RESEARCH TRIANGLE PARK, N.C. — Research organizations must address challenges posed by big data in order to thrive in an environment where data is collected and stored at an unprecedented rate, suggest authors of an article published in a special issue of the Journal of Organizational Design devoted to big data. The article was published online April 10.
In the commentary, “Big Data and Organizational Design: Key Challenges Await the Survey Research Firm,” the authors describe how survey research organizations are aligning to meet the demands of big data for emerging business opportunities.
Big data refers to the ever-expanding volume of information – ranging from Facebook posts and Twitter feeds to 911 call transcripts -- that is difficult to validate and analyze using traditional approaches or database management tools. Due to the scope of big data, survey research organizations must address how to capture, validate, and draw meaningful conclusions from these disparate data sources.
“Big data’s transformative nature presents unique challenges to organizations, requiring them to re-calibrate technological savvy and subject matter expertise to meet emerging business opportunities,” said Tim Gabel, RTI International executive vice president of Social, Statistical and Environmental Sciences and the article’s lead author. “Research firms must organize staff to enable the type of cross-disciplinary innovation that big data demands. This is challenging for organizations like RTI who benefitted from successful organizational models in the past and are grappling with how best to organize to address the Big Data Revolution.”
The paper suggests that because big data calls for a cross-disciplinary approach, scientific research organizations face the challenge of reviewing human resource processes and restructuring organizational disciplines to leverage talent. Further challenges include revising job descriptions and hiring practices to attract new talent and create project teams with blended skill sets.
“RTI’s workforce needs are already being transformed by skill-set demands of big data,” Gabel said. “We anticipate a blurring of the lines between mathematics, statistics, computer science, and subject matter expertise to meet the demands of big data.”
To help tackle the big data challenges, RTI’s social, statistical and environmental sciences business unit has established the Center for Data Sciences, bringing together nearly 80 staff members, including data modelers, computational scientists, statisticians and experts in predictive analytics.
“We recognize that the challenges we face are similar to those facing our clients,” Gabel said. “Big data presents both challenges and opportunities for scientific research organizations. Firms like ours, and the clients we support, will need to adjust accordingly.”