What can master data management software analysis of Bernie Madoff's client list teach businesses about the danger of data silos? Plenty, says MDM vendor DataQualityFirst. While Bernard L. Madoff awaits sentencing from the comforts of his prison cell, the rest of world (financial and legal authorities) is untangling the web of investor connections, “feeder funds” and victims’ transactional data that grew out of his now-infamous Ponzi scheme. MORE ON CIO.com Data-Management Danger: Less Than Half of MDM Plans Are Effective MDM: Forgiveness for All Past Data-Management Sins? How Master Data Management Unified Financial Reporting at Nationwide Insurance Bernard L. Madoff Investment Securities LLC’s database of customer data (containing information on account owners, their addresses, and the relationships of the names and addresses to Madoff) and its spiraling connections is, in fact, not unlike what you’d find in many companies today: siloed databases chock full of customer, partner and supplier information that typically has consistency and data-cleanliness problems. This nearly universal business problem ultimately leads many a company to investigate and launch master data management (MDM) programs. MDM has always had the classic tech-industry buzz worthiness surrounding it: it’s a three-letter acronym; not everyone knows exactly what it stands for; and there’s confusion over whether it’s a technology or an enterprise strategy aided by technology. MDM has come along with a memorable catchphrase—MDM: Helping companies get to “one version of the truth.” “Do You Know Who You Do Business With?Unfortunately, due to the complexity of the topic, MDM conversations have been known to induce spontaneous yawns and blank stares across board rooms and IT departments when the topic comes up for discussion. (Read how Nationwide was able to pull off a massive MDM transformation, despite numerous obstacles.) With all this in mind, a new MDM vendor named DataQualityFirst seized on the Madoff scandal to offer a real-world example of how complex data management can be for businesses today and how a software solution can help understand and better manage the mess. The question that DataQualityFirst President Robert Rich poses in a report is this: “Do you know who you do business with and the relationships between them?” When the answer is “Absolutely!” good things happen, he contends, but as you move toward “Not really,” it can lead to bad outcomes. In the report, Rich explains how his software successfully completed a “proof of concept” exercise using the account and client list of Bernard L. Madoff Investment Securities LLC (BMIS). The software (named PartyQualityInsight) “integrates customer data from multiple sources, identifies and describes relationships between party types such as persons or businesses, and automatically identifies duplicate and incomplete records,” according to the company. PartyQualityInsight “translated and organized more than 13,561 account records into coherent, complete customer information” that could be loaded into data warehouses, MDM repositories and enterprise applications such as ERP and CRM, Rich explains. (Anyone can download the case study here.) There’s No Quick FixIn total, the software found 23,076 party instances (people or legal entities) on the Madoff client list and 13,593 unique parties—7,247 people and 6,346 businesses. When analyzing the BMIS customer account data, PartyQualityInsight discovered that of the 13,561 account records, 41 of them contained the words “Bernard” and “Madoff.” This, of course, raises important questions, notes Rich: How many of these accounts did Madoff himself own? What relationships does he have to other accounts? What are the different addresses related to Bernard? Rich explains in the report how these pieces of data can be gathered and how these important Madoff-related questions can be answered. For today’s enterprise, the Madoff-MDM example raises critical data-management questions: Just who inside the company owns the customer data? Who’s tasked with ensuring that the customer data is correct and consistent? 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