system engineering Read Chapter 5, Soft Systems Methodology, attached. Use the i
ID: 3671177 • Letter: S
Question
system engineering
Read Chapter 5, Soft Systems Methodology, attached. Use the ideas in this chapter to develop a holistic view of a “messy” problem. A messy problem is a complex problem that involves humans as well as engineered systems (existing or proposed), and in which there are many interdependent variables. Examples of messy probems are: Reducing mercury in the oceans Reducing carbon in the atmosphere Attaining universal healthcare Improving the energy grid I do not expect you to address a problem of this magnitude. there is an article about the London Ambulance System development. Read Darren Dalcher’s article about the London Ambulance System and apply Checkland’s methods to understand the problem. Consider Ackoff’s description of synthesis in doing this. You should look at the problem from different “world views”, that is from the views of diverse stakeholders. 1. Develop a “rich picture” of the problem situation (the purposeful activity), see p. 209 in Chapter 5, and fig. 5.11 on p.210. 2. Create a root definition for a purposeful system to be modelled, see p. 219 (Do P by Q, in order to achieve R). 3. Define “CATWOE”, see p. 220. 4. Create one or more models of the purposeful system, see figure 5.7 on p.205, and fig. 5.20 on page 225. Upload your response to Blac
Explanation / Answer
1.A complex picture of participants‘ inputs through interview reflected the situation as an
unstructured system of practice or rich picture‘ Efforts in analysis have been to
configure this somewhat complicated situation into a structured model for debate of what
constitutes a desirable and culturally feasible system of inquiry‘.
This was achieved by sorting out what people are doing, how they are doing it and why a
model, or models, of CCA research as a system of inquiry‘ is starting to emerge. Initially as a
means to start to examine how research is put together‘ interviews were considered for
some of the different types of model‘ participants used to construct their view of CCA
research.
2. Conceptual models are useful to look back on the wider discourse and policy response to
climate change and to consider how these findings on practice interact with the policy
context. They provide a means for opening up critique on the way research activity is
conceptualised and to define possible areas for improvement.
1) The first type represents linear rationality such as a decision tree or casual model used to
support decisions through scientific analysis. This generates a particular framing of the
biophysical world, e.g., plant- or animal-environment interactions and scientific interventions
to engineer better climate and food production outcomes.
2) The second type of conceptual models was that mobilising metaphor as a means to
interpret change, for example viewing farming as an opportunity system‘ or improving
literacy‘ on climate science. This translated an awareness of the environment, in this case
the market or climate, to inform practical action. For example where constraints led to new
views of opportunity or where a more informed reading of environment can lead to better
production planning.
3) The third set of models represents a policy construct such as agenda matching, action
accountability and new conceptualisations oriented towards social action. This provides a set
of different framings through which purposeful action is directed.
3a) Agenda matching represents climate change as one of many policy agendas that those
involved in government research had to respond to.
3b) Action accountability represents an accountability function for measuring returns for
investment based on monitoring and evaluating the impact of programs implemented.
3c) New conceptualisations represents a policy development process that included a wider
range of stakeholders, as end-users or up-takers, in research design.
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.