Hi, my name is Shenkut Ayele, Early Warning Assessment and Response Manager with Catholic Relief Services (CRS) for the Joint Emergency Operation (JEOP) in Ethiopia. JEOP is a USAID-funded emergency food assistance program that over two years is providing food aid to almost 1 million people. The program operates across Ethiopia and is a partnership between many agencies and government.
Until last August, I faced serious challenges: data were slow to arrive and often of poor quality. As a result, reports were delayed and decision-making hampered with serious consequences for JEOP’s ability to respond effectively. However, since August 2012, JEOP has been using an innovative solution that is strengthening our ‘Participatory Early Warning and Response System’. We are using DataWinners, an SMS-based solution implemented in partnership with Human Network International. Registered individuals across 79 districts collect and upload data via SMS each week onto a web-based database. I am able to use these data in real time to inform decision makers. Here are two graphics how the system works and the data collection and information flow.
Lessons Learned: After implementing our system for one year, we have learned that:
- Vulnerable communities should be viewed as both sources and recipients of early warning information.
- Adoption of our new SMS-based system has empowered local officials who are now using the reports to undertake better estimates of the number of individuals who might be affected by a disaster.
- Local officials are better able to represent the needs of vulnerable communities in discussions at higher levels of government.
- Local officials and others in JEOP have found the better quality data has improved their ability to target the most vulnerable communities.
- The system has the potential to accommodate other innovative uses, and government officials have expressed their interest to adopt the SMS system more widely.
Hot Tip: An effective SMS-based system provides a strong basis for a participatory early warning and response system because it enhances the likelihood that any data generated will be used to support better decision-making among different users.
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