If you are not interested in a technical peculiarity that occurs in aggregated data sets, just ignore this post.
I am often asked what my thoughts are about selecting the single best attributes (e.g., best name and best address) when multiple attributes are known. I always respond with, “truth is in the eye of the beholder.”
This came as a hard lesson. In the mid-1990’s, I built a data warehouse that was being fed daily by over 4,000 disparate operational systems belonging to handful of widely recognized consumer brands. The goal was to better understand the customer by recognizing when the same person was transacting across different brands all held by the same holding company. The underlying motivation: the more fully the customer is understood the more you can sell to the customer.
There I sat with a number of marketing VP’s, each representing their brand’s interests. And while everyone worked for the same parent company, there was one question no one could agreed upon: When a consumer has transacted with all of the brands, each time using a slightly different name or new address, which name and address should be considered the enterprise-wide GOLD standard? As it turns out, there is no such thing as a single version of truth.
The name and address supplied to a human resources system by an employee is the best name and address for an IRS filing, even if a different name and address has become available from another system. And a hotel statement better be sent to the address supplied by the guest when he or she checks out of the hotel – not some other address deemed “best” because of its perceived currency and reliability from some other data source. For a direct marketing piece, a name and address from a loyalty club program is generally better than the hotel reservation data provided over the phone. Why? Because loyalty club data is more reliable as consumers want to receive their points statement in the mail.
Thus, the definition of best varies based on who is asking the question. So when I am asked how to determine the single best version of truth I recommend being prepared to deliver every version of truth -- for truth is in the eye of the beholder.
Truth on demand … so to speak.