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Dirty Data's Domino Effect

by Gordon Daly, www.datamentors.comTuesday, August 17, 2010

The “Domino Effect”: a compounding repercussion or chain-reaction, which originates from what many consider an innocuous event.

Perhaps the best way to illustrate this would be by example. Here’s how the “Domino Effect” can adversely impact a business. Granted, this example may seem a “bit over the top,” but it’s intended to illustrate how costly dirty data could actually become.  Agreeing with the dollar amounts is insignificant.  What’s significant is; understanding the devastating impact, which dirty data can have on your organization.

THE PLAN

A national financial institution, using its proprietary database of 4,500,000 high value domestic retail 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

Nearly 23% of the database, which the marketing department used, included individuals no longer meeting the institution’s specific criteria necessary to receive the offer.  Here’s the hitch: the offer stated the named recipient on each piece of mailed collateral was already guaranteed to receive the $250,000 line of credit  based  on  their  prior  credit  history  and  current  relationship  with  the institution.  So, the 23% of bad data translated into a maximum potential financial risk of $1,035,000 wasted marketing funds for mailing to the wrong individuals-- right? Well, not exactly.

THE DOMINO EFFECT

“Injured”     mail     recipients     (those     bank     customers      no     longer     meeting     the qualifications) file a class-action suit against the institution citing “bait and switch” and other unfair business practices.

Investigations into the institutions business practices are undertaken by the FTC, FDIC Bank Examiners and the USPS mail fraud department.

The DM agency is saddled with the blame for using dirty data, prompting the relation between the fi nancial institution and the agency to be terminated.

Several of the terminated marketing department employees file a multi-million dollar suit against the financial institution, citing discriminatory employment practices.

Individuals in the marketing department, not fired from their jobs as a result of the direct mail debacle, being fearful for their jobs, begin to suffer post-traumatic- stress-syndrome and seek counseling and take extended leaves of absence.

The financial institution’s HR department becomes over-whelmed by employee attrition as a result of employees pursuing alternative employment.

Customer Service quality levels plummet as a result of reductions in staff. Shareholders demand action to resolve the multiplying issues including; the immediate restoration of stock value and brand equity, as high profile board members seeking to distance themselves from the troubled financial institution, resign their board of director 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 institutions misfortune and fuel all the collateral hemorrhaging as it unfolds.

THE REPERCUSSIONS

Reprinting and re-mailing a retraction offer for prior direct mail material? (Cost: $5,240,000) Plus, production rush charges (Cost: $900,000)

Institution  hiring  consultant  to  manage  new  ad  agency  selection  process, securing the services of a PR firm for “brand damage control” and to manage the mounting negative press coverage at $150 per hour for an initial 90 days?
(Cost: $1,250,000)

Brand damage causing BDI (Brand Development Index) and CDI (Category Development Index) to fall more than 40 points, reflecting 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)

Medical premiums increase as a result of high volumes in claim activity, which the institution promptly passes along to its employees?
(Cost: Additional $178 per month increase in employee paid healthcare premium)

Institution securing the services of an out-source HR service company to manage massive influx of new job postings as a result of the employee exodus stemming from initial employee firings and the dramatic rise in medical premiums?
(Cost: $200,000)

Increasing advertising expenditures in attempts to stabilize brand equity? (Cost: $35,000,000)

Institution hiring off-shore call-center to handle dramatic increase in customer service calls?
(Cost: $2,000,000)

Re-training of recently hired off-shore Customer Service call-center’s employees to speak understandable English?
(Cost: $3,000,000)

Postponing “indefinitely” Multi-billion dollar merger?” (Cost: $7,000,000,000)

Institution securing a law firm specializing in Chapter 7, 11 and 13 filings? (Cost: $ 4,560,000 paid in advance)

CONCLUSION

Having a whistle clean database…?
(Priceless)

EPILOGUE

Sure this is an embellished scenario, but its intention was to deliver a clear depiction of the potential negative ramifications from using dirty data and convey the need to preemptively invest in your company’s future success verses attempting to reactively rescue your business.

The average American company retains somewhere between 25 and 40 percent bad data. Not only is this data worthless, it’s a dangerous data liability as well.

Of course 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.

About the Author

Gordon Daly is director of marketing with DataMentors, www.datamentors.com, 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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