TMP Worldwide, talent acquisition technology company, has recently announced the release of Priority Score - a proprietary machine learning model for predicting and acting upon job performance. The new technology quickly identifies openings that are lacking necessary or receiving an inordinate amount of candidate flow and automates alerts and actions across the TalentBrew platform and into search, social and programmatic media channels.
Built on top of TMP's job classification engine, Priority Score leverages hundreds of millions of interactions to forecast an expected performance for individual and groups of openings by using information from similar jobs in the same market. Signals are then utilized to automate steps aimed at boosting traffic for jobs at risk of underperformance and reallocating funds and effort for those jobs that are overperforming.
"Incorporating predictive AI into process automation carries risks that can only be mitigated if the dataset is both extensive and carefully governed. Due to the depth and quality of our data, we're excited to release another industry-leading feature available exclusively to users of TMP's TalentBrew platform," explains Todd Maycunich, Vice President, Product Innovation. "Automating actions designed to drive candidate flow to jobs that need it takes pressure off sourcers and recruiters and can help save money and reframe how talent acquisition teams spend their time."
"As automation in media buying and optimization becomes more essential to helping employers scale their recruitment marketing strategies, we're acting on an aggressive plan to invest in both the data science and new technology to help our clients maintain their competitive advantage," said Michelle Abbey, President, and CEO of TMP Worldwide.
SOURCE TMP Worldwide