dc.contributor.advisor | Goede, R. | |
dc.contributor.author | Venter, Carin | |
dc.date.accessioned | 2016-05-05T09:21:00Z | |
dc.date.available | 2016-05-05T09:21:00Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://hdl.handle.net/10394/17138 | |
dc.description | PhD (Information Technology)--North-West University, Vaal Triangle Campus, 2016. | |
dc.description.abstract | The quality, timeliness and availability of appropriate information to appropriate
decision makers determine the quality of decisions; it therefore also determines the
subsequent effect of these decisions on organisations. Organisations that make
better decisions quicker than their rivals are more agile and competitive. Well-informed decisions improve organisations’ economic results and value; it improves
planning processes and enables organisations to swiftly react to ever-changing
business climates. Business intelligence (BI) systems enable organisational leaders
to make decisions more effectively and efficiently; BI is a business differentiator in a
world where organisations are becoming increasingly reliant on relevant, timeous,
and intelligible information to improve their operational efficiency.
Traditional development approaches, for example the Kimball lifecycle approach or
Inmon’s corporate information factory, are used to develop BI systems. These
traditional approaches are heavily influenced by the paradigm within which traditional
software development approaches emerged, i.e. the hard systems thinking
paradigm. The hard systems thinking paradigm is dominated by deterministic
problem solving methodologies such as operational research and systems
engineering; they focus on optimisation and design and are suitable for well-defined
problem contexts. Traditional approaches enable the development of technically
good and robust technological architecture and infrastructure (such as the data
warehouse). However, BI systems are social artefacts as well as technical artefacts;
they should aim to improve the organisational context of users, rather than merely
automate existing business processes. Successful BI requires more than an
appropriate data warehouse; it requires more than a data infrastructure and platform
built to access existing/known information better and faster. Successful BI system
development requires a critical reflective process that improves organisational
decision making capabilities beyond what is imaginable, rather than merely automate
what is easily observable. The critical systems thinking (CST) paradigm aims to explore relevant social
dimensions of a problem context and provide richer, more meaningful solutions.
CST aims to facilitate social improvement. CST is founded in critical and social
awareness; methodological complementarism; and a dedication to human
emancipation. Critical systems thinkers aim to emancipate the oppressed by
exploring and removing supressing societal structures. This study views business
users with unrealised business benefits as the oppressed; non-people oriented
(traditional) BI system development approaches are viewed as the suppressing
structures.
The CST paradigm does not render other paradigms, such as the hard systems
thinking paradigm where BI development approaches emerged, invalid. Rather,
within the CST paradigm the epistemological debate moved from the question of
selection a single problem solving method, to recognising the value of combining
different methods from different paradigms. This study explores the application of
critical systems methodologies (such as critical systems heuristics) from the CST
paradigm to complement a traditional BI system development approach. The
researcher follows an action research approach to develop guidelines for the use of
critical systems methodologies in BI system development.
This study concludes with guidelines to incorporate a critical systems methodology,
i.e. critical systems heuristics (CSH), in BI system development. The researcher
successfully applies CSH during the business requirements definition phase of the
Kimball lifecycle BI development approach; she also contextualises the classic CSH
boundary questions specifically for a BI context. | en_US |
dc.language.iso | en | en_US |
dc.publisher | North-West University | |
dc.subject | Business intelligence | en_US |
dc.subject | Data warehouse | en_US |
dc.subject | Critical systems heuristics | en_US |
dc.subject | Critical systems thinking | en_US |
dc.subject | Action research | en_US |
dc.title | Guidelines for the use of critical systems methodologies in business intelligence system development | en |
dc.type | Thesis | en_US |
dc.description.thesistype | Doctoral | en_US |
dc.contributor.researchID | 10085971 - Goede, Roelien (Supervisor) | |