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Workforce Analytics Is Making a Cameo at PAW Business in Las Vegas
Never fear, workforce analytics is here. While PAW Workforce isn't running at the 2018 Mega-PAW event in Las Vegas, we've put together a dedicated track covering Workforce analytics (retaining & optimizing HR with analytics) at Predictive Analytics World for Business in Las Vegas, June 3-7, 2018.
In addition to the sessions in this Workforce track, many other sessions at PAW Business are generally-applicable – so they benefit your work in HR analytics and beyond. These sessions include keynotes from the industry's hottest headliners, as well as breakout sessions on the most advanced cutting-edge methods. Check out the complete PAW Business agenda here.
Predictive Analytics is changing the face of HR and changing it fast. Check out how much is here for you:
Session on workforce optimization and retention:
What Millennial Employees Actually Value: Lessons from Predictive Modeling
What systematic differences REALLY exist between what millennials actually value in employment as compared to older employees?
Haig Nalbantian, Senior Partner, Co-leader Mercer Workforce Sciences Institute, Mercer
Tauseef Rahman, Principal, Workforce Strategy & Analytics, Mercer
Session on workforce analytics:
Case Study: Twitter, Using Statistical Modeling to Predict Workforce Attrition
Advances in statistical modeling have allowed us to predict and understand in depth and breadth why employees leave companies.
Menghan Chen, People Data Scientist, Twitter
Session on workforce optimization:
Case Study: Atlassian, News Feeds, Notifications, Recommendations: Is Collaborative Software Actually Promoting or Hurting Employee Productivity?
Learn the intriguing correlations between the usage patterns observed in workforce collaboration tools, and the productivity of the user.
Jennifer Prendki, Head of Data Science, Atlassian
Session on workforce optimization; sales analytics:
Case Study: Shell International Optimizing for Sales by Predictively Modeling Salesforce Effectiveness
Statistical modelling techniques (e.g. general linear modelling, logistic regression analysis, multi-level modelling) were applied to understand the effects of, for example, Personality, Career Types, and Team Leadership on Sales Performance.
Tashi Erdmann, HR Analytics Manager, Shell International
Linda van Leeuwen, HR Analytics Analyst, Shell International
Session on workforce optimization:
Case Study: Centric Consulting, Improving Employee Utilization with Machine Learning
Too many employees were not on billable projects so we designed and implemented a machine learning model to help us better understand even though we had only a few hundred rows of data with which to work.
Carmen Fontana, Talent Acquisition Lead, Centric Consulting
Session on workforce optimization:
Case Study: Baptist Health Medical Group, Improving Employee Engagement on a Shoestring Budget
1) Asking the right questions
2) Identifying engagement drivers
3) Communicating insights to leadership
4) Creating team-generated action plans.
Rebecca Guess, Baptist Health Medical Group
Matt Hayes, Director, Practice Optimization, Baptist Health Medical Group
Session on legality and ethics in operationalization:
Equal Employment Opportunity and the Use of Predictive Analytics Tools
An overview of foundational laws, theories of discrimination, and approaches for measuring adverse impact and validity in the use of predictive analytics for employment purposes.
Eric Dunleavy, Director of the Personnel Selection and Litigation Support Services Group, DCI Consulting Group
Kelly Trindel, Chief Analyst, Equal Employment Opportunity Commission
What makes Predictive Analytics World the most interesting conference in the world is people like YOU.
Each person you meet along your professional path is another opportunity. You will meet people who will help you, people who can show you how, and people who can help you succeed.
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