腐ったデータ構造が生む損失

先日参加したAgile2008で、Scott Ambler氏が何度も強調していた話。

Poor data quality problems result in a loss of over $600 Billion annually in the United States.

腐ったデータ構造が生む損失は米国だけで年間6000億ドルに達する。

• 6000億ドル＝60兆円強
• 結構な金額ではある...

Scott Amblerの話は、おそらく下記記事が元になっていると思われる。

• Data Warehousing Special Report: Data quality and the bottom line

The Data Warehousing Institute (TDWI) estimates that poor quality customer data costs U.S. businesses a staggering $611 billion a year in postage, printing and staff overhead (TDWI estimates based on cost-savings cited by survey respondents and others who have cleaned up name and address data, combined with Dun & Bradstreet counts of U.S. businesses by number of employees.). Frighteningly, the real cost of poor quality data is much higher. Organizations can frustrate and alienate loyal customers by incorrectly addressing letters or failing to recognize them when they call, or visit a store or Web site. Once a company loses its loyal customers, it loses its base of sales and referrals, as well as future revenue potential.

以前書いたCOOBOLの呪縛にも関係する話。腐ったデータ構造を抱えたシステムを後生大事に「既存資産」と分類するのは、果たして正しい事なんだろうか。