Guidelines for the use of critical systems methodologies in business intelligence system development

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.