Can you do business while doing good in the developing world? The answer is yes, but only if you focus on the data that matters.
Investing in the developing world is back at the top of the business agenda. And it’s about time, too. Emerging markets, including the burgeoning opportunities presented by some African states, are fuelling an upsurge in interest from the private sector. For example, in 2009, Angola registered a 109 per cent rise in foreign direct investment (FDI) as a percentage of gross fixed capital formation. As a whole in 2010, developing and transition economies attracted half of global FDI inflows, ‘leading the FDI recovery’ according to the United Nations Conference on Trade and Development (UNCTAD).
Opportunities like this are not only manifold and potentially lucrative; when carried out responsibly they can also act as a catalyst for transformation. Socially responsible investments won’t just lead to private gain – they have the potential to shape the world.
But the power to effect change is a double-edged sword; poor investments, irresponsibly made, will have just as wide an impact – only this time it won’t be for the greater good. When the ripples of investment seep beyond private borders, questions of risk and the potential for loss or gain become a global affair. Lives, not just bottom lines, are potentially at stake.
The historical challenge of investing in poorer parts of the globe was magnified by widespread decolonisation in the 1960s and ’70s. In Africa, expropriation of foreign-owned enterprises forced businesses to rethink whether it was necessary to own rather than maintain secure access to local assets. Over the next 40 years, companies lengthened their supply and subcontracting chains, and generated new types of relationships, from parallel investing with publicly funded Development Finance Institutions (DFIs), to using state-backed export credits, and developing other risk-sharing relationships such as leasing, forward-contracting and investment agreements.
However, the instinct that having a stake in a derivative income stream from an asset in the developing world is safer than an ownership stake in the actual fixed asset had to be reassessed after the global financial crash of 2007-8, since so much derivative stock was proved worthless or degraded. At the same time, such arms length contact with developing countries has often proved of little use to the countries themselves, sometimes provoking a backlash against offshore equity, as happened in Buenos Aires, which banned all investments from shell companies held in tax havens in 2005.
So how does one go about making sound and socially responsible investments in this new era? By focusing on the facts.
“When the ripples of investment seep beyond private borders, questions of risk and the potential for loss or gain become a global affair. Lives, not just bottom lines, are potentially at stake.”
The poorest countries often present the most challenges to today’s global investor, not least because future risk is highly context-specific. Assessing diverse and fluctuating contexts is generating ever-greater complexities of data, and bringing the worlds of business and academia – particularly political scientists and international development experts – closer together. Digesting that data, however, is another story entirely.
Business data, economic, social and governance indices, corporate social responsibility measures and development impact data are combining into effective predictive instruments. But hazards remain, not least in the level of mathematical complexity generated. Is the world really this complicated, or is the data industry out of control, feigning precise forecasting but exhibiting no greater reliability than gut instinct?
The only way through this statistical blizzard is to look at the figures, one dataset at a time.
Can it be measured?
There was a brief period in the 1950s when the boundaries of the Cold War defined a space that Western governments were prepared to protect for business. But that world is gone. In its place is a complex political geography where the apparent stability of a country can change quickly, as has been the case in Tunisia or Egypt. Conversely, countries widely considered dangerous, such as the eastern Congo, Angola, Myanmar/Burma, or Sudan, are proving profitable for business – as Chinese and Indian corporations have discovered, leaving the rest of the world trailing behind.
Faced with this unpredictable landscape, how does one spot a sound investment amongst those riddled with risk? The most common indices for investment risk are the International Country Risk Guide from the New York-based PRS Group; ratings from the Economist Intelligence Unit, and from Eurasia Group; alongside the more traditional Standard & Poor’s, Dun & Bradstreet and payments data from the Bank of International Settlements.
These indices focus on two aspects of political risk: regime (in)stability and the (un)certainty of the macro policy environment. But these indicators struggle to keep pace with nebulous political identities and regime characteristics. The predicted ‘top 10 most dangerous countries’ at the beginning of a decade are rarely the same 10 that actually collapse by its end. Evidence of political stability on its own is not enough: while authoritarian regimes can prove safe places for investment for a time, sometimes a long one, a lack of democracy means that change, when it does come, tends to be eruptive and unpredictable. Businesses can quite literally lose everything.
So how can predictive datasets like these be improved? For starters, institutional quality must be taken into account, since political risk ‘events’ (i.e. mass protest or regime change) are better understood by knowing how political institutions are likely to react. Some can manage rapid change, while others falter.
Institutional quality measures, which are proving reliable, will mark the future world, and it is in the contemporary design of these that academics and business people are meeting. For example, the Freedom House index, Transparency International’s Corruption Perceptions Index (CPI), or the quite specific Polity IV series all depict institutional quality, and provide context and depth to investment and risk planning.
The CPI is good for general context, but relies on perception, which can lag behind actual political change. Freedom House has only a handful of classifications: free, partly free and unfree. But the Polity IV gives accurate measures of the legal constraints on a country’s executive, which turns out to be a good predictor of transparency, which in turn is positively related to economic growth. The most recent World Bank Governance Indicators measure the quality of political institutions across six categories: voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law and control of corruption.
Making the numbers work for you.
Almost every aspect of a country’s socioeconomic reality is documented by statistics. But filtering through the abundance of information and retrieving a reliable dataset that answers questions about the world we live in is not always as straightforward as it seems.
Over 175 governments send data to the IMF for the International Financial Statistics and to the World Bank for World Development Indicators, which in turn are used by investment risk analysts. The most well-known development indices, the Human Development Index and the data collected for the purposes of checking progress towards the Millennium Development Goals (MDGs) provide an overview of wealth and wellbeing in developing countries. It may not be obvious at first how we can use this knowledge to make better, more effective and ethically sound business choices, but even a perfunctory analysis shines some light. For example, secondary school enrolments from World Development Indicators are a good sign of a more productive workforce, of better governance and the probability in turn of a stable macroeconomic environment.
These early development indicators have recently been complemented by more complex impact assessment tools – usually in response to demands from the public or donors concerned about a project’s wider impact. Concern with carbon emissions, or assessment of an investment’s impact on culture, heritage or happiness might seem irrelevant to the businessperson of the past, but future leaders will not be able to evade demands for quantifiable, evidence-based statements. In this way, data can help us achieve more transparent and accountable working practices.
“Filtering through the abundance of information and retrieving a reliable dataset that answers questions about the world we live in is not always as straightforward as it seems.“
But how do we value the quality of air, the protection of a heritage site, the treatment of workers? An overall assessment of a company’s ‘social worth’ is some time away, but those taking the bridgehead approach will be thinking about this now. Efforts in ‘greenwash’ will no longer satisfy the informed global public of the future.
So how can intangible externalities that affect social welfare or the environment be measured? An active relationship with a Development Finance Institution is a good place to start.
The DFIs are required to produce matrices of developmental impact, which means they demand more social value from their private sector co-investors. For example, the Corporate-Policy Project Rating (GPR) of the Deutsche Investitions-und Entwicklungsgesellschaft (DEG) and the Emerging Markets Private Equity Association (EMPEA) framework are both exemplary systems that measure the impact of a DFI investment.
Adopting measures like these aren’t just about ‘being good’. According to advocates of corporate social responsibility, meeting the ‘triple bottom line’ of financial, social and environmental returns – or ‘people, planet, profit’ – grows the business in the long term. Customers are increasingly demanding that their money be put to good use; that the businesses they choose to buy from promote democracy, social welfare and development on the ground – or, at the very least, don’t reverse patterns of progress. For example, widespread HIV awareness, such as that sponsored by Aureos Capital (with investment from CDC Group and Norfund) can reduce HIV prevalence, which can be measured by the World Bank’s Development Indicators. Successes like this make customers happy.
Better use of development indicators can prove corporate social responsibility and defend against the risk of reputational damage affecting the customer base. ‘Clean’ goods are in demand, and whether it’s diamonds vetted by the Kimberley Process or cocoa trading structures by The Fairtrade Foundation, ethically sound production practices can all be corroborated by datasets. Likewise, guaranteeing an associational distance from child labour, environmental harm and land grabbing is just as imperative, though they do require a much more sophisticated dataset.
All this information already exists. It can help you do business and ‘be good’. Learning how to filter the noise and focus on the facts that matter to you is the first step. Then an even bigger issue comes into play: how do you make sense of it, digest it and absorb its meaning into the work that you do? The answer is simple: you need to visualise what the data is trying to say.
The four organisations below are doing just that.
Gapminder / gapminder.org
If you think global statistics are boring, think again. Gapminder’s bubbly Trendalyzer tool breathes life into the trends shaping our world. By reimagining obscure patterns of social change as graphs that move organically over time, Gapminder is smashing through the mythical glass ceiling that hangs over the ‘developing world’ and inspiring more people to absorb the facts. Everything from wealth and health to education and climate is rigorously analysed, then effortlessly interpreted as dynamic graphs that represent life in every corner of the globe.
Development Seed / developmentseed.org
The straight-talking brains at Development Seed have created an innovative range of tools to combat information overload and ‘make data more actionable through design’. With a focus on international development, they help government agencies and the private sector embrace the open data revolution by making complex datasets easy to understand. Quirky toolkits like MapBox and Managing News turn tough data into easy-to-read visualisations or maps, and have been used by everyone from Google to the World Bank. Whether they’re processing election results in Afghanistan or monitoring relief efforts in Haiti, simplicity is key.
StatPlanet / sacmeq.org/statplanet
Free to download, StatPlanet is a browser-based application that creates customised maps, graphs and visualisations from all manner of interlocking datasets. It’s turned Transparency International’s befuddling Corruption Perceptions Index into an interactive gateway, and allowed Social Watch to publish a constantly updated map that charts relative poverty and wellbeing across the world. This easy-to-use tool has helped everyone from the UN to Dell realise that evidence-based decision-making can be a pleasure, not a chore.
HealthMap / healthmap.org
If the campaign for open data needs a poster child, then HealthMap is it. This online mapping tool aggregates information from disparate open data sources to offer a comprehensive view of the state of global health. This year sees the launch of Predict, a tool that will help the public track outbreaks of animal diseases that might affect humans. Pooling information from sources such as the World Health Organisation, Google News and the Wildlife Disease Information Node, HealthMap proves that freely available information can be a progressive social force.