Background of the Study
Data quality is a fundamental component of effective policymaking, as accurate and reliable data underpin the analysis and evaluation of public policies. In Nigeria, the relationship between data quality and policy outcomes has gained increasing attention amid efforts to modernize governance and promote transparency (Afolabi, 2023). High-quality data enable policymakers to diagnose problems accurately, design targeted interventions, and assess the impact of policies on economic and social indicators. Conversely, poor data quality can lead to misinformed decisions that exacerbate existing challenges rather than resolving them (Chinwe, 2024).
The Nigerian government has embarked on several initiatives to improve data collection and management processes, including investments in digital technologies and capacity-building programs. These efforts are intended to bridge the gap between available information and the requirements of modern policy analysis. As policymakers strive to adopt evidence-based approaches, the emphasis on data quality becomes even more pronounced. Accurate data not only enhance the credibility of policy decisions but also foster accountability and public trust in government institutions (Ibrahim, 2025).
Despite these advancements, significant challenges remain. Inconsistent data collection methods, limited access to updated information, and technical deficiencies have all contributed to persistent gaps in data quality. These issues, in turn, affect the formulation, implementation, and evaluation of policies across sectors such as health, education, and infrastructure. Moreover, the dynamic nature of Nigeria’s socio-economic environment demands that data collection systems be continuously updated and refined to capture emerging trends. This study examines the relationship between data quality and policy outcomes in Nigeria, aiming to determine how deficiencies in data can undermine policy effectiveness and to identify strategies for improving data management practices.
Statement of the Problem
The quality of data available for policymaking in Nigeria remains a significant challenge, impacting the effectiveness of policy outcomes. One major problem is the lack of standardized data collection protocols, which leads to discrepancies and inconsistencies in the information gathered by various government agencies (Oluwaseun, 2023). Such inconsistencies can result in divergent policy interpretations and, ultimately, ineffective interventions. Additionally, outdated or incomplete data hinder the ability of policymakers to accurately diagnose issues and predict the outcomes of proposed measures (Eze, 2024).
Another critical issue is the limited technological capacity to process and analyze large datasets. While investments have been made in digital infrastructure, many institutions still face challenges in integrating advanced data analytics into their operations. This gap in technological capability often translates into delays in policy implementation and a reduced ability to respond to emerging challenges. Furthermore, poor data quality erodes public confidence in government policies, as citizens become skeptical of decisions based on unreliable or inaccurate information. The cumulative effect of these challenges is a policy environment where decisions may not reflect the actual needs or conditions of the populace, leading to suboptimal outcomes and wasted resources.
This study aims to investigate the extent to which data quality influences policy outcomes in Nigeria, identify the underlying causes of poor data quality, and propose strategies for improvement. By bridging the gap between data collection and policy implementation, the study seeks to enhance the overall effectiveness of public policy in Nigeria.
Objectives of the Study
Research Questions
Research Hypotheses
Scope and Limitations of the Study
This study examines the role of data quality in policymaking within Nigeria’s public sector. Limitations include variations in data collection practices and technological disparities among institutions.
Definitions of Terms
Background of the Study
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CHAPTER ONE
INTRODUCTION
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