This session introduced Start Ready, a new financial service for the humanitarian sector that will use climate science, risk protection mechanisms, and financial best practice to protect more people against predictable disasters worldwide. Start Ready will sit alongside the Start Fund in Start Network's financing facility.
Recently the Start Network partnered with Complexity University and Global Fund for Community Foundations offering organisations a unique opportunity to take part in a radical experimental intiative. Global teams engaged in an intensive course looking at how we can work together to transform the humanitarian aid sector from the ground up. In this session, we presented the outcomes from the Crisis Response Resilience Lab and showcased some of the teams experiments and lessons from the innovation course.
This session provided an overview of Start Fund Bangladesh and Start Fund Nepal, and provided a platform for Start Network member and partner organisations to share what they have learned through the development and delivery of local Start Funds.
This session looked at the global Start Fund's lessons learnt, particularly focusing on locally-led decision making and enabling humanitarian action (by unlocking access to funding). It included findings from the localisation pilot and added value of local organisations leading humanitarian action
Analysis of humanitarian financing from 2014 - 2019 found that funding pre-organised in advance, based on pre-agreed triggers or plans (predominantly through regional risk pools and anticipatory humanitarian action systems) was equivalent to less than 1% of the UN appeals funding. However, more than 50% of humanitarian crises are somewhat predictable.
Humanitarian actors play an important role in disaster response in Bangladesh. As such, their decisions and actions can have a profound effect on the daily lives of disaster affected people. However, the accountability framework being used by different humanitarian agencies are different and to some extent inadequate to hold humanitarian agencies accountable to the affected people in rapid response. Affected people lack an effective voice in the decision-making process of the humanitarian agencies. Hence, new tools and mechanisms are needed at the local and national level to make the humanitarian actors more accountable to affected people and communities.
Humanitarian actors play an important role in disaster response in Bangladesh. As such, their decisions and actions can have a profound effect on the daily lives of disaster affected people. However, the accountability framework being used by different humanitarian agencies are different and to some extent inadequate to hold humanitarian agencies accountable to the affected people in rapid response. Affected people lack an effective voice in the decision-making process of the humanitarian agencies. Hence, new tools and mechanisms are needed at the local and national level to make the humanitarian actors more accountable to affected people and communities.
This handbook details the procedures which govern the use and allocation of the Start Fund.
This new quarterly one-page brief summarises some of Start Network’s key learning from January to March of 2021. The brief talks through the key learning takeaways and provides links to more detailed reports. It focuses on Ways of working: how can we improve our evidence and learning? Programmes: what to consider when implementing programmes and What we want to learn more about. The brief is provided in English, Spanish and French.
The humanitarian impact of extreme heat is an increasing concern, especially in low-income countries with limited access to quality healthcare and informal dwellings which can trap heat. This report analyses the knowledge, attitude and practice of Karachi residents in relation to managing extreme heat. It was conducted in 2020 following a messaging campaign led by HANDS related to extreme heat. The project was triggered through a disaster risk financing approach, using a heatwave model to trigger funding automatically when extreme heat was forecast.
