10: Data Is Not Neutral: How Information Becomes Narrative Power

When people speak about narrative power, they tend to think of storytelling in its most visible forms: film, literature, media, advertising, and the other cultural outputs through which societies represent themselves and are represented by others. They rarely think about spreadsheets. Yet in the modern world, spreadsheets carry stories as forcefully as cinema, and the stories they carry have more direct consequences for how capital is allocated, how risk is priced, and how policy is designed than most cultural outputs ever achieve.

Data is not simply information. It is interpretation codified into numbers, and like all interpretation it reflects the assumptions, priorities, and measurement choices of the people and institutions who designed the systems that produced it. Data determines how countries are ranked against each other, how sovereign risk is priced, how investment is allocated across geographies, and how policy reform is justified to external audiences whose support is required to fund it. It becomes the evidence that sustains or challenges perception, and evidence, unlike opinion, carries an authority that is difficult to contest without equivalent evidence. Which means that control over the data is, in practice, a form of control over the narrative, and the consequences of that control are material rather than merely epistemic.

Consider how consistently African economies are described in global financial and policy discourse through indices that were designed, maintained, and periodically revised by institutions located overwhelmingly outside Africa. GDP growth rates. Corruption perception rankings. Ease of doing business scores. Sovereign credit ratings. Political stability indices. These numbers circulate with the authority of objectivity because they are expressed as numbers, they are produced by institutions that command global credibility, and they are cited in boardrooms, investment committees, and policy meetings by people who treat them as established facts rather than as the outputs of specific methodological choices. But behind every index is a methodology, and behind every methodology are assumptions about what counts as corruption, what constitutes business ease, what indicators proxy for political stability, and how comparisons across enormously different institutional, historical, and economic contexts are made commensurable. Those assumptions are not neutral. They encode particular visions of what good governance looks like, what successful economic organisation requires, and which forms of economic life are legible as development and which are invisible to the measurement system.

The World Bank's Doing Business index, before its discontinuation in 2021 following a data manipulation scandal, shaped regulatory reform agendas across dozens of African countries for nearly two decades. Governments restructured commercial codes, reorganised administrative processes, and reoriented legal reform efforts specifically to improve their ranking position, because investor confidence and development finance were demonstrably linked to index performance by the institutions that controlled access to both. The reforms were real, and some produced genuine improvements in operating conditions for businesses. But the reform agenda was partially determined by the index's methodology rather than by domestic assessment of what the economy most needed, and the methodology's assumptions about what constitutes business-friendly regulation did not always correspond to the institutional conditions and economic structures of the societies it was measuring.

The historical development of Western data infrastructure illustrates what the alternative to this dependence looks like and what it requires to build. Over the course of the nineteenth and twentieth centuries, Western economies made sustained, large-scale investments in national statistical systems, standardised labour market reporting, financial market transparency requirements, credit bureau development, and the market intelligence infrastructure that tracks consumer behaviour, sector performance, and capital flows in real time. These investments were not made as an afterthought to economic development. They were understood as a component of it, because strong data systems reduce uncertainty, reduced uncertainty lowers perceived risk, lower perceived risk attracts capital, and increased capital strengthens the institutions that improve data quality further. The feedback loop is self-reinforcing once it is established, and the economies that established it earliest have benefited from its compounding effects for the longest period.

Across much of Africa, data ecosystems have developed under different constraints that are structural rather than reflecting any deficiency in technical capability or institutional intent. National statistical offices frequently operate with funding levels that constrain both the frequency and the granularity of the data they can produce. Census exercises may be irregular, leaving population and demographic data outdated in ways that affect every subsequent analysis that depends on it. Informal economies, which in many African countries represent a substantial share of total economic activity, are inherently difficult to capture through the formal reporting mechanisms that statistical systems rely on. Private sector data of significant economic value, produced by telecommunications companies, financial services providers, and multinational digital platforms, is frequently siloed within those companies rather than integrated into sovereign data systems that governments can use to understand and represent their own economies. The result is not that data does not exist. It is that the data is fragmented, and fragmentation creates narrative vulnerability of a specific and costly kind.

When domestic datasets are weak, inconsistently updated, or incompletely integrated into accessible national systems, external agencies fill the narrative gap. Multilateral institutions conduct surveys that become the primary reference point for understanding economic conditions in countries they do not govern. International rating agencies define creditworthiness through methodologies that incorporate historical perception as well as current fiscal data. Global indices categorise economies through frameworks whose design reflects the priorities of the institutions that created them. External consultancies produce market reports whose findings shape investor perception of markets they have visited briefly and understood partially. Gradually, narrative authority over how a continent describes its own economic reality shifts outward, toward the institutions and actors who possess the data infrastructure to fill the vacuum that fragmented domestic systems leave.

This shift has direct consequences for negotiation posture, which is where its material cost is most visible. If a country cannot confidently quantify the scale of its creative economy's contribution to GDP, its consumer market's current size and growth trajectory, or its productivity growth across key sectors, it enters international negotiations from a position of informational disadvantage that is structurally distinct from the disadvantage produced by weak fiscal fundamentals. It must rely on externally generated figures that may not fully capture domestic economic complexity, and it must do so in negotiations where the quality and credibility of the data it presents directly affects what it can demand and what it can be expected to accept. A government that cannot demonstrate the scale of its creative economy's export contribution cannot make the policy argument for the IP protection frameworks and distribution infrastructure investments that the sector needs to develop. A government that cannot accurately measure its informal sector cannot make the fiscal case for the tax policy changes that would bring informal economic activity into the formal system in ways that both increase revenue and provide informal operators with the legal protection that would allow them to grow.

In the creative industries, the implications of data fragmentation are particularly visible and particularly consequential. African music, film, and fashion are globally celebrated in ways that are now extensively documented in international media. Yet the valuation of these sectors for the purposes of policy argument and investment case construction remains underdeveloped because the data infrastructure that would make comprehensive valuation possible does not yet exist at the required depth. Royalty tracking systems are inconsistent across jurisdictions, which means that the revenue generated by African music on global streaming platforms cannot be accurately aggregated and attributed in ways that would demonstrate the sector's economic scale to the investors and policymakers who allocate capital and design regulatory frameworks. Publishing rights metadata is fragmented, which creates the conditions under which value migrates to the publishing infrastructure of other markets without the migration being fully captured in domestic economic statistics. Streaming analytics for African artists and African audiences are held primarily by foreign platform operators rather than by domestic institutions, which means that the data that would most powerfully demonstrate African creative industries' global reach is not sovereign. Visibility is high. The proof that converts visibility into investment and policy change lags significantly behind it.

Data shapes what is visible and what remains invisible, and what remains invisible cannot be argued for, funded, or reformed. If informal commerce is systematically undercounted, economic output appears smaller than the lived reality of the economy it is supposed to represent, and fiscal policy is designed around a smaller economy than actually exists. If digital entrepreneurship is poorly measured, innovation appears incidental to the economy rather than structural to it, and the policy and infrastructure investments that would support its development are harder to justify. If creative exports are not tracked comprehensively as an economic category, creative industries appear marginal when they are presented to the finance and trade ministries that control the resources they need to develop, and they remain governed as culture rather than as industry.

Numbers shape legitimacy in ways that qualitative argument cannot fully substitute for, because the institutions that control access to capital and that design the regulatory frameworks within which industries develop require quantitative evidence before they will commit resources. This does not mean that data collection is simple or that building the infrastructure to produce it is without cost. It requires sustained institutional funding, regulatory clarity about what data can be collected and how it can be used, technical capacity distributed across the statistical institutions that would operate the collection systems, privacy frameworks that make data collection legitimate and sustainable rather than creating the conditions for future political resistance to it, and public trust in the institutions conducting the collection. It requires governments to treat information infrastructure with the same strategic seriousness they apply to roads, ports, power grids, and the other physical infrastructure whose economic importance is more intuitively visible.

The cost of not building it is, however, higher than the cost of building it, even if the latter is substantial. When a continent's economic identity is continuously described through externally compiled metrics, it becomes dependent not only on the capital flows that those metrics influence but on the narrative framing that determines how those flows are understood and directed. Risk premiums remain elevated when uncertainty is high, because uncertainty is what risk premiums are designed to compensate for, and weak domestic data infrastructure is a form of economic uncertainty that is independent of fiscal fundamentals. Investors demand more information before committing, and when that information cannot be provided domestically, the gap is filled by external analysts whose understanding of the market is necessarily less detailed and less accurate than domestic institutions could provide. Policymakers design reforms to satisfy external benchmarks rather than internally defined strategic priorities, because the benchmarks are the condition of the capital that the reforms are designed to attract.

Narrative sovereignty, properly understood, is inseparable from data sovereignty. The ability to tell a new and more accurate story about economic strength, creative power, demographic advantage, and institutional development depends on the ability to measure those things convincingly, because in the institutions where the new story matters most, convincing measurement is the precondition for being taken seriously. Data provides the scaffolding that allows narrative to stand under the scrutiny that institutional audiences apply to claims that challenge their existing frameworks. Without it, the most compelling and most accurate story can be dismissed as aspiration rather than engaged with as evidence. With it, perception begins to shift from speculation to structure, from aspiration to documented reality, from narrative claim to institutional fact.

In the years ahead, the countries that treat data infrastructure not as administrative overhead but as strategic investment will gain increasing control over how they are understood in the global institutional environments where capital allocation, trade negotiation, and diplomatic positioning are determined. How they are understood will determine how they are priced, how they are partnered with, and where they sit in the global system of economic relationships. Information is not a by-product of development. It is one of its foundations, and treating it as such is not a technical decision. It is a narrative engineering decision, with consequences that compound across every domain where the narrative matters.