Adaptive Enterprise Architecture for Digital Innovation and Transformation

-
Enterprise Architecture (EA) could be considered a descriptive and/or prescriptive design of an enterprise. Traditional approaches to EA heavily  focus on the modelling and documentation aspects and tend to overlook the actual stakeholders and their needs, in particular, when dealing with complex and large digital innovation and transformation.

This calls  for the need of an adaptive EA. Based on ISO/IEC/IEEE 42010:2011, an adaptive EA is the fundamental concepts or properties of an adaptive enterprise service system or ecosystem:

  • situated in its environment (e.g. political, economic, sociological, technological, legal and environmental), 
  • embodied in its elements (e.g. interaction, human, technology, facility), 
  • relationships (e.g. type and strength) to each other and its environment, and 
  • in the adaptive principles of its secure design and evolution.



The Gill Framework ® V4.0


Adaptive EA requires a fundamental shift the way currently organisations operate their EA capability for digital innovation and transformation. Adaptive EA design can be sliced and diced, and iteratively evolve for a particular context and situation to address the stakeholder needs.  This requires avoiding boiling the ocean of enterprise modelling for developing the strategy, architecture and roadmaps for digital innovation and transformation. Instead of doing a big-upfront detailed architecture design or modelling, slicing of an adaptive architecture can be done from the following perspectives for a value within the given time period or timebox (week, month, quarter, year):

Balancing depth vs breadth within a value timebox.

Breadth (architecture layers or domains)

  • Interaction
  • Human
  • Technology
  • Facility
  • Security


Depth (level of details)

  • Ecosystem architecture
  • Enterprise architecture
  • Segment architecture
  • Capability architecture
  • Process architecture
  • Product architecture
  • Service architecture
  • Solution architecture 



This post only introduces to the concepts of Adaptive EA. In my next post I will discuss the adaptive EA design and practice concepts. Finally, I will discuss an application scenario of adaptive EA based on the real industrial case.

References:

Gill, A.Q., 2014. Applying agility and living service systems thinking to enterprise architecture. International Journal of Intelligent Information Technologies (IJIIT), 10(1), pp.1-15.

Gill, A.Q, 2015. Adaptive cloud enterprise architecture. World Scientific.

Gill, A.Q, Bunker, D. and Seltsikas, P., 2015. Moving Forward: Emerging Themes in Financial Services Technologies' Adoption. CAIS, 36, p.12.

Korhonen, J.J., Lapalme, J., McDavid, D. and Gill, A.Q., 2016, August. Adaptive enterprise architecture for the future: Towards a reconceptualization of EA. In 2016 IEEE 18th Conference on Business Informatics (CBI) (Vol. 1, pp. 272-281). IEEE.


Comments

  1. Allen Marry7 March 2022 at 16:07

    IT's very informative blog and useful article thank you for sharing with us , keep posting learn more about Product engineering services | Product engineering solutions.

    ReplyDelete

Post a Comment

Popular posts from this blog

What is Information? A Theory of Information Trilogy

-
Image
A Theory of Information Trilogy for Information Ecosystem by Asif Gill Information is/of Everything (IioE) We hear many definitions of information and related concepts such as data, information itself, knowledge and intelligence. Well, all these definitions seem useful from information probability, quantification, measurement, storage, processing and management perspective. We still wonder what is "it" and how to identity "it", which we call "information". This blog defines and describes nature ecosystem inspired definition of information, which is called here a "Theory of Information Trilogy" (ToIT).  This theory is defined with a view to define and identify information in complex and heterogenous information ecosystems.  This theory defines that the information is (1) matter and (2) energy, which has different (3) states or forms. Matter and energy flow in the natural ecosystem. Further, from natural ecosystem, these 3 matter, energy and their ...
Read more

Circular Information Lifecycle Management for Enabling Circular Economy

-
Image
Circular economy is about recycling, remanufacturing, reusing  products, services and information for continuous value re-co-creation while reducing waste and enhancing positive economic, environmental and social impacts. This requires to re-conceptualize and re-design the economic ecosystems and business models for optimisation and innovation.  Information management is extremally important to provide intelligence & insights for effective decision making  and actions enabling circular economy. This article presents the following circular information lifecycle management for enabling circular economy.  In circular information lifecycle management (CILM), information can be restored and recycled like another product or service in the circular economy.  The CILM is composed of six key stages: discover & collect, classify & secure, prepare & release, access & use, archive & purge, and restore & recycle.  Circular Information Lifecyc...
Read more

AI-enabled Intelligent Enterprise: AI Co-pilots

-
Image
AI-enabled Intelligent Enterprise  There is an increasing interest in Artificial Intelligence (AI)  systems for decision making, productivity gain, better quality products and services etc. There is a fear or assumption that AI systems will replace human. We should not assume that AI systems will replace humans, rather we can look at them as our agent or  assistants.  Human is the "Principal" who delegates the tasks to the AI system that is called an "Agent". Thus, there is a principal-agent relationship (delegation) between the human and AI system.   AI Co-pilot There are several facets of AI systems, in particular the AI co-pilot system that can assist humans for carrying out tasks on their behalf. These AI co-pilots can be embedded across the enterprise value chain. This article discusses the AI-enabled intelligent enterprise and the applicability of AI co-pilots across the connected core value chain of (1) strategy, (2) architecture, (3) development and...
Read more