍進/ファーウェイの戦略/トヨタの「中国版マルチパスウェイ」 – YouTube
•過去の遺産は食いつぶすためにある? 自社の名車を現代に蘇らせたメーカーたちの狂宴
過去の遺産は食いつぶすためにある? 自社の名車を現代に蘇らせたメーカーたちの狂宴 | トップギア・ジャパン Top Gear JAPAN
•続・トヨタが取り組むサーキュラーエコノミーとは?
TTR_Vol70-2_J.pdf
•TOYODA GOSEI 特集:様変わりする車社会を支える製品開発
vol.59.pdf
Parts of this article were developed with reference to generative AI suggestions and were reviewed, refined, and supplemented based on the author’s professional expertise and judgment.
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