On average, American companies believe that 25% of their data is inaccurate, finds Experian Quality Data in a recent survey. That’s higher than the overall average drawn from 6 countries – the US, UK, Netherlands, Spain, Germany and France – which worsened from 17% to 22% in just a year. While human error is by far the most commonly cited reason for data inaccuracies, companies appear to be lacking a centralized approach to data quality in a time when an increase in digital channels and mobile technology is bringing ever-larger quantities of information.
In fact, about 9 in 10 respondents to the survey said they suffer from common data errors, and 78% have problems with the quality of the data they gather from disparate channels. Interestingly, US companies find that company websites produce the poorest data quality, followed by call centers, while on a global level those positions were reversed.
Beyond human error, cited by 59% of respondents as a reason for data inaccuracy, lack of internal communication between departments (31%) and an inadequate data strategy (24%) are also important problems. Those point to a lack of internal sophistication in dealing with the growing amounts of data, and indeed, two-thirds of respondents said their companies lack a coherent, centralized approach to data quality.
While 55% say they use automated methods of data management, a similar proportion (53%) also rely on manual methods. The biggest change over the past few years? The use of software-as-a-service (SaaS) platforms: some 55% now use cloud or hosted solutions to manage their data quality, though security is still a primary concern.
Inaccurate data – obviously – has tangible effects on business results. Slightly more than three-quarters of the respondents believe that inaccurate and incomplete contact data – the most essential data type – affects their bottom line.
Problems are affecting companies in areas ranging from loyalty campaigns to business intelligence. The most common problems in loyalty campaigns are inaccurate consumer information, a lack of customer participation, and an inability to analyze customer information. Data inaccuracies also plague BI programs, as does a lack of flexible data and systems.
About the Data: The survey was fielded in December 2013 among more than 1,200 respondents. Industry sectors included in the sample were finance, public sector, retail, manufacturing, utilities and education. Respondents consisted of C-level executives, vice presidents, directors, managers and administrative staff connected to data management, across a variety of functions.