Makeover Monday, 2017 #2

A reviz of global iPhone sales over the last decade for week two of Makeover Monday in 2017.

On first glance the only thing I wanted to change from the original chart was the slight 3D affect on the columns, and maybe the background colour. Other than that the chart has a clear and simple title and highlights the data point addressing the question posed.

Digging into the quarter-by-quarter data there seemed to be a bit more of a story and, for me, the addition of a moving average helped to smooth out seasonality and see this story:

Global iPhone sales 2007-2016


Adding the bounding boxes around 2015 and 2016 was a mistake as they impinge upon the hover over functionality in the underlying workbook on Tableau Public. They also add some visual clutter, but I was keen to help differentiate and highlight the two years.

On a wider note, there was some good discussion amongst the community about the dangers of data quality and drawing false conclusions (for an example see my previous blog entry on the pitfalls of using taxable income data to draw conclusions about salaries and wages, or dive into this blog post by Steve Wexler and Jeffrey Shaffer and resulting twitter discussions).

To an extent these sorts of issue are inevitable within the constraints of Makeover Monday. Not everyone can commit the time to really dig into the data, and the recommended time of one hour arguably doesn’t encourage it.  For most people the focus seems to be on honing Tableau and data presentation skills. But this is where I think Makeover Monday can turn a weakness into a strength (isn’t that what it’s all about after all?). Whilst most people might focus on presentation in any given week some will focus on, and discuss, the data. That’s great – as a group we’ve then covered multiple aspects of the original viz and data set.

If we were to somehow curate those discussions back to the datasets page on the Makeover Monday website, and every viz had a standard footer re data source (they should have this anyway) with a caveat that linked back to that datasets page, would that address some concerns? Might it also ensure that any one viz viewed in isolation would guide people into the wider discussion and in depth analysis pulled together by the community? Might that be a positive thing in terms of improving understanding of the original story being told?

I’ve had a go at adding such a standard caveat to my viz this week. It could certainly be refined, as could the viz itself, but seems like a good start.