$url = 'NIPN-Guidance-Notes?rubrique=74§ion=110&article=4'; redirect($url); Six principles of data analysis specific to NIPN (3/5) - NIPN

Six principles of data analysis specific to NIPN (3/5)

Principle 3: Building NIPN’s credibility is essential: disseminate only valid, robust analyses that cannot be disputed

  • 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 ensures this global coherence (see data analysis plan below).
  • High quality data analysis does not necessarily mean using a complex data analysis method.
  • Recognising the need to rapidly establish the credibility of the NIPN, 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 (section 3.2) is an example of a rapidly produced analysis. It is useful ONLY if it is embedded in the policy dialogue supporting the formulation of questions (section 2).
How to build a data analysis plan?