By Elliot King

Elliot King

This should come as no surprise to anybody, but data does not take care of itself.

In fact, by its very nature, data degrades; it is corrupted; it becomes stale and in many other ways loses its timeliness and value. The ongoing onslaught on the quality of corporate data may be nasty to think about, but it is a fact of life. People just don’t want to deal with it.

A recent study found that while 99 percent of the companies it surveyed in the United States, the United Kingdom and France claimed to have a data strategy. Ninety-four percent said their databases were riddled with common errors and 92 percent said that poor data had an impact on their business. To top off the bad news, the respondents said that they were less likely to invest in data quality solutions than they were two years ago.

Why is it so hard to do the right thing? Sadly, most people just don’t care that much about data quality, so it is hard to generate a lot of enthusiasm for a data quality project. And at best, a data quality project will result in marginal improvements.

A customer service representative may have better information with which to respond to queries, but mistakes will still occur. Direct response campaigns will still generate waste. People know that theoretically data quality is important; many of them just don’t really believe that it has much to do with them and their job.

So how can you generate enthusiasm for a data quality project? For the people on the front line, be specific. If your focus is on improving logistics data, for example, don’t say that the project will improve the quality of the data by 10 percent. Demonstrate that improved data quality will cut down the time it takes to deliver a product.

If you can demonstrate to people how improving data quality will help them succeed at their job, you will get their attention and build support for data quality initiatives.





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