Best Practices

Know Better: A Data Literacy Best Practices Checklist

Data literacy is increasingly important as our access increases. Many of us walk around with powerful computers in our pocket (or, more honestly our hands) at all times. The first and last things we do in our days? Scroll through digital media. Yet, while the volume of data we’re interacting with increases dramatically, algorithms continually limit the perspectives we encounter. When we use data out of context or blindly accept the data we see, we compound the problem. To help you think critically about data, we’ve put together this checklist of data literacy best practices. Why we use data As discussed in our first article in this series, people use statistics and quantitative data for many reasons. These include: Reducing uncertainty and guesswork — e.g. a retail manager might use sales data to better understand when to schedule staff and what inventory to stock or put on sale. Solving problems — e.g. analyzing historic data for an organization’s interactions with different vendors in the supply chain might help a logistics manager identify bottlenecks or weak links. Tracking progress — e.g. establishing key performance metrics and then measuring those goals can help assess what’s working or needs refinement. Making plans — e.g. analyzing past patterns can illuminate larger trends to anticipate a future action or event. With data revealing new opportunities or shortcomings, a utility might optimize its energy production for sustainability gains. Whatever your motivation, data literacy is essential. Questions for those presenting and publishing data Effective data collection and […]