Most recruiters are forced to work with incomplete sets of talent data from multiple, disjointed programs. This is a painful time waster that way too many of us are struggling with, when none of us really need to. This post give you four ways to solve that problem for good!
1. Enrich It Using Other Data Sets
Whether you're using internal or external data sets, looking at multiple vectors of data will help you fill in the gaps. Many channels such as LMS, ATS, resumes, online job boards and open source http://www.swooptalent.com/product-solutioninternet sites have solid data you can use to tell the comprehensive story behind the talent you're targeting. And if you're using Talent Data as a Service, that can be completely automated, so you don't even need to have data entry people to keep it enriched and up to date.
2. Interpret and Deduce using Machine Learning
Got messy job titles? Missing skills information currently stored in unstructured text? A hodge podge of school and major names that don't match? These are just a few of the examples where talent data can be cleaned up and completed using machine learning.
3. Connect Your Disconnected Systems
When you integrate the various systems you already have, you can see all the data available to you, and the gaps you think exist may not be as pronounced as you believe. You'll need the right subject matter expertise in talent data management to accomplish this- or you'll need a platform that manages these connections automatically.
4. Have Technology Automate All of The Above
SwoopTalent's technology will store all your data in a private cloud. You'll have all your data centralized in one spot, using AI and machine learning technology to help interpret complex data sets.
SwoopTalent's talent data lake lets you maximize the impact of HR Tech by making it easier to do every single thing you need to do with data. If you're interested in taking your talent data management to the next level, contact us today!
Photo by Suad Kamardeen on Unsplash
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