Evaluating Analytics Professionals by Proxy or Directly?
By Greta Roberts, Mar 15, 2012
IIA Faculty Member Bill Franks, recently led an outstanding discussion titled, “What Makes a Great Analytic Professional”? Judging by the attendance and lively discussion, this was an important and timely discussion.
Analytics Professionals Struggle to Hire Just Like Non-Analytics Professionals
What struck me about this discussion is that analytics professionals (with the world of analytics solutions at their disposal) are having the same conversation non-analytics professionals have every day. The dilemma? How to reliably predict top performers when hiring.
It wasn’t lost on me that this traditionally difficult challenge, might provide an outstanding opportunity for the analytics community to teach businesses how to hire effectively – using an analytics approach.
Questions to answer:
- How to quantify the evaluation of analytics candidates?
- How to move beyond using proxy measures during the hiring process?
- How to create rigorous benchmarks that reliably predict top performers?
Evaluating by Proxy
Measures used today to spot the elusive ideal analytics professional span a range of “proxy metrics.” Some scan resumes for computer science, math or machine learning on resumes, others give puzzles to applicants. Some try to intuit whether a candidate is intensely curious. Others look for a storyteller - someone who can tell a good story using real data.
Bill Franks has had good success hiring outstanding analytics professionals. Among other traits his experience shows that outstanding analytics professionals are creative, suggesting that you “ask if they are artistic, or musical or have some kind of other creative experience in their background”.
It is possible, simple even, to come up with a benchmark of analytics professionals. Analytics professionals solve these kinds of problems all the time. It is this community’s strength and could be a time to shine as an industry, in a whole new category with the potential to affect bottom line business results and dramatically change the hiring industry.
Challenge to the Analytics Community
We suggest a challenge for the Analytics community can to solve together. What if we could use our own analytics methods to quantify the human characteristics that lead to success in our own field? This “benchmark” could lead to better hiring; reduced attrition and more focused professional development. Armed with a methodology, results, and the charts and graphs to prove it, we could lead the charge to introduce and implement similar analytical processes into the hiring processes of organizations at large.
About the author
Greta Roberts is an influential pioneer of the emerging field of predictive workforce analytics where she continues to help bridge the gap and generate dialogue between the predictive analytics and workforce communities. Since co-founding Talent Analytics in 2001, CEO Greta has successfully established the firm as the recognized employee predictions leader, both pre- and post-hire, on the strength of its powerful predictive analytics approach and innovative Advisor™ software platform designed to solve complex employee attrition and performance challenges. Greta has a penchant for identifying strategic opportunities to innovate and stay ahead of the curve as evident in the firm’s early direction to use predictive analytics to solve “line of business” challenges instead of “HR” challenges and model business outcomes instead of HR outcomes.In addition to being a contributing author to numerous predictive analytics books, she is regularly invited to comment in the media and speak at high end predictive analytics and business events around the world. Follow Greta on twitter @GretaRoberts.