Abstract

Persistent last-mile data gaps continue to undermine development planning and evidence-based policymaking across many emerging economies, particularly at the sub-national level. This paper presents a novel and operational response: Nigeria’s first Citizen-Driven Community Mapping System, pioneered by the Benue State Bureau of Statistics. The initiative demonstrates how community actors, specifically traditional governance structures, can be formally institutionalised within an official statistical system to expand coverage, strengthen trust, and improve data timeliness without compromising statistical quality or integrity.

Launched in January 2026 through a pilot in Gwer West Local Government Area, the model moves beyond extractive data collection by positioning community members as active data owners within the statistical process. Traditional rulers are formally designated as community data coordinators and integrated into the official statistical framework. Using standardised, offline-capable mobile applications, they collect granular, georeferenced data across critical domains including infrastructure, agriculture, and social vulnerability. The system embeds automatic disaggregation by gender, disability, and displacement status, ensuring inclusive representation and policy relevance. Participation by traditional authorities has been driven by clear community benefit and alignment with existing public service responsibilities, rather than financial incentives.

To safeguard adherence to the Fundamental Principles of Official Statistics, the system is underpinned by a three-tier validation framework. This comprises initial verification at the community level, structured spot checks by local government supervisors, and final audit by Bureau statisticians. This governance architecture balances decentralisation with institutional oversight, ensuring data credibility while extending statistical reach into previously under-observed areas. The paper presents early pilot evidence, including coverage expansion, validation outcomes, and operational lessons arising from the integration of community-led data into official statistical workflows.

The initiative is locally anchored and supported by participating Local Government Councils and development partners, and is designed for interoperability with state and national statistical systems, including the National Bureau of Statistics. Participation in the IAOS 2026 conference provides a critical platform to present, validate, and refine this approach within the global community of official statisticians.

The paper pursues three objectives. First, it shares a practical and replicable blueprint for decentralised, citizen-centred statistical systems capable of closing last-mile data gaps. Second, it subjects the methodology and early pilot evidence to expert scrutiny in order to strengthen technical rigour. Third, it seeks to catalyse cross-border dialogue on adaptation and scale. By documenting the operational mechanics, ethical safeguards embedded in a co-created Data Privacy Charter, and the formal role of traditional governance, this contribution advances concrete pathways towards resilient and inclusive statistical systems consistent with the UN Cape Town Global Action Plan. The paper demonstrates the critical role of subnational statistics offices and how mobilising community ownership can strengthen official statistical infrastructure that is not only for the people, but fundamentally built with them.