As we wrap up our work in corporate, we decided to reflect on a few of the lessons learnt along the way.
After almost a year, we’ve decided to wrap up the work we’ve been doing around corporate data and private sector accountability. This was an important piece of work that has culminated in a global investigation, with journalists from around the world. So, upon closing the lid on Transparent Corporates, or “TRACE”, it felt like a good time to reflect on some of what I wish we’d known when we started out, and all of the things I’ve learnt along the way.
When we started TRACE, I don’t think any of us really knew what we were doing. Sure, we had the combined experience of about a decade worth of journalism, and extensive knowledge of how to turn complex data into magic, but we didn’t really know what we were trying to achieve; or how we were going to achieve it. We spent some time trying to understand the landscape of what others were already doing in the fight for improved transparency and accountability, then tried to figure out how we could slot ourselves into that world and eventually, switched strategies entirely and actively worked towards telling important stories, using data. It was very challenging and took us the entire length of the project to realise that before we could start exposing private sector-related corruption - by pushing open data’s agenda - we first needed to make sure that the circles in which we were trying to work were acquainted with data; in skill, literacy and curiosity.
It’s easy to be overly critical of your own work, so there are dozens of things I wish I’d known when we started: how to find and read financial statements, what the law said about things like tax avoidance, beneficial ownership and corporate disclosure, how to navigate the companies registry and how to analyse data through the command line. I wish I’d started out with all of the connections, contacts and links that we needed to investigate companies accused of corrupt dealings; instead, my little black book was almost empty. With that in mind, I was lucky enough to have the opportunity of working with some of the smartest, most resourceful and dedicated people throughout the duration of this project, and looking back on all we achieved, I’ve realised that all of the things I wish I’d known were things I learnt during TRACE. Had we not set out to make corporate data freely and easily accessible to the public, then I wouldn’t have gained the skills I did, nor made the contacts I met along the way and wouldn’t have been part of an important, exciting and innovative experience. So, in light of this realisation, here are some of the things I leant, thanks to our work in corporate data:
Others are already kicking ass in the fight for accountability
There’s an extensive amount of work being done around improved corporate transparency and accountability, and it’s being added to all the time. Earlier this year, OpenOwnership launched the first online beneficial ownership registry in the world, and has information on over two million companies in the UK. This is so important in the fight against corruption and improved business integrity, and this is just one example.
Don’t pay for data if you can avoid it
Free information is better than paying for it, some of the time. Resources like Open Corporates, Investigative Dashboard and Source Africa are goldmines when it comes to finding information on companies from around the world, but the better acquainted you get with the world of corporate disclosure, the more you find that companies - especially the big, wealthy ones - are really good at keeping their details private. Which is why the third thing I learnt was so useful!
You need some funding to do this
Having the financial support to buy company records makes investigating them a whole lot easier. It doesn’t cost a fortune, but it isn’t something I could have afforded to do without the support of the organisation and our funders. Those little searches that cost R30 each add up over time and suddenly, you’ve spent hundreds of rands! This can be frustrating if you don’t find what you’re looking for, which is often, but it’s a good exercise in learning how to navigate the register and others like it. It also sheds light on the situation as a whole: transparency isn’t a top priority for so, so many corporates.
Learn to read a lot!
You have to be able to read, a lot, and often, it’s difficult to understand. I’ve been in the business of reading, researching and writing for a while now, but I’ve never read as much as I did during TRACE work. Reports, studies, surveys, company publications, director’s annual reports, academic research and endless news articles. So.many.words. I also haven’t picked up an economics textbook since I was in school, so my understanding of business jargon was extremely limited, and I spent a lot of time researching concepts before reading the actual document I wanted to.
When most people think of data, they see numbers and spreadsheets; they don’t see the possibility of storytelling. We’re nowhere near changing that perception entirely, but we’ve managed to make a start, and the more #GuptaLeaks, Panama Papers and Gaming the Lottery’s there are, the easier it will get.
Work closely with journalists
Working with the media is challenging, but so important. In reference to lesson number five, the media, like most of the public, aren’t well versed in working with data (yet). But, they’re good at getting the message across, so for now, a mutually beneficial collaboration works really well and through them, we’re spreading the gospel of data literacy in ways that make sense and allow people to relate to it.
Learn how to read financial records
Being able to read accounts is essential to conducting a thorough investigation. You cannot expect to uncover tax fraud if you don’t understand the numbers and just like learning to work with data, it takes a lot of practice to get it (even semi) right. If you’re like me then numbers can be crippling, but even a mathematical illiterate dummy can learn how to read complex financial records - at least, enough to understand what you’re looking for.
And legal documents
With that in mind, it’s equally essential to understand how to read legal documents.In order to understand what we were investigating, I spent a lot of time learning about different concepts, and some of that was spent reading letters, judgments and legislation. An extra tip: make friends with lawyers who understand company, tax and admin law, it’ll make your life a lot easier!
Command-line is your friend
Learning how to use the command-line is life-changing! I had one of my colleagues, a coding wizard, teach me how to use this simple but extremely useful little tool. I didn’t know that you could use it for more than making changes to your system, and I had no idea how much faster and more efficient my data analysis would be until I started using it properly. Forget excel, the terminal is my NBF and it allows me to make analytical magic happen!
It takes time
Sometimes, you spend weeks investigating a company, person or organisation and find nothing. You need to learn not to be so hard on yourself, your team and often, you’ll need to rely on actual reporting to figure it out. Continuously ask questions and compile those in such a way that when it comes time to ask a company, its director or employees about something, you know exactly what you’re looking for. On that note: keep records, of absolutely everything you do, you never know when that seemingly unimportant document becomes the key to your entire story.
If you’re interested in some of the work we did as part of TRACE, you should start with the lottery investigation we were involved with. eNCA has published a couple of South African-related stories, and there are still many more to come. We also spent some time trying to understand things like corporate tax, beneficial ownership and tax evasion.
And with that, it’s come time to put corporate data to bed and keep pushing for improved transparency, accountability and Open Data through other methods, like civic technology, co-governance, citizen empowerment and data literacy. Viva Open Data, viva!