When is the best time to start a data quality program?


Almost every business has a data quality problem.

In a study involving 75 executives only 3% found that their data fell within the minimum accepted range of 97 or more correct data records out of 100.

Yet for many businesses struggle on with poor data hampering their business and putting them at risk. The timing is never quite right to solve this fundamental problem.

So when is the right time to start a data quality program?

Like investing the best time is now!

More and more, business is relying on data to make the decisions that will differentiate, that will enable digital, that may ultimately be necessary for survival.

Big data adds complexity as well as volume

Big data, and advanced analytics techniques including Artificial Intelligence, are creating more data, more complexity, and, ultimately will be useless unless it can be correlated with existing information.

Customer data underpins many strategic programs – customer experience, digitisati0on, CRM, and data driven product design. Yet customer data is constantly changing.

Thinks about common customer data – details such as employer information, number of children,credit history, mobile number or email address.

How do changes to these (and similar) elements impact your ability to contact or segment your customers correctly and efficiently? What is your approach to keeping this data correct and how much wasted costs are inherent in a piecemeal approach to data quality?

Cost of bad data expected to rise

Bad data already costs US organisations $700 billion a year in wasted time and unfulfilled business. As data volumes and importance increases this cost will only rise.

The best time to start a strategic data quality program is now!

The longer that you wait, the more problems will be created. You don;t want to find yourself swamped in data issues in a year’s time that could have been resolved through a little foresight now.

A data quality program might start simply with the intention to assess and quantify external data sets prior to purchase to ensure that they are of sufficient quality and add value when integrated with existing data.

Talk to us about a data quality assessment and road map for the delivery of quality data now, and in the future

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