In Chapter 2, we took a big picture view of the problem by looking at it through a systems lens. In Chapter 3, we introduce some common methods for analysing data to better understand the problem. They cover a mix of simple and complex analysis techniques, as well as audience segmentation approaches.
As a society, we are dealing with increasingly complex problems and working in environments where there are many competing agendas. To build a shared understanding of the problem and uncover insights on the changes that organisations can make - and those which may be out of their control - we use systems, process, actor and influence mapping to identify the individuals, groups and organisations involved in the problem - and who may be part of the solution.
Influences, further reading and blog posts related to this chapter.
Associated with our work with Australia Post (left), is this this *paid* article in Behaviour and Information Technology, 4, 367-380. Borg, K. & Smith, L. (2018)
In the *paid* Journal of Classification, 23(1), 3-30 . Kettenring, J. (2006).
In this article, chapter co-author Kun Zhao and Luke Smillie (University of Melbourne) argue that personality science can help us better understand, measure and capitalise on individual differences when it comes to behaviour change.
Tabachnick, B. G. and L. S. Fidell (2019). Using multivariate statistics. Boston, Pearson.
Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS. Routledge.
Field, A. Miles, J. & Field, Z. (2012). Discovering statistics using R. Sage Publications
Howell, D. (2019). Fundamental statistics for the behavioral sciences. Cengage.
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