Background

The Sustainable Development Goals (SDGs) initiative has the potential to set the direction for a future world that works for everyone. The SDGs were approved by 193 United Nations member countries in September 2016 to help guide global and national development policies in the period to 2030. The 17 goals build on the successes of the Millennium Development Goals, while also including new priority areas such as climate change, economic inequality, innovation, sustainable consumption, peace and justice. Each of the 17 SDGs is to be assessed against agreed targets and indicators.¹ One hundred and sixty nine targets set out quantitative and qualitative objectives, with 232 indicators. Individual countries, supported by international organisations, notably the UN Statistics Division, are responsible for collecting and processing the data and generating the statistics required to measure the indicators.

Each goal presents a considerable challenge in terms of collecting and analysing relevant data and producing the statistics needed to measure progress. Measuring the indicators is intended to guide policy development, strategy design and, in general terms, the future direction of individual countries. Taken across countries, the measurements are widely expected to foster greater intergovernmental cooperation and the development of regional and even global strategies. However, as Morton Jerven² has pointed out, most governments in lower resourced countries (his research focused on Africa) have yet to introduce the control systems needed to produce high-quality, reliable data and statistics; those responsible for data collection and the production of statistics tend to be too few in number and to lack the expertise needed to introduce the necessary policies, standards, procedures and accountability structures. Jerven questions how anyone can rely on the data and statistics generated under these conditions to make decisions and set direction.

The implications are significant, not only for measuring the Sustainable Development Goals but for the broader ability to plan and achieve development. If progress cannot be measured accurately because of inadequate, inaccurate or flawed statistics, the results can be misguided decisions and doubts about the achievement of the goals. Failure to ‘get the statistics right’ can result in wrong decisions being made, wrong strategies being adopted, and wrong laws, policies and standards being established. It can also lead to a needless waste of resources.

Getting the statistics ‘right’ depends upon the quality and integrity of the data used to produce the statistics. These, in turn, depend upon the quality of the processes that support the collection, manipulation and analysis of the data and the production of the statistics. Ultimately, the quality of these data management and statistical processes depends on the availability, completeness and integrity of the records that document them. Without a documentary record to provide evidence of how the data were gathered and analysed or how statistics were produced and disseminated, it is not possible to confirm that the statistics used to measure the SDG indicators are complete, accurate, relevant and meaningful.

Moreover, records are important sources of information in their own right. They contain information about how, when and where the processes supporting the measurement of the SDG indicators were undertaken as well as information about the data and statistics themselves. This information, when well-managed, can be manipulated with other information contained in other records to support a wide range of purposes. For instance, it can be used to identify and act upon opportunities for merging data from related sources, to analyse trends in the quality of the processes, data and statistics, and to produce management statistics that support the administration of the processes that generate the data and statistics.

The significance of the quality and integrity of data and statistics for measuring the SDG indicators reliably has received considerable attention from a variety of global organisations, including the Sustainable Development Solutions Network and the Global Partnership for Sustainable Development Data.³ However, as yet, relatively little attention has been given to the role of records in providing evidence to demonstrate that the data and statistics are trustworthy and can be used reliably. Processing data to produce statistics is one thing but processing authentic and reliable data using auditable processes in line with international standards, such that the statistics can be trusted, is quite another.

In order to explore this issue and its implications, a UK Arts and Humanities Research Council project was set up towards the end of 2016 at the University of London’s Institute of Commonwealth Studies. Under the banner ‘Digital records as evidence to underpin Global Development Goals’, two workshops were delivered, one in 2017 and one in 2018, to explore the relationship between data, statistics and records as primary types of information for measuring the goals and to initiate an interdisciplinary dialogue among humanities scholars, development experts and information professionals, including data experts, statisticians and records management professionals.

The members of this team, each a specialist in one of these areas, saw the need to reach beyond the worlds of data and statistics to address the role of records in enabling countries to prove the integrity of not only the data and statistics but also of the processes used to collect and analyse them. Approaches to managing data, statistics and records are different, but viewing them as parts of a whole helps to ensure the quality and integrity of each and to identify errors and weaknesses. The workshop participants recognised that quality, completeness and integrity are difficult if not impossible to achieve without effective policies, procedures, standards and systems and without records management expertise. They considered, for instance, the challenges of achieving reliable data, statistics and records when it is not clear where the information has come from, why it was compiled and how it is to be protected for future use. They recognised that data, statistics and records are being lost regularly on a large scale, particularly in digital formats and particularly in lower resourced countries, where structures often are not in place to protect and preserve them.

They decided to explore these issues further from their own perspectives and to produce chapters that, together, would present an interdisciplinary perspective. The chapters explore a range of interrelated development issues which have not previously been articulated, but which affect the quality, veracity and trustworthiness of the data, statistics and records that are fundamental to measuring and achieving the SDGs. They focus particularly on Africa, which illustrates the substantial challenges for managing information. However, the issues identified are generic and will resonate with any country that is grappling with the challenges of managing the quality and integrity of the data, statistics and records they generate and use to measure the SDG and indicators.

The first three chapters explore the historical context for the challenges of managing data, statistics and records and the relationships between them. Anne Thurston provides an overview of background of the recordkeeping challenges and realities that African countries tend to face as they measure and implement the SDGs. Paul Komba and Ngianga-Bakwin Kandala offer a similar perspective from the world of statistics, tracing the developments and challenges for measuring development in Africa statistically. Geoffrey Yeo, in an interview with James Lowry, looks at the different meanings that have been attached to the terms data, statistics and records and the different ways in which their relationships have been interpreted and understood.

The second set of four case studies offers a glimpse of the realities ‘on the ground’ based upon country experiences. James Manor uses the Mahatma Gandhi National Rural Employment Guarantee Act and the Aadhaar initiative in India to explore how well-managed digital records can contribute to constructive development programmes but how, when unmanaged, they can undermine programme objectives, waste resources and lead to misguided decisions and actions. Andrew Griffin examines the relationship between data, statistics and records in the context of mortality statistics in The Gambia to illustrate the complexities of acquiring reliable information to measure the achievement of the SDGs, especially in a low resource environment. Justus Wamukoya and Cleophas Ambira examine the status of records in Kenya and draw on examples from mobile banking in Kenya to highlight the significant new risks that society faces in conducting financial transactions online through the use of smart phones. They also suggest that the sensitive nature of the transactions is focusing attention on the integrity and trustworthiness of the data, statistics and records that these transactions generate. Katherine Townsend, Tamba Lamin, Amadu Massally and Pyrou Chung present case studies from Sierra Leone and Cambodia that highlight the power of open data to promote democratic principles, increase transparency and empower citizens to contribute to policy making and corruption control. They also explore how records management could strengthen the quality, integrity and longevity of the data.

A third group of chapters focuses on the technical challenges of managing and preserving the data, statistics and records that support SDG initiatives. Information recorded in digital form is especially susceptible to loss and corruption because of poor storage conditions, dependence on changing technology and the lack of metadata to facilitate retrieval of the records. These chapters demonstrate that maintaining the integrity and accessibility of records requires careful attention to the formats in which they are stored, the standards for their classification and description, the conditions under which they are protected from alteration and unauthorised access, and the procedures for maintaining their integrity and accessibility through time in spite of changes in technology. James Lowry argues that the principles and techniques developed over centuries in the field of recordkeeping for the purpose of assuring authenticity can also be used to improve data quality, so that the information needed to implement and monitor the SDGs is not only available but authentic. Adrian Brown considers the practical implications of developing the digital preservation capabilities needed to ensure that data collected to measure the SDGs can be compared through time and that decision-makers can be held accountable for how it was gathered. David Giaretta then explores the complexities of collecting, using and preserving digitally encoded information, in particular scientific data, so that conclusions and actions arising from them are based on authentic and accurate information. He highlights the technical challenges of managing data in relation to the SDGs, the importance of international standards and the key issues that need to be resolved if the goals are to be achieved.

The final chapters identify strategies for managing the digital information needed to measure the SDGs. Victoria Lemieux presents the findings of a World Bank research programme on transparency and information management. She describes a tool developed for use in high-level assessments of systems of record to predict whether the records created and held in these systems will be available and trustworthy through time to support development goals. Elizabeth Shepherd and Julie McLeod use a maturity model to identify the competencies required to ensure that strategies are comprehensive, relevant and effective. They relate each level of competency to international standards and address the roles, responsibilities and competencies needed to manage information for development, particularly for measuring the SDGs reliably. John McDonald concludes the study by using a fictional scenario to illustrate both the issues that lower resourced countries face and the comprehensive strategies that they can introduce to enhance their capacity to manage the data, statistics and records needed to support the SDG initiative.

Taken together, these chapters open a window to an evidence-based approach to development and to the practical actions needed to address the information management issues the SDGs raise. To illustrate, even as SDG 3 seeks to ensure healthy lives and promote well-being for people of all ages, a worldwide global health crisis, the Covid-19 pandemic, is spreading human suffering, destabilising the global economy and upending the lives of billions of people. Bringing the virus under control requires a global solution supported by high quality data, statistics and records based on internationally accepted standards and protocols. The absence of such standards and protocols is undermining efforts to address the pandemic. More broadly, and by its example, Covid-19 is highlighting and bringing into stark focus the serious challenges countries are facing as they struggle to ensure the quality of the data, statistics and records required to support achievement of the SDGs by 2030.

Much can be learned from the data, statistics and records issues associated with Covid-19 that could help to reinforce the credibility, relevance and effectiveness of the data, statistics and records used to support the SDGs. Covid-19 has aggravated an already serious development crisis, and urgent action to accelerate progress toward addressing infections, hospitalisations and deaths is required worldwide. How can global leaders make difficult decisions about bringing the virus under control and dealing with its after-effects without reliable, verifiable and complete information that they can trust? Similarly, how can the results of the SDGs be trusted if the information used to support their achievement can’t be trusted?

Hopefully, this book will contribute a new perspective to the SDG initiative by highlighting the value of creating, managing and using high-quality data, statistics and records to achieve meaningful and realistic global and national development policies, now and in the critical period to 2030 and beyond.