Poverty Data Use Cases
Organizations that measure household poverty can use that data to report and improve their social performance. The following are common use cases for poverty data. If your organization uses the PPI, one or more of these use cases may apply.
Measuring Poverty Outreach
Simply put, an organization’s “poverty outreach” represents how well they are reaching the poor. After surveying at least a random and representative sample of households with the PPI and averaging those households’ poverty likelihoods, a practitioner can determine the percentage of those households that are living below the poverty line. From this data, the practitioner can analyze the organization’s poverty outreach in terms of poverty concentration, scale, and penetration. “Concentration” refers to the percentage of an organization’s clients who are living below the poverty line. “Scale” refers to the total number of poor clients served by the organization. “Penetration” contextualizes scale by comparing it to the number of poor households in the area. An organization may wish to analyze its poverty outreach by one or more of these definitions, depending on its mission and strategy.
Benefits of this analysis:
- Provides a stronger understanding of characteristics of current customers
- Assesses the organization’s methods for reaching the poor
Example case study:
- Poverty Outreach of Selected Microfinance Institutions of the Philippines (PDF, English)
- Microfinance in Karnataka, India (PDF, English)
- PT Ruma (PDF, English)
Benchmarking
Benchmarking is the comparison of an organization’s results to an industry standard or best practice. It is a popular method used by organizations to assess their performance and gain valuable insights into their relative performance. An organization that uses the PPI can benchmark its poverty outreach to national and regional poverty rates. The Guide on Benchmarking Poverty Data with the PPI provides practical advice on this analysis.
Benefits of this analysis:
- Contextualizes poverty outreach
- Helps to objectively assess a targeting strategy
- Provides an objective measure of performance for stakeholders
Example case study:
- Rags2Riches (PDF, English)
- Microfinance in Karnataka, India (PDF, English)
Segmenting Customers and Clients
PPI Users can use results from the PPI to segment clients by poverty level to assess differences in product uptake, performance, and program attrition. Segmentation can also be used in market research to better understand the needs of the specific client groups you are targeting.
Benefits of this analysis:
- Reveals correlations between certain characteristics and poverty bands
Example case study:
- CARD Bank (PDF, English)
- Friendship Bridge 2013 Impact Report (PDF, English)
Screening or Targeting
Many organizations include a household’s poverty level as an eligibility criterion for services in order to direct services to the households that need them the most. Organizations may screen out clients that are less likely to be poor, or combine poverty level with other characteristics to create a more holistic targeting strategy.
Benefits of this analysis:
- Helps the organization achieve the desired poverty outreach
- Directs services to the desired type of customer or client
Example case study:
- PRISMA Microfinance (PDF, English)
- Marie Stopes International (PDF, English)
Tracking Changes in Poverty
When an organization samples a representative sample of clients at multiple points in time, it can track changes in the rate of poverty among clients. While reduction in poverty does not automatically prove that the organization’s services are the cause, it is an essential part of an impact analysis.
Benefits:
- Reveals how client lives are changing
- Makes it possible to analyze impact on poverty
Example case studies:
- Drawing Insights on Poverty Movement with Multi-Year PPI Data (PDF, English)
- Grameen Koota (PDF, English)
Combining Poverty Measurement with Other Indicators
The PPI provides an objective measure of client poverty related to household expenditure. . When an organization analyzes client poverty levels alongside other survey results and indicators, it can gain richer and more meaningful insights about its clients.
Benefits:
- Gain richer and more meaningful insights about client households
- Meet industry standards such as the USSPM, COSA, and others.
Example case study:
- Chirag (PDF, English)
- InterMedia (Blog, English)