Happy Project

he Mastercard Foundation in partnership with Agri-Impact Limited has rolled out an ambitious and transformative program dubbed Harnessing Agricultural Productivity and Prosperity for Youth (HAPPY) to be implemented by eight Implementing Partners including NewAge Agric Solutions, National Service Scheme (NSS), Ghana Cares (MiDA), Ghana Enterprises Agency (GEA), Ministry of Food and Agriculture (MOFA), TechnoServe, Catholic Relief Services (CRS) and Jobberman. 

HAPPY is built on 3 intervention areas: i) increasing production and productivity within the poultry, rice, soybean, and tomato value chains, ii) promoting value addition, fostering entrepreneurship, and facilitating market development and iii) developing strategic policies and advancing youth, gender, social inclusion and voice and agency.  

The program aims to create 326,000 dignified and fulfilling jobs for youth (70% women) and persons with disability, increase food production by 190,000 tons, generate annual revenue of over $200million, and increase agricultural productivity in rice, soybean, tomato, and poultry value chains to reduce import of strategic foods by 10%.

Under HAPPY, Agri-Impact Limited is collaborating with the E-Learning Centre of Kwame Nkrumah University of Science and Technology (KNUST) to roll out the e-HAPPY Project. The e-HAPPY training programs seek to deepen the use of ICT, and youth-led digital solutions to transform the agri-food systems in Ghana. 

The objectives of e-HAPPY Program include;

• Build the capacity of 100 selected youth in the use of innovative digital technological and pedagogical tools through tailor-made coaching modules.

•  Train 500 trainers of trainers (TOT) youth to become HAPPY Program ambassadors to drive a technology-driven agribusiness ecosystem.

• Repurpose/co-create selected content suitable for virtual environments with Agri-impact partners.

• Create targeted, innovative online training/technology transfer modules based on identified needs along the Agri-food value chain.

• Equip youth to use programming for integrating and programming Internet of Things (IoT) devices in agriculture while using machine learning concepts to develop models for predicting crop yields, pest outbreaks, or optimal environmental conditions based on historical data.