DM p20-21 Capscan Paper Feb09.qxp 29/01/2009 13:18 Page 21
White Paper: Data Quality
29% of the companies for UK data and in only 17% with anything up to 15% higher responses for posi-
for international data. tive effects than for the mirrored negative effects. It is
The presence of software and validation levels clear that respondents see the positive effects but not
showed discrepancies. For example, whilst only always the associated negative effects.
38.6% of respondents had address validation software The way data is used within an organisation will
installed, 48% claimed to be validating that data define what effects bad quality data has on a compa-
using software. In large companies especially, there is ny, but in general the respondents underestimated
a tendency to over-estimate the amount of validation the effects. The greatest impact was perceived as
taking place. There are many gateways through being the effect on operational efficiency (66.1%), but
which data enters and rarely do all those gateways only 34.9% of customers perceived “inadequate data
implement controls over the traffic. Whilst almost analysis and an unclear view of customers” as being
90% of companies surveyed collected company name an issue.
and address information, only 48% validate this
“Of the 189
information using software. There is also a gulf Non customer-centric
respondents,
between the appreciation of the importance of data When asked to name their biggest data challenges,
quality and steps to put into practice processes to respondents took a largely operational line, continu-
only a single
ensure that high data quality is achieved. . ing the trend of considering data quality to be a tech-
person gave the
nical problem with technical solutions. response to the
ROI It is, however, promising to note that 69.3% of
question ‘who
27.5% of respondents stated that “establishing a link respondents suggested that one of their main chal-
holds
between data and ROI”, 31.2% “Getting senior man- lenges was “ensuring data is up-to-date and accurate”.
responsibility for
agement buy-in for a data strategy” and a massive
39.2% “Getting organisations to understand the Blame the customer
data quality
impact of poor data” were one of their biggest data It is perhaps understandable that staff in most com- management in
challenges today. panies regard customers as a nuisance but it remains
your business?’
Whilst it is dispiriting that staff who understand easy to forget that most companies only exist because
which shows true
and care about data quality must spend so much of of their customers. It is therefore fascinating that
understanding of
their time trying to bring this message to executives, 33.3% of respondents blamed “inadequate data entry
there are some small signs of improvement. by customers” as one of the main sources of their
data quality: ‘All
data quality problems.
staff’.”
Eternal optimism Far more (65.4%) blamed inadequate data entry by
A major barrier to better data quality is an eternal employees. In both cases, the organisation has the
optimism that many companies and staff have about power to improve results through technological
their data and its quality. implementation and procedural business process
52% of respondents viewed their organisation’s improvement and training.
data as being of excellent/good quality, and a further
40% considered their data to be “alright – but could CONCLUSION
be better”, leaving only 8% to admit that their data Whilst most people are increasingly aware of the
was poor. Given the relatively low number of respon- importance of improving data quality, there remains
dents utilising validation and cleansing software, it is a gulf between perception and action. Most organisa-
clear that the quality of data is being grossly overesti- tions do not have enterprise-wide data quality
mated. This may partially be due to the data being improvement programs, and responsibility for data
hidden behind complex programs and interfaces and quality is often perceived to lie with a single individ-
also due to data professionals not being able to recog- ual rather than every member of staff within a com-
nise problems in their data even with access to it. pany. Few companies have the policies, tools and
Data needs to be collected in as clean a way as pos- processes in place to manage data quality and most
sible, with validation at source, and it will start to companies their data.
decay even before it enters the database. It is clear Higher management is becoming involved in data
that if good quality data increases, for example, the management issues, but often still require proof that
ability to provide a good service to your customers, increased data quality will positively affect their bot-
then poor quality data will decrease that same ability. tom line. A great deal of work is still required to turn Graham Rhind is an
In this survey the respondents were asked how nega- around the perception of data quality issues and how expert in the field of
tive data quality would affect their business, and later they are to be tackled within companies of all types data quality and
how good data quality would affect their business, and sizes. The attitude that data quality is an opera- runs the Netherlands-
with a mirrored set of answer possibilities. tional and technical issue, divorced from business based GRC Database
Each respondent noted an average of 4 effects of processes and procedures, remains stubbornly in Information consul-
bad data quality, but 5.4 effects of good data quality, place.
n
tancy company.
www.dmarket.co.uk Database Marketing February 2009 21
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