Data Quality and the Blemishing Effect

In his book To Sell Is Human: The Surprising Truth About Moving Others, Daniel Pink discussed a variety of framing effects that can influence our purchasing decisions, including a 2012 marketing study on whether a negative could ever be a positive.  In one experiment, information about a pair of hiking boots was presented to participants as if they were shopping for them online.

“To half the group,” Pink explained, “researchers listed all the great things about the boots—orthopedic soles, waterproof material, a five-year warranty, and more.  To the other half, they included the same list of positives, but followed it with a negative—these boots, unfortunately, came in only two colors.  Remarkably, in many cases the people who’d gotten that small dose of negative information were more likely to purchase the boots than those who’d received exclusively positive information.”

The researchers dubbed this phenomenon the blemishing effect, where adding a minor negative detail in an otherwise positive description of a target can give that description a more positive impact.

I wonder if selling the business benefits of data quality could be positively affected by the blemishing effect.  In other words, instead of emphasizing the negative aspects of not investing in data quality, which often only makes our data quality sales pitches suffer from Chicken Little Syndrome, what if we emphasized all the positives first and then sprinkled in a little negative?  What if before talking about why our data quality needs to get better, we talk about why our data quality isn’t worse?

“But the blemishing effect,” Pink explained, “seems to operate only under two circumstances.  First, the people processing the information must be in what the researchers call a low effort state.  That is, instead of focusing resolutely on the decision, they’re proceeding with a little less effort—perhaps because they’re busy or distracted.  Second, the negative information must follow the positive information, not the reverse.”  Citing the researchers who performed the study, Pink explained that “the core logic is when individuals encounter weak negative information after already having received positive information, the weak negative information ironically highlights or increases the salience of the positive information.”

As Pink concluded, “if you’re making your case to someone who’s not intently weighing every single word, list all the positives—but do add a mild negative.  Being honest about the existence of a small blemish can enhance your offering’s true beauty.”

The next time you’re making the business case for a data quality initiative, try listing all the positives that high-quality data has brought to your organization—and then add a specific instance where poor-quality data negatively impacted the organization.  Perhaps being honest about the existence of a small blemish will enhance the true beauty of your data quality business case.


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