Supporting Evidence-Based Interventions (SEBI)

Programme 2

Data collection and modelling: Implementation of the BMGF harmonized indicators-framework through building an open data modelling Community of Practice (CoP).


To establish livestock productivity baseline data in the priority geographies, continue development of predictive models for measuring impact of interventions, and establish a global community of practice (COP) to promote and support further application of livestock data, models, and analytics.



  • Development of a platform for the integration of grant level monitoring data using a set of harmonised indicators. 
  • Strategic ex-ante analysis of productivity enhancing interventions for Ethiopia, Nigeria and Tanzania. 
  • Establishment of a novel, open, global community-of-practice focused on improving access to, and utilization of, improved livestock data and analytics.



To strengthen the priority setting, planning, and monitoring capabilities of key partners and stakeholders in the livestock development community.  The integration of a range of analytical approaches will improve the abilities of practitioners to better assess the potential impacts of a wide range of productivity enhancing and poverty reducing livestock interventions.  As improved data assets accumulate - over time, theme, and geography, particularly from grant level monitoring and outcomes, the broader livestock community will gain insights into the comparative merits of different technologies, services, and business models. 

The Livegaps2 project, under SEBI Program 2, identifies ways to maximise yields in livestock systems for poverty alleviation, global food security and sustainability. They achieve this by using new information from surveys and livestock monitoring systems to develop livestock and household simulation models. For more information on Livegaps, please check out the new  LiveGAPS website.



Current partners on Program 2 include the following (additional partnerships may be established as the program matures):