As a student of Deming's statistical and quality principals throughout my professional life, I grew accustomed to looking at data with skepticism before using it to development my own strategies. Who is the source of the data? How many data points were used to reach the conclusions? Is the data statistically significant or is it just random noise? All important questions that today's "move it, advertise it, fix it later" crowd has never learned.
Example:
Google AdWords marketing "expert" calls me to discuss my advertising campaign. He talks confidently (he works for Google!) and has a plan for me. As we go through my results, he points out that I had a conversion from a particular zip code so I should target that zip code. ONE conversion. I asked him if he didn't think that may ONE data point was a little light on developing a new strategy. He said no, that I was wrong to ignore even a single data point and I was foolish for not throwing more money that way.
I asked him, "so if a person happens to walk into my store and ask for a repair for an {insert esoteric phone model here - one where there are about 50 in the world made), then I should immediately shift my target market towards that phone?" In light of the new spin, he wasn't so sure.
Statistically speaking, until the # of data points approaches 30 or more observations, the results you are seeing are pretty random. You can flip a coin and get 5 heads in a row and assume the world is all heads but over time, we all know that isn't true.
Before using data to make important decisions, look at it through Deming's eyes. And if you don't know who Deming is, go find out.
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