The value of large data is gradually recognized 75% enterprises attach importance to business analysis

According to China Software Information Network, IBM published a new study on large data analysis in the world, "Analysis: The Blueprint for value" shows that in the current world-leading enterprises and organizations, the primary value of business analysis is defined as "growth" or "innovation" of more than 75%. Two-thirds of the companies and organizations agree that "policy" or "execution" is the most important factor impeding the maximization of value.

The IBM Institute of Business Value has conducted five research on "the adoption and application of analysis" around the world. In this survey, IBM found that more than two-thirds of respondents were using business analytics to support revenue-generation strategies and to achieve cost control, a number that was steadily rising compared with the previous one. In addition, the survey showed that nearly 40% of companies saw a rapid return on investment (ROI) within six months of the adoption of the analysis.

The survey found that the three main elements to promote business application analysis are: support, trust and skills. With the reduction of these three aspects, the application analysis of the enterprise will continue to increase the implementation of support, strengthen the trust across the enterprise, and build deep knowledge and skills.

"To give full play to the value of large data, companies need to identify different executive roles and take full advantage of analytics," said Fred Balboni, global head of business analysis and optimization at IBM Global Business Consulting services. New roles like chief data officer and chief analyst are helping companies build enterprise-wide data strategies to increase their competitive edge. Through consistent strategies, standards, technologies, and organizational structures, the potential for business analytics can be tapped. ”

Enhance management support

IBM's research shows that One-fourth of CEOs and chief operating officers pioneered the use of analytical Insights (24%). Although the ratio has increased by 10% since 2012, the distance between the broad shifts in management has been long. In addition to both, other corporate executives such as CIOs and chief marketing officers also have the power to drive large data and analytics across the enterprise.

Management's support and participation in large data and analysis are key to creating value. In enterprises with low management support, the use of analysis is hampered by lack of funds, resources and follow-up support. As businesses seek to grow, companies need deeper horizontal and vertical advocates to support these projects.

It is noteworthy that management support is critical to building a data-driven culture. In the future, more and more companies may consider appointing a chief data officer or chief analyst to help their companies analyze and drive results, and build a corporate culture around analytics to drive business success.

Break the trust gap

At present, most companies prioritize data-related investments and decisions to the business sector level.

The lack of trust within the enterprise has proved to be one of the most important obstacles to the value of the enterprise. About 60% of the best employees say they like a strong sense of trust among their internal members. This degree of trust between the business and IT departments fell to 47% when anonymous surveys were conducted.

Fragmentation can lead to a collapse of trust between people who use different ways to access, interpret, and use data. This gap stems from a fundamental distrust within the enterprise, i.e. who is qualified to analyze the data and act. The lack of trust between management, analysts and data managers can severely impact the willingness to share data and influence the value that is created by insight and collaboration. The IBM study found that the personal trust gap was an important indicator of the lack of trust in data authenticity. In this case, the overall cost of the enterprise will become very high.

Filling skills Gaps

Another factor hindering success through large data and analysis is the ability to spread around skills. The gap between the global demand for large data analysts and the supply of local talent is one of the major impediments to analysis and deployment in all enterprises. One-third of respondents said that the lack of skills to analyze and interpret data and translate it into business value in their businesses is a primary business challenge that hinders better value analysis.

The biggest skill gap comes from combining analytical skills with business knowledge to gain meaningful insights from the data. As a result, analysts who understand business and have a high degree of mathematical analysis are among the most sought-after in the market. More than One-third of respondents (36%) saw this as the biggest skill gap in enterprise development, followed by analytical skills (24%), Data management skills (21%) and business skills (19%).