South Africa was captured by a handful of families who with the help of the most senior politicians and civil servants looted government departments and state owned entities. One of those families was the Watson’s who owned Bosasa, a facilites company, that had contracts with dozens of state departments. In January a senior official at the company testified that they had paid millions of bribes to dozens of government servants every month to hold onto the contract. In less than two days the Mail&Guardian Data Desk sourced just under 10 000 invoices that had been paid to Bosasa by about 40 different government departments. This data was verified with the department of finance. We analysed the data and found that the company had been paid about R12 billion in less than ten years. This number has been the most quoted number when referring to how Bosasa captured the state. This was a very important project because over and above the bribes that were paid to secure government projects, the country, our readers needed to know how significant these contracts are. Bosasa is in the process of liquidation.
What makes this project innovative?
Investigative journalism and data journalism intersect with great results in this piece. With time constraints - the newspaper's deadline is Thursday as we hit the streets on Friday - and a small newsroom this is the conclusive piece of the extent of State Capture by Bosasa. With such a small data team (two members) and a lack of resources, the Mail & Guardian Data Desk was able to provide the readers and the Commission into State Capture - that is currently ongoing - to understand how deep the corruption is. There has not been an article in the country that has done what the Mail & Guardian Data Team was able to uncover in such a short period.
What was the impact of your project? How did you measure it?
The amount of R12 billion - paid to Bosasa - that our analysis found has become the most quoted number when referring to how Bosasa captured the state. This was a very important project because over and above the bribes that were paid to secure government projects, the country, our readers needed to know how significant these contracts are. Bosasa is in the process of liquidation. The significance of this article was seen through the level of engagement readers had. The article has been shared from the Mail & Guardian platform close to 2000 times. On Facebook the story was shared more than 500 times and had over two dozen comments. Ordinary citizens shared it and so did political parties and other news sites. The story has had over 10 000 page views (8 000 unique page views) and readers spending more than 3minutes on the page even though readers are known to stay on a page an average of less than a minute. The majority of readers who engaged with the article are aged 35 - 55 and were majority men - which is the Mail & Guardian demographic.
Source and methodology
I am an investigative journalist who has always had a passion for data. These two traits led the team to finding the data, ensured that it is verified with the holders of the data, the department of finance. The PDF was then coverted to excel and csv. To clean the data Openrefine was used and Python. Once the team was content with the veracity and sinsibility of the data, the departments involved were counted and how much each government department paid Bosasa. Time frames were very important as we could then match that to the testimony given by the former Bosasa official and other investigtive pieces that uncovered the extent of bribes for contracts. Using this time fram we could then see when a bribe was paid and when Bosasa was paid for work done on any specific contract. There were a number of hurdles as we did not have the actual contracts and some payments for the same contracts seemed to have been duplicated. Senior department of finance officials - investigative journalism skills in the team - explained what the payment numbers meant and how we would avoid duplication.
We converted PDF documents to Excel. We used Excel, Python and OpenRefine to clean and analyse the data. Python was used to visualise the data so we could easily see the trends over time and to find outliers such as road enfringement payments made to Bosasa by one of the government department.
Athandiwe Saba (Data Desk Editor) Jacque Coetzee (Data Journalist) Sabelo Skiti (Investigative Journalist) Thanduxolo Jika (Investigations Editor) Sarah Smith (Reporter)