A single statistic can tell an important story—but it rarely tells the whole story.
In public health, the way data are selected and presented can shape public perception, influence policy decisions, and affect how resources are directed. When complex issues are reduced to a single indicator, however, important context can be lost, leading to interpretations that may be numerically accurate but contextually incomplete.
The Risk of One-Sided Data Narratives
Consider adolescent birth rates. A decline may suggest progress in some aspects of adolescent sexual and reproductive health. However, this indicator alone cannot explain why the change occurred or whether other aspects of adolescent health improved at the same time.
A meaningful assessment requires looking beyond the birth rate to related measures, such as access to sexual and reproductive health services, contraceptive use, educational participation, and other determinants of adolescent well-being.
The same principle applies to other health challenges. An improvement in a service-coverage indicator does not necessarily imply comparable improvements in service quality, equity, or health outcomes.
The question is therefore not simply, “What does this indicator show?” but “What else should we examine to understand the situation?”
From Single Indicators to the Bigger Picture
This is where the Multisource Data Analytics and Triangulation Platform (MSDAT) becomes valuable.
MSDAT brings together health data from multiple sources, allowing users to examine related indicators, compare trends, and explore differences across locations and periods. Rather than viewing an indicator in isolation, users can interpret it within a broader evidence base.
For example, when examining adolescent health, users can view trends in adolescent birth rates alongside other available indicators of reproductive health and service access. This can help move the conversation from “Is the number going up or down?” to “What does the broader evidence tell us?”
Why Triangulation Matters
Triangulating multiple indicators does not mean that every indicator will tell the same story. Differences between data sources or indicators can themselves provide useful signals for further investigation.
This approach can help policymakers, programme managers, analysts, and other stakeholders:
- Identify patterns that a single indicator may obscure.
- Investigate unexpected or conflicting trends.
- Understand health issues across multiple dimensions.
- Ask better questions before making decisions.
- Inform interventions using a broader body of evidence.
From Data Narratives to Data Intelligence
In an environment where statistics are increasingly used to support competing narratives, responsible data use requires more than selecting a statistic that supports a particular argument.
It requires examining the evidence from multiple angles.
MSDAT supports this approach by bringing diverse health information together in one platform, enabling users to explore trends, compare indicators, and develop a more nuanced understanding of Nigeria’s health landscape.
Before drawing conclusions from a single statistic, look at the bigger picture. Explore MSDAT and use multiple indicators to move from one-sided data narratives to evidence-informed health intelligence.
Bibliography
- Angela Montesanti Porter. (2020, October 7). Triangulation for improved decision-making in immunization programmes. https://www.technet-21.org/en/topics/triangulation
- Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures and their consequences. SAGE Publications. https://doi.org/10.4135/9781473909472
- World Health Organization. (2018). Big data and artificial intelligence for achieving universal health coverage: An international consultation on ethics. World Health Organization. (World Health Organization)
