Number/percentage of target population <households, productive organisations, MSME> apply new acquired <knowledge, skills> promoted by the project to <strengthen, diversify, protect> their livelihoods [specify if necessary: improve the primary production or MSME, acquire a paid job, etc.] - Livelihoods Centre
Asset Publisher
Number/percentage of target population <households, productive organisations, MSME> apply new acquired <knowledge, skills> promoted by the project to <strengthen, diversify, protect> their livelihoods [specify if necessary: improve the primary production or MSME, acquire a paid job, etc.]
Code: | KOI-5-2 |
Result Level: |
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Objectives: |
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Description: | Change in number of people applying newly acquired skills / knowledge promoted by the project to improve (strength, diversify, protect) their livelihood activities. Increased application of knowledge and practices gained in all kind of livelihood activities: • primary production: application of best practices in agriculture; livestock; forestry; fishing • transformation and production processing • income generation activities and employment: improve or launch a business, get a paid job Definitions: • MSME: micro, small and medium enterprises (formal or informal) |
Disaggregated By: | Geography/Livelihoods zone; Gender, age, disabilities, chronic diseases (for individuals, associations members, etc.); Head of household’s gender, age, disabilities, chronic diseases, dependency ratio (for households), and any other relevant criteria, such as urban/rural context, religious, ethnic or political identities; Wealth groups; Livelihoods group (e.g. pastoralist, farmers, traders); Period to achieve the objective; Consider disaggregation of information by trained and non-trained households. |
Direction of change: |
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Data source: | Both secondary and primary data collection can be used according to context. • Baseline/Endline. If multiyear programme consider also a mid-term evaluation. • Secondary data. Reliable/relevant sources from other actors, clusters or government (e.g. assessment information). Unit of Measurement: Population (trained people) but can also be households, productive organisations, or MSME. If percentage: • Numerator: Number of trained people that is applying new knowledge / skills. • Denominator: Total number of trained people Data Collection methods: Secondary data analysis; Households Surveys and Focus Group Discussion; Key informant interviews; Productive organisation, MSMEs survey, focus groups and MSME records; Observation (crops, herds management, etc.) |
Sector/Subsector: |
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Source: | LRC-1 |
Examples: | At the end of the project X% of target farmers from Somaliland and Puntland (from those Y% are women) apply new livestock rearing and management techniques promoted by the project and the extension system to strengthen their livestock production. At the end of the project X% of target traders and small-medium businesses from Somaliland and Puntland (from those Y% are headed by women) apply new market techniques promoted by the project to strengthen their business. At the end of the vocational training programme X% of trained people (from those Y% are women) apply new knowledge to acquire a paid job. |
Measure Notes: | Measure the use of gained knowledge (all of them or one part). Typical approaches look at "X out of Y key practices" that drive productivity or quality. Measure application of good production practices and their effects such as: change of household income; change of market links, etc. (depending on the acquired knowledge). [primary production] Consider seasonal calendar to determine when to measure the indicator (e.g. main harvest, pests and diseases prevalence). [employment] Consider measuring not just quantitative aspects (get a new paid job) but also qualitative aspects (such as: prepare a CV, self-confidence, know worker’s rights and duties, etc.). |