The Division of Human Resources teamed up with Fox to harness the power of data analytics through a collaborative project utilizing a team of graduate students who analyzed data on HR sector trends and practices at Rensselaer over a 10-year period (2004-2014).
The Rensselaer Division of Human Resources is using data analytics to discover relationships among workforce data, uncover options for streamlining business transactions, and understand whether complex interdependencies are aligned with the strategies of the university.
“Harnessing the Power of Big Data for Sound HR Decision-Making,” written by Curtis Powell, vice president for human resources, along with Peter Fox, Tetherless World Research Constellation Professor, was the cover story in the College and University Professional Association for Human Resources (CUPA-HR) Higher Education Workplace Winter 2016-17 edition.
“Today’s workforce is incredibly diverse, so HR leaders need very specific information to support their decision-making. This is why big data analytics are not just an opportunity—they are an imperative for human resources today,” Powell wrote in the article.
The purpose of the project was to use big data from a 10-year period to determine myriad factors that could lead to both validation of current HR programs, initiatives, identification of new programs, revisions of HR policies, and precision in identification of key factors that support the recruitment and retention of top talent and leadership at the Institute.”—Curtis Powell
The Division of Human Resources teamed up with Fox to harness the power of data analytics through a collaborative project utilizing a team of graduate students who analyzed data on HR sector trends and practices at Rensselaer over a 10-year period (2004-2014). The effort focused on three major areas: compensation and benefits, training and job performance, and paid time-off and insurance claims. The process involved:
- data identification, collection, assembly, and cleaning
- pattern recognition and relationship analysis of the multidimensional data
- analytic model development and statement of findings
- validation of models and practices in the data collection and assembly, and
- suggested actions and process improvements going forward
“The collection and analysis of the data resulted in more than 125 discoveries, nearly 50 of which were deemed to be significantly impactful and a few that were considered startling,” Powell said. “The purpose of the project was to use big data from a 10-year period to determine myriad factors that could lead to both validation of current HR programs and initiatives, identification of new programs, revisions of HR policies, and precision in identification of key factors that support the recruitment and retention of top talent and leadership at the Institute.”
According to a Visier white paper titled “From HR Metrics to Workforce Analytics: Five Key Workforce Insights That Every Employer Should Capture for Greater Business Impact,” the most commonly measured workforce metrics are of very little help to HR professionals and business leaders in achieving real insight into maximizing their human capital investment. Says the author of the paper, “In order to make better business decisions about their workforce, leaders should see the connections in their workforce data and examine comprehensive workforce topics.”
“By doing just this,” Powell wrote in the Higher Education Workplace article, “Rensselaer human resources has paved the way for people analytics to become part of its routine practice. By mining multi-dimensional data, the HR function is now more proactive, predictive, and decision-making oriented.”
CUPA-HR includes more than 20,000 human resources professionals and other campus leaders at over 1,900 member organizations.
