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Estimating the cost of poor data quality and customer data cleansing

Estimating the cost of poor data quality can be a challenge. Read our expert's tips for estimating value of customer data cleansing and know how much dirty data is costing your company.

Estimating the cost of cleaning dirty data is a real challenge for the reasons you cited in your answer to an earlier question. Do you know of any studies that show how much "unclean" data costs Fortune 1000 companies? Or do you have a general sense of the average annual cost of poor data quality to businesses? Is it $1 million, $10 million or more? Any insight into this topic would be very much appreciated.
Our company has participated in a number of data quality assessments in which we considered various areas of business impact that rolled up into real money. The conundrum is that few, if any, organizations would be willing to publicly admit to any type of deficiencies in their data or data management processes, let alone publicize their costs that are attributable to unclean data. In addition, the negative impacts on a company may be hard costs or "lost opportunities" whose scope is difficult to assess.

However, let's do a quick thought experiment: What is the cost of a lost customer? There are direct costs, such as the loss of an immediate revenue stream (i.e., subscription payments) or the loss of future revenue from product upgrades, purchases of accessories, service contracts, etc. In addition, there are indirect costs, such as the loss of purchasing influence, word-of-mouth advertising or even communications via social networks...

advocating on behalf of the product or service. Clearly, there are computable costs for customer attrition; in turn, the next question is what percentage of customer attrition can be attributed to unclean data? That provides a baseline framework for addressing the cost issue, at least for one impact vector.

This was first published in April 2010

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