Wardley Maps offer a powerful way to analyse a business's competitive landscape, value chain, and the evolution of its components — but most Enterprise Architecture frameworks have not formally incorporated them. This paper examines how Wardley Mapping complements EA methods, proposes a meta model integration using the Inspired Holistic Architecture Language (HAL), and demonstrates practical benefits including reduced effort, improved model fidelity, and richer strategic insight. A useful read for enterprise architects and business architects looking to bring greater contextual awareness into their architecture practice.
An Integrated Meta Model for Strategy, Business Architecture, Risk and Change
Popular enterprise architecture frameworks like TOGAF and ArchiMate each provide meta models, but none are broad enough to fully support strategic planning, contextual analysis, and business architecture alongside risk, change, and programme management in an integrated way. This paper describes the development of HAL2023 — an updated version of the Inspired Holistic Architecture Language — synthesising concepts from TOGAF 10, ArchiMate 3.2, BizBOK 11, SABSA, MEMO, and the Inspired consulting practice into a single, coherent meta model validated across multiple industries. It addresses not only what the model contains, but how it can be practically applied without overwhelming practitioners.
A Business and Solution Building Block Approach to EA Project Planning
Enterprise architecture programmes frequently struggle with scope confusion, misaligned stakeholder expectations, and poor traceability between business requirements and delivery plans. This paper presents a building block approach — distinguishing Business Building Blocks (capabilities) from Solution Building Blocks (systems and technologies) — developed and validated on a multi-project transformation programme at a rapidly expanding South African telecoms company. The result was dramatically improved communication between sponsors, stakeholders, programme managers, and development teams, and a shared, navigable picture of what would be delivered, when, and in what sequence.
An Inspired Approach to Business Architecture
Most enterprise architecture frameworks treat business architecture as little more than context for IT decisions — leaving out competitors, markets, culture, partners, products, ethics, and organisational design. This white paper sets out Inspired's broader definition: the design of a desirable future state of the enterprise, informed by all its relevant dimensions and underpinned by a comprehensive, integrative meta model. It covers scope, techniques, method tailoring, the Holistic Architecture Language (HAL), and the tools and training that bring the approach to life.
Cooking up a MEAL: Creating a Meta Enterprise Architecture Language
Enterprise architecture tools struggle to interoperate, and existing exchange standards like XMI are notoriously unreliable in practice. This paper proposes MEAL — a Meta Enterprise Architecture Language — a human-readable, domain-specific language designed to define, populate, query, and analyse EA models and repositories, and to serve as a high-level API between tools. It presents the requirements, a prototype implementation in Smalltalk, and example syntax demonstrating the concept's practical promise.
Managing Large-Scale Collaborative Modelling: Meta Model Extensions for Enterprise Architecture Tools
As enterprise architecture initiatives grow to span multiple teams, geographies, and time zones, the repositories and tools supporting them face real challenges: information overload, ownership conflicts, version management, and the need to present different views to different user communities. This paper formalises a set of meta model and meta-meta model extensions — including context, domains, filters, versioning, and scenarios — developed through real-world deployment of a collaborative EA modelling platform. The result is a more manageable, flexible, and scalable foundation for large-scale collaborative architecture work.