Workforce Analytics Is a Business Issue
Recently, I had the opportunity to get answers to a number of burning questions that I have been collecting on the topic of predictive workforce analytics. I spoke with Greta Roberts, co-founder and CEO of Talent Analytics, Corp. In this first of a series of blog posts, read what Greta had to say when I asked her: Who should care about predictive workforce analytics and what problems can predictive workforce analytics help solve?
Greta will be a keynote speaker at The Predictive Analytics World for Workforce conference, which is being held in San Francisco from April 3rd through 6th in 2016. The conference is the premier workforce analytics event for HR professionals, business leaders, line of business managers, and analytics practitioners. This global, cross-industry event covers predictive solutions to today's greatest workforce challenges. Join Greta Roberts and APQC when you register today with 15% off code APQC15.
Elissa Tucker: Who should care about predictive workforce analytics and why? Is this just an HR issue? Why or why not?
Greta Roberts: Predictive workforce analytics is by no means an HR issue. It’s an entire business issue. Businesses make a big mistake when they make HR the single focus of applying predictive analytics to workforce issues. We like the term workforce issues, not HR issues. Every single line of business that has employees working in it needs to think about how to use predictive analytics tools and advancements to optimize the selection and output of their workforce. Employees really don’t work for HR. Except for the small subset of people that actually do work in HR, the rest of the people work for the line of business that they were hired into. So predictive workforce analytics is definitely not just an HR issue.
Elissa Tucker: What business problems does predictive workforce analytics help organizations solve today? Could you provide examples of the range of different business problems that the sessions at the Predictive Analytics World for Workforce conference will cover and add any others you think are important?
Greta Roberts: When we talk to customers or businesses that are thinking about predictive analytics, they often say: “I really want to learn how people are using predictive analytics in the workforce space.” What I love about the conference, Predictive Analytics World for Workforce, is the wide variety of amazing companies—brands that you would recognize—that are very innovative and showing off their work in a wide variety of use cases.
One thing for people to watch for at Predictive Analytics World for Workforce is which categories of prediction these use cases fit into. I think it is helpful to think about predictions in two different categories. One category is predictions about trends. An example would be a company predicting that 20 percent of their skilled welders are going to retire in the next four years. That’s predicting a trend. It’s still about the workforce, but it’s predicting a trend. The other category is predictions about an individual. An example would be predicting that an individual has a high probability of being a top sales performer. As people look within their own companies, it is helpful to think about the different applications of predictive analytics in light of these two categories.
Some of those specific use cases that will be at Predictive Analytics World for Workforce include:
- Predicting high performer compensation
- Predicting how communication among employees impacts happiness, individual performance, and organizational success
- Building a career advisor tool based on predictive analytics
- Using predictive analytics to reduce unemployment insurance costs
- Shifting the curve of sales performance with predictive analytics
- Matching retail store labor with customer traffic using predictive analytics
- Balancing privacy with powerful employee flight risk predictions
- Using predictive analytics to reduce hourly workforce costs
That’s the last one I’ll mention. I think there is a total of 25 different presentations at the conference so this is just a sample. But, I think you can see that almost all of these use cases would apply to most organizations. Most organizations care about these kinds of issues.
Learn More About Predictive Workforce Analytics
Check out APQC’s research into the business problems that predictive workforce analytics helped Cargill, Gap, IBM, Johnson Controls, and SAS solve by reading the following APQC content items.
- 5 Predictive Workforce Analytics Pioneers (Infographic)
- Getting Started with Predictive Workforce Analytics: Research Report