Data believability

The BBC news website has an article about how western demand for food and goods drives water shortages in developing countries. The interactive visual below is included. The problem I have with it is that the data just doesn’t seem believable – I’m not saying it isn’t true at all, just that when you deliver information with surprisingly high values (10,850 liters to produce a pair of jeans), you have to delve into that data to stop people instantly dismissing it. For example, how is that volume distributed over growing cotton, manufacture, and transportation? Are you including the water usage of the workers who have some involvement in the trade – is that a fair thing to include?

Without context, information becomes devalued, especially when the data seems outlandish (but may in fact be accurate).

I encountered some skepticism after writing a report concerning excess costs in U.S. shift work operations. The $206 billion annual lost opportunity seemed very high, but the methodology and charts that supported the conclusions made believers, I hope, of the listeners on NPR’s Talk of the Nation, and readers of the print publications who picked up the story.

Do you have believability problems with the data in your company – is it being delivered to the decision makers effectively through dashboards and interactive reports? I can solve your data visibility problems and make your business run more efficiently and profitably. 

One Comment

  1. [...] As with any charting decision you have to understand both what the primary message is, but also design the chart so that other information can be extracted. In this case we have that the public perception of drug use by USCB students far exceeds actual student use. I can’t discuss this chart without also touching on methodology – e.g. for ‘actual’ use did they conduct drug testing on students? Probably not, I bet they just asked the students – see my post on explaining your methodology. [...]

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