IQN, the leading, independent provider of non-employee workforce management solutions, is unveiling new advanced analytics capabilities at the 2016 Contingent Workforce Strategies (CWS) Summit on September 19-20. With industry experts spotlighting advanced analytics as “the next wave of technology to bring process efficiency, speed and heightened visibility into workforce sourcing and management1,” IQN is leading the industry in innovation with the release of ATOM, the first and only cognitive intelligence engine for non-employee labor programs.
ATOM, which stands for Automated Talent Ontology Machine, delivers previously unachievable insights on rates, time‐to‐fill, labor demand modeling and industry benchmarking–all driven by scalable data visualization and real‐time predictive analytics.
“Technology and globalization are transforming the way we work, giving rise to the gig economy,” says Joe Juliano, President and Chief Executive Officer, IQN. “Business leaders want to leverage contingent workers to cut costs, boost flexibility and fill specialized needs. ATOM enables our customers and MSP partners to win the war for valued talent by elevating the speed, quality and relevance of the business insights that IQN provides.”
IQN Presents New ATOM Capabilities at CWS Session, Tuesday, September 20
First previewed at IQN’s national customer event in April, ATOM combines advanced data science methodologies with multiple years of contingent labor data. IQN will demonstrate its months of enhancement to ATOM’s capabilities at the CWS Summit in Las Vegas. Speaking on September 20 from 11:30 to 12:15 pm (PDT), Anne Zelenka, PhD, IQN’s Vice President of Data Science and Data Products, will highlight how ATOM empowers procurement officers to proactively manage non-employee labor by comparing bill rate and time-to-fill data against industry benchmarks for more than 130 standard job titles in 260 United States metro areas.
“What makes ATOM such a game-changer is how it combines innovative machine intelligence with extensive human understanding of talent management needs,” says Zelenka. “ATOM learns from every user interaction so we are continuously ‘teaching’ our engine how to delve deeper into non-employee labor data to uncover hidden patterns. As a result, our proprietary solution dynamically advises decision makers by automatically adapting to their unique and evolving talent management needs better than any human expert or system alone.”
With its broad understanding of occupations, ATOM will tag an assignment with the occupation that best fits its job description; using natural language processing to map client specific job titles to standards. IQN customers and partners are able to explore patterns for exactly the jobs that are most important to their contingent workforce program. They can see, for example, the bill rate and time to fill in a particular metro area, and then compare how their programs are performing against ATOM benchmarks.