Predictive Analytics World Workforce San Francisco 2017

Description

Optimize your organization's greatest asset: its workforce. Every product built, service provided, goal achieved, sale made or error made — every single thing that happens at your company — happens because of an employee.

Until recently, predictive analytics approaches were used to drive enterprise performance by predicting customer, voter, debtor and other human behaviors. Today, predictive analytics can be similarly applied to drive performance and lifetime value of its workforce. Predictive workforce analytics can help answer questions such as; who will accelerate, who will terminate, who has the greatest lifetime value, and more.

Predictive Analytics World for Workforce (PAW Workforce) gathers workforce data scientists, employers, and vendors pioneering in the predictive analytics domain to solve these (and more) workforce optimization challenges. PAW Workforce 2017 will discuss case studies and brilliant workforce solutions in the following areas:

  • Predictive career paths for optimal succession planning
  • Predicting individual training success
  • Predicting flight risk pre- and post- hire to reduce employee attrition
  • Optimizing the workforce planning process using predictive analytics
  • Using a Learning Recommendation Engine to increase retail performance
  • Shifting the curve of sales performance with predictive analytics
  • Reducing employee attrition
  • The State of Predictive Analytics for Workforce Enterprise Applications
  • People Analytics: Using Wearables and Big Data to Reinvent Management
  • Should HR be bold with predictive analytics projects?
  • The "creepy side" of predictive workforce analytics
  • What workforce analytics can learn from the more analytically mature customer analytics domain
  • How predictive analytics can help to hire top workforce data scientists
  • Identifying top and bottom performers during the recruiting process
  • The importance of using survival analytics to calculate employee churn
  • Why role cost modeling is a key element of predictive workforce projects
  • Developing workforce analytics with incomplete and missing data
  • Busting predictive workforce analytics myths

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