Research Topics in Complex Systems

The Adaptive Complex Enterprise framework presented provides a basis for integrating many related areas of research into a services discipline. We have shown the framework is widely applicable to any kind of organization. Here our focus is on the articulation of further research needed for the IT-enabled business innovation, resilience and effectiveness. At a high level, see Figure 1, the related research topics are 1) ACE Co-engineering Theory which covers the development of context- based methods for the conceptualization, prioritization, and implementation of service-oriented solutions; 2) Knowledge Infrastructure for delivery of services, 3) Integrated Development Environment for service life-cycle management and continuous improvement of highly distributed complex systems, and 4) Transformation and Innovation Practice. While it is true that technology research in emerging trends like bio-info-nano integration will increase in importance, there is also a fundamental realization that the management of complexity will itself become a critical area of research. This is especially true since other related IT trends like virtualization, miniaturization, and distribution will also increase the complexity of deployed systems. Here we will explore the underlying challenges.

Co-Engineering Business Need and IT Services

Vertical traceability along the internal value chain illustrated in Figure 1 below allows us to establish a charge back system for the use of IT services. In addition the fine-grain Interaction approach to implementing chargeback also encourages the discipline needed for other initiatives like capacity management, audit procedures, and aligning of IT investments with business needs. How to achieve this alignment is the subject of this chapter.

Governance and Conceptual, Logical and Installed Architecture Alignment Using Work Products and Workflow

Governance and related alignment methods for the management of complex systems are introduced here to facilitate and better decision making. The goal here is to increase re-use and agility. We also show how EA governance can leverage technologies like middleware and workflow to enable service evolution. The methods and work products of the previous Chapter 2 along with the following EA layers guide continual service improvement.

Management, Monitoring, and Mining of Service Knowledge

There is consensus that explicit knowledge is information. In addition there is tacit knowledge that exists in the human minds. Tacit knowledge is applied unconsciously. It is a result of people \ Agents Interactions with each other and the environment. While explicit knowledge in the form of skills and competencies is normally acquired through training and Interaction, tacit knowledge is difficult to articulate. It is something that often cannot be expressed (Polyani 1966, Polyani 1996). Here we present various ways in which the creation and use of tacit knowledge can be assisted to become part of the Enterprise Knowledge Infrastructure to enable the BioS goals of the complex system.

Adaptive Complex Enterprise Framework

The ACE structure for coordination across various services using policies to meet overall goals is presented here. The more detailed depiction of the ACE structure in Figure 1 represents further details than in Figure 2, Chapter I. The structure includes the 1) BioS Stakeholders and Dimension, 2) the goal states of their interest, and 3) Agent Interactions that achieve those goal states. The Goal achievements are aggregated for continual improvement and used in decision-making to finetune Interactions. These underlying details are developed based on framework parts presented here. They include 1) Interaction ontology, 2) Modeling notation, 3) Principles for analysis, and 4) Work Products and their use in the continuous improvement. The result is goal-oriented ACE management by objectives at all BioS dimensions as we shall see.

Relating IT to Service Innovation

We explore how different types of opportunities for Interaction improvement - innovation, effectiveness, and resilience can be identified. Our goal here is to explore how an understanding of Interactions also helps identify opportunities for innovation and resilience. Previously we have already covered examples of IT use in Interaction effectiveness though Lean and Knowledge Management. Our focus here is on identifying opportunities through a systematic understanding of Innovation.

Strategic Improvement of Non-Routine Services

Organizations like the City are pressured to be more and more service oriented with fewer resources. The City has an expanding service area, fluctuating revenue, and a growing population that combine to place stress on existing response systems. The Mayor has instituted a “covenant” that includes a guiding principle that technology will be a key tool to achieve city objectives and improving service responses. To this end, the City consolidated its IT operations under Department of Technology (DoT) and began implementing a series of IT improvements. Looking to the future, the DoT wished to develop a plan more strategically aligned to the City departments that is DoT’s customer.

EA Knowledge for ACE Deployment

The knowledge infrastructure for enterprise architecture presented here has a taxonomy of useful patterns and pattern applications illustrated in Figure 1. The applications help deploy EKI and enable operations as illustrated herein. As emphasized previously, since the organization progresses towards more comprehensive or customer circumstance-based services, it becomes necessary to support many new types of Requests. From the business perspective, the underlying enterprise interoperability problem is typically stated as a requirement to produce an improved business result from services implemented in software tools. These include communication endpoints by which the systems can be considered to be components that will interact with each other and thereby form a new, integrated service capable of performing new functions. In turn, each system that contributes information or functionality is often required to expose new services. Thus, the trend is toward exposing more-and-more functionality from existing applications and using interoperability to compose these functions in different and new ways.

Co-Engineering IT Services for Lean Operations

The ACE structure is not only used to create BioS goals and work products, but also to perform the analysis needed to prioritize improvement projects and their tasks. We next show how the structure is used to define tasks and priorities to deploy in the context of existing enterprise systems and emerging technologies to reduce the time to install new PCs from seventeen days to one day. The related goals are met by quantifying the Interactions between global Lean and local Autonomic goals to achieve continuous improvement. Finally, we show here how a complex system ‘improves’ operationally through enhancements in a Role set that includes both Agents in the physical world and in the Electronic world. for related approaches to this also see Brittenham et al 2007a. We use the PC (personal computer) Build and Install service to illustrate methods for the improvement of underlying Interactions within a typical complex organization. This application was selected because it has the complex characteristics, yet it is representative and straightforward to understand. The techniques are widely applicable for the improvement of IT services and Primary services.