A framework for modelling complex business systems for transition to cloud hosted services

Spiteri, Kenneth J. (2018) A framework for modelling complex business systems for transition to cloud hosted services. Doctoral thesis, Anglia Ruskin University.

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Abstract

Complexity within business and its supporting systems is interlinked with the evolution of Cloud computing and Enterprise Resource Planning (ERP) systems. Business complexity is therefore a key factor in strategic technology investments such as a transition to Cloud hosted Software-as-a-Service (SaaS) solutions, as this has an impact on risk, cost and requirements. It is observed in practice however, that complexity is primarily a qualitative consideration within the early stages of current ERP implementations. Within a business context, existing validated complexity measures include Control Flow Complexity (CFC) and Redundancy Measure, which evaluate a business at the process level, but assume a static scenario inappropriate for a system implementation that can change through different configuration permutations. Previous studies have attempted to compare various complexity measures to identify a common element but have failed to establish a unique derivative measure, with comparison outcomes being reported in qualitative attributes such as reliability and ease of use. Furthermore, most of these metrics have not been validated theoretically or empirically, and associated tools for their application have not been made publicly available. The current research has identified a need to derive an alternative definition of business complexity and to develop a framework to analyse and quantify this property as a single measure. The proposed Spiteri Complexity Metric (SCM) developed for this research is a complexity measure that is process and system independent, and utilises a framework to quantify the complexity at an earlier point within the strategic ERP decision process compared to existing approaches. The SCM was theoretically validated using existing robust methods, whilst empirical validation was undertaken utilising 9 business case studies covering 32 companies. An index of complexity for each business case study enabled the calibration of the various components of the framework and required quantitative evaluation of approximately 700 million records, 48,000 data entities and 65 data mining and analyses worksheets. This work provides a validated complexity toolset that enables combining, unifying and connecting different complexity dimensions across business processes and systems architectures. A comparative calculation of business complexity using the Spiteri Complexity Framework (SCF) has a myriad of applications. Within a Cloud transition process this includes the quantification of risk, budget forecasts, SaaS service applicability, industry analyses, requirements analyses, service and system comparison, and time estimations. The possibilities for further developing the work to include scaling and extending automation tools for easier application and analyses are discussed.

Item Type: Thesis (Doctoral)
Keywords: Complex Systems, Business Systems, Business Complexity, Cloud Computing, Framework Modelling, Enterprise Resource Planning Systems (ERP), Software-as-a- Service (SaaS), Complexity Metric, Complexity Index, Unified Model
Faculty: Theses from Anglia Ruskin University
Depositing User: Lisa Blanshard
Date Deposited: 16 Sep 2020 15:13
Last Modified: 09 Sep 2021 18:57
URI: https://arro.anglia.ac.uk/id/eprint/705899

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