This case study describes KOMIDA’s journey towards implementing the PPI and using the results to improve its products and services to clients. The initial objective of adopting this tool was to understand client outcomes. Yet over time, KOMIDA realized the power of social data, particularly of PPI, in understanding client needs as well and, thereby, in enhancing its own ability to offer products and services that meet these needs.
Case Studies & Reports
Summary of Findings Across Four States of Uttar Pradesh, Madhya Pradesh, Odisha and Bihar
An examination of the portfolio of microfinance institutions across the four PSIG states revealed that nearly half of new MFI client recruitments are happening between the $1.25 to $2.5 2005 PPP Poverty Line segment, with a third between $1.25 and $1.88 2005 PPP Poverty Line segment. Against this encouraging sign it is to be noted that there is ample scope to expand the access of microfinance in the PSIG states below the $1.25 2005 PPP Poverty Line, especially to the poorest of the poor, as well as a need to spread its outreach to specific pockets hitherto highly underpenetrated.
This short case study describes how Friendship Bridge, a microfinance organization based in Guatemala, used data from the PPI to segment their market and build customer personas.
(excerpted from course materials for the +Acumen online course "Market Segmentation at the Bottom of the Pyramid")
This case study provides an overview of why Pride MDI chose to adopt the PPI, and articulates the organization’s challenges and learnings as it moved from piloting the PPI to integrating the tool into its core banking system and across all its branches. It also details how the organization intends to use PPI results going forward, to understand if its services are actually reaching poor clients, and to improve its services to better meet their needs. Lessons learned from Pride MDI’s experience will be a great resource for other organizations that plan to use the PPI, particularly those who are considering integrating the tool with their existing information systems.
This study randomizes the interview method for the Progress out of Poverty Index®, a short survey for estimating consumption-based poverty rates for participants in propoor programs. A face-to-face interview in participants’ homes is the most accurate, but it is also the most costly. In the test here in a poor, rural area in India, mis-reporting is disconcertingly frequent, yet the distribution of responses to survey questions—and estimated poverty rates—usually does not differ systematically between a given alternative method and the at-home benchmark. Estimated poverty rates, however, do differ across alternative methods, because completing an interview is linked both with the method and with participants’ poverty. To the extent that these results generalize, the PPI® can be used with alternative interview methods without affecting results as long as the alternative uses an enumerator and has the same (high) completion rates as with face-to-face, at-home interviews.
IFC partnered with the Grameen Foundation, the Cisco Foundation, and 14 MFIs that agreed to participate in this study. It covers six Latin American countries: Peru, Colombia, Bolivia, Ecuador, Guatemala, and Nicaragua. The study utilizes information these MFIs have collected in terms of poverty likelihood – using the Progress Out of Poverty® Index – supplemented by in-depth interviews with industry experts. The study found that MFIs that focus their commercial strategies in regions with higher percentage of poor reach more poor people. It also highlighted that the search for less competitive market segments – rather than principled mission statements – seems to be driving greater poverty outreach. This report also points to areas for further research. IFC is committed to this study of outreach, and development impact of microfinance institutions, and the market forces which affect them over time. By sharing the results of this research, and contributing to the debate around such topics, IFC seeks to support the development of the industry as part of its goal to reach universal access to financial services by the year 2020.
After 10 years operating the AIS Integrated Community Development Program in Bawal, Haryana, both AIS and their program partner, Youthreach wanted to better understand the impact of their outreach. They commissioned Grameen Foundation India to undertake a cross-sectional study on the changes in the lives of their beneficiaries, using the PPI to correlate the data with poverty-level segmentation.
This report uses PPI data from two MFIs in the Philippines to explore what types of poverty movement analyses can be carried out with multiple years of PPI data and what implications can be drawn from such analyses.
This publication lists the organizations that have reported that they are using the Progress out of Poverty Index® (PPI®), identifies trends among those organizations in terms of their missions and locations, and provides short case studies on a small number of such organizations. Its purpose is to commend the organizations that are using the PPI for their commitment to social performance management. This report may also serve advocates of social performance management by illustrating how poverty measurement with the PPI has been received around the world.
Chirag is a rural development organisation based in the Kumaun region of Uttarakhand in India. This case study explores how Chirag used the PPI to gather absolute poverty data to supplement the relative poverty data it was collecting via other means.
This report summarizes studies on the accuracy of the PPI when delivered via SMS or at a central location that is not the client's home.
Based on A Representative State-wide Study of Microfinance in Karnataka, India
This case study explains how an eco-ethical fashion company in the Philippines uses poverty data in pursuit of its social goals.
This case study explores how Gratia Plena Social Action Center (SAC-GP), an agricultural development organization the the Philippines, has used the Progress out of Poverty Index®, or PPI®, to better understand the needs of poor farmers.
This groundbreaking report analyzes PPI data from 10 microfinance institutions (MFIs) in the Philippines to illustrate how MFIs and other pro-poor organizations can use poverty measurement data to evaluate their social performance.
Marie Stopes International (MSI), a family planning organization, uses the PPI in Ghana to understand the poverty rates among its clients.
This case study illustrates the use of data analytics – including the use of the Progress out of Poverty Index® (PPI®) – to strengthen CARD Bank’s savings strategy. Grameen Foundation worked with CARD Bank extensively during its Microsavings Initiative, a three-year project funded by the Bill & Melinda Gates Foundation.
This case study illustrates how PRISMA Microfinance, an MFI in Peru, has collected three years of PPI data to reach and serve its target clientele. It also discusses the challenges and opportunities that the institution is facing and how it plans to address them.
Since 2008, Fonkoze has been using PPI and food security data to monitor and evaluate the progress of clients participating in its targeted programs for hurricane relief. Fonkoze is now also using it for earthquake recovery efforts.
This case study shows how PT Ruma, the first technology-for-development initiative to use the PPI, applied its findings to guide twin goals to reach more poor women with its mobile phone business microfranchises and to affirm its social accountability to shareholders.
The case study explores how Grameen Koota, a leading socially-focused microfinance institution in India, is using the PPI to measure and track its clients’ movement out of poverty.
In 2009, the Grameen Foundation selected CARD Bank, a Philippine microfinance institution (MFI) with over 580,000 clients, to participate in its Microsavings Initiative. This case study describes how CARD Bank has used the PPI to identify opportunities for product cross-selling.
This case study describes the role of Grameen Foundation in developing training programs for Oikocredit partner MFIs in the Philippines and Peru.
This case study describes how NWTF, an early adopter of the PPI, piloted and implemented the new poverty assessment tool. It outlines the experiences of NWTF management and staff as they made key decisions related to testing and data analysis.
This paper examines if a Rural-Only or Urban-Only PPI for India is significantly more accurate than an All-India PPI.
