November 27, 2016

This week in the workplace: Asia, algorithms and hiring emts

Talent science is going global. That’s exciting for us! All over the world, all kinds of organizations are rethinking hiring:

Is it possible to predict if your team’s best performer is going to leave you in six months? Or if that unassuming interview candidate is going to be your “rockstar” trader within the year? In a few companies in Asia, you can. Welcome to the world of people analytics.

Hacking hiring goes deep as well as broad. The Harvard Business Review is getting its machine learning on:

The question is not whether to use algorithms for hiring, but how to get the most out of them. That is, what sorts of decision rules should be used to select the candidate most likely to succeed?

Evidence-based hiring starts with understanding what competencies predict employee performance. Those predictors are unique to every organization:

To make the best, most qualified hires with good cultural fit, you have to take time to think about how you identify candidates. Yes, you can get a whole lot of people applying, but you need to make sure you’re building conversations and developing connections with people that would be beneficial to your organization, or you’re not being efficient.

…and now for hiring a little bit different

It’s easy to think of data-driven hiring as a quirk of tech and finance, but even Emergency Medical Services are getting in on the game:

The traditional public safety hiring approach solicits applicants, conducts testing, ranks applicants and selects top candidate for interviews. The focus on knowledge, skills and abilities doesn’t assess the applicant’s potential to fit within the organization. In addition, this traditional approach is slow, paper-based and creates lots of opportunity for bias.

After describing the growing influence of millennials in the workforce, Steward introduced a behavior-based approach using science and big data to find applicants. The approach starts with an internal assessment of top performers and the internally gathered data on behaviors is used to predict success. In the hiring process, candidates are compared to the behaviors of the success profile from existing personnel.