Data Storytelling: How to avoid telling Stories that Lie
Today, I’m going to tell you a story about our data (provided yesterday) that is great news.
Revenue is growing quickly, with December jumping significantly over November. You can see this in our revenue chart below:
This growth was led by a 1,150% jump in revenue for Product D! If the trend continues we would expect overall revenue to exceed $100,000 in January for the first time. This is an exciting time for the business, and this growth is a direct result of the strategic decisions I made in June of last year.
Why is this Story Good?
It’s not, it’s a lie.
Why is this Story Bad?
I’ve used some very common tricks in data storytelling to trick you into reading more into it than is really there. Specifically:
- Manipulating Scale. When looking at a chart, you are used to comparing the size of bars to determine relative size. By having the y-axis start at an arbitrary value, instead of zero, I changed the relative size to make it seem like there is significant growth where there isn’t.
- Cherry picking. I’ve selected only a few data points that make my case (growth rate of Product D), instead of considering the full breadth of the data and what it really conveys.
- Jumping to conclusions. I’ve jumped to conclusions based on the data despite there being no clear logical basis. Why would the decisions I made last June have affected revenue in December?
In this case I was being malicious and purposefully lying. Tomorrow we’ll cover how you can have the best intentions but still inadvertently mislead your audience.
Outlier tells you stories about your data. Outlier monitors your business data and tells you stories that capture insights about unexpected changes and patterns. If you’re interested in seeing a demo, schedule a time to talk to us.