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no big data strategy. More obvi-
ously, the survey data suggests
that poor adoption stems from
poor strategy, with absolute ma-
jorities in the worst-performing
adopters—75% in Singapore and
58% in China and Australia—
admitting they have made little or
no progress in their adoption of
big data so far.
 Many industries lag in their
adoption of data analytics:
Apart from the IT and technology
sectors, most industries are rela-
tively slow in their adoption of
data analytics, with many sectors
having made little or no progress
at all. Two exceptions are the
telecommunications and retailing So what are the barriers to Big  An inability to share data is
sectors, which show significant Data adoption? depriving firms of the value
levels of advancement in their that big data can provide:
big data adoption. Early adoption  A company’s biggest hin- Firms in the Asia-Pacific region
may stem from both of these in- drance to gaining value from are experiencing significant prob-
dustries generating and storing big data is often itself: Virtually lems due to limits on sharing and
vast amounts of customer data, all companies surveyed recog- collaboration. Respondents cite
which is routinely used for mar- nized internal roadblocks that an unwillingness to share data, a
keting purposes through initia- prevent them or slow them down lack of communication between
tives such as e.g. store loyalty from adopting big data. The big- departments and departmental
cards. The healthcare, pharma- gest obstacles are the lack of divisions as the biggest inhibitors
ceuticals and biotechnology in- suitable software and a lack of to big data adoption. A lack of in-
dustries, by contrast, are the skills. To some extent these can house skills and suitable soft-
slowest adopters of big data, be remedied by external ware are the most significant
with 72% of respondents stating sources, but other inhibitors stem factors separating big data lead-

that they have made little or no from issues within the organiza- ers and laggards.
progress. tion.
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