In my recent article for the Visual Business Intelligence Newsletter, titled Building Insight with Bricks, I introduced “bricks” as a new way to display quantitative values geospatially (e.g., on a map), which in theory can be read and compared more quickly and precisely than bubbles. Here’s an example:
Since the publication of the article last week, my concern for a particular limitation of this approach has grown. I mentioned in the article that bricks, unlike bubbles, do not work when they overlap. Even though I recognized this deficiency from the start, I didn’t fully appreciate at the time how much this deficiency limits the usefulness of bricks. Comments from readers, however, have raised my awareness. I especially appreciate the response from Andy Cotgreave, who took the time to mock up examples of bricks vs. bubbles to illustrate the problem, and from Joe Mako, who challenged my assumption that geospatial displays don’t usually involve overlapping values.
While discussing this issue with Joe, I asserted that business uses of geospatial displays don’t typically involve overlapping values. Joe challenged my assertion, inviting me to defend it. As I began to construct my case, it gradually dawned on me that overlapping values are more prevalent than I imagined while designing bricks. This oversight occurred, not because I’m not familiar with broad and common uses of geospatial data visualization, but because I had narrowed my focus to a subset of use cases and concluded too swiftly that this subset was much larger than it actually is. I never stepped back to recognize and sufficiently test my assumption. Even an informal round of peer reviews involving some of the brightest minds in the field didn’t draw my attention to this oversight. I suffered from a blind spot while designing bricks that I never managed to correct.
Bricks are still useful; just not as broadly useful as I imagined and hoped. I failed to add as much value through the invention of bricks as I expected. I’m disappointed, but not discouraged in my effort. I was trying to solve a very real problem, and even though I’ve potentially solved it to a lesser degree than intended, I’ve succeeded more thoroughly perhaps in raising awareness about the problem. I’ll keep working on it, and I hope that you’ll join me. This is how science works. Our limited successes and even our total failures are useful and as such ought to be shared. Others can learn from our mistakes, but only if we make them known. I invite you—challenge you even—to succeed where I failed. If you do, I’ll be content that I contributed through my failure to your eventual success. After all, the benefit that our work delivers to the world is all that ultimately matters.