Latest Developments in Workforce Analytics    John P. Hausknecht, Ph.D. Associate Professor Human Resource Studies Cornell University    

Rising interest in “analytics”

People analytics

HR analytics

Workforce analytics

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

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2

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•  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

Questions?