The Tableau #MakeoverMonday doesn’t need to be complicated

For a while, a couple of  key members of the insatiably effervescent Tableau community, Andy Cotgreave and Andy Kriebel, have been running a “Makeover Monday” activity. Read more and get involved here – but a simplistic summary would be that they distribute a nicely processed dataset on a topic of the day that relates to someone else’s existing visualisation, and all the rest of us Tableau fans can have a go at making our own chart, dashboard or similar to share back with the community so we can inspire and learn from each other.

It’s a great idea, and generates a whole bunch of interesting entries each week. But Andy K noticed that each Monday’s dataset was getting way more downloads than the number of charts later uploaded, and opened a discussion as to why.

There are of course many possible reasons, but one that came through strongly was that, whilst they were interested in the principle, people didn’t think they had the time to produce something comparable to some of the masterpieces that frequent the submissions. That’s a sentiment I wholeheartedly agree with, and, in retrospect – albeit subconsciously – why I never gave it a go myself.

Chris Love, someone who likely interacts with far more Tableau users than most of us do, makes the same point in his post on the benefits of Keeping It Simple Stupid. I believe it was written before the current MakeoverMonday discussions began in earnest, but was certainly very prescient in its applications to this question.

Despite this awesome community many new users I speak to are often put off sharing their work because of the high level of vizzes out there. They worry their work simply isn’t up to scratch because it doesn’t offer the same level of complexity.

 

To be clear, the original Makeover Monday guidelines did include the guideline that it was quite proper to just spend an hour fiddling around with it. But firstly, after a hard day battling against the dark forces of poor data quality and data-free decisions at work, it can be a struggle to keep on trucking for another hour, however fun it would be in other contexts.

And that’s if you can persuade your family that they should let you keep tapping away for another hour doing what, from the outside, looks kind of like you forgot to finish work. In fact a lot of the worship I have for the zens is how they fit what they do into their lives.

But, beyond that, an hour is not going to be enough to “compete” with the best of what you see other people doing in terms of presentation quality.

I like to think I’m quite adept with Tableau (hey, I have a qualification and everything :-)), but I doubt I could create and validate something like this beauty using an unfamiliar dataset on an unfamiliar topic in under an hour.

 

It’s beautiful; the authors of this and many other Monday Makeovers clearly have an immense amount of skill and vision. It is fascinating to see both the design ideas and technical implementation required to coerce Tableau into doing certain non-native things. I love seeing this stuff, and very much hope it continues.

But if one is not prepared to commit the sort of time needed to do that regularly to this activity, then one has to try and get over the psychological difficulty of sharing a piece of work which one perceives is likely to be thought of as “worse” than what’s already there. This is through no fault of the MakeoverMonday chiefs, who make it very clear that producing a NYT infographic each week is not the aim here – but I certainly see why it’s a deterrent from more of the data-downloaders uploading their work. And it’s great to see that topic being directly addressed.

After all, for those of us who use Tableau for the day-to-day joys of business, we probably don’t rush off and produce something like this wonderful piece every time some product owner comes along to ask us an “urgent” question.

Instead, we spend a few minutes making a line chart, that gives them some insight into the answer to their question. We upload an interactive bar chart, with default Tableau colours and fonts, to let them explore a bit deeper and so on. We sit in a meeting and dynamically provide an answer to enable live decision-making that before we had tools like this would have had to wait a couple of weeks to get a csv report on. Real value is generated, and people are sometimes even impressed, despite the fact that we didn’t include hand-drawn iconography, gradient-filled with the company colours.

Something like this perhaps:

Yes, it’s “simple”, it’s unlikely to go Tableau-viral, but it makes a key story held within that data very clear to see. And its far more typical of the day-to-day Tableau use I see in the workplace.

For the average business question, we probably do not spend a few hours researching and designing a beautiful colour scheme in order to perform the underlying maths needed to make a dashboard combining a hexmap, a Sankey chart and a network graph in a tool that is not primarily designed to do any of those things directly.

No-one doubts that you can cajole Tableau into such artistry, and there is sometimes real value obtainable by doing so,  or that those who carry it out may be creative geniuses -but unless they have a day job that is very different than that of mine and my colleagues, then I suspect it’s not their day-to-day either. It’s probably more an expression of their talent and passion for the Tableau product.

Pragmatically, if I need to make, for instance, a quick network chart for “business”, then, all other things being equal, I’m afraid I’m more likely I get out a tool that’s designed to do that rather than take a bit more time to work out how to implement it in Tableau, no matter how much I love it (by the way, Gephi is my tool of choice for that – it is nowhere near as user friendly as Tableau, but it is specifically designed for that sort of graph visualisation; also recent versions of Alteryx can do the basics). Honestly, it’s rare for me that these more unusual charts need to be part of a standard dashboard; our organisation is simply not at a level of viz-maturity where these diagrams are the most useful for most people in the intended audience, if indeed they are for many organisations.

And if you’re a professional whose job is creating awesome newspaper style infographics, then I suspect that you’re not using Tableau as the tool that provides the final output either, more often than not. That’s not its key strength in my view; that’s not how they sell it – although they are justly proud of the design-thought that does go into the software in general. But if paper-WSJ is your target audience, you might be better of using a more custom design-focused tool, like Adobe Illustrator (and Coursera will teach you that specific use-case, if you’re interested).

I hope nothing here will cause offence. I do understand the excitement and admire anyone’s efforts to push the boundaries of the tool – I have done so myself, spending way more time than is strictly speaking necessary in terms of a theoretical metric of “insights generated per hour” to make something that looks cool, whether in or out of work. For a certain kind of person it’s fun, it is a nice challenge, it’s a change from a blue line on top of an orange line, and sometimes it might even produce a revelation that really does change the world in some way.

This work surely needs to be done; adherents to (a bastardised version of) Thomas Kuhn’s theory of scientific revolutions might even claim this “pushing to the limits” as one of the ways of engendering the mini-crisis necessary to drive forward real progress in the field. I’m sure some of the valuable Tableau “ideas“, that feed the development of the software in part, have come from people pushing the envelope, finding value, and realising there should be an easier way to generate it.

There’s also the issue of engagement: depending on your aim, optimising your work for being shared worldwide may be more important to you than optimising it for efficiency, or even clarity and accuracy. This may sound like heresy, and it may even touch on ethical issues, but I suspect a survey of the most well-known visualisations outside of the data community would reveal a discontinuity with the ideals of Stephen Few et al!

But it may also be intimidating to the weary data voyager when deciding whether to participate in these sort of Tableau community activities if it seems like everyone else produces Da Vinci masterpieces on demand.

Now, I can’t prove this with data right now, sorry, but I just think it cannot be the case. You may see a lot of fancy and amazing things on the internet – but that’s the nature of how stuff gets shared around; it’s a key component of virality. If you create a default line chart, it may actually be the best answer to a given question, but outside a small community who is actively interested in the subject domain at hand, it’s not necessarily going to get much notice. I mean, you could probably find someone who made a Very Good Decision based even on those ghastly Excel 2003 default charts with the horrendous grey background if you try hard enough.

excel2003

Never forget…

 

So, anyway, time to put my money where my mouth is and actually participate in MakeoverMonday. I don’t need to spend even an hour making something if I don’t want to, right?  (after all, I’ve used up all my time writing the above!)

Tableau is sold with emphasis on its speed of data sense-marking, claiming to enable producing something reasonably intelligible 10-100x faster than other tools. If we buy into that hype, then spending 10 minutes of Tableau time (necessitating making 1 less cup of tea perhaps) should enable me to produce something that it could have taken up to 17 hours to produce in Excel.

OK, that might be pushing the marketing rather too literally, but the point is hopefully clear. For #MakeoverMonday, some people may concentrate on how far can they push Tableau outside of its comfort zone, others may focus on how they can integrate the latest best practice in visual design, whereas here I will concentrate on whether I can make anything intelligible in the time that it takes to wait for a coffee in Starbucks (on a bad day) – the “10 minute” viz.

So here’s my first “baked in just 10 minutes” viz on the latest MakeoverMonday topic – the growth of the population of Bermuda. Nothing fancy, time ran out just as I was changing fonts, but hey, it’s a readable chart that tells you something about the population change in Bermuda over time. Click through for the slightly interactive version – although of course, it, for instance, has the nasty default tooltips, thanks to the 10 minutes running out just as I was changing the font for the chart titles…

Bermuda population growth.png

 

 

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5 thoughts on “The Tableau #MakeoverMonday doesn’t need to be complicated

  1. Totally, I agree that it would be great to see people creating and sharing simple visualizations, elaborate ones, and everything in between. There’s definitely no “fancy only” rule. Thanks for making that point here, Adam.

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