Competitive Pattern-Based Strategies under Complexity

This chapter augments current Enterprise Architecture (EA) frameworks to become pattern-based. The main motivation behind pattern-based EA is the support for strategic decisions based on the patterns prioritized in a country or industry. Thus, to validate the need for pattern-based EA, it is essential to show how different patterns gain priority under different contexts, such as industries. To this end, this chapter also reveals the value of alternative managerial strategies across different industries and business functions in a specific market, namely Turkey. Value perceptions for alternative managerial strategies were collected via survey, and the values for strategies were analyzed through the rigorous application of statistical techniques. Then, evidence was searched and obtained from business literature that support or refute the statistically supported hypothesis. The results obtained through statistical analysis are typically confirmed with reports of real world cases in the business literature. Results suggest that Turkish firms differ significantly in the way they value different managerial strategies. There also exist differences based on industries and business functions. The study provides guidelines to managers in Turkey, an emerging country, on which strategies are valued most in their industries. This way, managers can have a better understanding of their competitors and business environment and can develop the appropriate pattern-based EA to cope with complexity and succeed in the market.

Enterprise Architecture of Sustainable Development

The Outcome Document of the recent international diplomatic conference on sustainable development, Rio+20, portrays it as a multi-stakeholder process aimed at increasing the wellbeing of present and future generations in a dynamic, inclusive, equitable, safe, lasting, and environmentally balanced fashion, emphasizing that it should lead to poverty eradication, social development, the protection of all human rights and the elimination of human-provoked damage to the natural environment and resource-base. This reflects a highly complex process. Whereas the wording of its features and purposes exhibits considerable progress in the international policy dialogue, it appears that, among analysts, policy-makers, and practitioners around the world, there could be still large dispersion in the precise understanding of many underlying notions, the main issues, and their interrelationships. Consequently, there is not yet enough clarity among all stakeholders as to how to proceed on the implementation of coherent and coordinated strategies and policies for sustainable development. This chapter presents an analytical framework to look at these matters from a systemic perspective, with the intention of inspiring non-specialists to consider the advantages of the Enterprise Architecture approach to generate more clarity, facilitate communication, enhance policy coherence, and foster cooperation and partnerships for improving sustainable development. Some practical uses of the systems approach to enhance strategy, organization, and management for sustainable development are suggested.

A Theory for Enterprise Coherence Governance

In this chapter, the authors pose a theory for the governance of enterprise coherence. The proposed theory consists of three key ingredients: an Enterprise Coherence-governance Assessment (ECA), an Enterprise Coherence Framework (ECF), and an Enterprise Coherence Governance (ECG) approach. The ECA provides an explicit indication of the degree at which an organisation governs its coherence, while also providing a base to achieve a shared understanding of the level of coherence, and actions needed to improve it. The ECF is a practice-based framework that enables enterprises to make the coherence between key aspects, such as business, finance, culture, IT, etc. explicit. The ECG approach offers the instruments to guard/improve the level of coherence in enterprises during transformations. An important trigger to develop this new theory was the observation that many transformation projects fail. These failures even included projects that used an explicit enterprise architecture to steer the transformation. The theory was developed as part of the GEA (General Enterprise Architecting) research programme, involving twenty client organizations. Based on a survey of the possible causes for the project failures, the requirements for the research programme are identified. In developing the theory on enterprise coherence, the following hypothesis is used as a starting point: the overall performance of an enterprise is positively influenced by a strong coherence among the key aspects of the enterprise, including business processes, organizational culture, product portfolio, human resources, information systems, IT support, etc. The research programme uses a combination of design science-based iterations and case study-based research to develop and iterate the theory for enterprise coherence governance. In this chapter, the authors also discuss one of the conducted (real world) case studies, showing the application of the enterprise coherence theory.

Enterprise-in-Environment Adaptation

Enterprise Architecture (EA) is a consulting practice and discipline intended to improve the management and functioning of complex organizations. The various approaches to EA can be classified by how they define what is to be architected and what, as a result, is the relevant environment. Traditionally, management has been understood as “Planning, Organizing, Command, Coordinating, and Controlling” (POCCC), that is, the role is bounded within the organization. The corresponding EA approach suggests architecting IT systems to support management, with the implicit environment being members of the organization as well as partner organizations. As the objective of EA practice expands to include organizational members, technical systems, and a wider set of stakeholders, so too does the complexity it must address. This results in an enlarged domain of issues and concerns. Finally, if the objective of EA is a sustainable enterprise, then physical, societal, and ecological environments radically increase the complexity of actualizing this goal. Corresponding to this increase in scope is a parallel shift in the scope of management concerns. With the goal of pushing EA towards concerns regarding enterprise sustainability, an open socio-technical system design perspective of EA, which we have named Enterprise-in-Environment Adaptation (EiEA), is discussed. EiEA offers a comprehensive approach to respond to the demands for complexity management that arise when working towards enterprise sustainability; yet, it requires that organisations also embrace deep culture changes, such as participative design, worker empowerment, as well as shared accountability and responsibility, to name a few.

Systemic Enterprise Architecture as Future

Governments are changing by design, necessity, and compulsion. This change is being exacerbated and shaped by megaforces that interact in a complex labyrinth of evolving nodes and connections. As a result, today’s government leaders and policy makers operate in a realm of confounding uncertainties and astounding complexities. These lead to incomplete and often non-actionable information that make decisions increasingly speculative. To unlock the grid and move forward, it is acknowledged that governments of the future have to be connected. Connected government is no utopia. It is simply a pragmatic approach to capitalize on complexity. Enterprise Architecture (EA) as a meta-discipline provides governments and leaders the means to address the twin challenges of dynamism and complexity. As governments become increasingly hyper-connected, they ought to be examined as systems, where holism, causality, heterarchy, and interrelationships are crucial to ensuring overall coherence in a state of omnipresent flux. This contrasts with the traditional fixation on efficiency and cost. Going beyond the rhetoric, this chapter demonstrates the value of amalgamating the systems approach within the EA methodology to address a national priority in Singapore, and provides insights to amplify the impact of EA by integrating creative thinking to tackle complex problems.

Navigating Complexity with Enterprise Architecture Management

Enterprises are like living creatures in the ecosystem – there are vast varieties of species; each individual in any species is unique, complex, dynamic, and constantly interacting with its ever-changing environment. Also, like living creatures, enterprises have many commonalities. These commonalities exist in all enterprises, regardless of their business, size, environment, culture, lifecycle stage, or any other factor. Enterprise Architecture (EA) management helps enterprises discover their commonalities, adopt best practices to manage the commonalities, and apply holistic and systemic approaches to tackling unique complexity encountered by enterprises. This chapter extracts thinking from many thought leaders in the EA discipline and consolidates a dynamic and multi-dimensional alignment approach to managing an enterprise’s architecture as a living system. This integrated approach utilizes the “Fractal” concept in Chaos Theory and identifies six common alignment dimensions in enterprises. This approach includes dynamic alignment mechanisms to help enterprises navigate the increasingly complex and ever-changing world. This approach bridges individual alignments with enterprise optimization. A fictional example of a disaster relief operation is used to illustrate how the EA approach could help a relief enterprise navigate through the complexity and dynamics of the disaster relief operation to achieve life-saving results.

Transitioning to Government Shared Services Centres

Services are fundamental to the provisioning of business activities. Enterprise Architecture (EA) is maintaining the relationship between strategy, business, and technology. A clear definition and agreed understanding of services is critical to realising information technology artefacts. Services, however, tend to be more complex than the mere act of interaction or working processes, and should be seen out of the cultural, organisational, and managerial factors surrounding them. This chapter uses a service model consisting of execution, context, and intention with an underlying claim that all three elements must be present to make services meaningful. EA must be seen in the light of this. This chapter addresses the issues related to combined transformation of organisations, service systems, and consequently, EA. The transformation changes loosely coupled, distributed organisations into Shared Service Centres (SSCs). A case study of a far-reaching SSC transformation from Denmark is presented where eGovernment services are moved from local government level into a national SSC structure referred to as Udbetaling Danmark (lit. PayDK). Major findings include: (1) When eGovernment reaches a certain level of maturity, it dissolves its original reason and no longer follows a progressive maturity model. Instead, it leads to a more radical reorganisation emphasising operational efficiency. (2) Development and management of complexities and uncertainties in governmental administrative services are closely associated with the development of eGovernment through ongoing refinement of EA and service frameworks. (3) The policy-driven reshaping of governmental services, originally themselves being SSCs, can lead to iterative SSC formations, each seeking to establish a professional logic of its own. (4) The systemic perception connected to EA and service science provides valuable insight into service transformation before, during, and after the transformation. This chapter aims at a deeper understanding and discussion of services in developing eGovernment policies and architectures, but findings are readily applicable in general business environments.

Federated Enterprise Architecture

The purpose of the chapter is to provide clarity on what a Federated Enterprise Architecture (FEA) is and what the benefits as well as risks are in contrast to a non-federated enterprise architecture. The chapter draws upon organizational theory, federalist theory, and case studies to explicate what constitutes a federated model and the expected federated EA benefits. There are a number of challenges with the concept of a FEA. Two are focused on in this chapter: the meaning of federated EA and associated benefits and risks. The first is the use of the term “federated,” which occurs rather frequently in ICT literature, such as “federated search” or “federated database design,” and in the context of IT governance, “federal model” in Drs. Weill and Ross’s book IT Governance. The term also appears in the non-ICT context such as “federated insurance.” However, the term “federated” is frequently not defined and when defined speaks to a decentralization concept. This distinction is relevant to the understanding and success of a federated EA implementation. In reviewing federalist theory, there is a clear difference between decentralization and federalism. It is argued that the so-called federal or federated “model,” as described, is not federated but is a form of decentralization. The second challenge within the EA discipline is the lack of benefits attributed to a FEA. In the few sources that exist for FEA benefits are either not stated or the stated benefits could equally apply to a non-FEA. It is argued that scalability is the singular key benefit that FEA provides over a non-FEA, and the following non-FEA benefits are enhanced: 1) agility and IT innovation, 2) process consolidation and business process standardization and discipline, and 3) interoperability. However, while there are clear benefits to FEA, there are inherent risks.

Complex Adaptive Systems Thinking Approach to Enterprise Architecture

Complex systems interact with an environment where a high degree of uncertainty exists. To reduce uncertainty, enterprises (should) create intelligence. This chapter shows that intelligence has two purposes: first, to increase and to assess (thus to correct) existing knowledge, and second, to support decision making by reducing uncertainty. The chapter discusses complex adaptive systems. Enterprises are not only complex systems; they are also most of the time dynamic because they have to adapt their goals, means, and structure to survive in the fast evolving (and thus unstable) environment. Crucial for enterprises is to know the context/ecology in which they act and operate. The Cynefin framework makes the organization and/or its parts aware of the possible contexts of the organization and/or its parts: simple, complicated, complex, chaotic, or disordered. It is crucial for the success of implementing and using EA that EA is adapted to function in an environment of perpetual change. To realize this, the chapter proposes and elaborates a new concept of EA, namely Complex Adaptive Systems Thinking – Enterprise Architecture (CAST-EA).

Enterprise Architecture’s Identity Crisis

This chapter outlines the rational foundations of the enterprise architecture discipline to date and describes ways and situations in which the traditional approaches of enterprise architecture fail to account for a number of contemporary market and economic situations and organizational behaviors. It characterizes new methods and approaches loosely based on systems thinking, with examples from the Australian e-government experience, and argues that the discipline must re-invent itself to incorporate a post-rational perspective to stay relevant. The chapter concludes with narratives of how the new enterprise architecture must engage with business to stay relevant over the next decade and beyond.