MENGELOLA PENOLAKAN TERHADAP PERUBAHAN DI BANK BTN Menggunakan Metodologi Serba Sistem Lunak Berbasis Riset Tindakan
Date
2013-11-27Author
Sadana, Stefanus
Pramesworo, Septo
Zainab, Rizka
Metadata
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Purpose – This paper, —Managing Resistance to Change at Bank BTN Using Soft Systems Methodology based Action Research— aims to show how soft systems as a part of systems thinking approach can be incorporated in action research (AR) interventions to successfully implement resistance to change at Bank Tabungan Negara (BTN). The case study in Bank BTN described in this paper would be useful to managers who want to implement change in their own organizations. Design/methodology/approach – This project used Soft Systems Methodology based Action Research (AR) as the methodology due to its flexible, responsive and emergent nature. There was soft systems thinking was used as a sense-making process while carrying out action research. As an added benefit this approach have resulted in successful research alternative. Findings – Soft systems methodology (SSM) based Action Research can help in addressing ill-structured problems faced by managers, in collaboration with stakeholders using questioning and reflection. SSM lead to an increased understanding about the problem situation. SSM uses a more structured approach while AR is emergent in its application. SSM practitioners advocate that action researchers would benefit by declaring in advance an intellectual framework to guide their research. This has the additional benefit of overcoming obstacles in an academic environment where research processes are still governed based on traditional research methods. Practical implications – The ideas presented in the paper could be particularly useful to a practice-based discipline such as project management where research into its practice is in demand. Originality/value – This paper would be useful to managers interested in a rigorous methodology to implement organizational change in addressing business problems. It demonstrates ways of combining SSM and AR, resulting in a powerful research tool to carry out rigorous research.