Poor data quality costs businesses €400 million yearly

The financial damage businesses yearly suffer as a result of poor data quality turns out to be shockingly higher than originally expected. Due to lack of quality in relationship data the Dutch businesses have to deal with €400 million extra costs every year as shown by a survey held among 20,000 Dutch organizations employing 10 or more people. The research was conducted by Ed Peelen, professor in direct marketing at Nyenrode Business University, by order of Human Inference and Cendris.

The total amount of €400 million consists of costs that are calculated based on directly quantifiable aspects, such as wrongly addressed invoices and product deliveries which do not arrive at the right addresses. If indirect and ‘opportunity’ costs made as a result of badly maintained prospect databases were counted in, the figure would be much higher. This entails for instance searching for telephone numbers and asset costs due to late collecting of invoices. Especially, missed revenue amounts resulting from poor prospect management are shockingly high.

Data-entry control procedures are not being followed
Although 92.6% of the organizations find maintaining the quality of relationship data important, it appears that only 52% of the companies actually monitor the entry of data. In many cases control procedures are said to exist but occur not to be followed. Many respondents consider such solutions as connections to external data files, which are being checked regularly, to be good alternatives.

Hugo Verwijs, CEO of Human Inference, and Henk Pilon, director of Cendris: “Although we knew beforehand that a great deal can be improved in the area of data quality, we are surprised by the large amount of €400 million. What startled us the most is that in many cases employees apparently do not follow the rules concerning data management and maintenance. In addition, management will have to be more aware of the importance of data quality and its necessary improvement.”

Great differences in quality measures per business segment
When one considers the number of quality measures taken, business segments show great differences.. Public services and financial institutions turn out to take an average of 3.5 to 4 out of 8 presented quality measures. The hotel and catering industry lags far behind with only one measure.

Summary of the conclusions:

1. 52% of the companies do not monitor data entry
2. Data entry via the Internet scores the lowest with respect to quality
3. There are great differences in quality measures per business segment
4. 71 % of the companies ignore procedures concerning data entry
5. The prospect databases at the larger part of the companies are being maintained very poorly

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