In-Depth
CRM ROI: What’s in a (Customer) Name?
In today’s compliance-crazy climate, data profiling is all but essential
Is it Dostoevsky or Dostoyevsky? Tolstoy or Tolstoi? Maybe Dostoevski and Tolstoj? The seemingly minor differences are too important to be left to the translators. In today’s regulatory climate, such variations have become a chief concern of IT organizations, too. With customer relationships more valuable than ever, it’s no wonder that keeping data clean and consistent is now a necessity.
After all, Fyodor Dostoevsky and Feodor Dostoyevsky could very well be the same person (read: customer), but you’d never know it if your data management software isn’t smart enough to make the match. And if your data management tools can’t get you this far, how are they going to determine that Fyodor Dostoyevsky and Anna Dostoevsky are actually married?
That’s where Language Analysis Systems Inc. (LAS), a provider of multi-cultural name identification, profiling, and cleansing software, enters the picture.
In business for 20 years, LAS has a host of customers in the government sector. Recently, the company expanded operations to include the commercial sector, too. The driver, says CEO Jack Hermansen, is regulatory compliance—and not just of the SOX variety. There’s the USA Patriot Act for starters, along with several dozen federal and international watch lists—including those maintained by the State Department and the Treasury Department’s Office of Foreign Assets Control (OFAC).
The point, says Hermansen, is that U.S. and international firms are prohibited from doing business with any of the governments, companies, or individuals on these lists. The rub, of course, is that because of the vagueness and inexactness of transliteration, not to mention the wild profusion of naming and syntactical schemes, it’s often difficult to distinguish the Saddam Husseins from the Prince Husseins.
“Names of people, places, and businesses—there are no dictionaries for them, there’s no way to look up [a name] and say, ‘This is wrong.’ We run into very, very intractable problems [in transliteration from] other writing systems, so if somebody’s looking for a name coming from the Korean culture, or the Cyrillic—for example, Tchaikovsky with a ‘T’ in front of it, because that’s the French transcription of his name—we have to be able to match that,” he explains.
That’s where LAS has invested the bulk of its time and research. For example, Hermansen points out, LAS recently released a new name-profiling tool, dubbed NameInspector, that complements its existing name and non-name tools: NameParser, NameClassifier (which can identify names on the basis of ethnicity, nationality, etc.), NameHunter (a name search optimization tool), MetaMatch, and others. Most of LAS’ other offerings have evolved over time in response to the specific needs of customers. NameInspector, on the other hand, is a product of the post-9/11 age. It helps identify parsing issues and erroneous names, highlights gender and culture distribution by name, and can pinpoint other name-based anomalies or insights.
The idea, Hermansen says, is that organizations can use a product such as NameInspector to simultaneously ensure compliance with (often draconian) regulatory requirements and improve the quality of their data. “[DBAs are] constantly frustrated by the inability to demonstrate return on investment, but where we’ve showed NameInspector, even before the formal announcement, people were very impressed with this idea that you had metrics [to measure improvement],” he says. “They want to have something to measure against, and NameInspector is really good at pinpointing where to look. Everybody who knows, and everybody who’s honest, knows that they’ve got problems with their data. NameInspector gives them a place to start.”
Does improvement of this kind translate into dollars and cents ROI? “I couldn’t quantify it in terms of actual ROI, but—if you think about the U.S. Postal Service (USPS), what’s called a National Change of Address, it manages all of those forms. … They’ve estimated that they lose $600 million a year because of an inability to match certain changes in address,” he says. “And it comes down to the name. They’ve pretty much squeezed all variation out of addresses and change of addresses, but they can’t make conclusive name matches.”
In this case, he says, a one percent improvement in the USPS’ sorting procedures would translate into a $6 million ROI. And NameInspector is priced to move, too, says Hermansen. “We’re looking at a new market where customers can make dramatic increases in their name searching without a huge investment. Our average sale to the government is about $200,000, but a lot of people just can’t make that kind of commitment. NameInspector will come in significantly lower, and it will make a dramatic improvement just by cleaning up the data.”
About the Author
Stephen Swoyer is a Nashville, TN-based freelance journalist who writes about technology.