DATA INTERPRETATION AND ANALYSIS. In an old fable, six blind people are introduced to an elephant and asked to describe it by touching only one part. One touches the broad side of the elephant and concludes it’s a wall; another touches the tail and decides it’s a rope, and so on. Each of the blind persons arrived at a conclusion depending on the data that he/she collected and though each described their own data correctly, none arrived at the true nature of the elephant. Interpretation and analysis of data and implementation information give depth and meaning to facts (data) in monitoring reports; and support evidence-based decision making. This is a crucial step in the M&E Methodology and one that needs time, attention, as well as resourcefulness and subject matter knowledge. The analyst must also display a reasonable level of objectivity. As the fable in the box illustrates, the angle of perception of the analyst can have as much to do with the conclusions he/she draws as the data itself. Most experienced analysts will recognize this and will adjust to accommodate it by trying to collect as much data as possible not only to fill in the gaps but to compare for a complete picture. Just for illustration purposes, if the people in the fable could walk around the elephant and feel all its sides, its trunk, tail and feet then they would have been able to reach a different conclusion by connecting the information into a coherent conclusion. The sense and meaning derived through analysis is used to make sound decisions on existing and future actions to improve the chances of reaching the outcomes and targets expected in the strategies. Qualitative and/or quantitative data and information is analyzed and interpreted by a variety of methods, the most common are: (i) describing and summarizing the data; (ii) identifying relationships between variables; (iii) comparing variables; (iv) identifying the difference between variables; (v) forecasting (modeling) outcomes. The analyst must look for patterns and insights relevant to the key issues, and use these to develop responses appropriate to the challenges and opportunities emerging from implementation of the initiatives related to the strategies. It is important to eliminate some common myths associated with data analysis and interpretation before exploring some of the basic characteristics of methods. Myths in Analysis and Interpretations • Complex scientific analysis is the only acceptable form. This may be the case for academic research or in-dept...
