Ventana Research has been researching and advocating operational intelligence for
the past 10 years, but not always with that name. From the use of
events and analytics in business process management and the need for
hourly and daily operational business intelligence, but its alignment
with traditional BI architecture didn’t allow for a seamless system, so a
few years later the discussion started to focus around business process
management and the ability of companies to monitor and analyze BPM on
top of their enterprise applications. Business activity monitoring
became the vogue term, but that term did not denote the action
orientation necessary to accurately describe this emerging area. Ventana
Research had already defined a category of technology and approaches
that allow both monitoring and management of operational activities and
systems along with taking action on critical events. Today, Ventana
Research defines Operational Intelligence as a set of event-centered
information and analytics processes operating across the organization
that enable people to take effective actions and make better decisions.
The challenge in defining a category in today’s enterprise software market is that prolific innovation
is driving a fundamental reassessment of category taxonomies. It’s
nearly impossible to define a mutually exclusive and combinatorially
exhaustive set of categories, and without that, there will necessarily
be overlapping categories and definitions. Take the category of big
data; when we ask our community for the definition, we get many
perspectives and ideas of what big data represents.
Operational intelligence overlaps in many ways with big data. In
technological terms, both deal with a diversity of data sources and data
structures, both need to provide data in a timely manner, and both must
deal with the exponential growth of data.
Also, business users and technologists often see both from different
perspectives. Much like the wise men touching the elephant, each group
feels that OI has a specific purpose based on their perspective. The
technologist looks at operational intelligence from a systems and
network management perspective, while business users look at things from
a business performance perspective. This is apparent when we look into
the data sources used for operational intelligence: IT places more
importance on IT systems management (79% vs. 40% for business), while
business places more importance on financial data (54% vs. 39% for IT)
and customer data (40% vs. 27% for IT). Business is also more likely to
use business intelligence tools for operational intelligence (50% vs.
43%), while IT is more likely to use specialized operational
intelligence tools (17% vs. 9% for business).
The last and perhaps biggest parallel is that in both cases, the
terms are general, but their implementations and business benefits are
specific. The top use cases in our study for operational intelligence
were managing performance (59%), fraud and security (59%), compliance
(58%) and risk management (58%). Overall we see relative parity in the
top four, but when we drill down by industry, in areas such as financial
services, government, healthcare and manufacturing, we see many
differences. We conclude that each industry has unique requirements for
operational intelligence, and this is very similar to what we see with
big data.
It is not surprising that our definition of operational intelligence
is still evolving. As we move from the century of designed data to the
century of organic data (terminology coined by Census Director Robert Groves),
many of our traditional labels are evolving. Business intelligence is
beginning to overlap with categories such as big data, advanced
analytics and operational intelligence. As I discussed in a recent blog
post, The Brave New World of Business Intelligence,
the business intelligence category was mature and was showing
incremental growth only a few years ago, but it is difficult to call the
BI category mature any longer.
Based on the results of our latest operational intelligence benchmark
research, we feel confident that our current definition encompasses the
evolving state of the market. As operational intelligence advances, we
will continue to help put a frame around it. For now, it acts very much
like what might be called “right-time big data.”
Regards,
Tony Cosentino
VP & Research Director
Original
Like Big Data, Operational Intelligence is Evolving to Deliver Right Time Value
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