A Thought Leadership Guide For SMBs Data: A Practical Approach for SMBs(clone) | Page 5

Chapter 1
Data Errors Cost Us All
. e begin this ebook with the premise that all companies that trade with electronic data should appoint a
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Chief Data Officer to ensure that their electronic data is clean and accurate. Here at VL, we have had first-
hand experience with some of our clients. After a succession of decisions, some are now stuck facing the
problem of poor data quality, desperately trying to correct errors and recover from the downstream effects
of their bad data.
A while back, detailed work research on the time cost of bad data was done by the British researchers - Profes-
sor Alan Braithwaite (of Chairman of LCP Consulting and Visiting Professor at Cranfield School of Manage-
ment), and Professor Richard Wilding of the Centre for Logistics and Supply Chain Management at Cranfield
School of Management. Their research expanded on earlier research done by GS1 in the UK, which indicated
that poor data accuracy cost the UK retail sector £ 200 million ($320 million USD at the time the research
was performed) on an annual basis.
These findings were astounding. In taking the original GS1 numbers and applying a more rigorous Six Sigma
methodology, the researchers were able to determine that data inaccuracy was costing the Big 5 UK retail-
ers and their suppliers £ 1.4 billion on annual basis. A truly staggering number.
Braithwaite said:
“From our experience of working with many companies, data accuracy is poor with errors in physi-
cal dimensions, pricings and operational parameters such as shelf fill, replenishment quantities and
order quantities. As this report shows there is a big opportunity cost hidden behind this problem.
Companies need to take a fresh look at their master data management processes alongside their
data identification and capture methods; the business cases from investing in both identification
and processes may be bigger than capture methods; the business cases from investing in both identi-
fication and processes may be bigger than they expect. This backroom stuff is crucial.” [1]
To this Wilding added:
“The reported levels of inaccuracy and their associated costs are worrying. This is especially the case
in the context of the enormous investments that all the big retailers have made in product identifi-
cation, data capture and supply chain integration, and the focus that many companies have put into
lean and six sigma methods.” [1]
The paper goes on to highlight another key challenge in the form of GTIN (Global Trade Item Numbers). This
number increases as more data types are included. As some of this data will bring liability implications for re-
tailers and manufacturers, corporate accuracy may yet become an issue of corporate governance and social
responsibility.
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