1.1 Introduction

Sound economic policy presupposes availability of timely, comprehensive, credible, and multi-purpose data that many African countries have lacked for a long period. It is not long ago when major policy reforms were implemented based on findings drawn from faulty data. A recent project by the World Bank on “Agriculture in Africa: telling facts from mythFootnote 1” is a clear illustration of how, for many years, policymakers in Africa formulated their policies toward smallholder farmers based on stylized facts that were inaccurate or untrue. The project identified over 16 well-established “myths” that generally had been taken as facts and informed decision-making in most African countries. We can cite many other examples as well that triggered significant policy actions driven by faulty data.Footnote 2 Some researchers also argued that Africa’s national statistics are significantly affected by measurement errors, poor data management, and weak capacity, making national development strategies incoherent.Footnote 3 On the other hand, relatively reliable data generated from large household or labor force surveys or census in most cases remain unused for policymaking for various reasons. It is here that AERC has played a major role in facilitating the use of such data sets for the analysis of Africa’s labor markets, poverty and inequality, small holder land and labor productivity, and so forth and made significant contributions to the understanding of African economies. Still Africa has remained the most under-researched continent to date.

The last two decades, however, has seen significant improvements in the availability of high-quality data that can be used for effective policy evaluation. The advent of behavioral economics, the availability of big data through satellite imagery by NASA and others, such as changes in temperature, rainfall, soil quality, vegetation, night light data, movement of people and traffic across borders through Google Maps, and most of all data generated by mobile telephony present unique opportunities for Africa. Recent years have seen a rise in cutting-edge research on African economies utilizing such data as well as well-designed field experiments. A combination of these two has given researchers unique advantages to explore frontier issues that were unthinkable a few decades ago. The digital footprint that flourished in the continent in the financial sector and the use of social media and other platforms also present advantages that enable economic research in Africa. The African Economic Research Consortium, with the support of the Hewlett Foundation, undertook a sco** study to bridge the gap between evidence and data, as well as evidence and policy, but more importantly to draw attention to appropriate data management policy, data use, data protection, and data governance in the context of Africa. The introduction section presents the key findings from the seven chapters contained in this volume and outlines the way forward.

The contributors to this book consist of economists, lawyers, statisticians, and data technology experts to assess the opportunities, challenges, and risks existent in the current state of data generations, sharing protocols, and consistency of legislations. Desirous of encouraging the widespread use of large data from different sources, ensure its reliability, and facilitate availability, the book seeks to identify opportunities, constraints, and impediments to the use of data and evidence to inform economic policy decision-making in sub-Saharan Africa and, in so doing, to engage policymakers on the implications for data governance that could provide safe access and foster its widespread use. The main objective of this book is twofold. First, to create a platform on data governance that raises awareness on basic principles/tenets of international norms and shares experiences and practices from across the world and Africa. Second, to initiate, promote, and advocate for data governance protocols in the era of digital revolution and assess the potentials for improving the digital market to enhance benefits to African consumers, governments, and businesses. To achieve these objectives, the chapters covered broad themes that provide better understanding of the challenges, opportunities, and risks in the process of data production, consumption, and utilization. Chapter 2, “A Prototype Data Governance Framework for Africa” by Bitange Ndemo and Aaron Thegeya, outlines a framework for data governance that ensures sovereignty, while at the same time enhances productivity within each African country and bolsters cross-country collaborations. The chapter proposes a continent-wide data governance strategy that “abide by core principles such as preserving accountability, ensuring data accuracy and quality, and facilitating interoperability and standardization of data.” The chapter discusses global practices that provide the principles and framework for data governance that promotes accountability in improving data quality, integrity, privacy, and security of data subjects, as well as ethical use of data.

Implementation of a robust data governance strategy requires a thorough understanding of the process involved in translating data into information and policy action. Chapter 3, “A Value Chain Approach to Data Production, Use, and Governance for Sound Policymaking in Africa” by Zachary Mwani Chege and Peter Maina Wanjohi, provides a schematic approach to data production, consumption, and application starting downstream (data generation) all the way up to data utilization and its application for decision-making. Using National Statistical Offices (NSOs) as the prime examples entrusted with the responsibility of overseeing publicly available data, the chapter presents the guiding principles that govern data generation, sharing, dissemination, and protocols that are enshrined in United Nations Fundamental Principle of Official Statistics (UNFPOS).Footnote 4 These principles touch upon a wide range of issues such as relevance, impartiality, and equal access; professionalism; accountability; prevention of misuse; cost-effectiveness; confidentiality; legislation; national co-coordination; international coordination and cooperation; as well as comprehensive documentation. The chapter reviews where Africa stands with respect to these principles and identifies gaps and areas for further improvement considering the rapid progress in digital technology, data revolution, and big data. Chapter 4, “Data Protection Legal Regime and Data Governance in Africa: An Overview” by Olumide Babalola, and Chap. 5, “Data Regulation in Africa, Free Flow of Data, Open Data Regimes and Cybersecurity” by Hanani Hlomani and Caroline B. Ncube, explore the regulatory and legal challenges with respect to data governance and policy in Africa. Chapter 4 presents the “legal framework around data protection in Africa in the light of their salient provisions, adequacy, efficiency, and enforceability in relation to data governance on the continent,” with emphasis on ratifications and declarations made under the auspices of Africa Union, such as the Malabo Convention. The paper’s key message revolves around the following: first, “free movement of both personal and non-personal data is best supported by the adoption and use of open standards for data and appropriate cybersecurity regulation.” Second, policymakers and legislators ought to consider the above threefold key message in formulating policies and drafting laws. Third, the chapter also suggests that “further research may be carried out on data localization laws and follow the developments pertaining to the African Union Commission’s Draft Data Policy Framework.”

Advances in digital technology, geospatial data, satellite imageries, and big data have transformed the landscape in which data governance has to be applied. Chapter 6, “Digitalization and Financial Data Governance in Africa: Challenges and Opportunities” by Bitange Ndemo and Ben Mkalama, elaborates and discusses how emerging technologies in the areas of artificial intelligence, robotics, Internet of things, and big data analytics have shaped business models across the globe. Africa needs to be ready to take advantage of these technologies, while mitigating the risks they pose in many areas including national security, privacy protection of data subjects, unethical use of data for purposes of disinformation and misinformation, and so forth. The paper notes that despite such significant opportunities afforded and heightened risk posed by the digital technology, many African countries are behind the curve in devising legislations and installing infrastructure necessary for data protection and management. A sharper example is found in Chap. 7, “The Economics of Blockchains Within Africa” by Aaron Thegeya, which discusses in great detail the upcoming blockchain technology that has transformed economic data in unprecedented manner with a potential “to boost levels of productivity and unlock capital flows to underserved sectors, in addition to leveraging the increasing returns of information as an input to production to spur economic growth.” The challenge, however, is that only very few countries in Africa (Mauritius and Kenya) have devised the framework, including legislation and regulatory provisions, to take advantage of blockchain technology in equitable and sustainable manner. The chapters identified structural and institutional challenges African countries face to exploit fully the advantages blockchain technology offers and the risk it poses for disadvantaged groups and regions. The final chapter, “More Than Just a Policy—Day-to-Day Effects of Data Governance on the Data” by Vukosi Marivate, presents the need and imperatives for data governance from the perspective of data science, which is an evolving discipline that applies algorithms and systems to extract patterns, and knowledge from both well-structured and noisy data. The chapter highlights the need for robust data governance systems to manage the proliferation of analysis, decision-making, and other impactful measures adopted by businesses, government entities, and others using data science where the margin for error and corruption is paramount.

1.2 The Way Forward

The chapters in this volume underscored that data intrinsically are generated in unlimited quantity, and, in most cases, it is a non-rival good that could be shared or used across users without creating any disincentives or diseconomies. These unique characteristics of data, coupled with the increasingly data-driven global economy, could create the risk of enormous power imbalances, inequalities, and diverging development clubs. Examples include the unequal access to broadband Internet across the globe, which has widened over time, leading to unequal generation and utilization of data. Divergent cybersecurity capabilities led to different degrees of protection of privacy and exposure to the misappropriation of national- and individual-level data. When it comes to Africa, the chapters note that national statistical offices generally are behind the curve in the understanding and utilization of digital technology in data creation as well as making it ready for use by researchers, decision-makers, and private citizens. The Covid-19 provided an opportunity for many African governments to recognize and experience the huge potential presented by the digital technology in generating, storing, and distributing data for purposes of real-time decision-making. Noting these insights, the AERC anticipates further engagement in the realm of data governance and policy in Africa. Some of the ideas are presented below.

1.3 Potential for Future Research

As noted above, African governments are at different stages of data governance and policy practices. But common to all seems the lack of appreciation of data policy to enhance decision-making based on solid empirical evidence, of which many African governments generally have subscribed to and aspire to inform their strategies and policies. This disconnect between the absence of data policy and the desire to influence policy through evidence is evident in almost all African countries. The following issues encapsulate future research to close such a gap:

  • Data policy and inclusive development in Africa

Many experts, including those in the policy panel, suggested that critical socioeconomic data are collected in unreasonable time intervals, are rarely available to inform policy on time, and are not accessible to researchers to conduct studies to build the stock of knowledge that could be transformative. It is not known how much such data management practice costs Africa in terms of lost development. For example, few African governments have reliable and up-to-date data on profile of their labor force, stock of skills, and employment opportunities. Yet, they formulate various labor market policies and legislations and develop plans on employment generation and even social protection programs based on outdated and incomplete data sets. Assessing the extent to which such data policies have prevented African countries from formulating reliable and achievable development policies is an important research undertaking.

  • Benchmarking Africa in the global data policy and governance

The Fourth Industrial Revolution is riding on the back of data and information. The full potentials of emerging new technologies are realized in countries where the data infrastructure and system are compatible with the global norm. Data policy is not just about protection. It is also about the right of full access, principle of usability, and integrity. Such a policy requires data-generating bodies to fully comply with the rules of data sharing, availability, and integrity protocols. Benchmarking African countries with the global norm could be an eye opener to various government agencies, private operators, and other data-generating agencies in terms of the opportunities Africa is losing to catch up with the rest of the world.

  • Map** data interoperability in Africa and the future of policymaking

One recurring theme raised during the RPF was the significant gap observed in Africa with regard to various socioeconomic and other individual-level data being fragmented, scattered, and poorly organized, costing governments enormous resources and time to manage the economy. Examples include important socioeconomic surveys designed and collected independently from each other, costing millions in resources and at the same time limiting their significance for policymaking. Examples include census surveys, labor force surveys, living standard measurement surveys, demographic and health surveys, which are designed and collected independently of labor force surveys and many other regularly conducted national surveys. These are also not linked with other vital statistics such as income taxes, financial transactions, health, and education services. Most develo** countries have now started to use unique identification codes for citizens that, with the right privacy policies, could be integrated with other data platforms. That offers policymakers important information to formulate public policies that are innovative and inclusive.