Frequently Asked Questions
What was the reason for creating this map?
One of the operational principles of the PSE policy is to build and act on the evidence of what works, and what does not, in PSE. The PSE Evidence and Learning Plan guides the Agency on learning what works and hasn’t on PSE and contributes to the Agency’s Self-Reliance Learning Agenda (SRLA). The PSE Evidence Gap Map will serve as a regularly updated PSE evidence repository.
We hope the PSE Evidence Gap Map will facilitate use of evidence in PSE approaches and help target evidence-building efforts to fill the knowledge gaps that remain. The tool consolidates what is known and unknown about PSE via a thorough literature review (internal and external for the last ten years), highlighting gaps.
It can be filtered by geography, sector, industry, private sector type, and document type. The next version will have a search function to search terms in the key findings, recommendations, title, partner, and publishing institution.
USAID’s Program Cycle Operational Policy, as articulated in ADS 201, stipulates that “USAID’s decisions about where and how to invest foreign-assistance resources must depend on analyses and conclusions supported by evidence.” The policy further elucidates that the evidence base comprises “formal assessments, evaluations, and studies conducted by USAID or other development actors…[as well as] structured thinking based on experiences, insights, and internalized knowledge.”1 The mandate for USAID staff to use evidence in program design, management, and implementation is clear in this and other USAID documentation.
We live in the information age, and so it would seem that using evidence for decision-making should be straightforward and easy. However, this is not always true in practice. In the case of Private Sector Engagement, among other operational areas, one challenge to applying evidence is the almost overwhelming amount of information in some areas and the dearth of information in others. The evidence gap map provides a structure for making sense of the body of evidence around PSE and allowing users to distill the evidence base into a corpus that is most useful for their particular context. In this way, you can sift through the noise in getting to the evidence that is relevant and actionable for programmatic and strategic decisions. It also identifies areas for further evidence generation.
What gap is it filling and who will it help?
The Evidence Gap Map could just as easily be called the “Evidence Map”, meaning that it is a visual representation of existing evidence, using a matrix of USAID’s conceptualization of PSE means and value added. We hope that by compiling this evidence in one place with a number of filter and search features, we will help facilitate the use of evidence.
The “gap” in the title is referring to understanding where there is good evidence in the matrix and where there are holes in our knowledge base and understanding. As users interact with the evidence gap map and the filters, they will be able to visually see where there is knowledge and where additional investments in research and evaluation might be warranted to further build the evidence base. This is also an opportunity to collaborate with our team as well as alert us to any evidence we may have missed.
The map was designed for a primary audience of USAID technical staff and program designers. Secondary intended audiences include USAID implementing partner staff and private sector employees seeking to engage in development work.
How did you collect the evidence currently in the map?
The EGM team began the process by obtaining a list of PSE project numbers for the past 10 years in the agency. These project numbers served as a vehicle for searching the Development Exchange Clearinghouse for all information related to those project numbers. A list of evidence types was generated in partnership with USAID, and all the documents within the acceptable evidence types were reviewed and tagged with metadata.
The USAID PSE team also provided a set of search terms which were used to search external databases and repositories, allowing us to include additional materials in the EGM. These additional materials underwent the same review and tagging process as the internal documentation.
What partners did you work with to collect the evidence?
The key partner for this work was USAID’s Center for Transformational Partnerships team, particularly the group tasked with implementing the Evidence and Learning strategy for the PSE policy. They provided valuable input, feedback, and direction throughout the process. We also worked with the Notre Dame Center for Research Computing in building the visualization and webpage components of the EGM.
How did you decide how to categorize pieces of evidence that could fit into multiple categories?
In discussions with the EGM team and USAID, the decision was made to make tagging and categorization as inclusive as needed. In other words, if a document fit in multiple places in the framework, the document was tagged accordingly. As such, do not be surprised if a resource pops up more than once in the framework.
What else about the process might be interesting to potential users of the map?
We view the EGM as a live resource, meaning that the process of identifying and tagging relevant evidence is ongoing, and the resource will continue to be updated as new materials become available. We encourage users of the EGM to contribute resources that they might be aware of that is not present in the EGM or to suggest corrections to the existing resource categorizations.
What's the most valuable way for people to use the map?
The most valuable application of the map is for people to use it to use the filters and categories to get at the evidence that is most directly relevant to one’s context. In this way, instead of seeing the EGM as a repository of hundreds of resources, one can see it as a tool to weed out those PSE resources that are not useful for informing clear and present evidence needs. There is also a search functionality in case users would like to further query the repository using key words that go beyond the built-in filters.