Not all data are equal — especially in Africa

Reporting with data is supposed to be less messy than dealing with humans. Each spreadsheet column is an set of facts. We don’t have to trust someone’s opinion or faulty memory. Numbers, as they say, don’t lie.

But of course, this isn’t true. Numbers can be made badly. They can be falsified, manipulated, or misrepresented. Nowhere is this more important to remember than in Africa, where the quality of official statistics, though improving, is often in doubt. Sometimes the numbers you need simply don’t exist.

How is one supposed to tell the good from the bad? As with any source, the most important thing is to approach the data skeptically. Ask questions and make sure you get good answers. Here’s some to start with:

• Where did these data come from?
• How were these data made?
• What is included in this data?
• Are the data complete?
• Which data are the most unusual? Why?
• Do the data really mean what you think they mean?
• Could the data have been manipulated?

The last one is especially important if you’re working in a country with weak political and bureaucratic norms. Entire books have been written about inaccuracies — some intentional — in the GDP calculations of African countries. Other research has shown that African national statistics consistently overreport school enrollment, which can impact government spending and aid distribution. Sometimes, data may be correct but understanding how they are calculated, and if there is disagreement or controversy over those calculations, is important in providing context for readers: unemployment is one example.

Try to think of creative ways to validate your data, and incorporate that into your reporting, and even your writing, if you’d like to explain to your process to readers. For example, in a story about remote work, I cited multiple, unrelated surveys that reinforce the same conclusions. In a story about food shortages in Southern Africa, I structured the narrative around the process famine prediction experts use to gather data and make predictions from it.

It’s important to ask if there is a second source that could corroborate the numbers you’re using. That might be an international organization such as the African Development Bank or the World Bank. It might be a trading or treaty partner. It could be a nonprofit that’s active in Africa such as Oxfam or the Center for Global Development. It might be a business that collects its own data. Maybe it’s just a person who can say, “No, I wasn’t counted.” For statistical models or technically complex data, consider asking for help from academic statistician or data scientist.

Data are never perfect, but there are many stories that simply can’t be told without them. If you’re skeptical and diligent about verifying your data, they’ll rapidly become your favorite sources.

This blog post is part of a series written for Atlas for Africa, an initiative to bring Quartz’s chart-building platform, Atlas, to newsrooms and organizations across Africa for free, in support of greater access to Africa-focused data sources and visualization. Interested in a training session with the Atlas for Africa team? Email atlasforafrica@qz.com. Atlas for Africa is supported by Code for Africa’s innovateAFRICA fund and the Bill and Melinda Gates Foundation.