Wise Practitioner – Workforce Predictive Analytics Interview Series: Carl Schleyer of 3D Results
By: Greta Roberts, Conference Chair, Predictive Analytics World for Workforce 2015
In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Using Predictive Analytics to Create a Leadership Index, we interviewed Carl Schleyer, People Strategist & Senior Principal Consultant Workforce Analytics and Planning at 3D Results. View the Q-and-A below to see how Carl has incorporated predictive analytics into the workforce of 3D Results. Also, glimpse what’s in store for the new PAW Workforce conference.
Q: In your work with predictive analytics, what specific areas of the workforce are you focused on, (i.e., optimizing workforce productivity, using big data to solve workforce challenges, building a workforce analytics driven culture, etc.)?
A: My personal focus on value creation and enhancing the internal brand of HR have led to analytic work interventions across the entire employee lifecycle as well as helping Operations with scheduling and productivity optimization.
Q: Do you primarily work inside of HR – or inside of the Line of Business? If Line of Business – which one(s):
A: While I grew up in Line/Operations at a national retailer, my last 8-10 years have focused exclusively in HR Analytics.
Q: What workforce outcomes do your models predict?
A: Some of my favorite predictive interventions involve:
1) Staffing algorithms that proactively determine where vacancies should be posted
2) Performance reviews simplified with metrics and goals that inspire profitable employee behaviors and
3) Identification of where Leadership Risk exists within organizations (more on that later).
Q: What is one specific way in which predictive analytics actively drives decisions?
A: Candidate preferencing. Like it or not, our lives are becoming increasingly dependent on algorithms. Many employers are using them to mine through the big data their Applicant Tracking Systems produce in order to prioritize applicants and recruiter workload. If you can get a referral from an employee at your targeted company, you’ll likely more than double your chances of an interview and offer.
Q: Can you describe a successful result, such as the predictive lift of one of your models or the ROI of a predictive analytics initiative?
A: I worked on an enterprise sales force effectiveness program that designed, tested, communicated, piloted, executed, and validated a data driven approach to helping field managers coach consultative sales associates. This approach leveraged targeted metrics that were tied to profitable employee behavior, and then incentivized through a new variable compensation plan. Our first department was so successful we couldn’t convince the business to stay in pilot phase longer and after 3 months they deployed nationally. From there we took our model to other departments and 12 months after the multi-department implementation we had generated an 8.3% improvement in productivity and an incremental $100 Million in margins. Those were fun times and I was blessed to be surrounded by talented team members.
Q: What is an example of surprising discoveries you have unearthed in your data?
A: This is the hardest part of our work as there are often many layers to a problem and it can be difficult to know when to stop. Outliers in the data often point to process or systems problems and can be interesting but time consuming to chase. But it’s the spicy myth busting discoveries that immediately come to mind… Once we proved that internally placed managers run more profitable stores in their first 12 months. This finding reversed an alarming external placement trend that was nearing 50% AND changed the business focused towards developing internal bench strength. Another politically charged discovery was around the cost of a FT employee. Benefit costs are often managed by reducing the ratio of FT employees, but we proved that the performance differential on key financial metrics of FT versus PT employees fully offset the cost of benefits. As a result we added FT jobs to the following year’s staffing plan instead of cutting them.
Q: What area of the workforce do you think has seen (or will see) the greatest advances or ROI from the use of predictive analytics?
A: Culture. The intentional use of culture to drive business results is not done enough. Many feel culture of an organization develops naturally and cannot be changed. However, culture is driven by specific leader and employee behaviors. Today’s technology connects leaders with information on an unprecedented scale. Enterprise-wide data warehouses and big data analytics provide the ability to inform decisions and validate actions like never before. With this information, empowered leaders can manage performance in deeper and more meaningful ways, inspire employee behaviors and achieve desired results. The data outcomes of those actions could then be identified, quantified and used as predictive measures that help an organization develop or maintain its desired culture. That means we should be able to build models to assess the impact of organizational or leadership changes on culture, engagement, and ultimately the bottom line. Cultural Models would likely have executives rethinking many enterprise decisions.
Q: Why do you think Business Leaders, HR Leaders and Analytics professionals should attend Predictive Analytics World for Workforce?
A: This is still an emerging space. Traditional educational degrees do not adequately prepare practitioners to do the work. I believe that all of us are smarter than any one of us and quality conferences like PAW are the best way for us to upskill ourselves and create future standards.
Q: Do you feel any urgency you want to pass along to your fellow HR and Business Executives to implement predictive analytics to help solve employee challenges? Why?
A: From a business perspective there are only two options- evolve or die. And that extinction just might happen to the Human Resource function. If we, as HR Analytic professionals, don’t learn how to adequately solve organizational problems, someone else from Finance, Strategy or Operations will.
Q: What is one misunderstanding people have about using predictive analytics to solve employee challenges?
A: We DV 8. That was my license plate for a while. We deviate was meant to express that humans are complex and frequently change their minds. They are engaged one morning, but looking at a job posting e-mail that same afternoon. What drives and motivates someone one month/year isn’t of interest the next. The needs of the workforce are so segmented and dynamic it’s difficult to get the degrees of precision that mathematicians, chemists, or engineers expect.
Q: How involved has the business unit been in the work you’ve done inside of your organization?
A: I have a somewhat controversial answer to this question. Our work should be focused on improving the lives of our employees, the brand of our HR function and the profitability of our organizations. This means the business unit has to be a strong partner in our work and should be actively involved with the analysis, design, testing, and deployment of our interventions. In fact, my personal formula for success includes more involvement with the business than with my HR partners. Just don’t tell that to the CHRO who lobbied hard to fund and grow the Workforce Analytics team. As long as you are finding meaningful problems to solve and collaborating- you are on the right path. The more strategic the question, the more likely we need access to information that extends beyond HR’s reach. That means the internal owners of customer, financial, or operational data should be aware and involved in what you are doing.
Q: SNEAK PREVIEW: Please tell us a take-away that you will provide during your Presentation at Predictive Analytics World for Workforce.
A: After Recruiting, my first break into the HR Generalist space was a role in Ethics. I later had the opportunity to manage a centralized employee relations team. It was both fascinating and scary to see what happened when the communication and collaboration between the employee and the supervisor broke down. The process of watching over thousands of cases and seeing the negative energy and outcomes planted a question deep in my mind. What if… What if I could detect the places where poor leadership exists? What if I could intervene before the smoke turned to fire? What if I could scan for management risks real-time? What if I could identify and proactively resolve workforce conflict before it escalated? What if I could prevent expensive employee relations scenarios from occurring?
After many focus groups, round tables, and quantitative attempts, a process I call The Digital Fingerprints of Leadership TM emerged. At the conference I’ll present a new perspective on quantifying Leadership. It’s a method of reimagining employee engagement, but without surveys. Through the usage of readily available surrogate metrics you can target areas where communication, respect, and trust are breaking down. Once identified, HR resources can be deployed, action plans can be created, and progress can be measured.
Imagine being able to augment the once-a-year organization engagement survey? Many forward thinking companies have already realized that this snapshot in time approach to measuring the passion of their workforce is outdated and doesn’t suit their needs. The concept of leveraging existing real-time data opens the door for significant improvements to dynamically measuring action plans, retention efforts and overall business performance.
Don't miss Carl Schleyer’s conference presentation, Using Predictive Analytics to Create a Leadership Index, at PAW Workforce, on Tuesday, March 31, 2015, from 4:55-5:40 pm. Click here to register for attendance.