According to a study by The Data Warehousing Institute (TDWI), 83% of organisations suffered from problems caused by poor master data.
The biggest problems included inaccurate reporting (81% of organisations), arguments over which data is appropriate (78%) and bad decisions based on incorrect definitions (54%).
Alan Snow, services director for InfoBlueprint, says some problems with poor quality data can be quantified, as outlined in the 2002 estimation from TDWI that stated poor quality customer data, such as contact details, cost US businesses $611 billion a year, on things like stationery and postage.
However, problems such as reputational damage, customer alienation and lost sales opportunities make a negative impact, although they are abstract, he says.
Recently, InfoBlueprint encountered a hospital losing R4 million a year in theatre revenues because a theatre sister was logging times based on an analogue wall clock. This is an example of a small mistake snowballing into huge losses, explains Snow. There is also the risk of criminal charges arising from poor governance and compliance.
The company that fixes an obvious issue temporarily, says Snow, misses out on the opportunity to find the root of the problem. He also explains that many companies put off fixing their data quality issues because they do not understand the true cost to the company that poor quality data incurs.
He recommends companies to find the areas where poor data is causing the most trouble, and start there.
He cites an example from SARS: after implementing a data quality programme, compliance increased and SARS delivered several years of better-than-expected revenue collection. "Of course nobody likes paying taxes - but eliminating the free riders means the individual burden is lighter for everyone," he says.
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