2. Dead men cast no votes
Data cleansing can be a matter of life and death -- literally. PR specialist Nancy Kirk was volunteering in the congressional elections of 2006, calling registered voters to get them to the polls, when she noticed something odd: Three out of ten voters she dialed were deceased and thus ineligible to vote (except in certain precincts in Chicago).
The problem of having data that is literally dead is not uncommon in the commercial world, and it has real consequences for the living.
Jim Keyser, president of The Keane Organization's Investor Retention and Communication Solutions division, has spent the past year rolling out an investor data quality program for Keane's clients, which include major insurance companies, mutual funds, and Fortune 500 firms.
Keyser says they often find 8 to 15 percent of clients' data records contain anomalies such as mistyped Social Security numbers or outdated addresses. But about one in five of those anomalies is a shareholder who's been dead for more than five years. In one case, a client had an “active” account for a shareholder who last drew breath more than 72 years ago.
“This isn't client negligence, it's just a naturally occurring problem,” Keyser says. Private companies go public, change names, get acquired, or spun off, and their shareholder data follows along, often for decades.
But the consequences can be greater than just money wasted on unnecessary mail. The biggest concerns are fraud and identity theft. Some stranger could be cashing the late shareholder's dividend checks, the rightful heirs could be denied their inheritance, or confidential company info could leak out.
The solution? Software such as Keane's Score application can identify data anomalies across different systems and flag them for review. But all companies must exercise due diligence, have good internal controls, and scrutinize their data on a regular basis, says Keyser.
“Virtually every business has this problem to some degree,” he says. “From a risk management point of view, the best practice is to make sure you're keeping it in check. Understanding how this natural phenomenon impacts you is a good first step.”
3. Duped by duplicates
User error is bad. User ingenuity can be worse. Take the case of the major insurance carrier that kept most of its customer data within a mainframe application from the 1970s. Data entry operators were instructed to first search the database for existing records before entering new ones, but the search function was so slow and inaccurate that most operators gave up and entered the records from scratch.
The result? Individual companies ended up in the database 700 or 800 times, making the system even slower and less accurate.
Unfortunately, the application was so deeply embedded in the company's other systems that management was reluctant to spend the money to rip and replace. Finally, the carrier's IT department made the business case that the company's aging data app would ultimately prevent it from being able to add new customers, costing it $750,000 a day in new premiums.
At that point, the company used SSA-Name3 by Identity Systems to clean the data, ultimately weeding out 36,000 duplicate records.