While more than 75 percent of the highest performing organizations cite growth or innovation as the chief value of business analytics, almost two-thirds of them say some form of political or executive resistance is the primary barrier to realizing the full value of their investments, according to a new IBM study.
In its fifth global examination of the adoption and usage of analytics, IBM found that a steadily growing number of respondents (more than two-thirds) are applying business analytics to support revenue-generation strategies, versus cost containment. Additionally, the IBM Institute for Business Value study, entitled "Analytics: A Blueprint for Value," found that almost 40 percent of companies see a rapid return on investment (ROI)—within the first six months of analytics adoption.
The study also found three essential factors to advance business analytics within organizations - sponsorship, trust and skills—and significant gaps in each area. By addressing these gaps, analytics leaders have an opportunity to increase executive advocacy, strengthen trust across the organization, and build deeper knowledge and skills.
"In order to unlock the value of data, organizations need to identify different C-suite champions to get fully behind the use of analytics. Emerging roles like the Chief Data Officer and the Chief Analytics Officer are helping companies build an enterprise-wide data strategy to gain competitive advantage," said Fred Balboni, Global Leader and Partner, Business Analytics and Optimization, IBM Global Business Services. "It takes the right alignment of strategy, standards, technology and organizational structure to reap the full potential of what business analytics offers."
Executive advocates needed
Today, only a small percentage of C-suite leaders are strong advocates for the use of Big Data and analytics to speed decision-making and institute change. IBM's study reveals that one-quarter of all Chief Executive Officers (CEO) and Chief Operating Officers (COO), act as the lead advocates for the use of analytic insights (24 percent). This is a 10 percent increase from 2012, but still far from the pervasive leadership required to spark widespread change. Besides the CEO and COO, other C-suite executives such as the CIO and CMO have the power to advance the use of Big Data and analytics across the enterprise.
Executive sponsorship and involvement in Big Data and analytics are key to value creation. In organizations with low levels of executive support, analytics implementations are hampered by lack of funding, resources and follow through. As organizations seek to grow, there is a need to have deeper horizontal and cross-company advocates to help pay for projects.
This draws attention to the fact that executive sponsors are critical to building a data-driven culture. In the future, more companies may think of appointing a Chief Data Officer or a Chief Analytics Officer to help his or her company analyze and drive results, and build a corporate culture around analytics to drive business success.
The trust gap
Most organizations today prioritize investments and decisions about data at the business-unit level.
A lack of trust within organizations is proving to be one of the most significant hurdles to achieving value. While about 60 percent of top performers enjoy strong levels of trust among individuals within their organization, the level of trust drops significantly (47 percent) when it is anonymized between business units and IT departments in general.
A fragmented approach can result in a breakdown of trust among different groups of people who may be accessing, interpreting, and using data in different ways. This gap stems from a basic distrust about who is qualified to competently analyze and act upon the data. A lack of trust among executives, analysts and data managers can significantly impact the willingness to share data, rely on insights and work together to deliver value. IBM's study found that a trust gap among individuals is a leading indicator of lack of trust in the veracity of data. When this happens, the overall costs to a business are high.
For example, a major global banking institution duplicated its data collection efforts from two different sources because banking executives did not trust the work of another team from a different geography, which led them to doubt the authenticity of data.
Nationwide Insurance in Columbus, Ohio, is an example of an enterprise using increased communication and education to bridge the trust gap.
"By empowering our organization to build trusted relationships, we have accelerated our Big Data and analytics objectives," said Wes Hunt, VP of Analytics at Nationwide Insurance. "We break down trust barriers by an increased focus on education and personal interaction, so everyone understands and interprets data similarly. It is imperative that there is trust– both in the data and in individuals – so the organization can more quickly act on those insights from the data."
The growing skills gap
Another factor that is creating a barrier to success with Big Data and analytics is around skills. The gap between the demand for Big Data and analytics talent globally and the supply of talent locally is one of the key obstacles to analytics implementations across all organizations. One-third of respondents cited the lack of skills to analyze and interpret data into relevant business actions as the top business challenge impeding better value analytics within their organizations.
The largest skills gap is the ability to combine analytics skills with business knowledge to draw meaningful insights from the data. The analyst who both understands the business and performs higher mathematic tasks is the most sought after in the market. More than one-third of all respondents (36 percent) cited this as their organization's most pressing skills gap, followed by analytic skills (24 percent), data management skills (21 percent) and business skills (19 percent).
About the "Analytics: A Blueprint for Value" study
IBM conducted its analysis with nearly 1,000 business and IT executives from 70 countries. Survey topics included executive activities, business process activities, data management practices, human resource management, competency measures, software usage and hardware implementation. IBM conducted this survey by using a global team of business strategists, consultants, data scientists and statisticians.
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