Representativiteit is dood, lang leve representativiteit!

I'm in Amsterdam where for the last two days I've attended an ESOMAR conference that began as a panels conference in 2005, morphed into an online conference in 2009 and became 3D (a reference to a broader set of themes for digital data collection) in 2011. This conference has a longstanding reputation for exploring the leading edge of research methods and this one has been no different. There have been some really interesting papers and I will try to comment on a few of them in the days ahead.

But as an overriding theme it seemed to me that mobile has elbowed its way to the front of the pack and, in the process, has become as much art as science. People are doing some very clever things with mobile, so clever that sometimes it takes on the character of technology for technology's sake. Occasionally it even becomes a solution in search of a problem. This is not necessarily a bad thing; experimentation is what moves us forward. But at some point we need to connect all of this back to the principles of sampling and the basic requirement of all research that it deliver some insight about a target population, however defined. Much of the so-called NewMR has come unmoored from that basic principle and the businesses that are our clients are arguing about whether they should be data driven at all or simply rely on "gut."

At that same time we've just seen this fascinating story unfold in the US elections that has been as much about data versus gut as Obama versus Romney. The polls have told a consistent story for months but there has been a steady chorus of "experts" who have dismissed them as biased or simply missing the real story of the election. An especially focused if downright silly framing of the argument by Washington Post columnist (and former George W. Bush advisor) Michael Gerson dismissed the application of science to predict electoral behavior of the US population as "trivial."

So today, regardless of their political preferences, researchers should take both pleasure and perhaps two lessons from the election results. The first is that we are at our best when we put the science we know to work for our clients and do them a major disservice when we let them believe that representivity is not important or magically achieved. Shiny new methods attract business but solid research is what retains it. The second is that while the election results were forecast by the application of scientific sampling, it was won with big data. The vaunted Obama ground game was as much about identifying who to get to the polls as it was about actually getting them there.