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 platform and the host organisations.
• 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 overall coherence.
• High quality data analysis does not necessarily mean using complex data analysis methods.
• Recognising the need to rapidly establish the credibility of the platform, it is important to identify one initial question which requires analysis 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 used to establish the policy dialogue with decision-makers (see section 2).