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Make Data Work
Dec 4–5, 2017: Training
Dec 5–7, 2017: Tutorials & Conference
Singapore

Talent Flow Behaviour Analytics: A Data Driven Approach to Human Capital Management

Philips PRASETYO (Living Analytics Research Centre, Singapore Management University), Ee-Peng Lim (Singapore Management University)
2:35pm3:15pm Wednesday, December 6, 2017
Data science and advanced analytics, Machine Learning
Location: 323 Level: Non-technical
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

Data scientists

Prerequisite knowledge

None

What you'll learn

Talent flow analytics

Description

Analyzing talent flow behavior is important for the understanding of job preference and career progression of working individuals. When analyzed at the workforce population level, talent flow analytics helps to gain insights of talent flow and organization competition. Traditionally, surveys are conducted on job seekers and employers to study job behavior. While surveys are good at getting direct user input to specially designed questions, they are often not scalable and timely enough to cope with fast-changing job landscape. In this paper, we present a data science approach to analyze job hops performed by
about a population of working professionals. We develop several metrics to measure how much work experience is needed to take up a job and how recent/established the job is, and then examine how these metrics correlate with the propensity of hopping. We also study how
talent flow behavior is related to job promotion/demotion. Finally,we perform network analyses at the job and organization levels in order to derive insights on talent flow as well as job and organizational competitiveness.

Philips PRASETYO

Living Analytics Research Centre, Singapore Management University

Philips is the principal engineer in Living Analytics Research Centre of Singapore Management University. His research interests include social media mining, job analytics, and machine learning.

Photo of Ee-Peng Lim

Ee-Peng Lim

Singapore Management University

Dr Lim Ee Peng is a professor at the Singapore Management University (SMU). His research interests include social media analytics, information integration, and information retrieval. At SMU, he is also the Director of the Living Analytics Research Centre, an NRF supported research centre focusing on data analytics research for smart nation application domains.

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