individual vs. firm By type or size of firm (MSME, SME) By sex By age
By type or size of firm: Relevant disaggregation depends on the PSD actor's portfolio. If client firms are very different in size, then disaggregation by size of firm is valuable, as the size of the companies accessing a value chain partly determines the development impacts.
By gender: Number of female self-employed individuals, percentage of women employed, and/or number of female-owned firms.
Calculations and reporting on female ownership should use regional or local laws or norms when they exist. Where laws or norms do not exist, female-owned firms could be defined as firms with a minimum of 51 percent female ownership, or a majority of women in their boards. In case shares are publicly traded or owned by institutions these cannot contribute to the number of female owned shares (adapted from IRIS ID OI2840).
By age: Number of self-employed youth, youth employed, or firms owned by youth (age 15-under 25). Calculations and reporting on youth should use regional or local laws or norms when they exist. Where laws or norms do not exist, youth workers can be defined as aged 15- 25 (United Nations, 2017)
Issue for consideration While disaggregating by gender can help understand gender issues related to interventions or investment, the data should be interpreted with care, as different explanatory factors may be at play.
Unit for measurement: Number of self-employed male or female individuals reporting new access to value chains (adapted from HIPSO). Number of firms reporting new access to value chains (adapted from HIPSO).
Coverage:
Data need to be specific to the relevant value chain, which varies by local, national or international level, sector and product. See key measurement challenges.
Delineating which clients or beneficiaries actually gained new access requires a clear definition and baseline of existing participation and new participation of clients or beneficiaries in local, national or global value chains.
Including consumers is not advised to avoid inflating the figures
Data Source: Measurement is context and intervention specific, and is best done within a confined geographic space, or in a specific well-defined part of the value chain. See key measurement challenges. Data can be self-reported by firms or individuals involved in the intervention or collected via a survey approach. Depending on the specific intervention and context, Chamber of Commerce data could be a relevant data source.
Data quality: Survey design should adhere to strict quality criteria, through internal quality checks and consultation with relevant teams. Further data verification in the field is recommended. Self-reported data may be verified by the PSD actor implementing the intervention or investment or external auditors for example checking outliers and logical inconsistencies. To assess new access to (a) value chain(s) baseline data can be valuable. As an alternative, or in addition to collecting new baseline data, existing data may provide useful information, for example on the business environment in a country, see the 46 DONOR COMMITTEE FOR ENTERPRISE DEVELOPMENT http://www.enterprisesurveys.org/ of the World Bank. Given the fundamental key measurement challenges, these challenges need to be addressed to ensure data quality, especially in terms of clear definitions and delineations of what is precisely measured and how it can be plausibly linked to the intervention.