This paper reflects upon the teaching of soft systems methodology (SSM) to undergraduate, postgraduate, and executive students. The paper presents SSM as an all-purpose approach to tackling complex situations, which can be conceived as an experiential learning cycle. SSM adopts a participative approach to problem solving and uses systems modeling to structure discussion between stakeholders. After introducing the basic nature of SSM, the paper discusses issues with teaching it. These are seen to stem from the flexible nature of SSM and the unusual modeling language. An example case study and module blueprint are then presented that have proved successful with preexperience and postexperience students. The teaching approach is based upon the principles of experiential learning and the paper shows how a realistic consulting project helps students to experience the use of SSM and grasp the nature of the systems modeling. The paper argues that student groups need to be facilitated though role-play to achieve a productive experience and acceptable analytic outcomes.
The ethical aspects of data science and artificial intelligence have become a major issue. Organisations that deploy data scientists and operational researchers (OR) must address the ethical implications of their use of data and algorithms. We review the OR and data science literature on ethics and find that this work is pitched at the level of guiding principles and frameworks and fails to provide a practical and grounded approach that can be used by practitioners as part of the analytics development process. Further, given the advent of the General Data Protection Regulation (GDPR) an ethical dimension is likely to become an increasingly important aspect of analytics development.Drawing on the business analytics methodology (BAM) developed by Hindle and Vidgen (2018) we tackle this challenge through action research with a pseudonymous online travel company, EuroTravel. The method that emerges uses an opportunity canvas and a business ethics canvas to explore value creation and ethical aspects jointly. The business ethics canvas draws on the Markkula Center's five ethical principles (utility, rights, justice, common good, and virtue) to which explicit consideration of stakeholders is added. A contribution of the paper is to show how an ethical dimension can be embedded in the everyday exploration of analytics development opportunities, as distinct from a stand-alone ethical decision-making tool or as an overlay of a general set of guiding principles. We also propose that value and ethics should not be viewed as separate entities, rather they should be seen as inseparable and intertwined.
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This paper describes a mixed methods approach using problem structuring methods to conduct applied research into fitness-to-drive arrangements within the UK Department for Transport. Computer-supported group causal mapping was used to collect and structure qualitative data from stakeholder groups concerning the delivery of medical standards on fitness-to-drive. The data were subsequently coded and analysed using the modelling language of soft systems methodology. This enabled data to be linked to the concept of a 'fitness-to-drive system' and developed further in the form of systems models based on alternative worldviews. The paper reports on the process of developing and implementing the approach and discusses issues concerning the conduct of mixed methods research using problem structuring methods. Journal of the Operational Research Society (2009) 60, 1637-1648. doi:10.1057/jors.2008.125 Published online 19 November 200
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