See Data, Feel Data, Touch Data...for free?

Much has already been said about the growth of free alternatives to Microsoft Office - between Google, Zoho and others, the competition leads predictably to questioning the incumbent as well as continued innovation from Redmond.

Meanwhile, Google may also be seeking to make a dent in the area of data visualization. Building on last year's acquisition of Gapminder's Trendanalyzer, Google released a data visualization API, essentially a platform to create interesting displays based on structured data stored in Google Docs.

Initially, there's simply a "cool" factor at work here - "If I could get that salary list, I could post a piles-of-money gadget around the office!" But are there competitive implications? It's interesting that for as many years as it's taken for real on-line competition for Office to emerge, there could be a viable alternative in the much younger data visualization space much sooner.

There are so many questions - What are Google's long-term intentions in this space? Will it be a drag for the leading BI vendors, or will it help popularize the concept and "raise all boats"? Will Google's experience in search engines mean we can expect it to lead the way with unstructured data visualization?

Lowering the Bar for Data Visualization

The luxury watchmaker Romain Jerome has created a $300,000 watch. For billionaires to tell time? Not exactly - the watch doesn't actually tell you the time. What's more, it sold out in 48 hours!

So what does the watch actually do?

“With no display for the hours, minutes or seconds, the Day&Night offers a new way of measuring time, splitting the universe of time into two fundamentally opposing sections: day versus night.”

Day versus night, huh? And it sells out for an unbelievable price?

I'm going to start working on a new dashboard project, directed at CEOs of multi-billion dollar firms.

It won't have KPI's, trends, links or navigation; all it will do is flash two words - either "MAKING MONEY" or "LOSING MONEY".

Next I'll develop a separate version to sell sports teams - a new scoreboard that flashes only whether the home team is "WINNING," "LOSING" OR "TIED".

Another example on how to visualize data...

Being a Boston Red Sox fan and always looking for new and intersting ways to visualize data, I found this tool on Boston.com very interesting. It tracks Manny Ramirez's 496 career home runs and provides different ways to visualize what could be some pretty boring data if presented in a typical grid (see the HR information grid at the bottom). As a baseball fan, it is interesting to see the distances and ball parks where he has hit his homeruns. As a opposing manager, the Pitch count graphic would certainly be a tool to use when facing Manny. Certainly this only scratches the surface on the different ways that baseball measures performance (see Bill James and sabremetrics).

Taking the Heat Out of a Hot Kitchen

(Long-time fans of the Pittsburgh hockey team will understand the title of this post. Go Pens!)

We’ve all seen ‘heat maps’ used as visualization tools. A heat map is a graphical representation of data where the values taken by the variables are represented as colors. Often, heat maps are used in conjunction with an actual map – like the weather map on the back page of USAToday, or the real-time traffic display at traffic.com. And while the information from these maps is useful - “It’s cold and rainy in Boston in April, and the traffic on the Mass Pike is really bad at 5:00pm” - it’s not particularly insightful.

Here’s an interesting application of heat map visualization. It’s from Purdue University’s Project Vulcan, which is quantifying North American fossil fuel carbon dioxide (CO2) emissions at space and time scales much finer than have been achieved in the past. This 5-minute video provides an overview and shows several fascinating examples of the heat map visualizations used in representing the underlying data:



Again, some of the results are expected – "carbon dioxide emissions are high where there are lots of people spending lots of time in their cars" – but not overly insightful. More interesting, however, are the discoveries that researchers have made from analyzing the data in graphical form. There’s an excellent summary in the April 27, 2008 issue of the Boston Globe and two results stand out:

“When you rank America’s counties by their carbon emissions, San Juan County, NM – a mostly empty stretch of desert with just 100,000 people – comes in sixth, above heavily populated places like Boston and even New York City. It turns out that San Juan County hosts two generating plants fired by coal, the dirtiest form of electrical production in use today.”

And the heat maps shows a small, bright-red area (high carbon emissions) in the northwest corner of New Mexico surrounded by wide expanses colored green.

“Purdue researchers discovered higher-than-expected emissions levels in the Southeast, likely due to the increasing population of the Sun Belt, long commutes, and the region’s heavy use of air conditioning. According to Kevin Gurney, assistant professor of atmospheric science at Purdue and the project leader, this part of the map also overturns the prevailing assumption that industry follows population centers: In the Southeast, smaller factories and plants are distributed more evenly across the landscape. Cities, meanwhile, prove less damaging than their large populations might suggest, partly thanks to shorter commutes and efficient mass transit.”

Work is underway to add Canadian and Mexican data to the Project Vulcan inventories. It will be interesting to see what other non-intuitive conclusions will be reached with these analytical and visualization techniques.

Seeing What You Want To See

Before reading further, please watch this 1-minute video:


I first saw this video in an article on “car vs. bicycle” traffic accidents, which noted that motorists almost always say “I never saw him” or “She came out of nowhere” after snapping the bike and/or rider like a twig. The video, produced as a public-service message by Transport for London, is a brilliant illustration of how people often fail to see a change in their surroundings because their attention is elsewhere.

I’ll save my post on bicycle safety laws for another day, and instead ask whether this same phenomenon applies in BI or Performance Management applications – do your reports, scorecards, and dashboards show you “what you want to see” or are they designed so that you can spot the “moonwalking bear” in your company’s performance?

Here’s just one example, from an article in USA Today, where data was potentially mis-interpreted and mis-used with disastrous results. Documents from Vioxx lawsuits indicate that Merck & Co. apparently downplayed evidence showing the pain-killer tripled the risk of death in Alzheimer’s-prone patients. Was Merck so anxious for the clinical trials to be successful that they “saw what they wanted to see” in the results? The company claims they did nothing wrong; we’ll see what the lawsuits ultimately determine.

Sometimes the data is good, but the visualization of that data is bad. Dashboards that look like this



are useful if you’re interested in variance analysis of high-level metrics. But the visualization (essentially a hardcopy report with traffic-lights) doesn’t help with the really interesting stuff, which are the drivers underneath those high-level metrics.

Advanced visualization methods are becoming more prevalent in dashboard designs. Over the next few weeks, we’ll look at some examples of visualization methods that can improve awareness of underlying data and help spot the moonwalking bears.

In the meantime, do you have examples of good techniques you’ve used or situations where better visualization of data would’ve helped improve performance?