Photograph: Joel Maisonet
Q: How are you using predictive analytics in your position as workforce analytics manager?
A: In January 2016, Allianz Life brought me into the human resources (HR) group to start building our analytics capability. Prior to then, we were focused on reporting and data gathering with limited use of analytics to drive business decisions from a people perspective. In our first year, we have not only begun building the infrastructure necessary for an analytics capability, but we have been involved in a few analytics projects already. There is a significant leap from descriptive to predictive analytics, but we have started to make that leap. One specific example is identifying indicators of individual success (both performance and retention) in one key area of the company, and then translating those indicators to enhance the candidate profile used during the recruiting and hiring process.
Q: What kinds of problems are you solving using data analytics? How is this different from the issues you would address in the role of a more traditional actuary?
A: In addition to enhancing candidate profiles, we are using analytics for projects related to diversity (gender and ethnicity), performance ratings, turnover and organizational expertise. You will get different answers when you refer to “traditional actuarial” roles, since solving problems can be very different in product development, product management, valuation, reporting, profitability management and other areas considered to be traditional.
While blanket statements are difficult, in general, when we consider actuarial problems, there tends to be more of an emphasis on the “right” answer—or at least a “right” answer given an agreed-upon set of assumptions. When dealing with workforce analytics, it can often get a bit messier, as there can be far more factors, several of which are based on nonrational behavioral (unconscious bias, for example).
With that said, however, there are techniques that are consistent. Consider projecting future lapse rates on an annuity for the purposes of an economic valuation: You would make some assumption as to the relationship between lapse rates and the broader economic trends (such as interest rates). In the same way, when predicting future turnover, you would build in a relationship between turnover and the broader economic trends (such as unemployment).
Q: What professions did you consider before you decided to become an actuary?
A: Upon entering college, I only knew I wanted to do something in math or statistics, with the default to potentially teach high school. Frankly, I had never heard of actuarial science until my adviser made me aware my freshman year.
Q: What about your job brings you the most satisfaction?
A: I have much more exposure to the broader organization, which helps me understand how the overall vision and strategies are pursued at an organizational level. Further, being new to HR, I am gaining a much better understanding of people strategy and what happens behind the curtain. After nearly 25 years on the business side, I did not have an appreciation for what it takes to run an effective HR function. I have also enjoyed more team camaraderie and chemistry being a part of the HR function. While I am still an analytic and enjoy my individual spreadsheet time, I also enjoy being part of a group that values the interpersonal relationship side of our lives.
Q: What skills positioned you for work in predictive analytics?
A: I have a degree in math and have spent the majority of my professional career as an actuary. I also have been heavily involved in capital market hedging on two occasions: once building a program from scratch and more recently leading the variable annuity daily production efforts for a hedge program here at Allianz Life. Not only have these experiences built the technical skills used in predictive analytics, but I have been surrounded by brilliant people and have absorbed so much in how they approach thinking about problems and digging for answers.
The analytical skills are often where people focus when considering who would make effective analysts in this area. However, while you need a full dose of analytics, it is very easy to overlook the importance of the softer skills—the ability to cast a clear and compelling vision, develop and communicate effective strategies, collaborate and build trust, manage the processes, understand the big picture of both the problem and results, and clearly communicate the findings at the right level to the right audience. My background with several entrepreneurial endeavors (both inside and outside of the corporate world) has been huge in positioning me for success in this field.
Q: What is the most successful and efficient way to see a project to completion?
A: Vision, vision, vision. If you know me at all, my answer to just about every question involves some mention of vision. I have become less engaged with plans that fully detail every step that will lead to the end of a project; that can be time consuming, frustrating and often leads to missing some key insights. I would much rather take the time to understand the clear vision and keep asking the question, “What are the next steps to stay aligned to that vision?” This is a good way to mess with the minds of analytics, but my experience has found this to be a much more effective approach to managing a project.
Q: How did you learn the tools and techniques of modeling? What sparked your interest in this area?
A: Throughout my years in actuarial and hedging, I was exposed to several different models. I have always appreciated the power of technology to process vast amounts of data, analyze impacts over time and return results that can powerfully drive business decisions.
Q: What skills do you think actuaries bring to analytics that other professionals may not bring to the role?
A: Beyond the pure analytical, statistical and technical experience, most actuaries generally have a future perspective, thinking in terms of “what could happen” rather than “what happened.” While both perspectives are important, the world of predictive analytics requires a perspective that is always looking to the future.
Q: What has been the most exciting project you have worked on during your career and why?
A: Wow, that’s a loaded question! I have been extremely lucky to be on a number of great projects. One of my favorites was developing a retirement income optimizer that resulted in me being a co-holder of a patent. This project leveraged all of my experiences and skills, including analytics, psychology, collaboration, leadership, product, legal, systems, communication and so on. There was a wonderful group of people involved who worked extremely well together to develop this industry-leading approach that is still in action today.
Q: How do you see the role of predictive analytics in the next five to 10 years? Where will actuaries fit into the equation?
A: Predictive analytics is here to stay, although it will undoubtedly morph over the years. Specifically within HR, where I am working, I expect this to become a core competency as C-level executives continue to see the return on investment (ROI) impact from predictive analytics. This is a phenomenal opportunity for actuaries who tend to be interested in the nontraditional route with skills in communication, vision and collaboration. I would expect actuaries who move into leadership roles within HR analytics to become strong influencers not only in HR, but also throughout the organization.
The one difficulty will be in helping HR leadership, and potentially other leaders, get comfortable with the skill sets these actuaries have and the market pay that typically accompanies them. The actuaries making this transition will somehow need to figure out how to communicate their value.
Q: What advice do you have for people who may be interested in positions in predictive analytics?
A: I can only speak from the HR/workforce analytics perspective. This is a pretty huge career change to move directly from one to the other. I would strongly recommend getting involved in a project that is happening now. In most cases, there may not be an active analytics group or an obvious project to get involved with. I would recommend that the interested actuary set up time to chat with the existing analytics team or HR leadership to talk about his or her interest and the potential value he or she could add. I would go so far as to think about an area where deeper analysis could have a huge value and volunteer to provide some analysis. Through that process, the actuary would get a feel for the work and also start understanding how the culture and collaboration may differ from what he or she has experienced. It would be a good initial test of fit.
Q: What is the most challenging aspect of your work?
A: I would be surprised if any analytics person wouldn’t say, “data.” We are doing a ton of work to consolidate and improve the quality of our data so we can increase the impact of our reporting and analytics output. In many companies, HR data has been viewed as a necessary part of the process without the rigor of understanding the potential impact of incorrect or inconsistent data—and without the perspective that good, complete data has the potential to be an extremely valuable asset. So we are working through these issues now as we work to build out a warehouse that will give us immediate, consolidated data from sources that include HR systems, other internal systems and external feeds.
Q: Can you tell our readership something they may not know about predictive analytics, such as possible opportunities for actuaries in this arena?
A: I expect predictive analytics to embed itself in all major technical, social and societal issues—everything from car insurance to security to nonprofit work. So the question may not be how to get into analytics, but how to incorporate analytics into whatever you decide to do. Being aware of what is happening will position you well to increase the value you add to your organization.
Q: What are some of your best professional memories/experiences as an actuary?
A: I generally have taken a more nontraditional route, which has resulted in a number of cool opportunities. I tend to be a career risk-taker, moving into roles that I find interesting and think will be a great fit. I have had a chance to be involved in capital market hedging, asset liability management, building a retirement strategy, profitability management and product development. The credibility you get from being an actuary (deserved or not) has definitely opened up many other doors for me. I have been pursued to be on project teams, nonprofit boards of directors, speaking opportunities and several other cool opportunities, both personally and professionally. Becoming an actuary can be difficult—especially when you go through exams with newborn twins and three kids under age 5 like I did—but being an actuary has been a wonderful experience that has opened numerous doors for me.
Q: How do you measure success?
A: As I mentioned earlier, I am a “vision guy”—success is lined up with how well you are achieving your vision. In my career, I would measure my success as my contribution to helping my organization, department or team accomplish its vision. If I am measuring my success more broadly, I need to consider my personal vision, which is “to have transformational impact.” As I consider my career and life outside of my career, I measure my success by how much of an impact I am having in transforming things in a positive way. While money, recognition and power are nice, they have nothing to do with my measure of success. What I measure is how many of the world’s poor have access to clean water because of my involvement. Are people’s lives better for having a relationship with me? Have I been able to bring unity into an otherwise divisive situation? Has my employment done more than just fill a seat? Has the company realized the full value of its investment because processes or perspectives have improved?