Presenting statistics with motion

Whilst sifting through my Delicious links archive (in the process of moving those still relevant into the library direct on this site), I came across this Twitter ‘Just landed’ data visualisation, courtesy of O’Reilly Media’s Strata Gems. Interesting to see how popular Twitter is on internal flights across North America

The O’Reilly post goes on to explain how to write your own (links at the end of this post).

Hans Rosling’s TED talk on global economic and health trends was one of the first presentations to bring statistics to life by using timelines in motion.

Seeing data presented this way is still a rare event yet showing changes across a period of time in motion rather than a series of static charts can deliver a much clearer perspective. And there is software available that doesn’t require money or clever coders.

The image below shows the difference between putting £1,000 in a savings account earning 2% interest versus an ISA with 6% interest over 3 years. (Please don’t laugh, I created it at the beginning of 2008, the decimal point needs moving to the left.)

Click the Play icon to run the motion.

OK, maybe not quite as artistic as the Twitter video. It’s simple little chart but the motion helps emphasise how the gap in interest earned grows over time. How did I create it? Using a Google Docs spreadsheet and its built-in Motion Chart tool. In 2007, Google acquired Trend Analyzer from the GapMinder Foundation. The chairman of GapMinder? Hans Rosling.

If the same can be done in Microsoft’s Excel, I haven’t found it. Leave a comment if you know how.  Excel trumps Google Docs in many ways, displaying motion charts doesn’t appear to be one of them.


Dashboard Design

As a follow on to a previous post – Diluted information, this is a quick review of just two ideas within Stephen Few’s excellent book – Information Dashboard Design.

Spark Lines

Spark lines are an idea from Edward Tufte, author of books such as Envisioning Information. The concept of a spark line is simplicity itself – take a line graph and delete everything but the line itself. This enables you to present a big chunk of information in a very small space, perfect for dashboards. Take the following example:

This is fairly typical of a dashboard or scorecard used to present key performance indicators (KPIs). You’ve got the sales figure, a green light and an arrow going in the right direction. Sales must be good! But how much information do you really have here? You know that your sales number is in a good position today, and compared to your last measurement it is going in the right direction. What does that information really tell you?.

Let’s use a sparkline instead:

The spark line enables you to present a far bigger range of figures with minimal extra space. When you use the traffic light and arrow, you can only see the last two points on this line. But now you can potentially see a whole year’s worth of data. And what does this spark line tell you? That sales are currently good and going in the right direction, but the pattern through the year looks very erratic. Who knows what next month’s figures will look like. Why is that? Can anything be done to settle into a growth curve or are the causes all external and out of your control? Are your suppliers letting you down, disrupting your production line? The spark line encourages you to investigate, providing you with an opportunity to be proactive in resolving issues. Traffic lights create a reactive approach – you only start to investigate when they go red or the arrow is already pointing in the wrong direction.

Bullet Graphs

Bullet graphs are an idea from Stephen Few, providing an alternative to the popular dashboard tool – gauges. Another example:

This is a classic gauge, displaying a measure and the range of values that indicate where you would like it to be. In this case, customer satisfaction is healthily in the green at above 75%. But again, how much information have you been given? A measure and where it sits within a range. That gauge takes up an awful lot of screen estate to give you so little. Enter the bullet graph:

A bullet graph is the perfect diet – it slims down a gauge and gives you extra value to boot. Styled like a thermometer, you can still see the range of values, but now a simple line indicates your current measure. But in addition, the horizontal line can provide a clear alternative measure (this is harder to do with the gauge, where it ends up looking like half a clock). That horizontal line might represent last month’s figure, or could represent the target. Either way, you now have a comparative measure.

To put these two ideas together, it’s worth comparing two dashboards to demonstrate how much or how little information is often presented:

Here is a classic dashboard, with lots of pretty graphs and charts. But, before you even figure out what it all means, how much does it really tell you? Now let’s look at an example that uses spark lines and bullet graphs:

Before you even start to interpret what this dashboard contains, you can see a lot more information is available in a format that you can analyse. And now let’s take it a stage further… Let’s take that dashboard out of the browser…

This screenshot is Excel – your good ol’ spreadsheet (and it’s not even the latest version at that). This simple screen of data inside Excel contains more useful information than I’ve seen in far more complex and expensive business intelligence tools.

How do you create a spark line in Excel? Simple – just create a normal line chart and delete out everything other than the line (go into Chart Options, delete the grid lines, the axis, the heading, the background, everything!).

The screenshots above are all available over on The Dashboard Spy’s web site, a blog I recommend you subscribe to if you are interested in this subject. Having read Stephen Few’s book, it is great fun to critique the different dashboards on display there. I was going to create my own examples in Excel, but others beat me to it and I’m all for not reinventing the wheel. I’ll use a later post to explore if/how Excel 2007’s new data visualisations can enhance dashboards… …and since starting this post, The Dashboard Spy has beaten me to it again.

Final tip

If you are tasked with designing a dashboard or scorecard, there is one important question you should always ask the audience who will be using the end result. Is the dashboard being designed to provide quick answers or prompt for more questions? Too often, the answer is the former when it should be the latter but that’s a whole different political question 🙂 Let’s just focus on designing for the desired role…

Going back to the first image – the sale figure with a green traffic light and an arrow going upwards. That is a classic ‘answer’ KPI. Are my sales good? Yup! Are they going in the right direction? Yup! Great! I can move on to the next task. If that really is all the audience wants to know, then stick with the colourful images and minimal content. The irony is, dashboards that provide quick answers are largely redundant any way. Quick answers are answers you already know and just want validated. If you are interested in sales, you are going to know if the company is doing well or not before you even look
at that dashboard. Just walk down the corridor, lurk by the water cooler, linger in the toilet even – you’ll know from the atmosphere within the office if your sales are good or not. It won’t necessarily tell you whether they are going to stay that way…

The spark line is far more suited to the valuable use of a dashboard – to prompt proactive investigations when the numbers may be good but don’t look quite right…

Technorati Tag: Dashboard

Misleading Pictures

Jon Udell has an excellent blog post showing why you should not assume that images are providing an accurate picture.

He mentions reading two of Edward Tufte’s books over Christmas. Coincidentally, I was also reading some of Tufte’s work during December: ‘The Visual Display of Quantitive Information‘ and ‘The Cognitive Style of PowerPoint‘. Both are excellent reads if you are interested in doing a better job of presenting information, as well as how to spot misleading visualisations.

Here is one snippet that should be observed by all those (mostly Microsofties, at the moment) who are swooning over the new visualisation features in PowerPoint 12 and Excel 12:

The number of variables depicted should not exceed the number of dimensions in the data. The use of 2 (or 3) varying dimensions to show one-dimensional data is a weak and inefficient technique, capable of handling only very small data sets, often with error in design and ambiguity in perception.

Anybody who uses 3d bar charts needs to consider this point carefully. Here’s a simple example:

The data presented in these two charts is identical, but it is much clearer and easier to analyse on the right. The shaded area in the 3D version on the left does not add any information and makes it harder to compare the data values.

On a related subject (I had a bit of a reading splurge during December) the book Freakonomics provides some great examples that demonstrate why we should not jump to conclusions and assume cause and effect when we see correlation between two data sets. Correlation only indicates a relationship between two elements, it does not prove that one causes the other. One of the most common abuses of statistics is to present indicators as causes.

As the technologies to store and analyse large quantities of information improve, it is important that we also improve our abilities to correctly interpret and present the information if we are to avoid poor decisions and the resulting consequences.

Related posts:

Dashboard Dangers

The concept of ‘dashboards’ – tools that present top level information collected from different data sources and presented in a single consolidated view – first appeared in the early days of portals (most v1 portals looked like dashboards). They are now making a comeback, often under the title ‘business scorecard’ with ‘key performance indicators’ (KPIs). Real-time communications and analysis technologies enable us to aggregate information, analyse, discuss, and decide quicker than was ever possible before, and dashboards are becoming the meeting point where it all happens – new richer web applications and development tools have reignited the trend in dashboard interfaces. In the world of application integration, ‘business activity monitoring’ is gaining ground, where processes are monitored and updated in real-time.

But there is a risk associated with relying too much on dashboards, particularly when making decisions that can affect business strategy. Having a single ‘dashboard’ can look nice, neat and tidy compared to switching between multiple applications on your desktop. But the price can be over-simplification of complex issues. The ease and convenience of viewing top-level patterns may stop us from drilling down into the messier, time-consuming details, and those details often hold the keys to real causes.

This concept has been noticed by others. The following quote is taken from an entry over on Steve Pavlina‘s web log. (The full article is here)

…In her book ‘Brain Building In Just 12 Weeks”, Marilyn vos Savant suggests that TV reduces your capacity for rational thought. One reason is that TV over simplifies reality. You are presented with subjects in a matter of minutes where everything is nicely wrapped up at the end. Reality is reduced to labels like good or bad, funny or serious, smart or dumb. This harms clear thinking by conditioning you to expect that most problems have a simple clear solution (and, if not, then it will be an overly dramatic solution). But real people and events defy labels. Real life weaves a much richer tapestry than TV. TV skews your map of reality…

Spot the similarities? There are roles where a dashboard adds huge value. Automated management of I.T. systems for starters, where a red alert flashing on a dashboard (and sent to your mobile phone) can warn you about a systems failure that needs immediate action. Business activity monitoring can provide an early warning system for processes that don’t produce the desired results and enable them to be changed before problems escalate. But sometimes (in fact, quite often), allowing time is the essential ingredient for success. Compare the following two charts:

The first chart shows data plotted for 1 year, between 1992 and 1993. The line appears linear – quantity has increased over time. It’s also quite flat – we might think the increase in quantity is not sufficient to warrant the investment we are making, and decide to change the system. But what if we had persevered? The second chart shows the same data but within 10 years of results. The line is clearly exponential, it just took longer than planned for the investment to pay off. We would not have been able to see or prove this growth curve until after it had happened.

It’s not just time that’s important. Often, particularly in innovation and idea generation, unexpected ‘failures’ create new solutions. We learn from our mistakes. Dashboards can be used to prevent us from making those mistakes.

Charles Handy describes this risk, in his book ‘The Elephant and the Flea‘.

…My first independent command was running Shell’s marketing company in Sarawak. There was no telephone line to the regional head office and my bosses in Singapore. We managed because we had to. And maybe it was better, because there was no real way they could judge me other than by results. Things had to be pretty worrying for anyone to spend two days coming to visit me in what was not the most luxurious of places… If I made a mistake I at least had the chance to correct it before anyone noticed. That might not be possible today without a lot of self-discipline by superiors. Fewer mistakes, maybe, but less learning, less responsibility.

Make sense? It does to me. The danger with dashboards is that they encourage us to over simplify and jump to early conclusions that may not be representative of the real situation. They can prevent us from making mistakes, when making mistakes can provide vital learning opportunities. They can discourage us from trusting people to take responsibility and find a solution. We are no longer satisfied with viewing the results after they happened, we want to use the dashboards to predict the future and enable us to change direction immediately. We can do that, and there will be times when that ability provides great results. But we also need to appreciate the risks involved in not giving people the time and trust to find solutions for themselves. Dashboards in the wrong hands can ruin an organisation…

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  • Related site topic: Growth – explaining the differences between linear and exponential growth

Update: broken link fixed