This document presents gender performance indicators and how well women are being treated. If an institution is targeting women, as 74% of microfinance institutions do, then it should be able to measure how well it is serving women. Similarly if an institution's mission declares a commitment to women, then performance should reflect that commitment. Recognizing a lack of information beyond basic measures, Women's World Banking set
out to develop an evaluation framework that defines the key metrics that will allow microfinance providers to measure how effectively they are serving women, both internally and externally.
- Microfinance needs a universal analytic framework to measure gender performance if the industry is to move "beyond the numbers," to consider not only how many women it serves, but how well and with what outcomes.
- The indicators of the gender performance framework outlined in this manual are organized within several areas: 1. Client-Centric Focus 2. Institutional Focus 3. Financial and Social Outcomes.
- This report flags the corresponding Social Performance Task Force (SPTF) Universal Standards for Social Performance Management (USSPM), Smart Campaign's Client Protection Principles, and the Pro-Poor Seal of Excellence.
- Only by measuring commitment to women throughout the organization will an institution be able to truly gauge whether it is meeting its mission and truly serving their women clients.
- According to data published by the World Bank, 62% of projects that included substantial gender indicators delivered positive outcomes, as compared to only 30% of those projects that did not include gender indicators.
- Research conducted by the Pro-Poor Seal of Excellence suggests that disaggregating data by gender is relevant and useful in measuring and evaluation.
- analyzing indicators for institutions that have either men or women clients that comprise 10% or more of their client base. For institutions that have fewer than 5% of men or women clients, it may not be a worthwhile exercise to disaggregate the data by gender.