Talent Sprocket is delivered as a complete SaaS recruiting solution for sourcing-through-selection. Talent Sprocket performs the tasks of developing requirements, posting ad to job boards and social media, applicant tracking, and candidate evaluation. In just days, an employer or recruiter can go from a newly opened requisition to a short list of the most qualified candidates culled from hundreds of applicants — without any significant understanding of the position.
The process begins with an approach called Distributed Participatory Design. A form of crowd sourcing, DPD allows an unlimited number of people to contribute what they know about to design the job model and its requirements. Managers, peers, and other stakeholders directly input the requirements they think are important. They also rate employees that already work in the position. These rated employees indirectly contribute their biographical data, work performance and behavioral traits. With each input, the Talent Sprocket machine learning engine finds new patterns that predict superior job performance and adapts the job model dynamically.
Talent Sprocket casts a wide net over massive numbers of passive as well as active candidates. Talent Sprocket publishes your job opportunity to numerous general and industry specific job boards and social media. The Talent Sprocket machine learning engine provides the ability to automatically compile an unlimited amount of information from the candidate pool. As interested candidates apply, Talent Sprocket compares each candidate to every other candidate, thus achieving a rigorous and repeatable process of candidate analysis.
The mass of raw data contained in paper resumes and applications is distilled into simple tables and graphic visualizations. No applicant is overlooked, and the right candidates to interview are easily identified. As candidates are hired, their data further refines the job model.