Big Data, Beautiful Data
Big Beautiful Data
Large and reliable datasets are few and far between in the rising economies of East Africa. However information is available if one is innovative and willing to experiment. One underutilized source is telecommunications data. It is available for most societal sectors, and harnesses two key factors; location and finance. This is one of the few sources of big data available here.
In developed economies, accurate data is available from a variety of sources and for a variety of purposes. This data is available for a few reasons. The vast majority of citizens are on the grid from the cradle to the grave. Their birth and death are registered. In between taxes, property purchases, bank accounts, addresses are linked to an individual and available in a variety of databases for decision-making by the state.
This is less-so the case in developing economies, such as Uganda. Although huge strides are underway to rectify the situation, these datasets are often unavailable, inaccurate or incomplete. The informal economy accounts for 43% of the economy and is growing.
Telecommunications data is the treasure trove; undoubtedly the most comprehensive and accurate dataset available in East Africa. But what, you ask, can telecommunications data tell us?
They know where you are. They know where you’ve been.
The location of each individual carrying a phone is tracked. Do you travel the same route each day at 07.00 and the reverse at 18.00? You may have a steady job. Does your location remain close to where you spent the night? You may be unemployed or a farmer. Or does your location move occasionally at chaotic speed and urgently swerve? You may be a boda boda (motor bike taxi) rider.
They know where we all are. They know where we’ve been.
One can scale this to understand traffic patterns by analyzing the movement of mobile phone signals on a road. Various agencies around the world are using this data to understand live traffic patterns; where and when do blockages occur. Using this information, agencies can tackle the real problem areas for maximum effect. Long term projects, such as road development or upgrade also greatly benefits from this data.
In East Africa, the UN is already crunching these datasets to study large scale population movements. This equips decision-makers with the information about the scale of the problem and where to devote the limited resources.
Show me the money!
Where is the wealth? Where is the poverty? Where, when and how is money moving? As the most widespread financial service available in Uganda, telecommunications data is best placed to answer these questions. At its most basic, one can identify wealthy and poor areas by studying the sums people load to their mobile accounts, the value of calls/SMS/data used, the money they receive and the money they send.
One can then build on this to study financial movement over time and how it relates to other factors. Will we see a reduction in money transfers in a specific region following poor rains and crop failure? Six months after the construction of a bridge to improve market access in rural area X, what is the impact on the spending habits of the target community? The evidence is there, waiting to be appreciated.
Telecommunications data is a beautiful resource for decision-making at all levels and a variety of sectors. True, not everyone has a phone but its value is enhanced by the lack of alternative sources; more have a phone than have any other link to a centralized database. One key question stands though, will the network providers share it?