Does it really matter if you round your model results?

I worked with a fantastic marketing EVP, that adored analytics and would use it to drive her decisionmaking despite not being so math-savvy.  She quickly discovered that not all insights were equally strong.  Due to differences from assumptions, measurements of error, or dirtiness of data, some insights were much better than others.  She asked me to color-code the insights coming from my team with my assessment of how strong the insights were.   I was honored by her trust in me to net out the confidence of each insight, but also felt the responsibility of taking all the uncertainty of an analysis and communicating it with a color.  It was challenging.

In recent years, I’ve recognized that I continue to do this communication – maybe not as directly with color coding, but with the rounding and format of my charts and insights. I try not to present data as more exact or precise than it actually is, and this helps set expectations for the viewers.

IMG_20171026_152951Take for example, this picture of a speed limit sign from a downtown street.  It’s a bit silly — we all know that vehicle speeds aren’t measured that precisely.  But yet, when you do an analysis and output a value, if you show a number, like 5.2435, the recipient thinks that you have a very exact answer — and it doesn’t matter if elsewhere on the screen you say ‘results are accurate to +/- 1%’. Rounding is a conscious choice, and the rounding that you choose communicates your confidence in the preciseness of the answer.  To an analyst, sometimes, model outputs are just a number… but for a business person, there is value in whether you round to the nearest penny, dollar or thousands of dollars.  It communicates your certainty in your analysis.

Since realizing this, I have tried to always be intentional in my rounding and consider in graphs what I show and what it means. The better your communication, the better your chance to make an impact!

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