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Hrm 531 Week 1 Case Study Of Big Data

1636 Words7 Pages

Big data is any form of data, but is also a term referring to data sets that are so large and complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying and information privacy. According to Lopez (Manyika, et al, 2011), big data presents opportunities to drive innovation, improve productivity, enhance customer satisfaction, and increase profit margins. However, most senior management still struggle to handle the new influx of data due to the failure to harness, prioritize, and understand the data flowing in. According to SHRM, most employers have barely scraped the surface when it comes to mining big data, in part because …show more content…

Evolv found that employees without call center experience were just as successful as those who had it, allowing Xerox to broaden its candidate pool. Creative personalities stayed longer than those with inquisitive personalities, as did candidates who belonged to at least one but not more than four social networks. Armed with such detailed information on what made a successful hire, Xerox was able to reduce attrition by 20 …show more content…

A survey of 220 organizations (including fortune 1000 companies) showed that more than three quarters of all participating companies (76.8%, n = 169) indicated that they have an individual or function dedicated to HR research and analytics. In terms of staffing levels for the HR research and analytics function, 62% of the companies reported staffing levels of five or less people in the group, and 92% reported 12 or less people assigned to this function. Additional analyses found that the staffing level of this function was higher in companies with higher gross revenues and a larger workforce (Falletta, 2013). Even these results were and are still underreported. Feffer (2014) states that, before total buy-in can happen, a number of obstacles that need to be addressed. Firstly, tools to integrate certain HR data need to be available. He states that, data has to be compiled from disparate systems that don’t always talk to each other and often don’t agree when they do; such pertinent data resides in systems tracking payroll, time and attendance, applications and educational

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