Abstract

For the past three decades, enterprise modelling (EM) has been emerging as a significant yet complex paradigm to tackle holistic systematic enterprise analysis and design. With a high fluctuation in the global economy, industrial stability and technology shift, the necessity of such paradigms becomes crucial in determining the decisions that an enterprise can make for surviving in such a highly dynamic business ecosystem. EM practices have focused for a long time, on the design-time of enterprise systems. Recently, there has been a rapid development in data analytics, machine learning and intelligent systems from which an EM platform can benefit. EM needs to cope with the new changes in both business and technology; it should also help architects to determine optimum decisions and reduce complexity in technical infrastructure. In this paper, the author discusses several challenges facing enterprise modelling practices and offers an architectural notion for future development focusing on the requirements of a platform that can be called intelligent and adaptive.

Highlights

  • In recent years, we have seen a rapid advancement in practices and technologies that aid enterprise development and their ability to support informed and timely decisions

  • We propose using advanced analytics and artificial intelligence (AI) (Artificial Intelligence), to enable selfhealing or the correction mechanism enterprise systems that are performed by systems instead of humans [4, 5]

  • Traditional enterprise modelling practices have been challenged by the immense scale of changes in the economy, industry and technology, to which enterprises have been forced to react to in order to deal with past, present, and future decisions

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Summary

Introduction

We have seen a rapid advancement in practices and technologies that aid enterprise development and their ability to support informed and timely decisions. This paper argues that future EM can support this notion through the use of intelligent and knowledge-based systems toward an adaptive enterprise modelling platform. We propose using advanced analytics and AI (Artificial Intelligence), to enable selfhealing or the correction mechanism enterprise systems that are performed by systems instead of humans [4, 5]. In this case, the role of the enterprise designer is limited to monitoring the dashboards to check the enterprise status and to recreate only if adjustment is required for any part of the enterprise models. There is discussion of the current challenges of these practices from an IT paradigm shift perspective toward more adaptive and intelligent platforms.

Historical Background
Current Themes and Capabilities in EM Research
Requirements and Future EM Adaptive Platform
Requirements for Adaptive Enterprise Modelling Platform
EM for Adaptive Enterprise Systems – Future Scope
Conclusions
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