Overview
Text should include: Step by Step, Checklist, SOPs, Tips
Analysis workflow
The analysis workflow describes the bigger picture of analysis and the different steps to undertake when analyzing a topic, and how each step builds upon the findings of the previous ones. Analysis needs to be planned and designed. The analysis workflow has four steps, each of which has several guiding questions and possible outputs. Four steps of analysis workflow
|  |
- Design: The design phase precedes analytical processes and is about selecting the best strategies for ensuring quality analysis. It is preparatory in essence and elaborates and refine the focus, approach, method, tools, and plan necessary to provide relevant and credible conclusions.
Preparedness (CODs, indicators, assessment registry, HID) - Tips (e.g. six -hat or point system)
Analysis Spectrum and the HPC
(provide details on the process for each phase/product of the HPC)
- 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
Focus: 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 & 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 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
Focus: What is written in these sources? What does the data tell us about a given situation? Who is affected, where, how many people? Summarise and describe the data, to reduce the amount of data and make it easier to compare. Comparison is key to analysis
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 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:
Prescriptive:
Process
Text should include: Step by Step, Checklist, SOPs, Tips
Outputs/Resources
Text should include Essential Reading, Additional Readings, Templates. Examples, Tutorials
Guidance
- text
- text
- text