The CIO focus on business intelligence (BI) and analytics looks set to
continue through 2017, according to Gartner.
Gartner said that
the
benefits of fact-based decision-making are clear to business managers
in a broad range of disciplines, including: marketing, sales, supply
chain management, manufacturing,
engineering, risk management, finance and HR.
"Major
changes are imminent to the world of BI and analytics including the
dominance of data discovery techniques, wider
use of real-time streaming event data and the eventual acceleration in
BI and analytics spending when big data finally matures," said Roy
Schulte, vice president and distinguished analyst at Gartner. "As the
cost of acquiring, storing and managing data continues
to fall, companies are finding it practical to apply BI and analytics
in a far wider range of situations."
Gartner outlined four key predictions for BI and analytics:
By 2015, the majority of BI vendors will make data discovery their prime BI platform offering, shifting BI emphasis
from reporting-centric to analysis-centric.
Over
the past several years, the BI platform market has grown largely
through companies investing in IT-led consolidation
projects to standardize IT-centric BI platforms for large-scale systems
of record. These have tended to be highly governed and centralized,
where IT production reports were pushed out to managers and knowledge
workers. Gartner predicts that going forward,
companies will shift their future investment away from IT-developed
reporting solutions toward business-user-led analysis solutions. IT will
focus most of its effort on data modeling and governance. As a result,
data discovery will displace IT-authored static
reporting as the dominant BI and analytics user interaction paradigm
for new implementations by 2015.
While
IT authored, system-of-record reporting will not disappear, it will
become a smaller proportion of overall analytics
use. Only 30 percent of business people have direct access to BI and
analytics today only, but this will grow as a result of the shift to
data discovery.
"BI
leaders should scrutinize the road maps of both data discovery and
IT-centric vendors to determine their suitability
to meet growing business user and enterprise requirements," said Mr.
Schulte. "It's important to acknowledge that one size rarely fits all."
By 2017, more than 50 percent of analytics implementations will make use of event data streams generated from instrumented
machines, applications and/or individuals.
As
enterprises continue to recognize the economic value of information,
and see the opportunity to capture and apply
ever greater volumes of detailed data, they will come to expect access
to analytics technologies capable of making sense from event streams.
This goes beyond traditional and mainstream BI to a breed of
technologies capable of producing autonomous insights
and inferences quickly.
To
produce and harvest this data from physical assets and other event
sources, the market will expand for flexible, multipurpose
sensors for temperature, humidity, vibration, pressure, sound,
light/color, electrical or other utility flows, motion, facial
expressions, voice inflection, health monitoring and other systems.
Moreover, such event data from physical assets (operational technology
[OT]) is sometimes combined with event data from administrative
information systems (information technology [IT]) to develop richer,
more powerful holistic systems (creating an IT/OT convergence). In
addition, technology and consumer product vendors are hastening
to enable their wares to capture and emit more consumption and
environmental data. Several SaaS application vendors in particular, have
already intensified their ability to collect more usage data and are
devising quid-pro-quo arrangements with customers that
allow leveraging their de-identified data for alternate commercial
purposes.
"Nontech
businesses leaders should create an inventory of the range of current
data collected by their products and services,
then consider what additional high-value information could be captured
through further instrumentation," said Mr. Schulte. "Application and
other technology managers should ensure that the data collected from IT
systems, applications, devices and users is
maximized with equal consideration for performance implications and
probable future business relevance."
By 2017, analytic applications offered by software vendors will be indistinguishable from analytic applications offered
by service providers.
Traditional
vendors of analytic platforms recognize that in order to expand their
reach beyond traditional power users,
they must deliver packaged domain expertise and applications to enable
self-service by a wider range of users. Service providers are seeking to
turn custom project work and domain expertise into repeatable solutions
that can be adopted by other organizations
more easily.
The
result is that end-user organizations selecting analytic applications
will have a significantly wider variety of
possible providers to evaluate. Organizations evaluating software
vendors will almost always find a SaaS version of their packaged
applications, and the similarity of product concepts will shift the
emphasis of competition to the domain expertise embedded
by the vendors into the application. Software vendors will increasingly
face a co-opetition situation with their traditional service provider
channels, forcing them to augment their own professional service
capabilities. Service providers will use packaged
applications as an integral part of their customer relationships,
implying that there is a greater specialization in the services that
they provide.
Until 2016, big data confusion will constrain spending on BI and analytics software to single-digit growth.
Despite
the strong interest in BI and analytics, confusion around big data is
inhibiting spending on BI and analytics
software. Until 2016, service providers will garner business by closing
the gap between available big data technology and business cases. As
big data matures and more packaged intellectual property is available,
big data analytics will become more relevant,
mainstream and, ultimately, hugely disruptive.
Recent
Gartner surveys show that only 30 percent of organizations have
invested in big data, of which only a quarter
(eight percent of the total) have made it into production. This leaves
room for substantial future growth. Analytics plays squarely into the
big data trend, where the growing volume, velocity and variety of data
create opportunities outside of the traditional,
established BI domains and buying centers. However, that also makes the
sourcing of analytics bigger and more technically complex than what has
been done before.
Paradoxically,
the confusion that surrounds the "big data" term and the uncertainty
about the tangible benefits of big
data are partially to blame for the soft BI and analytics market.
Procurement cycles have slowed while budget holders try to match the
right tooling to the right business case. In the interim, BI and
analytics continue to remain at the forefront for CIOs,
and service providers will attempt to bridge much of the confusion. The
gap will completely close when those services will become
"productized." This, in addition to a confluence of technology maturity
cycles, is expected to occur around 2016. Beyond 2016,
when the solution has found the problem, when the discussion has
matured from technology to business, and when there will be more
off-the-shelf capability available, big data analytics will pervade
almost everything that we do, helping push society unequivocally
into the digital age.
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