A leading US healthcare staffing company received job orders from many vendor management systems (VMS), each in its own format. Turning those orders into clean, usable jobs for recruiters took 12 to 14 hours, while open positions were filling faster than ever. Blackstraw built an intelligent job order extraction platform that pulls orders from every VMS, normalizes and enriches them with NLP and machine learning, and delivers them to recruiters almost in real time. Order intake time fell from 12–14 hours to under 10 minutes, and manual data cleanup was no longer needed.
Healthcare job orders follow no industry standard. Every VMS presents key details such as discipline, specialty, shift type and shift time in its own way, so each source had to be handled differently. Orders arrived slowly, and the client’s team had to clean them by hand before recruiters could act on them. In a market where candidates shop across agencies, every hour of delay meant losing positions to faster competitors. The client needed a way to capture orders from every source, standardize them automatically and get them to recruiters while the jobs were still open.
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