One of the biggest challenges I see and experience in working with and using data to support narratives is selecting the right scope for comparison. There are lots of different ways in which scope plays a factor, but one of the most common comparisons to make is across time: at this time last month, last year, etc.
Sometimes shorter timelines are presented due to restrictions in data collection/structure, but often time frames are manipulated to reinforce a narrative rather than giving you the big picture. Often, a favourable benchmark is set like “compared to this time last year” without more context: was the result last year normal, and if so, compared to what? For more tips on contextualizing data, and a deeper look at how this relates to bias, I found this resource helpful.
Are there any other resources or frameworks you all use for helping to address fair comparisons and mitigate bias in your data? I’d love to hear about them!