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Implications for data analysis (3/4)

However, simple does not mean quick and dirty. What is done must be done correctly

  • To influence policy makers, the data analyses and results must be undisputable. Disseminating the findings of a shaky analysis can be detrimental to the reputation and credibility of the project and the organisation.
  • The proposed analysis must be of high quality, given the available resources.
  • This means coherence between the question, the data availability, the data quality, the data analysis method and the capacity of the data analysis unit. A well-designed, detailed data analysis plan (see below) ensures this global coherence.
  • High quality data analysis does not necessarily mean using a complex data analysis methods.
  • Recognising the need to rapidly establish the credibility of the NIPN platform, it is important to identify one initial question which requires limited analysis and that can be rapidly produced (collecting the “low-hanging fruit” first).
  • The NIPN nutrition dashboard (see section 3.5) is an example of a rapidly produced analysis. It is useful ONLY if it is embedded in the policy dialogue (see section 2).
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How to design a data analysis plan?