Melted Dead Dinosaurs or Super Heated Sand?

Dishwasher full and running — I need a cold drink after working in the yard. My wife offers me one of the kids’ plastic cups — I choose a half-size juice glass telling her I prefer super heated sand over melted dead dinosaurs.

Married readers will be quite familiar with the look she gave me.

It did get a laugh (eventually) and a suggestion that it was a great article title. So here it is. This kind of labeling is fundamental to data analysis. What you call something influences your perception. I won’t get into the current political circus, but you can see where names and labels in politics drive opinions and emotions across the spectrum. Democrat or Republican — Liberal or Conservative. These cause people to react viscerally, instantly disagreeing with or defending the viewpoint. Some percentage of people overcome that reaction, examine the data more closely, then confirm or adjust their position. As a data analyst we don’t have the luxury of letting people get a second look. Emotion can stomp on our most carefully crafted reports. That emotion causes a lack of trust in the data, and without trust there is no value, or action.

Vulcan Clarity

 Do we strip all emotion from our analysis? Use only titles like “Column 1” or “Attribute Z”. Absolutely not. We construct the data to convey selected emotions. Not bias, or an intent to sway our audience -but to convey confidence, trust, and reliability. We do that by using emotion — and ADMITTING IT. Show the origin of our labeling. Be clear about methodology.

A Better Name

Let’s look at my title: melted dead dinosaurs or super heated sand. Clear bias in labeling. I wanted the glass, so labeled it such. This could have been: colorfully formed specialty cups or well-stirred burned dirt. Much different messaging. Put this in the context of an analysis.

Report Showing Lack of demand for dead dinosaur products

100% of sweaty husbands in the study prefer super heated sand over the alternative.

Knowing the story, you can see it is ridiculous. It is also entirely factual. To present this professionally, there are a few key points we could change.

  1. State the purpose of the study.
  2. Indicate your population.
  3. Show your yardstick (Measurement Systems Analysis).
  4. Use consistent names for data elements.
  5. Be honest about gaps.

Report on Consumer Demand for Types of Drinking Vessels

Produced by National Glassblowers Association

Study Population: 1

Data obtained via verbal survey. No repeatability or reliability tested.

Test products: Plastic 12 oz drinking cup and Glass 8 oz drinking cup.

Study inconclusive due to MSA and statistically insignificant population.

Why it matters

Repeat business. Bottom line, you might make a single customer happy with the marketing spin on the first report but not only will he not trust your integrity, you’re not building a reputation that will drive additional business your direction. Here’s the key: offer next steps. The study was not sufficient. Clear, factual, but so what? The business owner can’t act upon that. Your report needs to identify actionable next steps. Something like: suggest 10 study groups comprised of 15 people each, ages 28–35, male, ethnic and income diversity to reflect population of southern Miami. Even better — give a cost estimate and a time line. Biased data should not drive biased decisions. . . it should drive better data.

For the record, the kids chew on the edges of the melted dead dinosaur cups and it really grosses me out. No offense intended T.Rex.


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