Distilling Diagnostic Analysis and Findings

When the diagnostic is complete and the project team has reviewed the supplementary questions and gathered applicable country information, the next step is to integrate the desktop and field-based findings. Teams should use all findings to conduct an informed exercise that prioritizes the gender-related issues revealed during the diagnostic process, taking into account short-term versus long-term goals and issues repeatedly raised in the focus groups and interviews. Prioritizing potential interventions should also reflect discussions with the in-country government and key stakeholders to discern their priorities and views on feasibility and costs and to foster potential implementation partnerships. See below for guidance on how to develop multimethod analysis using both quantitative data and qualitative information.

Multi-Method Use of Qualitative and Quantitative Data

Economists are trained to value quantitative data, but qualitative interviews can be seen as insufficiently “objective.” From the broader perspective of social science research, however, the two types are complementary and preferable when used in a multimethod analysis. The quantitative, “macro” data offer a view from a distance, but no explanation for results. The qualitative information offers a ground-view explanation, but with the limitations of a local perspective.

A multimethod analysis is especially required for evaluating women’s economic data because of (1) significant measurement gaps remaining in available data, and (2) the high risk of projecting analyst bias to explain quantitative data.

The process is to tack back and forth between methods, checking one against the other to validate, reconcile, or select the final findings, sometimes by using additional sources. Below is a process diagram that provides a structured approach to synthesizing quantitative data and qualitative information into a coherent diagnostic analysis.

Multi Method analysis

Validating Analytical Findings

Findings from the diagnostic provide both the information needed to conduct a comprehensive analysis and the underlying details project teams can use in designing interventions directed toward women entrepreneurs, focusing on those with a digital component and that have been designated by multiple stakeholders in the entrepreneurial ecosystem as desirable and useful. Findings from the desktop and field-based diagnostic should help identify potential interventions of benefit to women entrepreneurs and highlight for policy makers existing environmental constraints, allowing them to respond by supporting and encouraging the emergence of new female entrepreneurs and the growth of existing enterprises. The diagnostic can also inform policy reforms with broad benefit to women-owned microbusinesses, women entrepreneurs, and WSMEs and that specifically improve the country’s ease of doing business. The findings can be shared with governments to help policy makers formulate actions that reflect gender awareness and promote entrepreneurship across all sectors and industries, ultimately contributing to inclusive and sustainable development.

The toolkit’s diagnostic process was piloted in Peru to validate the scope and usefulness of the automated data-generation tool, to test content and protocols of the field-based discussions and to provide an initial set of recommendations to the government.