Two statistics present contrasting pictures. One hospital reports a very high maternal mortality rate, while another in a different district reports rates that are half as high. On paper, the first hospital appears to be performing poorly. However, in reality, it is a government-specialised hospital for high-risk pregnancies, such as mothers with severe complications that other clinics refuse to accept. The elevated mortality rate reflects the challenging cases they manage, not necessarily poor performance. Without this context, the raw numbers can be misleading.
This core issue in impact measurement across Africa is intensifying with the rising demand for quantitative evidence. Funders, investors, and regulators increasingly seek more data, more often, and in standardized formats. Organizations capable of providing such data are recognized and rewarded, while those unable to do so are ignored. However, much of the data generated often lacks the necessary context to be truly meaningful, and in some cases, this omission can make the data misleading.
Consider a company that plants 10,000 trees. While impressive, this figure provides no information about whether the trees are native species that help restore degraded ecosystems or non-native ones that may displace local flora. It also reveals nothing about community involvement in planting or ongoing maintenance. Additionally, it says nothing about the previous state of the land or how it will look in ten years. The number itself isn’t incorrect; however, without context or a story to explain it, it becomes the entire narrative.
The organizations with the most credible impact evidence are not always those with the most advanced data systems. Instead, they are the ones that recognize the limits of their data — and communicate those limits upfront. Providing an honest account of what was measured, what was not, what the numbers reveal, what they hide, and what changed versus what stayed the same is more trustworthy to a serious funder than a polished impact dashboard.
Narrative integrity in impact reporting means more than just storytelling as a decorative element for the numbers. It uses a story as a framework that renders the data meaningful—guiding the reader on how to interpret the numbers and which aspects should be approached with caution.
The necessary change is mainly epistemic rather than technological. Organizations that start with a compelling story and then support it with evidence tend to produce reports that are credible under scrutiny. In contrast, organizations that begin with data and then craft a story around it often generate reports that, while technically accurate, can be misleading on an institutional level.