World Humanitarian Day 2017

Photo: WFP

Photo: WFP/ Regional Bureau of Cairo

To celebrate World Humanitarian Day 2017, this week we interviewed one of the humanitarians who makes mVAM possible. Hatem works as a data scientist in the Cairo Regional Bureau so we asked him more about his work – remotely monitoring food security in conflict zones in the Middle East.

1. Duty station: Regional Bureau of Cairo (RBC)

2. Job title: Data Scientist (VAM)

3. What does your job entail? My job is mainly focused on the data analysis, aggregation and visualization of the monthly mVAM food security surveys in L3 Countries (Yemen, Syria & Iraq). The process starts with the monthly data collection done by call centres or operators. I follow up with the call centres to make sure that the data they’ve collected is in good format and has minimal or no errors. I also make sure that they are following the sampling guidelines and methodologies designed by our team in headquarters. After that, I perform some data cleaning and validation before storing the data in our database. Then, I run some statistical tests on different variables so that I can understand what significant changes there are in the data compared to previous months. According to the analysis results, trends and statistical tests, as well as secondary data/news, me and my team start to gather the most important/significant data and create a brief story that summarizes the food security situation in the country. The bulletin is usually 4-5 pages containing text narratives, charts, images and sometimes maps.  There is also usually a qualitative analysis part based on the open text comments of the respondents. It is usually an interesting yet challenging process to find new ways of visualizing open-ended comments from respondents (usually around 1,000-2,000 comments).

4. How does your work help WFP’s response in conflict zones? The mVAM bulletins provide up-to-date and almost real-time data about people that live in conflict zones who you can’t reach by any other means other than mobile phones. These bulletins inform the programme teams about their needs, the most vulnerable areas and the most vulnerable population groups such as displaced people. This ensures WFP is in a better and more informed position to take any programmatic decision on who is affected by conflict, where they are and how they can assist these people most effectively.

5. What’s the most challenging part of your job? Creating a full story from raw data. As a data scientist I usually face technical difficulties – whether it’s in the data cleaning, storage, or analysis code. However, the most challenging part is usually correlating all the data from mVAM and other sources to represent them in a meaningful and complete story that briefly describes the situation in a specific country.

6. What’s the most rewarding part of your job? Working in the humanitarian sector is very rewarding, even if it is not directly with beneficiaries. Not to mention working with data related to conflict zones where there are rapid changes and up-to-date data is in high demand. The fact that I’m a part of a process that makes other people’s lives better, especially those who are in serious need is, in itself, a huge drive to make me do what I do.

Our 5 mVAM Highs from 2016


1. Awards for Remote Mobile Data Collection Work

At the Humanitarian Technology 2016 conference, our paper Knowing Just in Time Knowing Just in Time’ won Best Paper for Outstanding Impact. In the paper, we assessed mVAM’s contribution to decision-making by looking at use cases for mVAM in camps, conflict settings and vulnerable geographies. Check out our blog Tech for Humanity for more on it and our other conference paper  mVAM: a New Contribution to the Information Ecology of Humanitarian Work

To close the year, we had a nice surprise from Nominet Trust, the UK’s leading tech for good funder. We made their 100 most inspiring social innovations using digital technology to drive social change around the world.  

2. New Tech

In this day and age there’s a lot of buzz around data visualization. We’ve been honing our skills with Tableau. Check out the data visualizations we did for Yemen and Haiti.

We’re also in the era of Big Data. We partnered with Flowminder, experts in analyzing call detail records, to track displacement in Haiti after Hurricane Matthew.  Find out more in ‘After the storm: using big data to track displacement in Haiti

We’re also super excited about the chatbot we started developing for messaging apps and our roll out of Free Basics in Malawi which is allowing us to share the food prices we collect in mVAM surveys with people in Malawi With mVAM, our main focus has been reaching people on their simple feature phones. But we know that smartphone ownership is only going to increase. Contacting people through internet-enabled phones opens up loads of new forms of communication and data collection. is still reaching people on their -free basics

3. Expansion!

mVAM expanded to 16 new countries facing a wide set of challenges: conflict, El Nino drought, hurricanes, extremely remote geographies. We’ve been tracking and learning about what remote mobile data collection can add to food security monitoring systems and what its limits are in different contexts. For some of the highlights, check out our blogs on Afghanistan, Democratic Republic of Congo, Haiti, Nigeria, Papua New Guinea, and  El Nino in Southern Africa,

4. Dynamic Partnerships

To have a lasting impact, we need to work with governments. We are really proud of our partnership with CAID, the Cellule d’Analyses des Indicateurs du Développement  under the Prime Minister’s Office in the Democratic Republic of Congo. We collaborated on setting up a national market monitoring system- mKengela that they are now running. We’ve had intensive technical sessions with the CAID team in Rome and Kinshasa to work on solutions that will fit their data management and analysis needs. The CAID team even traveled to Johannesburg to share their remote mobile data experience with other African countries and help other governments use this technology.

We’re also working with Leiden University. Bouncing ideas off of their team at the Centre for Innovation helps us move forward on tricky challenges. We’re also collaborating with them to develop an online course where we’re going to share our methodologies and how to use remote technology to monitor food security. Check out Welcome to Vamistan for more.

We are in the field of tech. So we can’t do our job well without partnering with the private sector. It’s definitely a dynamic area, and also one where we at mVAM are learning what works best in melding our humanitarian goals with the exciting private tech potential out there. Check out our blog From the Rift Valley to Silicon Valley and our hackathon with Data Mission for more.

5. Learning- the neverending process

In addition to trying out new technology, we’ve been trying to answer some important questions about the live calls, SMS, and IVR surveys which make up the bulk of mVAM data collection.  We’re also doing mode experiments to understand how people answer differently based on which mode we use to contact them. Check out our first Mind the Mode article with more coming in 2017. In Kenya, we are looking into whether we can ask nutrition indicators through mVAM methods. A major challenge is reaching women through phone surveys so we organized a gender webinar with partners to learn from what they are doing- check out our key gender takeaways. These are key questions and they can’t be resolved overnight. But we’re making steady progress in understanding them, and we’re excited for what more we’ll find out in 2017.

Thanks to everyone who has supported our work this year and kept up with our blog!

WFP Yemen M&E: Reaching Beneficiaries During Widespread Conflict

As mVAM has been expanding we’ve started to see the remote technology used in other areas of WFP’s work. This week’s blog is from Katy Huang who works for the Yemen Country Office. She shares how the M&E unit is using remote live calls to get feedback from beneficiaries about WFP’s assistance. 


WFP/-Asmaa Waguih

Before joining WFP Yemen’s Monitoring and Evaluation (M&E) unit 8 month ago, I worked as a researcher for the New York City Health Department. As I love the creative process of collecting, analyzing and reporting data, I was excited for the opportunity to manage our unit’s “remote M&E” (rM&E) system. Currently, Yemen’s Emergency Operation assists about 3 million beneficiaries a month. Our rM&E system uses an third country call center to conduct phone surveys with beneficiaries post-distribution to hear about their experiences receiving and using the assistance. The center completes about 2000-2400 surveys per month.

Before establishing the rM&E system in September 2015, we learned in a previous post-distribution monitoring survey that a large majority of our emergency in-kind food beneficiaries owned a mobile phone or had access to a friend or neighbor’s mobile. We also found out that a large majority of mobile owners were able to charge their mobiles on a regular basis. This information meant that conducting mobile surveys proved to be ideal within the context of Yemen’s ongoing and widespread conflict as it allowed us to reach large numbers of beneficiaries without compromising the safety of field monitors. Other benefits of using rM&E include it’s relative low cost and being we can reach beneficiaries in all the governorates where we offer assistance. Also, in the 15-20 minutes it takes to complete a survey, we have been able to collect all the key process and food security outcome indicators that we also collect in our longer bi-annual face-to-face post-distribution monitoring surveys. Ultimately, rM&E complements other M&E systems (i.e., on-site distribution monitoring and beneficiary hotline) to triangulate and confirm findings.


WFP/Asmaa Waguih

Although there are many benefits to using rM&E, challenges do exist. Bias is the main issue as data collected by rM&E tends to be more biased than data collected face-to-face. Some of the biases we face relate to the following:

  • Sampling frame bias: We don’t have the entire list of mobile numbers of beneficiaries for random calling. The amount of mobile numbers we receive depends on what cooperating partners collect from beneficiaries at the time of food distribution. We have had to regularly remind cooperating partners about the importance of sending us these mobile lists. In addition, some beneficiaries don’t own a mobile phone and they may have different characteristics, such as being more poor or vulnerable, than those that do own mobiles.
  • Gender bias: The frequency of female respondents for rM&E (about 5 percent) are lower than that of face-to-face (about 10 percent). This may be due to more males than females owning mobile phones. To try to address this, the call center recently hired more female enumerators to engage female beneficiaries to respond.

Despite these biases, the amount and quality of data we have been able to collect on a monthly basis have been invaluable. The large sample size has allowed us to report nationally representative data and to disaggregate data by activity type (i.e., in-kind, voucher) or demographics (i.e., displacement, gender). With regular monitoring, we are able to see trends and compare results over months and quarters. To see how we used this data for reporting, please see our Yemen M&E Quarter 1 2016 report.

For more information on mVAM’s work in Yemen, please visit the mVAM Yemen site.

Fifty Shades of Data

Thanks to new technologies, we’re collecting increasing volumes of data. Our fast-growing online databank now includes more than 100,000 records, it’s actually increased sevenfold in only the past year! We’re aware that our data might seem complex from the outside and so we’ve been working on making it more user friendly to ensure that managers and executives in our organization and the general public can easily understand it. We’ve particularly been focusing on creating visualisations so we’ve worked on dataviz with OCHA’s Humanitarian Data Exchange and recently launched our own VAM DataViz Platform. Check out years of agro-climatic data from around the world! Our mVAM data is coming soon! With all this DataViz work going on, we were therefore interested in Tableau – a widely used data analytics and visualization package – to improve and share visuals of our household data.

We decided to do a 3-day prototyping session on Tableau giving us a few days dedicated to understanding the software and applying it to our use cases. Our partners at the Center for Innovation at Leiden University facilitated the event and provided us with a venue and Tableau sent two of its specialists to show us the ropes. It was great to come together as a group to hone our skills.  The WFP participants were organized into teams that worked on different products like dashboards and storyboards.  The best product ended up being a dashboard that displayed food security and market indicators in Yemen:


One lesson that came out of the workshop was that deciding what to show on a dataviz is probably the most difficult thing to do. Understanding who the audience is and defining a message turned out to be much more of a challenge than the technical implementation. The teams that sketched out their products on paper first ended up producing the best results in the end. As in much of our experience with tech tools, the objective and the process matter much more than the shiny new toy.

winners picture for mvam blog post on Tableau

On the last day of the session we worked together with the guys from Tableau and successfully managed to embed the prototypes, incorporating them into our DataViz portal, confirming our ‘Proof of Concept’. We’re now working with open source dataviz tools, including D3, that have complementary functionalities so that we can create our hybrid portal and start putting the vision we have for our data into practice.

We’re now hoping to blow you away with outstanding data viz products, making mVAM information more tailored to the needs of readers. So keep an eye on our website!

Yemen: Against All Odds

Aden – Dar Sa’ad District, Main Roads

Dar Saad District, Aden, Yemen buildings destroyed during the conflict. Photo: WFP/Ammar Bamatraf

In July, Yemen was declared a Level 3 Emergency – the highest priority level in the global humanitarian system. At WFP, we knew we needed real-time information to track needs on the ground. Mobile surveys had worked well for us in emergencies in Iraq and the Ebola epidemic. So WFP managers in Yemen decided to launch a phone survey-based food security monitoring system.

But, would mobile phone surveys work in Yemen?

Concerns were immediately voiced: Would people readily take survey calls in the midst of a conflict? Did people have access to electricity to recharge their phones? Would the phone network function well enough let us call all parts of the country? Would people trust us?

Guess what- people not only responded to our calls but many responded consistently! We started calling people at the end of July, reaching about 2,400 people with each survey round. Many respondents- 60%- have stuck with us month to month. This means we can offer trend analysis on food security indicators- check it out in our monthly food security updates.

First WFP ship carrying food docks at Aden port as humanitarian needs soar In Yemen

Yemen is declared a Level 3 Emergency and food assistance arrives to Aden in July 2015. Photo: WFP/Ammar Bamatraf

So, what have we learned from using mobile surveys in Yemen?

  • Working with a professional call center has been a great asset.Due to the conflict, we’re placing calls from a call center outside the country. Our operators had to go through a ‘learning’ phase where they picked up Yemeni dialect — food items seem to have quirky names and vary somewhat from Arabic spoken in other countries.
  • Random digit dialing works, just be patient! We used random digit dialing because we did not have access to a phone number database for Yemen. So we created our own! A computer dialed up random numbers, using the mobile network operators’ prefixes and generating the final five to seven digits. If a phone number worked and the call went through, it was immediately routed to an operator.  As you can imagine, this took some time, but after a few weeks, we figured out what bands of numbers are active in Yemen and ramped up the call volume. We always quickly get through to people in the capital, Sana’a, but it takes longer to reach enough people in less populated governorates. Patience has been a virtue. But we’re pleased to be at the stage where we can complete a round of data collection in 2 weeks in such a complex environment.
  • A qualitative, open-ended question provides rich information. In addition to asking people a quantitative food consumption score, we have an open-ended question where we ask people to describe the food security situation in their community. We analyze these responses using tools such as pattern sentiment analysis and word clouds. In the November Yemen bulletin, our pattern sentiment analysis showed a decline that we also saw in respondents’ reports of food consumption. This correlation not only shows that we are getting reliable data through open-ended questions but also that potentially, we could use people’s perceptions of food security to measure an actual deterioration in food security.
  • Time of day for calling is important. In Yemen we learned, call at night. We had a hard time reaching respondents when we called during daytime hours. It turned out that people were keeping their phones switched off during the day to preserve the battery in order to make calls in the evenings. When the call center noticed that 90% of the calls were going through during evenings, they allocated more operators to evening shifts. This helped us reach our targeted number of respondents.
WFP operations in Abyan, Yemen

WFP is also using mobile surveys to monitor the distribution of food assistance. Here, people pick up food in Al Dew village, Abyan Governorate. Photo: WFP/Ammar Bamatraf

Monitoring IDPs, Cyclones, and Operations

Yemen is another case where mobile phone interviews have enabled mVAM to reach households located in the most conflict-exposed areas, where we could not do a survey face-to-face. We are even able to reach internally displaced persons (IDPs)- currently over 1/3 of our sample. Interviewing IDPs is key in a conflict that has caused widespread displacement.

The system has also been flexible: in November, when the southern coast of Yemen was hit by two successive tropical cyclones, we were able to immediately place calls to affected areas of Al Maharah and Abyan. Mobile surveys have also allowed us to monitor our food assistance programmes. We are also currently calling 1,200 beneficiaries every month to ask about the food they received and track their food consumption. We’ve found our results to be in line with previous face-to-face surveys, confirming the reliability of remote mobile data collection.