Competing With Data & Analytics
What to Read Next
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.
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.
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 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 NewVantage, 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.
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 Time-to-Answer through 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.
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.
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.