Such tools are now becoming available, and companies that develop a strategy for deploying enterprise social software, and use the tools effectively in various organizational areas, can capitalize on the vast amounts of data this activity will generate. Analyzing this data can provide tremendous visibility, into patterns of interaction that go beyond email and phone logs. Examining enterprise social software data, along with data from other sources such as ERP systems and customer service operations, can help identify causal relationships between patterns of interaction, and operating performance.
By Eric Openshaw and Jerry Belson
The convergence of social software platforms and big data analytics is creating new avenues to explore the factors driving business performance. From a marketing standpoint, businesses continue to make significant progress in examining social media interactions with and among their customers to learn about and address needs, desires, and opinions. And businesses are in the early stages of analyzing social data in combination with other data sets from both within and outside the enterprise to guide strategic decisions.
The Impact of Social Media
In the past several years, businesses have begun using analytics to mine social data in combination with big data to understand external customer priorities and interests. However, efforts to similarly analyze internal and business partner data have lagged, largely for lack of effective tools.
To date, companies have made only limited inroads into exploring social media-based activities and interactions inside the enterprise and with supply chain and distribution partners. However, the results of a few nascent efforts hint at exciting emerging capabilities for using social media and big data analytics to identify patterns of social interaction internally, assess how those patterns affect performance, and then leverage those lessons in near real-time feedback loops to improve organizational performance.