For emerging economies there is supposed to be a simple equation: mobile + computing + internet = growth. Mobile technologies put communication in the hands of even the poorest. Computers – nowadays in the form of smartphones – turn communication into an ever more affordable economic tool. The internet hosts the data those tools create, a massive ‘big data’ store that can be freely accessed, shared, and visualized, creating new knowledge and wealth. It is the biggest leapfrog moment in economic history; countries like those of sub-Saharan Africa that have been chronically poor suddenly have a fast-track route to prosperity. That’s the theory: the practice is a bit more complicated.
The promise of a data revolution is real. Big data has the potential to transform African economies and government for the better. But as with everything Africa, the story is getting ahead of itself. The data revolution has very many obstacles to batter down before it bears fruit. It is going to take money and intelligent policymaking to get from here to there.
The problem in Africa is that these new technologies still need infrastructure, and the infrastructure is not yet there. They need the physical infrastructure of mobile phone masts and network provider capacity in fast data networks. That is developing, albeit much more slowly than the prophets of revolution would have it. But they also need a human infrastructure of skills, and this is where Africa has a serious deficit.
But first, the good news. There are already tangible benefits flowing from the use of very large scale digital data sets in some of the world’s poorest countries, something that could not even have been imagined only a decade or so ago. The most striking come from West Africa, where the vast stores of information created by mobile phone records have helped to defeat the ebola epidemic.
The best long-term defences against ebola will be based on effective vaccines and effective treatments. But those were of no use in the epidemic that took hold in West Africa last year: neither vaccines nor proven treatments existed. The reason that ebola was so effectively contained was that health authorities used knowledge of human geography, based on communications data. Control and limitation of the spread of disease was achieved by tracking the precise movements of individuals across the region, something that was only possible using mobile phone data.
In Sierra Leone, IBM working with NGOs and telecoms providers set up a text message reporting system for ebola-related data. That in itself was useful, but not qualitatively different from pre-mobile communications systems. But the data could also be analysed in bulk to create precisely-located ‘heat maps’ of opinion and concern that allowed the health authorities to pinpoint preventative measures in advance of the appearance of the disease.
In Senegal and Ivory Coast, the Swedish non-profit organisation Flowminder has used anonymised Call Data Records or CDRs to create maps of likely paths of disease spread ahead of the disease itself. Although the system can track population movements in close to real time, these population pathways don’t actually change much over time: the ‘mobility maps’ that proved so effective in controlling the spread of ebola were initially based on CDRs gathered before the appearance of ebola. Visualisations of the mobile phone data create what amounts to a physical model of deeply embedded human habits, giving an entirely new advantage to forecasters and policymakers.
Using and analysing CDRs requires collaboration between many organizations, public and private. But there is also a mass of publically-available data in the form of the online record of exchanges on social media platforms. For example, last year Portland Communications released its latest annual analysis of Twitter use across Africa’s biggest cities. How Africa Tweets shows a picture not only of where the fastest growth is of high-level engagement with the internet through social media, but also of what motivates and concerns most users.
Twitter is not in fact the social medium of choice in Africa: according to the Lagos technology consultancy Naijatechguide, Twitter applications do not even make it into the top seven social media apps in Nigeria, and only Blackberry users rate Twitter as a leading social media service. Nigerian users are much more likely to use the local 2Go messaging and chat service, or WhatsApp, which unlike Twitter do not rely on fast broadband connections. But Twitter represents the most sophisticated (and well-heeled) mobile internet users in Africa, and it is likely that patterns of Twitter use point the way to the future. How Africa Tweets shows, for example, that the biggest ‘Twitter City’ in West Africa is not wealthy Lagos, but the Ghanaian capital Accra, and the most active Twitter City outside of South Africa is Nairobi – despite Nairobi being only one third of the size of Lagos.
These results have lessons for investors and for policymakers. Companies can learn where the centre of gravity of internet activity is in Africa, and locate accordingly. Policymakers can learn whether their digital economies are growing as fast as they should be: for example it is clear that Nigeria – a country that most visitors would conclude is internet-obsessed – is in fact falling far behind many other African economies.
How far behind can be gauged from the latest Global Information Technology Report from the World Economic Forum. The report is the best rolling measure of how effectively economies are responding to the opportunities created by communications and internet technologies: its annual Networked Readiness Index rates 143 countries in terms of their political and regulatory environment, their business environment, their digital infrastructure, skills and affordability, as well as usage and impact of networked digital technologies.
If that all sounds like a mouthful, the simple way to read the Readiness Index is as a measure of how close economies are to realising the promise of Big Data. And the results show that Africa is not performing well. The continent that is promising a new ‘Silicon Savannah’ is actually falling seriously behind, especially in infrastructure and skills.
The highest-scoring African country in the Readiness Index is South Africa at number 75; next, perhaps surprisingly, is tiny and poor Rwanda, with an unusually high level of government usage, affordability, and a favourable regulatory environment. Within the African group Kenya scores relatively highly, although its skills level is below its overall level. Nigeria – the biggest economy in sub-Saharan Africa – only makes it to number 119 in the world, with particularly poor digital infrastructure, and a digital skills level close to the worst in the world. Perhaps most surprising of all is the high cost of networked connectedness in Africa: most countries in sub-Saharan Africa are among the world’s most expensive when it comes to getting online.
This is the reality behind the explosive growth of mobile communications in Africa. Mobile adoption in Africa may be running at around double the global rate, but the great majority of that growth in connections represents a low and intermittent level of engagement with the online world.
Policymakers will have to do some creative thinking if Africa is not to be left even further behind. They will have to work out how to address the diminishing returns of communications investment (the profitability of new mobile subscriptions is declining, as the last-to-adopt customers are also the poorest), and how to up their game in skills creation. Cost is probably the most important challenge. If India manages to be the cheapest country in the world to access the internet, then Africa could certainly make a much better showing. The alternative is to be excluded from what promises to the most powerful cycle of change since the industrial revolution.
