There are right ways and wrong ways to show data, there are displays that reveal the truth and displays that do not [...]Some have momentous consequences
I recently found this quote from an unknown author:
Make business decisions with your heart and you end up with heart disease
...at the same time, I finished reading the book "Visual and statistical thinking: Displays of evidence for making decisions" by Edward R.Tufte.
Both say you need evidence to make business or general decisions. The later goes deeply: such evidence needs particularly good displays to finish enlightening the truth. Indeed, even if you collect good, numerous and consistent data, "making decisions based on evidence requires the appropriate display of that evidence"*.
In his book, E. Tufte explains how good and bad displays of evidence had momentous consequences: a cholera epidemic stop during the 19th century in London and the explosion of the space shuttle Challenger several seconds after launch in 1986.
In the first case, Doctor John Snow reached the right cholera-infected well by displaying the numbers of dead people on a map. In the other case, engineers failed to show correlation between O-ring damages and cool temperatures using poor tables while a simple scatter plot would have stopped the launch. They unfortunately didn't manage to display data "causally" and the NASA still decided to launch Challenger by 29°F outside.
In those 2 cases, scientists and engineers gathered quantitative data to show relationships between causes and consequences then made decision. Ones proceeded with consistency, used quality methods, thought "causally" and let no doubt while displaying evidence, when others did all the contrary by obscuring and unrelating data so that unconvincing charts provoked some doubts about the evidence. And led to a death decision.
What does it mean? No cause and effect statement = no argument = no credibility = none or irrational decision-making
According to E.Tufte,
if displays of data are to be truthful and revealing, then the design logic of the display must reflect the intellectual logic of the analysis. It includes: Documenting the sources and characteristics of the data Insistently enforcing appropriate comparisons Demonstrating mechanisms of cause and effect Expressing those mechanisms quantitatively Recognizing the inherently multivariate nature of analytic problems Inspecting and evaluating alternative explanations
That's why at WE ARE CLOUD, we tried to propose you relevant widgets to draw and display charts respecting information design principles (through color choice, non-data pixel minimization and more). Moreover, our future METRICSDICTIONNARY will allow you to share and find new displays. The aim is to propose you alternatives to enlighten your data, then evidence, for best decision-makings.
*E.Tufte's quotes from "Visual and statistical thinking: Displays of evidence for making decisions"