Thursday, April 24, 2008

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?

No comments: