Oyo State Builds MSME Database To Unlock Funding

By Ogbuefi O. Emelike

The Oyo State Government, through the Ministry of Investment, Trade, Cooperatives, and Industry in Ibadan, recently initiated a statewide data collection exercise across all 33 local government areas and local council development areas to build a comprehensive Micro, Small and Medium Enterprises (MSMEs) database. The Commissioner for Trade and Industry, Adeniyi Adebisi, represented by Olajide Okesade, Permanent Secretary, confirmed deployment of a train-the-trainer model using aggregators and field agents to capture business data in real time, supported by a centralised technology platform to improve funding access and planning accuracy.

DECISION HIGHLIGHT
Adoption of a decentralised, technology-enabled MSME census model to correct data gaps and integrate businesses into funding and policy systems.

DECISION MEMO
The initiative addresses a structural constraint in subnational economic management, unreliable MSME data. The 2024 exercise exposed identification gaps, particularly absence of Bank Verification Number and National Identification Number linkages, which effectively excluded businesses from formal financing channels.

By redesigning the data architecture around verification and real-time capture, the state is repositioning MSMEs from informal economic actors to traceable financial participants. The aggregator model reflects a scalability strategy, trading central control for coverage efficiency, while introducing execution dependency at the local level.

The Chief Executive Officer of Global Sight Services Limited and consultant to the state government, Dayo Bello, stated that “accurate data is essential for unlocking funding from government agencies and international development partners.” Bello added that the technology-driven system would ensure “real-time data transmission… to enhance transparency and efficiency.”

The policy logic is clear, data integrity becomes the gateway to capital access and targeted intervention. However, the outcome will depend on data quality enforcement and sustained system usage beyond initial capture.

DATA BOX
• Coverage: 33 local government areas and local council development areas
• Model: train-the-trainer, aggregators with 10 agents each
• Target segments: traders, artisans, farmers, small-scale industrialists
• Key gap (2024): weak identification data, Bank Verification Number and National Identification Number deficiencies
• System: centralised, real-time data transmission platform
• Objective: funding access, policy precision, MSME inclusion

WHO WINS / WHO LOSES
Winners: Verified MSMEs, state planners, development finance institutions, data-driven policymakers.
Losers: Unregistered or unverifiable businesses, informal operators resistant to formalisation, intermediaries exploiting data opacity.

POLICY SIGNALS
Shift towards data-led economic governance at subnational level, with MSMEs positioned as formal economic units within planning and financing frameworks.

INVESTOR SIGNAL
Improved MSME data visibility enhances pipeline clarity for development finance and private capital targeting small business segments, reducing information asymmetry.

RISK RADAR
Primary risk is data integrity failure at collection level. Secondary risks include low compliance from informal operators, system underutilisation post-capture, and fragmentation if inter-agency data integration is not sustained.