How Bad Data Undermines Business Results

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How Bad Data Undermines Business Results

How Bad Data Undermines Business ResultsHow Bad Data Undermines Business Results

Inaccurate data inhibits a company’s ability to provide an exceptional customer experience—and something as simple as a typo can have major consequences.

Essential InformationEssential Information

84% of survey respondents say data serves as an integral part of a business strategy.

Working PlanWorking Plan

55% say their organization has a big data strategy in place to analyze large sets of data, and 33% say their company plans to introduce one within the next 12 months.

Biggest Reasons for Maintaining a High Quality Data StrategyBiggest Reasons for Maintaining a High Quality Data Strategy

Increased efficiencies: 56%, Enhanced customer/user satisfaction: 41%, More informed decisions: 39%, Greater cost savings: 39%, Better protection of organization’s reputation/brand: 34%

Reporting ErrorReporting Error

75% of survey respondents say inaccurate data undermines their ability to provide an excellent customer experience.

Most Common Data ErrorsMost Common Data Errors

Incomplete/missing data: 60%, Outdated information: 54%, Duplicated data: 51%, Inconsistent data: 37%, Typos: 30%

Cause and Effect, Part ICause and Effect, Part I

56% of survey respondents say human error accounts for one of the top causes of inaccurate data, while 31% cite a lack of internal, manual resources.

Cause and Effect, Part IICause and Effect, Part II

28% say inadequate data strategies account for one of the top causes of inaccurate data, while 27% cite a lack of current, relevant technology capabilities.

Passive ApproachPassive Approach

65% say their company waits until there are specific issues with data until teams address and fix them.

Planned Data Management Projects over Next 12 MonthsPlanned Data Management Projects over Next 12 Months

Data cleansing: 37%. Data integration: 37%, Data migration: 31%

Expect the UnexpectedExpect the Unexpected

79% of survey respondents say it is difficult to predict when and where the next data challenge will emerge.

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