...
- Exploratory
- Aggregation, disaggregation
- Chronologies, timelines
- SDR
- Describe
- Prioritization (sudden onset)
- Severity (sudden onset)
- Explain
- Cause and effect
- Interpret
- Ratings, rankings and uncertainty
- Anticipate
- Prediction, forecasting
- scenario building
...
Exploratory Analysis
Focus: To identify if data required is available (credible, reliable, timely) and structure it in a way that best suit the requirement and identifies information gaps.
Main activities and questions
- Familiarise yourself with the data and check its characteristics - How relevant, sufficient and reliable is the data?
- Clean & and enrich your data to ensure it is as good as it gets - How clean and ready for analysis is the data? Do I have enough data?
- Are potential signals hidden in the data?
- Sort, aggregate and disaggregate and define suitable taxonomy of categories. Code & refine your data – Can the data be better prepared for queries?
- What are the main results so far?
Examples of Exploratory analysis findings
- There is a variety of information sources on food insecurity in country X, primarily from IPC, Fewsnet, WFP and FAO.
- Some are purely observational, some are quantitative.
- Recent figures on food security are available after a comprehensive national survey by WFP
- Findings are mostly aligned.
- No recent information is available from the southern region where accessibility is limited
- There seem to be higher levels of food insecurity in rural areas.
...
Descriptive Analysis
Focus: Summarise and describe the data, to reduce the amount of data and make it easier to compare. Comparison is key to analysis.
Main activities and questions
- What is written in these sources? What does the data tell us about a given situation? Who is affected, where, how many people?
...
Main activities
- Group similar observations and reduce your data - What meaningful comparisons reveal differences?
- Select the metric that best describes the situation – How can I summarise my data in a way that best describes it?
- Compare and contrast between and within groups of data to identify meaningful and significant differences and similarities - What consistent patterns, trends, or anomalies emerge from the data?
...
- Compare to what?
- Humanitarian standards (e.g. humanitarian conditions vs SPHERE standards)
- Time (e.g. Pre- vs in-crisis)
- Geographic (e.g. Governorate A. vs Governorate B.)
- Population group (e.g. Refugees vs IDPs
Examples of Descriptive analysis findings
- There are 15 million people in country X who are food insecure.
- The large majority is in rural areas.
- Conflict-affected areas such as district A, B and C have the highest proportion of food insecure people about the total population.
- The proportion of food insecure people has more than doubled in the last five years.
...
Explanatory
Interpretive:
Anticipatory:
...