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Dirty Data’s Domino Effect

Originally published April 27, 2009

The “domino effect” is a compounding repercussion or chain reaction, which originates from what many consider an innocuous event.

Perhaps the best way to illustrate this phenomenon is through example. Granted, this example may seem a “bit over the top,” but it’s intended to illustrate how costly dirty data could actually become to an organization. Agreeing with the dollar amounts cited in this article is insignificant – understanding the devastating impact dirty data can have on an organization is not.

The Plan

A financial institution, leveraging its proprietary database of 2½ million “high value” domestic residential customers, mailed a $250,000 pre-qualified 3.5% home-equity line of credit offer. The campaign’s cost was $5,240,000 (postage, paper, printing, power and people). The strategy behind this marketing tactic was to build a tighter bond with these customers while generating incremental revenue. However, the inverse actually occurred.

The Catch

Twenty-two percent of the database used by the marketing department included individuals who no longer met the institution’s specific criteria for qualifying to receive the offer. Here’s the hitch: the offer stated the named recipient on each piece of collateral was guaranteed to receive the $250,000 line of credit based on their prior credit history and current relationship with the institution. The institution was aware it had bad data, but the marketing dollars wasted on these records were justifiably acceptable. Well, not exactly.

The Domino Effect

  • “Injured” mail recipients (those bank customers no longer meeting the qualifications) file a class-action suit citing “bait and switch” and other unfair business practices by the institution.
  • Investigations into the institutions business practices are undertaken by the FTC, FDIC Bank Examiners and the USPS mail fraud department.

  • The marketing agency is assigned fault for using dirty data, prompting the relationship between the financial institution and the agency to be terminated.

  • Several terminated marketing department employees file a multimillion dollar suit against the financial institution, citing discriminatory employment practices.

  • The financial institution’s HR department becomes overwhelmed by employee attrition as a result of employees pursuing alternative, more secure, places of employment.

  • Customer service quality levels plummet as a result of staff reductions and attrition.

  • Shareholders demand action to restore stock value and brand equity, as high profile members of the board of directors – seeking to distance themselves from the troubled financial institution –resign their positions.

  • Merger discussions with a multinational financial institution are put on “temporary hold” citing a need for reevaluation.

  • The media promptly begins to follow the institution’s misfortunes while fueling the negative press as it continues to unfold.

The Repercussions

  • Retraction reprinted for prior direct mail material including rush charges?

    (Cost: $5,240,000)

  • Hiring consultants to manage new ad agency selection process and securing the services of a PR firm for “brand damage control?”

    (Cost: $1,250,000)

  • Brand damage resulting in BDI (Brand Development Index) and CDI (Category Development Index) to fall more than 40 points, and an 18% loss in market cap?

    (Cost: $3,343,005,000)

  • Court fining in favor of “injured” mail recipient plaintiffs?

    (Cost: $18,750,000)

  • FTC fining institution for deceptive business practices?

    (Cost: $2,444,000)

  • Securing the services of an out-source HR service company to manage massive influx of new position openings as a result of the employee exodus?

    (Cost: $200,000)

  • Increasing advertising expenditures attempting to stabilize brand equity?

    (Cost: $5,000,000)

  • Institution hiring off-shore call-center to handle dramatic increase in customer service calls?

    (Cost: $850,000)

  • Re-training of recently hired off-shore customer service call-center’s employees to speak understandable English?

    (Cost: $500,000)

  • Postponing “indefinitely” multibillion dollar merger?”

    (Cost: $2,000,000,000)

  • Institution securing a law firm specializing in Chapter 7 and 11 filings?

    (Cost: $ 4,560,000 pre-paid)


  • Having a whistle clean database…?



The average American business retains somewhere between 25% to 40% bad data. Not only is this data worthless, it’s also, as just illustrated, a dangerous data liability.

Certainly this kind of risk exposure can be averted, for just a fraction of the financial institution’s original printing costs (referenced above), by leveraging the power of a robust integrated data management software solution. Investing in high quality data standardization and business intelligence analytics software will help mitigate a business falling prey to a dirty data disaster.

It’s extremely difficult to put a monetary value on investing in highly scalable data management software. Because, using the right software, you may never know exactly what it made you, not to mention…what it might have saved you.

  • Gordon Daly
    Gordon is director of marketing with DataMentors, a privately held data quality, data management and business intelligence analytics software company headquartered in Tampa, Florida. Gordon has more than 20 years sales and marketing experience including stints with several global advertising agencies and Fortune 50 technology and software companies. He has developed numerous highly successful corporate sales and marketing programs for companies such as MCI, US West, Qwest Communications and Subaru of America. Gordon attended Johns Hopkins University and holds an Advertising Communications degree from MICA.



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