Person of Interest meets Recruitment - Predictive Analytics for HR and Recruitment™

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Information about Person of Interest meets Recruitment - Predictive Analytics for HR and...
Business & Mgmt

Published on March 20, 2014

Author: Joberate



A presentation of a Predictive Analytics for HR and Recruitment™session at TalentNet Live Austin, March 7, 2014 by Michael Beygelman.

1   Person of Interest meets Recruitment Predictive Analytics for HR and Recruitment™ Austin, TX: March 7, 2014 Tweet questions and comments to: #WeFollowYou

Joberate leadership at TalentNet Interactive   2 Michael Beygelman CEO •  18 years Recruiting & HR leadership experience, public, private, startup, turnaround •  President of recruitment process outsourcing (RPO) business for Adecco Group •  Executive Director of HR Services and Technology Association (formerly HROA) •  COO of Careerbay, recruitment technology startup (merged with JWG, sold to TMP) Aki Kakko Co-founder, Head of Product •  Product innovator and serial entrepreneur, mission to disrupt recruitment and HR •  Invent, speak, blog and tweet recruitment, and HR technology evangelist •  Considered one of the leading gurus in social media

A one slide shameless plug about our company J   Our mission is to help society better understand job-seeking behaviors of the global workforce, one human being at a time •  Developed machine learning technology platform based on web services (connect via API) •  Helps companies gain actionable insights from the digital footprint of the global workforce - Save time and cut recruitment costs - Retain valuable employees - Predict future workforce needs 3

Big Data (in context of HR) is in the news   •  A lot of interest in leveraging Big Data •  Predictive Analytics are an evolution from traditional data analysis •  In context of HR and Recruitment, the possibilities are limitless 4

Areas in which Predictive Analytics can help HR   5 Only kidding

Areas in which Predictive Analytics can help HR   Most industry solutions focus on new applicants and existing employees •  Assessment: mindset, skillset, cultural fit •  Development of job descriptions -  Ideal personality in context of target job -  High potentials, leadership development •  Potential behaviors •  Team development and alignment •  Knowing who is likely to switch jobs, when 6

Context: Reporting vs. Predictive Analytics 7 Predictive Analytics •  Predictive models (i.e. credit score, life events) •  Probability of events and/or their timing Data Analysis •  Statistical analysis, and relational models •  Understanding cause and effect Dynamic Reporting •  Aggregate view of data sources •  Benchmarking or validation (Traditional) Reporting •  Measure results •  Efficiency, compliance •  What is happening now? •  Why did it happen? •  What happened? •  What can happen?

I think à à à à à   8 Social data has become a disruptor I know   Investment Flow A constantly evolving data stream that is “external” to HR systems, creates enormous opportunity (current state)                                                                                                                                                            (future state)

Companies need to track external people data   9 Age of corporate dominance Age of knowledge workers Attractpeopletofollowyou Startfollowinginterestingpeople Cultural shift has created demand for HR tools to help companies make this critical transition

A simplified example of an analytic   •  Based on internal historic data (e.g. known data) •  Often built on relational models •  Batch oriented nature (e.g. produces results at time of report) 10

A simplified example of a predictive analytic   11

12 What we’ve decided to focus on in the near term   Social data streams have (so far) left some basic problems unsolved by HR technology HR Business Function Existing Employees Recruiting Pain Point (Problem Statement) More than 70% of the workforce would entertain a conversation for a new job, leaving companies exposed to leavers and vacancies Other than skill and experience, companies have limited insights about which people should be contacted first, or even when Opportunity Know if people are active job seekers Know the ideal time to contact a person Benefits •  Early detection of employees at risk •  Identify possible mgmt. issues •  Real-time talent planning •  Gain competitive advantage •  Reduce cost, save time, gain focus •  Follow interesting people

13 Select metrics   The development of a hard dollar business case for Predictive Analytics Data points January February %Change (+/-) Profiles being tracked 5,269 6,799 +29% Jobseekers predicted as Active and Semi-active 857 1,082 +26% Conversion Jobseekers predicted Active and Semi-active who changed jobs 104/857 130/857 12% / 15% = +27% (YTD)

The softer side of things   Let’s imagine what is possible, and how Predictive Analytics might shift a paradigm •  What if there was a simpler/organized way for recruiting departments to follow interesting people, and be alerted to the ideal time to contact them? •  What if companies could automatically knew who to contact first for an open role based on that person’s job-seeking interest level? Is the applicant serious or just fishing? Etc. •  What if a company knew that their best employees were at risk of leaving? •  What if there was a way for people to send “signals” to targeted companies that they (he/she) might be interested in hearing about an opportunity but they don’t want anyone to know that they are looking? 14

In closing   •  If I stand here any longer, we will begin talking about morals, big brother, privacy, and a host of other topics that will kill the rest of the day L •  So, simply…thank you! •  Let’s have some Q&A not about the first bullet 15

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