When The Global Information Technology Report (GITR)
and the Networked Readiness Index (NRI) were created
more than 13 years ago, the attention of decision
makers was focused on how to develop strategies that
would allow them to benefit from what Time Magazine
had described as “the new economy”: a new way of
organizing and managing economic activity based on
the new opportunities that the Internet provided for
businesses.1 At present, the world is slowly emerging
from one of the worst financial and economic crises
in decades, and policymakers, business leaders, and
civil society are looking into new opportunities that
can consolidate growth, generate new employment,
and create business opportunities. Information and
communication technologies (ICTs) continue to rank high
on the list as one of the key sources of new opportunities
to foster innovation and boost economic and social
prosperity, for both advanced and emerging economies.
For more than 13 years, the NRI has provided
decision makers with a useful conceptual framework
to evaluate the impact of ICTs at a global level and
to benchmark the ICT readiness and usage of their
economies.
EXTRACTING VALUE FROM BIG DATA
Data have always had strategic value, but with the
magnitude of data available today—and our capability to
process them—they have become a new form of asset
class. In a very real sense, data are now the equivalent
of oil or gold. And today we are seeing a data boom
rivaling the Texas oil boom of the 20th century and the
San Francisco gold rush of the 1800s. It has spawned
an entire support industry and has attracted a great deal
of business press in recent years.
This new asset class of big data is commonly
described by what we call the “three Vs.” Big data is
high volume, high velocity, and includes a high variety of
sources of information. Next to those traditional three Vs
we could add a fourth: value. This is what everyone is
looking for, and this is why big data today gets so much
attention. In the quest for value, the challenge facing us
is how to reduce the complexity and unwieldiness of big
data so that it becomes truly valuable.
Big data can take the form of structured data such
as financial transactions or unstructured data such as
photographs or blog posts. It can be crowd-sourced or
obtained from proprietary data sources. Big data has