Information: it's the fire that fuelsinnovation. But its true potential is locked away within the massive volumes of content and data that exist within your organization. Discover how to accelerate timely access to insights so you can increase the pace of meaningful innovation.

1. ACCELERATING THE
INSIGHT-INNOVATION
CYCLE
WHITE PAPER

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Accelerating the Insight-Innovation Cycle
ACCELERATING THE
INSIGHT-INNOVATION CYCLE
Commentators of all persuasions agree that productivity (and the growth it creates) is the
result of investment, innovation, skills, enterprise, and competition. Among these, innovation
- in product and process - has become a critical objective in every organization’s strategy. The
pursuit of meaningful discoveries, which drive valuable innovation, has emerged as a core task
for business and technology professionals alike. This powerful discovery-innovation cycle, that’s
transformed economic activity from earliest times, continues unabated in today’s markets.
In our digital age, both the volume and complexity of
information used for discovery grow by leaps and bounds.
For many organizations, these surges make meaningful
discovery increasingly unlikely. Until organizations find a
way to systematically harness these forces to produce
more discovery and innovation, they will stand exposed
to disruption, disintermediation, and dismemberment.
Avoiding these distasteful outcomes raises a fundamental
question– How can organizations increase the pace
of meaningful innovation?
Like any activity that relies upon research, reflection,
or reconsideration, discovery thrives when properly
supported. Since the community of ‘discoverers’ feels
the direct, immediate burden of information volume
and complexity, the answer to the question is clear and
immediate. Organizations must deploy ‘innovation-support’ solutions – solutions that
provide discovery communities with enhanced abilities to find (“Aha!”), reveal (“I see…”),
and correlate (“… the connection”) information, regardless its volume or complexity.
With such a support solution in place, the pace of discovery and innovation are certain
to increase.
How to recognize
innovation-support?
Imagine a solution that scales with
the volume of information useful
for discovery; one that integrates
disparate content types (structured,
unstructured, streaming, multi-
language); an automated component
that that finds and correlates relevant
events, unrestricted by either volume
or complexity. Finally, imagine an
’insight-friendly’ interface that reveals
those correlations to a heterogeneous
community of discoverers.

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Accelerating the Insight-Innovation Cycle
WHAT INNOVATION-SUPPORT
SHOULD DO
Innovation-support solutions are different. They support activities that have three discovery-centric
objectives – Find, Correlate, and Reveal. Whatever these objectives may have in common from
one industry, or domain, to another, one thing is certain. The traditional methods of discovery are
besieged when content volume and complexity explode. If we untangle the content knot, there are
three imperatives for inspiring innovation.
Accelerate Timely Access to
Information
Just as Einstein took advantage of his
patent examiner position to develop a
new framework for physics, the modern
discoverer is more likely to succeed if s/
he uses the widest range of potentially
relevant information. Though the
‘domains of discovery’ vary widely across
industries and markets, the forces of information expansion
and complexity operate in each and every one. Together,
they are opening an ever-widening gap between what the
discoverer sees and what’s available to know. To insure
that all things are considered - how can organizations
effectively add new content into the discovery-
innovation cycle?
Traditional IT solutions, such as databases, indexes, and query-
based interfaces impose limitations on discovery. They assume
a discoverer capable of asking a properly-framed question,
which is inherently related to properties of the answer. While
some discovery can draw upon existing frameworks, some
of the most valuable (Einstein’s work on relativity, Pasteur’s
on microbiology) won’t. Instead, discovery-support solutions
need to connect rapidly growing, increasingly disparate, and
potentially relevant content sources for the discoverer –
quickly, seamlessly, and productively.
The Power of Seemingly
Unrelated Content
As a young physics graduate from
Zurich Polytechnic, Albert Einstein
struggled to find a teaching position
for nearly two years. Through a friend’s
assistance, Einstein obtained a position
as patent examiner in the Swiss patent
office. The position afforded him access
to many questions, notably about
the transmission of electrical signals
and the electrical and mechanical
synchronization of time.
His investigation of these questions
spawned numerous thought
experiments. He subsequently
employed many in his development
of relativity and the nature of light,
electromagnetism, space, and time.
As an excellent example of discovery
support, the information collected and
managed by the Swiss patent office
contributed significantly to Einstein’s
research, reflection, and his ‘miracle
year’ (1905) publications – discoveries
that transformed modern physics and
the world.

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Accelerating the Insight-Innovation Cycle
“ A new generation of insight-focused solutions
utilizes software platforms designed for widespread
deployment and timely information integration.”
With modern discovery-support solutions, the traditional
costs and delays associated with constructing, deploying, and
maintaining query-based applications are evaporating. In the
past, the expense of implementing and supporting solutions
created a very real impediment to wide-scale deployment. This,
in turn, effectively reduced both the extent and the vitality of
an organization’s discovery community. With modern solutions,
organizations can expand support for a wider community of
discovery, at a fraction of the cost.
Emerging software platforms couple the compelling
economics and convenience of machine learning with
open, extensible interfaces for ingesting the full range
of content formats – structured, unstructured, and
streaming. Some solutions include powerful analytic engines
that separate and relate context, content, and concepts
– augmenting the traditionally time-consuming process
of human review. Revealed through discovery-prompting
visualizations, the best of solutions provide a timesaving
workbench for observing and understanding.
Focus on Relevant Correlation
Rather than serendipity, the most
common characteristic of discovery is
correlation – the observation that events
or conditions co-occur. Information
volume and complexity make finding
mutual, multiple associations that
characterize a discovery increasingly
difficult. Increased volume lengthens the time to find new
relationships.
Observation and Discovery
Having lost three of five children
to typhoid fever, Louis Pasteur
was motivated to find the causal
mechanism behind infectious disease.
Asked by a friend to solve a problem
common to the fermentation of
beer and wine, Pasteur linked the
problem definitively to the growth
of microorganisms, through careful
experiment and observation.
His famous presentation before
the French Academy of Sciences
convincingly established germ theory
over spontaneous generation. This
framework motivated Lister’s work
on antiseptic surgery and Pasteur’s
own work on anthrax and rabies
vaccination.
Trained as a chemist, he once
remarked, “In the field of observation,
chance favors only the prepared
mind”. Pasteur’s ability to correlate
information from diverse aspects
of life led to his discoveries. Those
discoveries not only gave rise to
the modern germ theory of disease,
but also started the modern
field of microbiology. Pasteur’s
discoveries fueled innovations in
food preservation and immunization,
without which modern, urbanized
societies might never have developed.

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Accelerating the Insight-Innovation Cycle
Increased complexity complicates the use of traditional database, search, and analytic methods
across disparate domains. To avoid these analytic bottlenecks, how can organizations
actively foster sound inference across expanding, disparate domains?
To correctly and efficiently associate events or conditions, all discoverers employ a common
measure, or yardstick, when looking for relationships. For Einstein, it became the speed of light;
for the assembly line team at Ford, it was the elapsed time to complete a fixed task; for Pasteur,
it was the causal links of before and after, or with and without. Arranging events or conditions
along a common yardstick is the critical first step in establishing correlation.
Though humans have evolved successful means for identifying and measuring with these
yardsticks, volume and complexity are increasing more rapidly than organizations can hire
capable discoverers. Without a yardstick solution, the pace of discovery and innovation will
inevitably plateau. The best recourse is to identify machine-based techniques that
adequately mimic human powers of association. Fortunately, modern discovery-support
solutions now have access to proven, efficient methods.
These methods (typically called machine learning) effectively mimic the way humans analyze
information. They construct meaning from co-occurrence (or correlation) and context – even
across disparate languages or content formats. Since the commercial emergence of these
methods in the last three years, machine-learning methods have emerged as the superior
technique for replicating the way humans correlate.
Gains in computer processor and memory technologies make it possible to deploy analytic
technologies across entire organizations. Because they’re machine-based, these solutions can
scale efficiently as content expands or complicates. Because they learn, these solutions work
better with dynamic, evolving disciplines. In addition, because they mimic the way humans
associate concepts, their results accord with our intuition.
For an informative, non-mathematical review of machine learning and other text analytic
approaches, see “5-Minute Guide to Machine Learning” – another document in this series.

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Accelerating the Insight-Innovation Cycle
Create a Holistic Perspective
Today, the pursuit of product and process innovation is
continuous and enterprise-wide. Nevertheless, for most
organizations, the support for discovery and innovation is
often isolated to specific functions or individuals, viz. the
experts. This isolation exacerbates the challenges of volume
and complexity – challenges that already work to slow the pace
of discovery and innovation. To overcome the effects of
isolation, how can organizations effectively expand the
scope of the innovation cycle?
Machine-based tools for finding correlations help discovery
communities compare disparate content efficiently. However,
recognizing discovery is a critical third step. New, insight-
friendly interfaces - rich with visualizations that reveal
expected and unexpected correlations – enhance
recognition for experts and novices alike. Deployed with
the integration and analysis capabilities outlined above, these
interfaces enhance human discovery in two ways.
First, by stimulating our visual cortex, they utilize the most
intensive and evolved portion of our brain, leveraging its
powers of discrimination. Second, they establish a common
framework accessible to everyone in a discovery community.
This empowers collaborative discovery (as exemplified by
Ford’s innovation on assembly line production). By activating a
community’s intensive (visual cortex) and extensive (scope and
size of the community) capacity to recognize correlation, the
likelihood of discovery and innovation will increase.
Insight-friendly interfaces that activate recognition are a natural
complement to the efficient connectors that integrate our
four principal sources of information – internal documents,
open-source information, paid-research, and socially mediated
communications. Together, these interfaces and connections
increase the likelihood of finding and correlating both the
unknown and the unexpected. The result is a consistent, ‘holistic’
perspective that underwrites more effective discovery and
innovation.
Collaborative Discovery
Though widely
heralded as
the inventor
of the modern
manufacturing
assembly
line, Henry
Ford wasn’t. The patent for the
assembly line belongs to Ransom
Olds (immortalized by the
Oldsmobile brand). Henry Ford was,
however, the sponsor of a great,
collaborative discovery-community.
Working together over a period
of five years, a team of six Ford
production managers effectively
reverse-engineered the traditional
‘disassembly’ methods of meat-
packing – and launched one of the
greatest productivity booms in
human history, increasing Ford’s
productivity eight-fold.
From Adam Smith’s concept
of the division of labor (which
Smith originally applied to pin
manufacturing), Henry Ford’s
discovery team delivered innovations
that improved working conditions
and incomes, created a global
automotive industry and market,
won a world war, and led to
industries and processes beyond his
team’s wildest imaginations.

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Accelerating the Insight-Innovation Cycle
ENRICH YOUR INNOVATION CLIMATE
Insight and innovation are inseparable and essential. In our digital age, both slow when the
volume and complexity of information expand too rapidly. This exposes the deleterious effects
of weak collaboration, incomplete or irrelevant correlation, and missing information. Fortunately,
emerging solutions offer robust support for insight from the familiar technologies of enterprise-
scale search.
These solutions transform information volume and complexity from challenges into
opportunities. They deliver rapid content integration, correlation with enhanced relevance,
access to powerful visualization, and common collaborative focus. Widely deployed, these
‘insight-friendly’ solutions will help a new generation of discoverers find, correlate, and innovate
like never before.
“ The problem is … we can’t hire enough knowledgeable professionals to spot all the
opportunities out there...”
ABOUT ATTIVIO
Attivio is the leading cognitive search & insight company. Our Fortune 500 clients rely on us
to drive innovation, operational efficiencies, and improve business outcomes. Our solutions
provide industry-leading natural language processing, machine learning, analytics, and
knowledge graphing capabilities at scale. We have a proud, rich history of boosting productivity
by expediting search & discovery, personalizing customer interactions by delivering highly
contextualized information at point of need, and minimizing enterprise inefficiencies by
dramatically accelerating business processes. Attivio provides immediate visibility to all the right
information so you can boost your enterprise’s IQ, make better decisions company-wide, and
seize every opportunity. Let Attivio empower you to act with certainty.
For more information, please visit www.attivio.com