The new research provides valuable insight into the state of and use of predictive analytics and the ways in which it is transforming business across roles and departments. IT finds that marketing (48%) and operations (44%) are the business units that most often apply predictive analytics and that organizations most commonly apply predictive analytics to customer (50%) and marketing (44%) information, followed by product (43%), financial (40%) and sales (36%) information. The research reveals that use of predictive analytics is moving into the lines of business where it is being used to generate insights that help decision-makers achieve the organization's business goals.
Analysis of the findings of this benchmark research lead us to conclude that predictive analytics should be viewed as a business investment rather than an IT investment. Since our previous research on this topic in 2012, funding authority has shifted from general business budgets (from 44% then to 29% now) to line of business IT budgets (from 19% then to 27% now). Predictive analytics is being used most today in areas critical to revenue and profitability, and its use is growing: More than seven out of 10 organizations participating in the research already use predictive analytics, and the remaining 28 percent plan to.
Ventana Research defines predictive analytics as the application of mathematical computation and models to generate forward-looking insights that can be used to optimize business and IT processes and decisions. Predictive analytics improves an organization's ability to understand potential future outcomes; its results enable decision-makers in key areas of the business to choose the best courses of action.
The research finds persistent barriers to making changes in the use of predictive analytics. More than half (52%) of organizations lack the resources they'd need to do so, and nearly as many (48%) lack awareness of the need for changes. Analysis of the research findings shows that issues of expertise and training are critical considerations in adopting and using predictive analytics effectively. In half (52%) of organizations the people who design and deploy predictive analytics are the ones who utilize the output of the predictive analytics processes. The most common reasons that users don't design analyses themselves are that they don't have enough skill training (79%) and don't understand the mathematics involved (66%).
As for simplifying use, the research uncovers a trend to blend predictive analytics with more established tools, a choice that can bring the technology closer to mainstream use and help businesses respond faster to challenges and opportunities. Participants most often said they would like predictive analytics integrated with business intelligence (56%) and within business applications (49%), and a majority of these want it embedded in both.
The research shows that while the conventional tools of flat files and relational databases on standard hardware are still the most commonly used for predictive analytics with big data, more than half (52%) now use data warehouse appliances and 31 percent use in-memory databases. Within a year another 19
percent plan to use in-memory databases and the use of Hadoop, the open source big data technology, will nearly double, from 25 to 49 percent.
The key point is that the business units and IT should work together with the common goal of making predictive analytics deliver value to the enterprise, and the research finds evidence of this happening. For example, they agree about how best to deploy the tools. Within two percentage points, both expressed a greater preference to deploy on-premises (business 53%, IT 55%) and there was even closer agreement among those who prefer to do it on demand through cloud computing (business 22%, IT 23%). More than 90 percent on both sides said the organization plans to deploy more predictive analytics, and they also were in close agreement (business 32%, IT 33%) that doing so will have a transformational impact, enabling the organization to do things it couldn't do before.
"Predictive analytics has become a critical focal point for gaining a competitive edge, as a substantial majority of organizations indicated in this new landmark benchmark research," said Tony Cosentino, VP and research director. "But organizations are still challenged concerning the skills required to take on this essential analytic processes. And the research makes clear that the technology needs to become easier to use, as the highest percentage of organizations, 89 percent, identified usability as the most important product attribute in the acquisition process."
"I am very happy to bring this new market research in predictive analytics to market as it is essential to the effectiveness of businesses both today and in the future," said Mark Smith, CEO and chief research officer. "Our firm has provided the best possible research and education in analytics for more than 13 years, and while many in the industry talk about predictive analytics, we are the only analyst firm that has the research and expertise on the topic across business and IT, and that's reflected in this research."
Ventana Research undertook this benchmark research as part of its vigorous annual research agenda to determine the attitudes, requirements and future plans of those who use predictive analytics and to identify the best practices across business and IT in the organizations that are most proficient in it. The research focused on understanding the current and evolving reasons for adopting advanced analytics and the challenges associated with deploying them. It examined use across lines of business and industries and the importance of various elements of advanced analytics, including statistics, forecasting, data mining, simulation and optimization. The research uncovered companies' best practices in managing predictive analytics implementations and the benefits they receive or expect to receive from their implementations. It examined the application of predictive analytics to big data and the use of collaborative tools to make predictive analytics easier to use. It also assessed the relevance of cloud computing to predictive analytics in both using the software and accessing data.
Those interested in learning more about this benchmark research can download an executive summary at http://www.ventanaresearch.com/NextGenerationPredictiveAnalytics/ and where further education to advance the business and IT potential in predictive analytics. The research was sponsored by IBM and our community partner KDnuggets. Ventana Research, a leading business technology research and advisory services firm, provides qualified research participants with an incentive and complimentary report of the research findings as well as access to a free educational webcast on best practices from the benchmark research.
About Ventana Research
Ventana Research is the most authoritative and respected benchmark business technology research and advisory services firm. We provide insight and expert guidance on mainstream and disruptive technologies through a unique set of research-based offerings including benchmark research and technology evaluation assessments, education workshops and our research and advisory services, Ventana On-Demand. Our unparalleled understanding of the role of technology in optimizing business processes and performance and our best practices guidance are rooted in our rigorous research-based benchmarking of people, processes, information and technology across business and IT functions in every industry. This benchmark research plus our market coverage and in-depth knowledge of hundreds of technology providers means we can deliver education and expertise to our clients to increase the value they derive from technology investments while reducing time, cost and risk.
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