A decision-making approach for enterprise architecture evolution using simulation

2019 ◽  
Vol 36 (2) ◽  
pp. 188
Author(s):  
Sérgio Guerreiro ◽  
Khaled Gaaloul
Keyword(s):  
Decision Making ◽  
Enterprise Architecture ◽  
Architecture Evolution

An Applied Mathematical Model for Business Transformation and Enterprise Architecture Projects

2020 ◽  
pp. 211-247
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Knowledge Management ◽  
Enterprise Architecture ◽  
Real Life ◽  
Knowledge Management System ◽  
Complex Case ◽  
Avant Garde ◽  
Business Transformation ◽  
Implementation Model

This chapter presents the holistic and dynamic knowledge management system (H&DKMS) concept that is implemented in a proof of concept to prove the feasibility of the chapter using the book's HMM approach. The H&DKMS supports business transformation projects (BTP) and enterprise architecture projects (EAP) (simply project). The H&DKMS is supported mainly by an adopted fictious case from the insurance domain. The uniqueness of the proposed HMM promotes a holistic architecture and implementation model that supports complex case studies. The integrated knowledge management and decision-making process are used in a day-to-day business and technology problems solving. In this chapter, the proposed solution (or model) is supported by a real-life case of business transformation methodology in the domain of H&DKMS that in turn is based on the alignment of various standards and avant-garde methodologies.

An Applied Mathematical Model for Business Transformation and Enterprise Architecture

2020 ◽  
pp. 172-210
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Research Method ◽  
Enterprise Architecture ◽  
Financial Analysis ◽  
Applied Mathematics ◽  
Decision Making System ◽  
Information And Communication ◽  
Software Modelling ◽  
Business Engineering

This chapter proposes a cross-business domain holistic mathematical model (HMM) that is the result of a lifetime of research on business transformations, applied mathematics, software modelling, business engineering, financial analysis, and global enterprise architecture. This research is based on an authentic and proprietary mixed research method that is supported by an underlining mainly qualitative holistic reasoning model module. The proposed HMM formalism attempts to mimic some functions of the human brain, which uses empirical processes that are mainly based on the beam-search, like heuristic decision-making process. The HMM can be used to implement a decision-making system or an expert system that can integrate the enterprise's business, information, and communication technology environments.

A Network-Based View of Enterprise Architecture

2007 ◽  
pp. 306-319 ◽  
Author(s):  
B. Iyer ◽  
D. Dreyfus ◽  
P. Gyllstrom
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Enterprise Architecture ◽  
Process Data ◽  
Dependency Networks ◽  
Support Tools ◽  
Design Production ◽  
Data Requirements ◽  
Over Time

Traditional notions of architecture have focused on the components and (or domains of interest—process, data, and infrastructure) aspects of architecture. Their goal is to separate concerns into modules and provide interfaces between modules. This view helps designers understand the ideal or espoused view of architecture. In our work, we view architecture from a dependency perspective. These dependencies evolve over time, creating an emergent architecture. The emergence is influenced by both technical and social factors. Dependencies occur during the design, production, and use of enterprise components. This leads us to use network-based analysis techniques in order to understand the emerging dependency networks. In order to provide architects with support tools to communicate and make decisions about architecture, we describe the data requirements and algorithms that can be used to build a decision support system that enable enterprises to incorporate a network perspective in their decision making process. We present our approach and methods in the context of a case study

The Business Transformation Framework and Enterprise Architecture Framework

2021 ◽  
pp. 535-566
Author(s):  
Antoine Trad
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Money Laundering ◽  
Asset Management ◽  
Enterprise Architecture ◽  
Real Life ◽  
Concrete Case ◽  
Business Transformation ◽  
Architecture Framework ◽  
Enterprise Architecture Framework

In this chapter, the author based his research on his authentic mixed multidisciplinary applied mathematical model that is supported by a tree-base heuristics module, named the applied holistic mathematical model for organizational asset management (AHMM4OAM), where the proposed AHMM4OAM is similar to the human empirical decision making process, which can be applied to any type of asset management discipline, in order to support the evolution of organisational, national, or enterprise asset management. The AHMM4OAM can be used for the detection of financial irregularities, assets optimisations and eventual dangers for the organisation's or national assets. In the case of gigantic financial misdeeds that endanger national assets, which are related to fraud and money laundering that damage many organisations and even countries, and in this concrete case it is related to the Swiss, Union des Banques Suisse (UBS), in which 32 trillion US dollars are hidden and is the problem of global financial disequilibria. The AHMM4OAM is supported by a real-life case of a organisational (or business) transformation architecture in the domain of organizational (or enterprise) asset management (OAM) that is supported by the alignment of a standardized organisational or enterprise architecture blueprint.

The Business Transformation and Enterprise Architecture Framework

2020 ◽  
pp. 304-339
Author(s):  
Antoine Trad
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Enterprise Architecture ◽  
Selection Process ◽  
Business Case ◽  
Knowledge Management System ◽  
Business Transformation ◽  
Architecture Framework ◽  
Decision Making System ◽  
Enterprise Architecture Framework

The HSD&E activities are supported by a central decision-making system (DMS) (in which a HR subsystem is included), knowledge management system (KMS), and an enterprise architecture project (EAP). The chapter's proof of concept (PoC) is based on a business case from the insurance domain where the central point is the capacity of the selected manager skillset to successfully start and finalize a BTP or an EAP (or simply a project). The PoC shows the selection process of a manager's skillset to transform the traditional insurance enterprise into an agile and automated enterprise. Projects are managed by managers, who are (or should be) supported by a methodology and a framework that can estimate the risks of failure of a project; at the same time, they should be capable of managing the implementation project processes.

Green Enterprise Architecture Using Environmental Intelligence

2013 ◽  
pp. 58-65
Author(s):  
Bhuvan Unhelkar
Keyword(s):  
Decision Making ◽  
Carbon Emission ◽  
Enterprise Architecture ◽  
Green It ◽  
Systems Architecture ◽  
Management Software ◽  
Information Processes ◽  
It Systems ◽  
Strategic Approach ◽  
Carbon Control

This paper discusses Green Enterprise Architecture (GEA), which is an extension and application of Enterprise Architecture in the environmental domain. A GEA makes strategic use of the green IT systems otherwise also known as CEMS – Carbon Emission Management Software – that results in an all-encompassing approach to the greening effort that incorporates carbon data, information, processes, and knowledge in the organization’s decision making. This paper highlights the significance of such a strategic approach to carbon control in practice. The challenges associated with implementing Green IT in organizations can be handled through a carefully construed green IT systems architecture that will not only enable implementation of dedicated system for carbon measures but also facilitate upgrade and integration of existing suite of ERP applications that incorporate carbon measures.

Framework of Knowledge and Intelligence Base

Data Mining ◽  
2013 ◽  
pp. 474-502
Author(s):  
Marc Rabaey ◽  
Roger Mercken
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Information System ◽  
Enterprise Architecture ◽  
Service Oriented Architecture ◽  
Naturalistic Decision Making ◽  
Military Organization ◽  
Knowledge Culture ◽  
It Systems ◽  
Service Oriented

This chapter introduces the concept of the “Intelligence Base,” developed in a study on the information requirement of the management of an (military) organization. The purpose of the study was to conceive, for each level of an organization, an appropriate Decision Support System (DSS) and/or Knowledge and Information System. All systems would eventually have been integrated in an overall Enterprise Architecture (EA). By discussing the OODA-cycle of John Boyd and the Naturalistic Decision Making (NDM) the authors show that the concept of Intelligence Base can be a DSS for very demanding environments. Related topics are knowledge, culture, and real options (business example). The proposed framework is based on Service-Oriented Architecture (SOA) and Cloud Computing, which will determine the configuration of the Information Technology (IT) systems.

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