Exe cu tive E D GE
Three Kinds of Innovation
The Verisk Analytics innovation model
consists of three subsets:
• process innovation – drives efficiencies
in business operations
• product innovation – extends existing
products with new functionality and
capabilities
• invention – redefines markets and
creates new industry ideas
We implement all three, with an emphasis on invention. Invention stems from our
collaboration with customers, allowing us
to gain a thorough understanding of what
challenges confront the markets we serve
and how we can find solutions to those issues. Equally, collaboration with our customers enables us to discover what works
well and where the growth opportunities
exist for them – and, consequently, what
services we need to create, revive, or expand to meet their growing requirements.
With customers deeply involved in our
development process, we gain the benefit
of real-time insights and reactions as they
move through phases of innovation with
us – from ideation to prototype to adoption.
That kind of collaboration has redefined
what innovation truly means today both at
Verisk and for many other organizations.
Innovation: What’s Next?
Investing in innovation requires a
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culture that supports innovation, ensuring
employees understand and rally around
an organizational philosophy defining what
innovation means and why it matters. The
Verisk concept of innovation is based on
our n+1 philosophy: To be competitive today, organizations must strive for what we
call the n+1 data set. If a company’s data
set has a certain number of elements —
n — it must constantly be working to include one more. It must continually add
elements, advancing toward the next layer,
adding richness to its analysis. To be sure,
such an approach requires investment – in
data resources, in analytics, in technology,
in people. But the return on investment is
to thrive, rather than simply survive or ultimately fail. That’s true for all industries but
especially so in data-driven industries such
as insurance, healthcare and supply chain,
among others.
The n+1 philosophy can help a company answer such crucial questions as,
What’s next? and What should we do to
improve efficiency, reduce risk, indeed
turn risk into opportunity and increase
growth?
For example, a comprehensive supply
chain risk management strategy – along
with the incorporation of an array of predictive analytic tools to measure and manage risk – often extends beyond the supply
chain itself to encompass all major operations of the organization. In fact, modern
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