While nearly 60% of executives expect big data to disrupt their industries, only 13% have full-scale big data initiatives and only 8% consider their initiatives very successful. Most organizations lack a well-defined roadmap with milestones and timelines for their initiatives, and 55% have scattered resources or a decentralized model. Additionally, 74% do not have well-defined criteria for selecting use-cases and 67% lack defined success metrics. In contrast, those organizations with a well-defined roadmap, criteria for selecting use-cases, and defined success metrics are tasting more success with their big data initiatives.

1. Making Big Data Work:
It pays to be Systematic
Nearly 60% of executives agree that Big Data will
disrupt their industry in the next three years
However,
only 13%of
organizations
have their initiatives in
full-scale production
of initiatives
are “successful”,
27%
Only And
8%
are
“very successful”
Most initiatives are yet to take off,
despite the buzz…
Most organizations are not doing it right…
No planned approach
do not have a
well-defined roadmap,
with milestones and
timelines, in place
55%
either have scattered
pockets of resources or
follow a decentralized
model for analytics
initiatives
47%
No well-defined criteria
do not have well-defined
criteria to identify, qualify
and select use-cases
do not have well-defined
success criteria (KPIs)
to measure the success
of their Big Data initiatives
74% 67%
$
Those that are,
are tasting success…
Well-defined
roadmap
51%
22%
Yes
No
Criteria for use-case
selection
53%
29%
Yes
No
Well-defined
success criteria
51%
28%
Yes
No
53%
Scattered
Pockets
Ad-hoc, isolated
analytics teams
43%
27%
20%
Decentralized
Separate analytics
teams for separate
departments
Centralized
Central team acting as a
competence center for Big
Data, and coordinating
initiatives for all
business units
Business Unit
Analytics team as
a distinct
profit-making
division
Comparison of Big Data initiative success rates
Lack of a defined
organizational structure
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Source : Capgemini Consulting, “Big Data Survey”, November 2014