How Time-to-Insight Is Driving Big Data Business Investment
Blog: Colin Crofts - Business Process Improvement
For many corporations, obtaining insights rapidly is the true value of Big Data.
They say that time is money, but Fortune 1000 executives polled in the
fourth annual Big Data Executive Survey conducted by NewVantage
Partners have boldly confirmed that reducing time-to-insight rather than
saving money is the primary driver for their Big Data business investment.
fourth annual Big Data Executive Survey conducted by NewVantage
Partners have boldly confirmed that reducing time-to-insight rather than
saving money is the primary driver for their Big Data business investment.
Conducted in November and December 2015, and published on January
11, 2016, the survey confirms that Fortune 1000 firms believe that Big
Data will deliver competitive advantage by enabling their firms to act
faster when it comes to analyzing data, gaining insights, making critical
decisions, and bringing new capabilities to market. The survey reflects
the evolving perspectives of chief data officers, business presidents,
chief information officers, and the heads of Big Data initiatives for
nearly 50 prominent Fortune 1000 firms.
11, 2016, the survey confirms that Fortune 1000 firms believe that Big
Data will deliver competitive advantage by enabling their firms to act
faster when it comes to analyzing data, gaining insights, making critical
decisions, and bringing new capabilities to market. The survey reflects
the evolving perspectives of chief data officers, business presidents,
chief information officers, and the heads of Big Data initiatives for
nearly 50 prominent Fortune 1000 firms.
Survey participants included Fortune 1000 top 50 mainstays such
as CVS Health, JPMorgan Chase, Bank of America, and Johnson
& Johnson. Large financial services firms were heavily represented,
and as an industry group, have long been at the forefront of investments
in data management solutions.
as CVS Health, JPMorgan Chase, Bank of America, and Johnson
& Johnson. Large financial services firms were heavily represented,
and as an industry group, have long been at the forefront of investments
in data management solutions.
As measured by investment and business adoption, it has taken just four
short years for Big Data to assert itself as an essential component of the
corporate mainstream. Among the Fortune 1000 firms surveyed by New
Vantage, 62.5% reported having Big Data initiatives in production or operationalized across the enterprise — nearly double the 31.4% of firms
at this stage in 2013. While only 5.4% of firms reported Big Data
investments in excess of $50 million in 2014, the number of firms that
project investments in Big Data of greater than $50 million leaps to
26.8% by 2017, a steep and rapid increase. For the first time, a majority
of firms (54%) reports having appointed a Chief Data Officer, up from
just 12% in 2012, providing further corroboration that data has become
a corporate priority.
short years for Big Data to assert itself as an essential component of the
corporate mainstream. Among the Fortune 1000 firms surveyed by New
Vantage, 62.5% reported having Big Data initiatives in production or operationalized across the enterprise — nearly double the 31.4% of firms
at this stage in 2013. While only 5.4% of firms reported Big Data
investments in excess of $50 million in 2014, the number of firms that
project investments in Big Data of greater than $50 million leaps to
26.8% by 2017, a steep and rapid increase. For the first time, a majority
of firms (54%) reports having appointed a Chief Data Officer, up from
just 12% in 2012, providing further corroboration that data has become
a corporate priority.
What is driving the sharp increase in Big Data investment? According
to the NewVantage survey, a clear pattern has emerged. Organizations
feel a need to learn quickly and act faster. While only 5.6% of firms
identified cost savings and operational reductions as the primary driver
of Big Data investment, 83.5% of survey respondents named factors
relating to speed, insight, and business agility as the primary reasons for
Big Data investment.
Of this total, 46.5% firms pointed to factors aimed at increasing speed and
reducing the time-to-insight. This is illustrated in the chart showing a
breakdown of Big Data investment factors relating to time-to-insight.
to the NewVantage survey, a clear pattern has emerged. Organizations
feel a need to learn quickly and act faster. While only 5.6% of firms
identified cost savings and operational reductions as the primary driver
of Big Data investment, 83.5% of survey respondents named factors
relating to speed, insight, and business agility as the primary reasons for
Big Data investment.
Of this total, 46.5% firms pointed to factors aimed at increasing speed and
reducing the time-to-insight. This is illustrated in the chart showing a
breakdown of Big Data investment factors relating to time-to-insight.
So, how will organizations respond and leverage Big Data investments to
accelerate the time in which it takes to capture and analyze data, identify correlations, derive insights, and validate their insights in the market?
accelerate the time in which it takes to capture and analyze data, identify correlations, derive insights, and validate their insights in the market?
Accelerate Time-to-Answer through
Test-and-Learn Processes
Test-and-Learn Processes
Business analysts have long been bound by the time it takes to capture,
organize, and make data available to non-technical users. Big Data
processes have consolidated the time it takes to engage in analytics by
reducing up-front data engineering and putting data into the hands of
business users faster. By starting with smaller sets of data, business
analysts can engage in iterative processes such as test-and-learn to
identify patterns and correlations that allow them to focus on the most
useful data quickly. This ability to accelerate the process of insight is
alternately referred to as time-to-answer, time-to-analytics, or
time-to-decision. The net result is the realization of greater insight faster.
organize, and make data available to non-technical users. Big Data
processes have consolidated the time it takes to engage in analytics by
reducing up-front data engineering and putting data into the hands of
business users faster. By starting with smaller sets of data, business
analysts can engage in iterative processes such as test-and-learn to
identify patterns and correlations that allow them to focus on the most
useful data quickly. This ability to accelerate the process of insight is
alternately referred to as time-to-answer, time-to-analytics, or
time-to-decision. The net result is the realization of greater insight faster.
Accelerate Speed-to-Market with
Data Discovery Environments
Organizations are employing new approaches to traditional data
management. These approaches include the deployment of analytical
sandboxes, Big Data labs, data hubs, and data lakes. All of these
approaches are designed to introduce greater flexibility and agility into
the process of taking data and transforming it into business insights.
The big breakthrough of Big Data comes from enabling firms to deploy
rapid analysis environments that facilitate data discovery. These more
nimble environments produce faster insights, which enable organizations
to move rapidly to action and accelerate the speed with which they can
bring new product and service capabilities to market. As a driver of
Big Data investment, “speed-to-market” experienced the greatest uptick
from previous years. Firms are looking for measurable results, ratified
in the marketplace.
management. These approaches include the deployment of analytical
sandboxes, Big Data labs, data hubs, and data lakes. All of these
approaches are designed to introduce greater flexibility and agility into
the process of taking data and transforming it into business insights.
The big breakthrough of Big Data comes from enabling firms to deploy
rapid analysis environments that facilitate data discovery. These more
nimble environments produce faster insights, which enable organizations
to move rapidly to action and accelerate the speed with which they can
bring new product and service capabilities to market. As a driver of
Big Data investment, “speed-to-market” experienced the greatest uptick
from previous years. Firms are looking for measurable results, ratified
in the marketplace.
With the emergence of a digital economy over the course of the past
two decades, leading firms have learned quickly that they must act
faster to respond to customer needs and competitive dynamics. Firms
can no longer wait days or months to analyze indicators of customer
interest and sentiment, or detect and respond to security threats or credit
breaches. Market leaders will not wait while their competitors uncover
critical insights that drive new product and service capabilities. Fortune
1000 firms have come to the conclusion that the ability to act faster
correlates with market survival and success. The need for faster
time-to-insight will be the driving force behind Big Data investment
for the years ahead.
two decades, leading firms have learned quickly that they must act
faster to respond to customer needs and competitive dynamics. Firms
can no longer wait days or months to analyze indicators of customer
interest and sentiment, or detect and respond to security threats or credit
breaches. Market leaders will not wait while their competitors uncover
critical insights that drive new product and service capabilities. Fortune
1000 firms have come to the conclusion that the ability to act faster
correlates with market survival and success. The need for faster
time-to-insight will be the driving force behind Big Data investment
for the years ahead.
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