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Tool 2: Wellbeing monitoring step-by-step Step 5. Analyse and present the data The survey results are useful only if they are presented in a clear and meaningful format. One way to do this is to create an index for each government sector or poverty sphere. An index is a single number that combines information from all questions related to a topic. Indices are easy to understand because they summarise the results of questions into a single number. An example is a health index, which might combine the results of several questions related to health. A. Calculate an index for each sphere To create an index, add the values (3 points for ‘good’, 2 for ‘intermediate’ and 1 for ‘critical’) and normalise them so that questions can be compared with each other (see Box 23).
Calculate an index for each sphere. Present the results graphically to help users visualise the results. Box 23 provides an illustration for the health sphere. All responses to the questions related to health in the survey carried out in Kutai Barat were combined into one index. B. Present the indices in a table Once you have calculated all the wellbeing sphere indices, it is time to present the monitoring results to decision makers. There are many different ways to present data. One way to compare communities quantitatively is by listing the wellbeing sphere indices in a simple table. Use colours to identify whether each sphere is critical, intermediate or good.
Box 24 shows the indices that were calculated from the indicators of each sphere. The colour code shows whether an index is in critical, intermediate or good condition. The boundaries between the three colours depend on the indicator value ranges of each sphere. Some indicators might only have two possible values—i.e. score 1 (critical) and score 3 (good)—while others offer three—i.e. including score 2 (intermediate); thus, the boundary of critical (red) is somewhere between 0.333 (if all indicators have a range of 1–3) and 0.5 (if the values are 1 and 3, without 2) depending on the respective sphere. C. Present the results in the NESP format or bar charts Not everyone likes reading tables. If you want to present the results in a more attractive way, use the NESP model (see Part I) or bar diagrams. The NESP model allows users to compare households, communities or subdistricts at a glance (see Figures 12 and 13 for an example from Kutai Barat in 2006). Figure 12. NESP representations of wellbeing/poverty spheres in four communities in Kutai Barat (February–March 2006).
Figure 13. Bar diagrams of poverty sphere scores for the same 4 communities as in Figure 12. Abbreviations as per Box 24.
Each way of graphically representing poverty data has strengths and weaknesses. While NESP gives a quick overview of the overall poverty situation of a community (or household or subdistrict, etc.), including critical sectors and possible trade-offs, bar diagrams show a more nuanced picture that also allows the comparison of indices of the same colour code in a more quantitative way. Both versions instantly show which sectors are in a critical condition. In the bar diagram example of Figure 13, Community A lacks knowledge and healthcare and has problems in the economic sphere, Community B lacks knowledge, while Community C clearly has environmental problems, and Community D suffers from inadequate infrastructure and government services. All these red spheres are alert signs for the respective government agencies that need to follow up with a more in-depth analysis of the underlying causes. When reviewing the results, keep in mind that there is no natural distinction between the poor and the non-poor. Every poverty line is based on a certain poverty definition. In this example, a local monitoring team defined ‘poor’ (i.e. score 1 or red colour) by using local concepts of poverty and wellbeing (see Step 2A). However, this definition is not permanent. If living standards change, the meaning of what deserves a critical score will also change. D. Create poverty maps Poverty maps show where poverty hotspots are. Figures 14 and 15 show poverty maps that were created for Kutai Barat. Develop a poverty map for each wellbeing sphere by locating the results by community on a map (see Tool 1 for a more complete description of this process). Poverty maps help answer the question ‘Where are the poor?’ However, the patterns revealed by the poverty maps do not automatically provide answers to the problem ‘Why are they poor?’ The maps can only show correlations between different aspects of poverty. Nonetheless, these correlations are a good starting point for understanding the underlying causes of poverty. Figure 14. Health aspects of poverty in Kutai Barat, 2006.
Figure 15. Condition of natural sphere aspects, Kutai Barat, 2006. Each coloured dot represents the condition of the natural environment of a community.
© 2007 Center for International Forestry Research (CIFOR) |
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