The complexity of many problems, or networks of problems, presenting no clear-cut solutions, is often a reason for delaying action on them. (The Cambodian term "shrimp soup problem" describes the intertwining of shrimp antennae in the soup so it is impossible to pick just one out of the bowl.) The complexity is such that many approaches have to be explored to meet the various requirements of different constituents: regions, countries, areas within countries (both rural and urban) and sections of the community, particularly the underprivileged and minority groups. In addition, analysis tends to be simplistic and to lead to simplistic solutions (whether programmes, organizations, information systems or models) which do not match in complexity the network of problems on which they attempt to focus.
In addition to delayed and simplistic analysis and solution proposals, the perceived complexity of data on problem families or clusters gives rise to elaborate computer systems which process millions of pieces of information with ease. With equal ease, based on mathematical formulae, they generate what appear to be infallible forecasts and probabilities, and graphic-displayed models and systems flows. These are not simplistic but over-sophisticated, and this in itself causes delays in analysis. In addition, since the data encompass too many problems or variables, the uncertainly generated is too high. Examples can be seen in global economic forecasting of humanity's needs in the next fifty to one hundred years.