Highlights from our webinar with Michael Housman and Andrew Knight.
On Tuesday, Michael Housman, workforce scientist and chief analytics officer at Cornerstone OnDemand, and Andrew Knight, PhD, assistant professor of organizational behavior at Washington University in St. Louis, presented “Applying Predictive Analytics to Decisions About Your Workplace.”
“We all hear a lot about big data and analytics, but at the end of the day, there aren’t a lot [of people] who actually know how to use it. Just calling a project ‘big data’ isn’t really a big data iniative,” said Housman. “We want to really dive in and understand what is big data and how can it help your organization.”
What is big data?
Housman defines big data with the “3 V’s”:
- Volume – Today’s datasets are huge (petabytes or larger). “When we think specifically about HR, volume represents the amount of data being produced at regular intervals,” said Housman. “Increasingly, the case is that data has to be housed on large servers.”
- Variety – Right now, organizations are contending with many types of data from many locations. “Previously, we saw big data emerge primarily from HRMS, or maybe performance management systems,” said Housman. “Nowadays, the data is coming from everywhere. These datastreams are emerging from a variety of different sources, so now there exist the tools to integrate them into a single big data framework.” Many types of data from many locations
- Velocity – It used to be that “these databases weren’t updated on a very regular interval,” said Housman. “Now, we’re seeing data that’s emerging by the day, hour, minute, second.” He used Twitter as an example: “These databases are growing exponentially and in real time,” he said. “That presents a real challenge but also an opportunity to integrate that data, analyze it, and try to make sense out of the noise.”
“We’ve seen big data hit a number of different industries,” said Housman. “Everyone’s familiar with the Moneyball example, in the way that the Oakland A’s were pioneers within Major League Baseball in terms of using data and analytics to make better decisions around their talent. Likewise, financial services has, for a number of decades, been using big data algorithms in order to make better decisions around how to issue credit.”
“We’re only recently now starting to see this same trend within workforce and HR issues,” said Housman. “Previously, whether a single recruiter or another interviewed someone had a huge difference on whether that individual was offered a job. We’re now hoping to make those decisions much more consistent, so that big data and analytics can inform decision-making throughout the employee lifecycle.”
What can predictive analytics do for you?
Housman polled our audience to find out if they currently have or are planning a big data initiative for their workforce in 2015. Forty-five percent indicated that they do; 55 percent indicated that they don’t. Housman said that this mirrors what they typically see. They’re seeing an upsurge in interest, but it’s still relatively early. “Organizations are still exploring this,” he said.
How is big data being used to drive HR decisions?
Big data allows “a shift from reactive to proactive decision-making,” said Housman. “Where we think the industry is headed is taking a more proactive stance, asking questions like, Who are the hires that I can bring on board that will deliver the best customer experience?, or, How can I drive up customer satisfaction by optimizing and incentivizing front line managers?”
Surprising workplace insights from big data analytics
In Housman’s work at Cornerstone OnDemand, some of the findings they’ve found that are directly related to workplace design issues include:
- 54 percent of variance in employee tenure is due to workplace relationships. “Toxic employees and the individuals on your team have a huge impact on attrition and performance,” said Housman.
- 16 percent is attributable to macroeconomic trends. “The good news is that the economy is improving,” said Housman. “But the bad news is that not only do we see attrition rise when the economy is improving because people are finding better opportunities, but we’ve actually found that the quality of worker looking for a job is slightly lower.”
- 11 percent is attributable to job characteristics, like work-at-home policies. “On the one hand, work-at-home employees stay on the job 28 percent longer than individuals who have to come into the office,” said Housman. “On the other hand, we looked specifically at productivity, and found that those individual who work from home actually have lower productivity than those who come into the office.” Further, Housman said those productivity levels mirror eachother for the first 90-100 days, at which point, productivity continues to improve for in-office employees, but drops off for the work-at-homers.
“These are the types of issues that really can affect the bottom line in a real way,” said Housman.
Thanks to everyone who joined us for the presentation! Tickets and details on our next webinar, “Bring Work to Life: Creating Fulfillment through the Workplace”, are available here.