Christmas and other family reunions are a challenge when it comes to healthy eating habits. You always add a kilogram or two (maybe even three). However, your weight chart is almost flat. There is no bump. How come?
While the holidays are in full and there’s an inflow of Christmas cakes, you begin to ignore the weight scale values. You might look at it and be a bit upset, and then the next lunch or dinner comes and you forget about it.
When data begins to show a change of habits, sometimes we chose not to record it, or simply to ignore it. Because it will pass. This is a phase. It was a blip. However, for someone looking at your chart, and knowing, this will come as a (bad) surprise.
Your audience can be surprised by your graphic
The first case is when a chart doesn’t show all the data:
- data is missing because you don’t have it or because you choose to not include it
- data is misinterpreted because the analysis was not completed or you didn’t use all the data
- the chart is missing important context which could explain your conclusions
In this case, you should review your choices regarding the data and its interpretation.
The second type of surprise is when the chart’s focus is not on what’s expected. You could be wrong about the conclusion. Or the data is “wrong” and leads your chart to a partial or incorrect conclusion. In this case, you need to look at your conclusion. Challenge it and try to show it’s wrong. Then improve your arguments or fix your graphic.
Of course, the good surprise exists too. This happens when the chart confirms your expectations and adds more arguments. This is when someone did her job and gave you a synthetic way to present your arguments. This is the way you become a part of the conversation through your graphics.
Avoid bad surprises! We are already mid-January and it is time to subscribe to receive the Tiny Graphics book for free (the waiting list is closing January 31st).