Analysis Spectrum

(Chataigner 2018).

As a means to structure the different steps of the analysis process, the analysis spectrum was visualized (ACAPS 2016). The spectrum describes six stages of analysis that an analyst undertakes in order to turn data into information and provide the best possible answers to a question. 

Examples are given at each stage to further clarify the steps. In the example, an analyst is situational analysis on the humanitarian crisis in country X, particularly on food insecurity. The analyst collates available reports on Reliefweb, from WFP, IPC, FewsNet, UNHCR, ICRC, and clusters.

Prior to starting the stages of analysis, the collection of secondary data sources/data acquisition has already taken place. Read more on this in the Secondary Data Review sections.

1. Exploratory analysis

1. The first stage looks at what data is available, which sources you have to your disposal, and whether it can be used. You mostly focus on finding whether you have what you need.

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?
• Code & refine your data – Can the data be better prepared for queries?
• What are the main results so far?

Example: 

• 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.

2. Descriptive analysis

The second stage looks at what this data actually says. What is written in these sources? What does the data tell us about a given situation? Who is affected, where, how many people? You summarise and describe the data in front of you, to reduce the amount of data and make it easier to compare data.

Main activities and questions

• Group alike 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/similarities - What consistent patterns, trends, or anomalies emerge from the data?

Compared to what?

• Humanitarian standards (eg humanitarian conditions vs. SPHERE standards)
• Time (eg. Pre- vs. in-crisis)
• Geographic (eg. Governorate A. vs. Governorate B.)
• Social group (eg. Refugees vs. IDPs)(ACAPS 08/2013).

Example: The analyst tags pieces of information DEEP. Not only is data available on food insecurity, there is also data on conflict developments.

• There are 15 million people in country X who are food insecure
• The large majority is in rural areas.
• Conflict affected areas have the highest proportion of food insecure people in relation to the total population
• The proportion of food insecure people has more than doubled in the last five years

3. Explanatory analysis

In the third stage you provide answers the questions of why something is happening, and what factors are at play to make a situation occur. You look for associations and correlations. The focus is on: Why is it like this?

Main activities and questions

• Connect the dots and look for association and correlation – What follows what?
• Link causes to effects – What happened next?
• Review processes & underlying factors – How does it work?
• Develop plausible explanations and entertain rival explanations – What else could explain this?

 Example: The analyst connects the above pieces of information: 

• Current food insecurity is linked to the blockade starting in November 2017, severely restricted imports of essential goods.
• People in rural areas suffer food insecurity mostly for lack of food products and diversity in markets. In urban areas, food insecurity is driven by lack of financial resources and social discrimination.
• Prior to the blockade, Country X already faced the largest food security emergency in the world with the on-going conflict destructing assets, infrastructure and food sources.

4. Interpretative analysis

The stage where you start turning mere ‘data’ into information. What are the actual implications of the data? “So what”? What does it mean and why does it matter? You start drawing well-supported conclusions.

Main activities and questions

• Rate severity of humanitarian outcomes - What is important and why?
• Prioritise most important issues and underlying factors - What is important and why?
• Evaluate evidence and assess plausibility - How sure are you?
• Generalise and transfer results where appropriate - Can results be applied to other settings or groups?
• Focus on main findings and build a case - What are the key messages?

 Example: 

• Results of a recent comprehensive food security survey shows that 10% of the returnee population in the north is facing acute food insecurity and is in urgent need of humanitarian assistance. This proportion rises to 27% in the south.
• Key priorities include reducing acute food insecurity for displaced population in the south and returnee populations in the north
• The survey could not assess areas affected by the conflict in the south. Several informal reports indicate an extremely alarming situation in besieged areas where the resident population is trapped, and food resources are scarce. This is consistent with findings in recently accessible besieged areas where acute food insecurity levels were extreme.

5. Anticipatory analysis

The fifth stage looks at the future. What will happen next? If X, then what does this mean for Y? What are the next possible things to happen? What is plausible? This can be done in for example risk analysis or scenario building.

 Main activities and questions

• Extend current conditions to forecast future outcomes - What will happen if nothing changes?
• Examine and develop alternative futures - What else might happen?
• Evaluate likelihood and impact - What might be the consequence if this happens?
• Update interpretation based on likely developments - How does this change current conclusions and key messages?
• Identify triggers and track new developments - How can I tell if this happens?

Example: 

• With current levels of assistance, Country X faces a risk of Famine (IPC Phase 5) given the potential combined impact of the blockade and the extension of the conflict to the center regions.
• Without a scale up of food interventions, an additional 15% of people facing acute food insecurity could be expected in the next 6 months.

 6. Prescriptive analysis

Stage six is about recognising the current and future humanitarian needs, and advising what concrete actions humanitarian decision makers can take to respond to humanitarian needs.

 Main activities and questions

• Link problem to a strategy and targets - What should we do about it?
• Examine and weight the impact of response options - What set of action(s) will have the greatest and quickest impact?
• Suggest and advise on response priorities - In which order does this need to happen?

Example: 

• Reestablishing access to food products in urban areas for XX people
• (Advocate for) Immediate lifting of the blockade to re-establish pre-conflict import level
• In-kind food and nutrition support to acutely food insecure people in rural areas
• Cash support to acutely food insecure people in urban areas

Remember

The analysis spectrum is continuous and does not occur linearly. On paper, the spectrum appears to be linear. However, analysis is an iterative process which continues until it is possible to draw conclusions with a reasonable conclusion.

The steps beyond description should be done in collaboration with subject matter experts, to strengthen agreement and interpretation.