THE CHALLENGE: Reducing Turnover for the Staffing Industry
U.S. employers paid more than $600 billion in turnover costs in 2018, with one in four employees leaving their jobs last year; both numbers are indicative of increasing turnover in the workforce. The staffing industry is particularly impacted by this phenomenon, with a 386% turnover rate in 2017. America’s staffing companies hire 17 million temporary and contract employees every year, but the average tenure is less than 12 weeks.
As employers look at ways to reduce turnover by hiring the right people in the first place, social media has become an increasingly important tool to help screen potential candidates. More than 70% of employers now research social media sites during the screening process, and 57% have found content that has caused them not to hire a candidate. While these manual social media screens may provide meaningful insights, they have three barriers:
1. The human resources and time required to conduct these searches;
2. The incompleteness of a social media search against the sheer volume of publicly available information on the Internet;
3. Privacy concerns.
Radiance is a deep-web listening tool that uses machine learning and artificial intelligence to assess and prioritize risk.
Radiance scours publicly available data across the entire Internet, correlating names entered into the system with content related to 25 different risk factors, known as Behavioral Affinity Models (BAMs), and cross-referenced with more than 1 million queries into Lumina’s proprietary databases of risk.
Searches provide near-instant results, delivering meaningful, actionable intelligence to identify and prevent risk.
The S4 app is a crowd-sourced, mobile application that allows users to confidentially report concerns in real time.
THE SOLUTION: Revolutionizing the Screening Process through Deep Web Listening and AI
More than 2.5 quintillion bytes of data are added to the web every day. Radiance overcomes the challenge of massive unstructured data ingestion, evaluation and prioritization through machine learning and artificial intelligence.
Radiance’s 25 BAMs include criminal conduct, alcohol consumption, drug involvement and misuse, workplace violence, sexual behavior, Islamic and right wing extremism, and financial crimes – all relevant to hiring risks. Radiance includes more than 8,250 different terms related to these behavioral affinities. The platform conducts nearly 165,000 searches across all publicly-available data on the web, correlating names with these terms and cross-referencing over 1 million queries into Lumina’s proprietary databases of risk.
Radiance pulls all applicable content into a comprehensive report. The results are prioritized, making it easy to further analyze the findings and determine potential risk. A manual web search of this magnitude would take 1 year and 4 months for one person to complete.
S4 app can be configured as a workplace tool, allowing employees to submit information related to potential risk behaviors exhibited by co-workers. A centralized management portal allows clients to access real-time threats to geo-fenced facility locations.
While a background check is still a necessary part of the hiring process, Radiance’s capabilities augment historical data found in background checks with real-time data available on the web that a traditional check would not uncover.