Three Ways to Build Literacy in an Industry Built on Data
Paystack is a payments company based in Lagos, Nigeria. We help companies accept payments online and offline, across the African continent. As a payments organization, we are deep in the business of data – financial data and reporting are, in fact, our products – so data literacy is crucial to the success of our mission.
Our team of data engineers, architects, product owners and analysts are focused on prioritizing analytics as we track card transactions, success rates, fraud and dispute occurrences, rate of onboarding completion, on a day-to-day basis. All these activities give us a lot to focus on, so driving data literacy among our 250 employees is core to moving the business forward. If you’ve been wondering how to build data literacy in your company, I see it as a three-step process:
- Align the organization around your goals.
First and foremost, you need to help people to understand what you’re trying to achieve with data. If you don’t, why should they care? They need to know how data helps the product and finance teams, and how it helps with expansion. Data leaders should focus on communicating their goals effectively and properly so that everyone is aligned. There is a self-interest in this as well, of course. If you don’t build a data culture across the organization, colleagues will default to the data team every time they have a question, and that has an impact on the backlog of projects you may be working through. So remember that attending to data literacy also benefits your efforts.
Assuming that you are managing this volume of work, you should be transparent and tell your team members that if they come to you to get every question addressed, they may not get an answer immediately. But if they’d like to know how to answer it themselves, how about joining this data literacy training? Once you cross the barrier to make people more self-sufficient, you are on the way to winning their buy-in and support.
- Train everyone to speak the language of data.
Everyone in your organization should have the ability to understand the data they generate. If you work in a payments business, this is obvious. We track how long it takes for a merchant to complete their first transaction, how they’re using our products, and how their customers are engaging with them. For high-volume merchants, we generate reports to show them how their performance is tracking and recommend necessary changes to improve the rate of successful transactions which is key to their businesses.
- Enable self-service analytics.
Training users to find answers to their questions not only lessens the burden on the core data team to respond to everyday requests; it makes users feel empowered as well. Otherwise their requests may just get added to a backlog.
Part of my responsibility is ensuring that everyone in the business is using the right tools, has the right access to generate insights, and can make data-driven decisions. Enabling self-service is one way to make their jobs easier for them. I like to say to my colleagues, imagine a world where you don’t need to come to us, and your request doesn't have to go through a service management ticket system. Imagine knowing where to find the models or the tables that you require, and that you’re able to dig deep into the data and explore without waiting for somebody to come and help you. This usually inspires them to start thinking differently.
Remember technology and data governance
Two key pieces of the data culture puzzle are technology and data governance. Technology helps you to address the challenge, “What do we do to ensure that we’re not answering the same questions over and over again?” This is why a proper data discovery and data warehousing system is essential to help users query the database efficiently and find the resources (dashboards and tables) they need to get to the insights they need to produce dashboards. If it’s easier to query the database, people are more inclined and encouraged to actually dig deep into the data and find answers for themselves.
Of course, self-service doesn’t mean that all data is open to use. Though we don't have a data governance specialist per se, there are controls in place so that access to data is only on a need-to-know basis. Before you are granted access to sensitive data such as personally identifiable information (PII), you need to understand how this data that you're accessing relates to your work.
I feel fortunate to work in a company where we don’t have to emphasize the importance of looking at data. We prioritize ensuring that everybody is reporting from the same centralized sources. But when you think about it, how many businesses are left that aren’t also in the business of data? This makes it all the more important that we use our influence as data leaders to make data literacy a requirement rather than an option. It may take time to figure out how to build data literacy in your company, but once you do, everyone in the organization can thrive.