the well-oiled data machine' from experian data quality
DESCRIPTION
Our new infographic ‘The Well-Oiled Data Machine’ illustrates some of our key findings from the Experian Data Quality 2014 global research.TRANSCRIPT
see outdated contact information as the
biggest issue.
of companies waste an
average of
say it’s their website.
Multi-channel strategies are increasing the
room for error.
A business machine can’t be efficient when…
of revenue due to bad data quality.
41%
suspect their data might be inaccurate in some way.
* Average turnover of UK businesses with 250+ employees: £212 million. Source: The Government's Department for Business Innovation & Skills (https://www.gov.uk/government/organisations/department-for-business-innovation-skills).
86%
The inner workings of a business are dependent on good, clean, quality data; it’s the oil that keeps the business cogs turning! Our most recent research
reveals common data quality issues in organisations.
of companies have a data strategy, but common issues and errors are damaging data quality.
say incomplete, missing data is
the most common problem.
Research shows businesses are experiencing data breakdowns.
What are the main outputs businesses want from their data machine?
44%
having problems when generating meaningful business intelligence.
The impact translates to...
Better customer satisfaction
Cost savings
not having enoughinformation aboutcustomers.
UK businesses are wasting
£197.788m each year*.
recognise the call centre as the most problematic channel.
52%
All data used in this infographic is drawn from ‘Global Data Quality Research 2014,’ an independent market research report commissioned by Experian Data Quality and produced by Dynamic Markets
Find out more: www.qas.co.uk/datamachine
75% 14%
49%
Human error
Poor internal communications
An inadequate data strategy
Lack of resource
Insufficient budgets
59% 31% 24% 22% 20%
But what is the root cause of data errors?
Interestingly...23%
Increaseefficiency
62% 54% 44% 43%
Increased opportunities through customer profiling
81%
24%
of companies depend on manual methods to check their consumer data.
34%use dedicated back-office software to clean new data.
38%use point-of-capture solutions to verify entered information.