Information Management during disaster response: Cyclone Idai, Mozambique
Litres of water distributed, relief items distributed, community feedback, total number of people reached — a humanitarian response to a disaster generates reams of data and information. Understanding and analysing this data in an efficient and clear way is key to enabling the response. But how do you approach such a challenge?
Last month I faced this exact question when I was deployed as the Information Management (IM) Coordinator to Mozambique, as part of the IFRC response to Cyclone Idai. The approach I adopted followed the ‘Disaster Information Cycle’.
The ‘Disaster Information Cycle’ breaks down information management into 4 stages: collect, collate, analyse, disseminate. Using my experience in Mozambique, I’ll aim to go through each.
1) Collect
“What are the best methods to collect data and information?”, “How can we report our activities effectively?”
To understand our impact, reach and be able to understand the effectiveness of our work, we need to collect data and information.
When I arrived in Mozambique, the sectors were already using or developing Mobile Data Collection forms or surveys. Working together we ensured that the surveys being developed would (1) collect data that the sectors themselves required for operational agility, (2) would report what the operation or clusters required and (3) was in a format which enabled efficient translation from data to table, chart or visualisation, such as maps! Here I collaborated with the sector specialist to identify the data that they were collecting at present and create an analysis plan.
The disaster response was moving towards recovery with new surveys were being created tailored towards longer term programmes and tracking against indicators. This was prime time to ensure that data collected: is collected in a useful way from the outset reducing the need for cleaning, stored in selected locations, with set sharing permissions as well as common training for admins and volunteers. Mapping out and harmonising how data was collected was a goal of mine. Collaborating and sharing documents and learning between all sector specialists was a very helpful exercise, during the response phase, trainings were conducted, and documents made, therefore there was a need to make sure best practice, documents and learning was brought together and used in the future.
2) Collate
“How can data or information be efficiently pieced together?”
Once all information had been collected effectively and information flows sorted, the next step is to clean, store and structure the data. Ensuring that all data collected is stored in a single place and in a format enabling analysis and reporting makes an IM’s life much easier!
Arriving two and a half months into the disaster response, the process for collating daily response data was in a single Excel table. The table contained everything from exact locations, administrative areas, sector, individual and households reached, as well as sector specific information among others. It really was the “Master Tracker” with all the data since the beginning of the response!
It was clear that the “Master Tracker” table had many additions, edits, and changes related to the evolution of the response and changing needs from the sectors meant that it was time for a revamp (which is a good thing!). The response data also now no longer matched how the sectors collected their data — we were mid streamlining data and information flows. Working with each sector and leadership, it was clear they all required their own individual analysis. We therefore created their own data structure and tables, defined by their collection, but still allowing space for iteration. All these tables then needed to come together as one providing a headline overview.
3) Analyse
“How can the data and information be analysed in a way that meets the needs of the sectors, leadership and National Societies?”, “Where is our reach and where are our gaps?”
The big one! Analysis can be many things: graphs, charts, maps, even just the representation and filtering of data.
As IM coordinator, understanding how the data being collected was going to drive decision-making, identify reach, or be used is paramount. The first version of analysis was identified at the outset, however representing data in different forms of analysis can drive further questions, and iterations — which it did!
Firstly, I focussed on the “Master tracker”, with all the response data! To show the CVM (Mozambique Red Cross Society) and IFRC impact, easy to use by sectors, understandable, quick to iterate, available offline and usable with limited internet, Excel was the tool of choice. I went about creating Excel dashboards driven by way-to-many pivot tables, one for each sector, and then an overall dashboard containing headline figures for the overall response — such as the total number of people reached — quite a big task!
All these dashboards were custom made to A4 pieces of paper, so easily printed and shared, and could be updated with one click of the “refresh” button with new data. They also included numerous filters, slicers and formulas. Sectors came to IM with new requests, identified problems and wanted new features or filters — Success!
Sectors also requested specific analysis as other types of visualisation, such as maps. The WASH ERUs (Water, Sanitation and Hygiene Emergency Response Units) for example were rehabilitating water points, supplying water to communities and building latrines. Identifying where these were, populations reached, and their sphere of influence, visually displayed the impact of their work. Other maps were produced working with the Assessment teams, identifying the progress of assessments over time and where the CVM and IFRC were planning to work in the next couple of years.
4) Disseminate
“How can we show our impact?”, “What are the total number of people reached over time?”
Ensuring products are shared and known, whether that be internal or external, enables continued feedback, iteration and communication. This may be upwards to leadership, directly to sector staff, or to volunteers. In Mozambique, the headline figures showing CVM and IFRC response were disseminated via the weekly SitRep. Some sectors included the data and/or dashboard as part of this report. Other visualisations such as maps were shared within the ERUs or at cluster meetings. Key data was used by leadership to quickly display to donors and governments the impact and reach of CVM and IFRC with up to date figures. One of the most important was reporting the total number of people reached by the Federation (IFRC and all National Red Cross and Red Crescent Societies) and Movement (including the ICRC) for the three-month Cyclone Idai anniversary!
Reflections
I had an excellent deployment! I was part of a brilliant, collaborative team where we could all share learning and experiences and come together to harmonise data and information collection, to identify the best ways and processes for data and information to be analysed and shared.
Once data and information are analysed, visualised and shared it is amazing to see the appetite grow. The part IM plays can really support sectors positively, changing the concept of ‘reporting’ to ‘analysis’ and ‘dissemination’, becoming a decision-making tool.
Being able to see the IM process from data collection in the field (yes, I did unload a few kitchen-sets at a distribution which were in my Excel “Master Tracker” and dashboard a few days later) to analysis and dissemination is amazing. It helps to make the whole IM role more understandable, enabling better collaboration with sectors and ultimately for IM to become more effective!
Thanks to all previous and future IFRC IM delegates as well as CVM, IFRC and National Societies involved in the response.
Let me know if you have any questions or comments in the section below!
Paul
