Recently, my wife and I were shopping for eye glasses at a popular national retailer. After finding frames she liked, we walked up to the sales counter to make our purchase.
“Have you purchased from us before?” the sales clerk asked my wife. In order words, he was asking if she was already a customer that he should be able to find in their customer database.
“Yes,” my wife responded, “in fact, I bought my current glasses in this very store last year.”
“Excellent,” the sales clerk said as he prepared to enter her information into the computer, “we really appreciate that you have returned to purchase from us again, what’s your last name?”
“Damianakis.”
“Uh-huh. Could I see your drivers license?”
No, my wife wasn’t getting carded before she could buy a pair of glasses. The sales clerk wanted to make sure he typed in our last name exactly as it is spelled.
“Hmmm,” the sales clerk muttered while staring at the computer screen, “I can’t seem to find your account.” To his credit, he decided (I swear that I just stood there quietly smiling) to try intentionally misspelling our last name – five different ways.
“Are you absolutely sure that you purchased your glasses from this store?”
“Yes, absolutely.”
“Oh well,” the sales clerk responded, “I guess I will just have to enter you into the system again. For the inconvenience, I will take another 5% off the price.”
I couldn’t help but think to myself – I just witnessed the creation of a duplicate customer – despite the diligent efforts of a front line employee!
It can sometimes be difficult to make a compelling business case for data quality. But what company doesn’t value repeat business? However, if your current reports are telling you that only 15% of new sales this year have been from repeat customers, how many of those apparently new customers are in fact, already a customer?
Furthermore, isn’t it time that we get computer systems to adapt to us, instead of us always adapting to their limitations?In this particular case, the sales clerk knew to try several intentional misspellings but was unable to find the right record. That’s backwards – the clerk should have entered the information he knew and the computer should have done the hard work to find the right record.
There is a better way! What are we waiting for, let’s eradicate this problem!
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Recently I received this email from a friend.
Stef,
Thought you’d get a kick out of my experience over the weekend. It seems to illustrate a novel sort of data quality problem. I was visiting my friends who live in Baltimore, and managed to lock my keys in the car. So I called the locksmith I found in the yellow pages, and handed my cellphone to my friend to describe where the locksmith should go. He said, “We’re in Hamilton, on Twin Oak, just a couple of blocks south of Hamilton Ave.” This seemed to satisfy the operator, and I was promised a locksmith within the hour.
50 minutes later I get a call on my cellphone. It was the locksmith, “Hey, I’m trying to find Twin Oak, and not having any luck.” I put my phone on speaker, and explained the situation to my friend. He said, “We’re between Harford and Walther.”
The locksmith paused for a moment. ”I don’t know either of those streets.”
My friend shot me a look like the locksmith was crazy. ”What do you mean? Those are two major streets in Baltimore.”
“Baltimore? I’m in Hamilton, NJ.”
“NJ? How did that happen?”
“Oh, jeez. Sorry about that. A couple of months ago we started using a regional call center that’s located in central Jersey. Don’t worry, this happens all the time. First time I’ve gotten a call for Baltimore, but I get calls for Indiana all the time. I’ll call back the dispatcher, and I’m sure they’ll get someone out to you soon.”
Sure enough, about half an hour later a locksmith showed up and opened up my car. But I guess when the operator saw that my cellphone had a 609 area code, and heard Hamilton, she just assumed it was NJ. Of course, we were calling into a local Baltimore number. We just assumed they’d know we were in Baltimore. It just shows how things can get messed up these days.
Cheers,
Michael
My friend is right, I do find it fascinating. The consolidation of customer service centers carries the potential of lower cost and better availability, but also eliminates local knowledge and local context that used to minimize errors before they occurred. It’s just one more reason why companies need to be more vigilant than ever about data quality, and need to provide front line personnel with tools to keep it under control.
All these butcherings of my last name remind me of something that happened a few years ago.
We were meeting with a large hospital near the west coast and, as I often do, I gave a few examples of my own experiences having “Damianakis” butchered (how can you not butcher such a name?) and how that affected my experience with various organizations. And of course, the flip side, how the organizations were impacted as well (added expense and risk, etc).
At one point during the meeting I was fielding questions about the advantages of our mathematical modeling approach when the CIO raised his hand and asked me “is Damianakis your stage name?” I was caught off guard, “No, I’m not involved in the performing arts” I responded. “No”, he said, “is that your real name?” Then it finally registered…
It’s good to know that I have the right name for my chosen profession.
Surprisingly though, most people suffer the same problem with their names as well. At least that’s the result of my informal, unscientific poll. Even people with short common names often end up having their names being butchered. Common responses in my poll were “they never get my name right” and “they often make a mistake,” etc…
Unfortunately computers are equal opportunity offenders, so the problem isn’t confined to just names of people, it happens with every kind of data they store.
