1. TechFit Group 2

2. Framework development Collect context measures to link to technology attributes – find the link between decision steps 1 & 2 Determined categories & measures: – Land & NR base (e.g. wage/land, %grazing, tlu/ac) – Labour & markets (e.g. labour/milk, % milk sold) – Inputs & services (e.g. ext contacts, credit, suppliers) – Complementary technologies (%crossbred, mech.) – Capacity (e.g. schooling, mobile phones, groups) – Tradition & culture (e.g. gender, openness to change)

3. The village (1) Collected data to determine context measures Mason village near Nainbagh bazaar – N30.5662; E78.05044, 1211m Rainfed intensive cropping Livestock mainly dependent on grazing, cut & carry (CPR) & crop residues Increasing labour shortage (schooling, jobs) Improving market access Livestock numbers (cattle) have declined Milk sales have recently increased

4. The village (2)

5. The village (3) Few key informants (well exposed) NGO representative supported Many quantitative measures seemed sufficiently easy to achieve (market linked) Framing questions was critical (wheat bran feeding was initially overlooked) Required level of detail not easy to determine (cows & buffaloes) Difficult to follow logical thread while going through check-list

6. The process What we did with what we found in the village – Collected context data validated context measure check list – Collapsed measures into scores to enable matching Setting up our matching system – Determined correlated technology scores (land requirement, labour requirement, novelty) – Deduced that thresholds are more than matches – Found two types of scores: resources & requirements

7. Is feed the issue? All possible feed technologies (74) Thresh hold reached? Does context resource score equal or exceed technology requirement score? Does technology supply score equal or exceed context requirement score Technologies ranked by fit to context (Tech FIT index) Short list of contenders (<5) Participatory social- economic assessments The TECH that FITs ® Assess biophysical requirements Cost benefit, gender, culture Do something else Technology attribute measures (1- 74). Globally constant Score - (Scale 1-5) Location specific Context measures Score - (Scale 1-5)

8. Our example

9. Gaps Data – Quantification of use and management of CPR – Seasonal feed composition – Bio-physical requirements of interventions (apply to short-list Integration with Feast Reflection on audience (Which capacity is required to collect context data and to determine scores)

10. Next steps Refinement and testing of context measures Improve the link between context attribute measures and context scores Expand list of technologies Improve link between technology attribute measures and technology scores