With More Data Comes More Complexity
Companies are increasing their investments in social analytics to help them interpret the volumes of data coming in from social media platforms and monitoring tools, new research indicates.
According to the Hypatia Research Group study "Social Analytics and Intelligence: Converting Contextual to Actionable," 39.5 percent of the more than 500 companies surveyed plan to allot more than 5 percent of their annual marketing budget to social analytics in 2013. Sixty percent plan to invest between 1 percent and 2.9 percent.
It's no surprise that the volume of user-generated content in social media is valuable for companies. But early adopters of social analytics solutions need to be aware of their objectives and approaches to benefit from unstructured data.
"Knowledge transfer and training is a huge part of effective leverage of social analytics and intelligence," notes Leslie Ament, vice president and senior analyst at Hypatia and author of the report. "Metrics should match either operational business issues or corporate goals. Too many companies focus on tactical metrics that align with individual goals rather than with the needs of the enterprise."
In "The Deciding Factor: Big Data and Decision Making," an Economic Intelligence Unit report, a survey of 607 C-level executives spanning 20 industries, two-thirds of respondents consider their organizations to be "data-driven." More than 40 percent say social media, in particular, has become increasingly important in organizational decision-making.
But the report, commissioned by Capgemini, revealed a disconnect between intent and execution. Of 168 North American respondents, 58 percent said they plan to increase their investment in big data analysis during the next three years. However, 71 percent struggle with data inaccuracies on a daily basis, while 46 percent lack the time to interpret data sets.
Nearly four in 10 North American respondents (39 percent) said unstructured data is "too difficult to interpret." While executives expressed familiarity with spreadsheets and relational databases, they struggle with text analytics and sentiment analysis.
The Capgemini study notes the correlation between the digital and social explosion and the rise of big data.
Big data is "fueling a major change, requiring organizations to adopt…more effective methods to obtain the most meaningful results from their data that generate value," Scott Schlesinger, vice president and head of business information management at Capgemini U.S., said in a statement.
Ament found that 53.2 percent of North American respondents use more than five sources of unstructured, social, and user-generated content for big data analysis, more than twice that for Asia and the Pacific Rim and Europe.
"Many organizations are in discovery mode, seeking important signals within the information tsunami of volume, velocity, and variety," Ament maintains.
But there are bottlenecks, including questions like, "Who is responsible for each business issue or is just one team responsible for analysis of big data on an enterprise level?" Others revolve around the processes, analytical models, and visualization techniques that will be used, accountability for interpreting and acting on big data results, and operationalizing any insights that surface, Ament concludes.
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