Data is Life: The Unseen Force Driving Nigeria’s Progress and the Urgent Need for Quality Insights

The old adage in Nigeria, "Data is life," has never been more true. From the bustling markets of Lagos to the agricultural fields of the North, data is the unseen force that shapes policies, drives innovation and determines who succeeds. It is no longer just a term for tech enthusiasts, it is the new oil, essential for turning Nigeria’s immense potential into tangible progress.
But a critical problem exists: while the need for data is high, the journey to obtaining quality data is filled with unique, homegrown challenges. To build a truly data-driven Nigeria, we must first understand this importance and then courageously tackle the obstacles that compromise our insights.

The Essential Role of Data in Nigerian Daily Life
Data — this can be anything; whether it is the number of people watching a skit on TikTok, the price of tomatoes in Kano, or the prevalence of a disease in a local government area (LGA), is the foundation of informed decision making.

1. Fueling Economic Growth and Innovation
   For entrepreneurs, data is the compass. Businesses use analytics to understand customer behavior, optimize supply chains and detect fraud. This enables them to target their products better and reduce waste. For the government, data on economic performance and market trends allows for the creation of policies that are not based on assumptions, but on evidence, fostering sustainable economic empowerment.

2. Improving Public Health and Education
   Data literally saves lives. In the public health sector, data science enables accurate disease surveillance, allowing health officials to target interventions quickly during outbreaks. In education, analyzing student performance and resource allocation data helps stakeholders identify failing curricula or under-resourced schools, directly contributing to a better future for Nigerian youth.

3. Guiding Infrastructure and Policy
   Data-driven planning ensures that scarce resources are directed where they are most needed. Analyzing demographic and geographic data helps optimize the deployment of infrastructure projects, from roads and power grids to fiber optic cables, paving the way for a resilient and interconnected nation. Without reliable data, policy formulation becomes a guessing game, leading to wasted resources and failed initiatives.

The Battle for Accuracy: Limitations to Getting Quality Data

Despite its profound importance, Nigeria faces persistent, established structural, organizational, and behavioral challenges that compromise data quality across various sectors. These factors make it difficult to gather, process and analyze the clean, complete and accurate information necessary for national development.

1. Organizational and Infrastructural Deficits Inadequate Funding and Infrastructure: Many government agencies and institutions suffer from inadequate funding for data management. This often translates to a shortage of working tools (like computers, reliable software, and secure servers) and a reliance on antiquated, manual systems often paper records, which are prone to human error, loss and inconsistency.
2. Poor Capacity and Training: There is a shortage of professional data experts and a lack of continuous, structured training for existing data managers. Data collection is often entrusted to personnel with low digital literacy, leading to fundamental errors in data entry and processing.
3. Behavioral and Human Resource Challenges
4. Low Motivation and Workload: Personnel responsible for data collection, particularly in sectors like health, often face excessive workloads and short deadlines to submit numerous reports. Furthermore, a lack of acknowledgment or incentive for good data quality, coupled with low pay, leads to low morale and an indifferent attitude toward the importance of accuracy and completeness.
5. Lack of Accountability and Governance: In many organizations, there are unclear or weak accountability mechanisms for data management. This lack of clear ownership and consequence allows for the persistence of poor data practices like over-reporting or under-reporting.
6. Systemic Issues
7. Data Proliferation and Inconsistency: Different organizations or departments often use multiple, non-standardized data tools and different definitions for the same variables. This makes it nearly impossible to merge datasets, leading to inconsistent and incomparable national statistics.
8. Connectivity and Access: While internet penetration is growing, poor connectivity in remote areas hinders the use of real-time digital collection tools. This forces reliance on manual collection, which is later entered in bulk, introducing greater opportunity for delay and error.

Paving the Way Forward: Solutions for Data Quality
Addressing these deep-rooted issues requires a comprehensive, multi-pronged strategy focused on technology, people, and governance.
Challenge Suggested Solution
Inadequate Funding & Manual Processes Digitization and Automation: Prioritize investment in digital data collection tools (like mobile forms) that allow for real-time validation and can function offline. Move away from paper-based records to centralized, secure cloud-based systems.
Poor Capacity & Literacy Structured Training Programs: Implement mandatory and continuous training programs on data collection protocols, data management systems and data literacy for all staff involved in data handling. Employ more certified data professionals.
Low Motivation & Accountability Incentives and Governance: Establish clear data governance frameworks that define roles and responsibilities. Introduce a system of non-financial incentives and public recognition for high-quality data management to boost morale and foster a culture of data appreciation.
Inconsistent Data Standards Standardization and Simplification: The National Bureau of Statistics (NBS) and relevant sector ministries must enforce standardized data dictionaries and collection tools across all states and LGAs to ensure comparability and consistency. Simplify the reporting burden by merging redundant tools.

Lack of Data Use Feedback Loops: Data producers (the collectors) are often separated from data consumers (the policymakers). Regular, constructive feedback should be provided to collectors showing how their data is being used to make key decisions. This demonstrates the data's value and encourages better quality.
By committing to these solutions, Nigeria can move past the limitations and truly harness the power of data. We can transform raw numbers into undeniable knowledge that will guide us toward sustainable development, better governance, and a higher quality of life for all Nigerians.

Ridwan Ibrahim