SEBI-Livestock mobilises data and generates insights to inform investment decisions
What we do and why
Funders need evidence to make informed decisions on how to allocate resources for livestock development initiatives that can make a difference to farmers local economies in low-and middle-income countries. They also need to know whether the interventions they have funded are working, and where further efforts are needed. SEBI-Livestock works on behalf of the Bill & Melinda Gates Foundation to monitor projects in their livestock portfolio. We provide data insights that help track progress, understand impact, and guide future investments.
Objectives
We aim to develop tools and measures that allow the foundation and its grantees to enhance their data, track performance, and inform future investment decisions. Our long-term ambition is to contribute to globally relevant metrics which allow donors to work more effectively with national governments and the private sector on livestock development.
How we do it
SEBI-Livestock works closely with the foundation and its grantees to develop indicators and disseminate best practices in Monitoring and Learning. At the project level, we help grantees to report on these indicators, allowing them to demonstrate the impact of on-the-ground activities.
To help the foundation understand the overall impact of their investments, we use rigorous and comparable measurements which allow analysis of aggregate impacts for the entire portfolio of livestock projects. We also collaborate with evaluators at an agriculture sector level to help the foundation understand the role of livestock in sector level and economy wide change.
We are building models to estimate the impact of interventions, and we will collaborate with grantees to provide feedback on results and ground-truth findings.
SEBI-Livestock will collate and curate data about the wider livestock development context, including health, production, populations, gender, nutrition, economics and the environment. Given that datasets relevant to livestock are often difficult to access or are not available, we will work with our partners at the University of Edinburgh’s Bayes Centre to employ innovative data generation techniques that can extract data and insights from new sources. Application of state-of-the-art techniques such as machine learning and data scraping can accelerate the development of novel datasets at scale, while ensuring transparency, repeatability of work, and up-to-date data.
To foster learning, SEBI-Livestock will amplify communication and engagement on livestock monitoring and learning (ML) through the well-established LD4D Community of Practice, which includes livestock grantees and modelers.
Key activities
- Develop and disseminate best practices for monitoring and learning across the livestock portfolio
- Support the foundation and the livestock data sector with a data repository, analytics, and innovation
- Provide access to a continually improving repository of contextual datasets via livestockdata.org
- Foster learning from historic livestock portfolio investments, with the potential to expand to the broader livestock community
Related stories and publications
- Scientists deploy machine learning to close data gaps on Ethiopian animal health
- Veterinarians get data-savvy to map livestock health
- Working together to track the impact of livestock development projects
- What do we know about livestock diseases in Ethiopia? A birds-eye view of recent evidence
- We need new ways to measure animal health
More information
The work package on Monitoring & Learning is led by Dr. Louise Donnison, Senior Data Scientist.
Header photo: Researchers from the International Livestock Research Institute African Chicken Genetic Gains (ACGG) project in Tanzania review vaccination schedules for Sasso day-old chicks. Photo: ILRI (source).