There are hundreds of recruiting solutions available today. However, solutions that automate the recruiting process without improving the outcome just deliver bad choices faster. To identify the top candidates, a recruiting solution must understand the requirements of the position — including skills, experiences, background, affinities, and many other qualities — and determine which candidates best meet those requirements. No hiring solution does all that as this well as Talent Sprocket.
Machine learning systems teach themselves to recognize patterns in complex data sets that allow them to make intelligent decisions. Talent Sprocket uses machine learning to recognize and prioritize requirements that are critical to job performance using an wide variety of input sources. Then Talent Sprocket finds the best pattern matches from among the dozens, hundreds or even thousands of applicants for a position and presents them in a simple visualization.
Talent Sprocket uses Distributed Participatory Design (DPD) to gather the input from all stakeholders, design a model of the job and develop it's requirements. This form of crowd sourcing lets experts and non-experts contribute equally while validating their contribution against real-world performance.See How >
Talent Sprocket publishes your job opportunity to hundreds of media platforms including social media as well as general and industry-specific job boards. Talent Sprocket casts a wide net over massive numbers of passive as well as active candidates.See How >
Talent Sprocket uses information visualization to present job applicants. This form of user interface allows large-scale collections of non-numerical information to be quickly understood, assessed and ranked.See How >