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Latest Developments in Workforce Analytics John P. Hausknecht, Ph.D. Associate Professor Human Resource Studies Cornell University
HR Analytics Systematic data collection and analysis designed to improve talent and business-related decisions
Recent HR applications
WORKFORCE PLANNING
• Inventory current talent/future needs
• Forecasting retirements
• Optimizing staffing
ATTRITION/RETENTION
• Predictive models • Network
approaches • Linkage to
operational & financial performance
RECRUITMENT/SELECTION
• Sourcing channels: cost & yield
• Assessing predictive value of pre-hire data
Evolution of HR Analytics
Metrics
Ratios and indexes Single indicators “Reporting” mindset
Analytics
Increasing rigor Linking data across sources and/or time “Predictive” mindset
Insights
Unanticipated truths Challenge conventional wisdom Novel interventions “Strategic” mindset
Where are companies today?
• Some companies split these activities • Reporting skill set ≠ analytics skill set
Heavy on reporting, but moving toward analytics
Systems enhance/constrain opportunities
Better organizational structures to support analytics
1
2
3
• Data access issues • Relevance and accuracy of data • Different versions of the “truth” • Attention to data governance issues
• Teams with analytics as core responsibility
• Diverse skill set needed; consulting, data analysis, HR, business
• Background not always HR (oftentimes not)
Where are companies heading?
1. Better systems/greater linkage ability
2. Building analytics teams 3. Data visualization 4. More sophisticated designs 5. Talent data as business data 6. Pilot testing and experimentation 7. “Big data” applications: social
media, unstructured data