Technology Decisions Jun/Jul 2013 | Page 27

bridge the gap between insight and action
actionable meaning from reporting and
by supporting peoples ’ natural decision-
analytics .
making processes .
2 . Increasingly dispersed workforces have
heightened the need for , and benefit of ,
Gartner has suggested that around 15 % of
fast information sharing and collabora-
BI deployments now combine traditional
tive decision-making .
BI and collaborative components in a single
3 . The need to provide context to action-
decision-making environment . I believe this
able information to underpin accurate ,
figure is extremely conservative . Or if it ’ s ac-
fact-based decision-making .
curate , far too many vendors are hopelessly
behind the fast disappearing ‘ ball ’.
I ’ ve also found that clients who embrace best
practice collaborative BI have the ability to
This demand for better enterprise collabora-
improve productivity and visibility across
tion , and collective decision-making capabili-
the breadth of organisational operations ,
ties , is part of a wider spike in demand for
via enhanced knowledge sharing .
© iStockphoto . com / Er Ten Hong
CDM software . Analyst firm IDC reported a 5.1 % uptick in CDM software sales across 2012 , making it the fastest growing global software segment last year .
More specifically , Wayne Eckerson ’ s ‘ Collaborative Business Intelligence : Optimizing the Process of Making Decisions ’ report found that 87 % of BI professionals believe that “ col-
The need : why is collaboration important when using analytics ?
The demand and drivers for collaborative BI
seem clear . But why is conducting effective
collaboration so important when attempting
to use BI content to make better decisions ?
Information sharing and discussion allows
laboration tools can have a positive impact
human insight and understanding to be
when drawn together , enable a collective
on analysis and decision-making activities ”,
added to data , making it more meaningful
decision to be made .
while “ Fifty-eight percent of BI professionals
and actionable .
plan to evaluate collaboration features when
BI veterans Claudia Imhoff and Collin
they purchase their next BI tools .”
Collaboration exposes the ‘ why ’ and ‘ how ’
White provide a useful definition of col-
behind data , helping us move beyond the
laborative BI , “ BI software enables business
According to InformationWeek ’ s 2012 Busi-
simple ‘ what ’ and onto a deeper level of
users to report on and analyse business
ness Intelligence , Analytics and Information
analysis and comprehension . For example ,
processes and associated activities , while
Management Survey , 59 % of IT pros list “ the
you might work for a sporting goods com-
collaboration tools enable the results of BI
ability for users to share and collaborate ” as
pany assessing the monthly sales report . In
queries and reports as well as other related
the most important feature to consider when
one instance , that report might indicate a
information to be accessed and shared by
purchasing a BI solution . Only mainstays
massive jump in the sale of boxing equip-
multiple users .
“ ease of use ” ( 63 %) and “ fast data explora-
ment . By sharing data with all the relevant
tion ” ( 62 %) ranked higher .
business groups - Sales ( did we have a focus
“ The ultimate goal of any BI environment is to make timely and better business
Drivers
on clearing boxing equipment this month ?),
Marketing ( did we run a campaign ?), IT
decisions . A collaborative BI environment
Over the years I ’ ve found three key factors
( do we have errors in our data sets relat-
supports team efforts to assess situations
driving client demand and interest in col-
ing to boxing equipment ?) - we ’ re able to
and make decisions .”
laborative BI :
determine not just what happened , but why
Demand for collaborative BI
1 . The increased demand for real-time information , in conjunction with the
and how it happened . Collaborative BI is
about connecting the right people with
If executed correctly , collaborative BI has the
rapid expansion of corporate data assets ,
the right data to maximise the effective-
ability to form crucial connections between
has resulted in organisations searching
ness of data analysis and achieve better
people , process , data and technology - to
for faster methods to share and derive
decision-making .
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