INDUSTRY NEEDS FOR DATA WAREHOUSING STUDENTS: USING SSM AS HERMENEUTIC DATA ANALYSIS TOOL FOR INTERPRETIVE INTERVIEW DATA
Keywords:soft systems thinking, interpretive data analysis, qualitative data, data warehousing
The soft systems methodology was developed by Peter Checkland over an extended period of time to assist organisational improvements. It provides tools to assist different stakeholders to articulate their perspectives on the best action to be taken in problem environments. It is grounded in the ideas of soft systems thinking, where systems are viewed as conceptual models to make sense of a messy real world environment. The original focus of soft systems methodology is organisational use rather than academic use. In this paper we demonstrate how the soft systems methodology can be used to guide and analyse interpretive interviews with participants in an academic research project in the context of interpretive research methodology.
We reflect on the hermeneutic nature of interpretive qualitative data collection and analysis and then we show that an activity diagram as used in the soft systems methodology, is a valid data analysis technique in terms of the epistemological context of interpretive data analysis.
We demonstrate our proposal by means of the data analysis of interpretive interviews of data warehouse practitioners on their perspectives of the required skills of information technology students majoring in data warehousing. We compiled activity diagrams and used them in communication with our participants, thus enabling our participants to verify our data analysis and enhance our understanding of their perspectives. We show how different perspectives can be represented and reflected upon after compiling activity diagrams and how different perspectives can be accommodated to develop a single strategy for change.
Our main contribution is to demonstrate the suitability of the soft systems methodology in data collection and analysis in interpretive cases studies where strategies for changes are studied.
The paper is organised in four main sections, starting with a discussion on the ontological and epistemological assumptions of interpretive case studies in order to show that it is possible to use the soft systems methodology from an interpretive research perspective. The second section provides a very brief discussion of the soft systems methodology. Our main contribution is in section three, providing justification and guidance for using the soft systems methodology to guide data collection and analysis in the context of interpretive research methodology. We demonstrate our proposal in the fourth section, where we show how we analysed interpretive interview data. Our paper concludes with reflection and recommendations.