Eliminating the "noise" in hiring decisions.

Those who have read the Third Edition of our book “Lab Dynamics” (2018) know that one of the chapters new to that edition is Chapter 4, “Bring them on! Interviewing, Selecting and Hiring Scientists.” That Chapter, based on a wealth of social science research, presents a data-driven approach to hiring that goes a long way towards minimizing the impact of our conscious and unconscious biases in the hiring process, enabling us to make more informed hiring decisions.

So, we were thrilled to read the newly published book “Noise: A Flaw in Human Judgement” (2021) by Kahneman, Siboney and Sunstein, which is a masterpiece of social science exposition. The book, as its title suggests, is about all the ways our decision-making processes are subverted by extraneous input and faulty analysis – in short, noise of various types. We were drawn to Chapter 24, “Structure in Hiring,” which summarizes Kahneman et al’s recommendations for making better and more informed hiring decisions and were especially gratified to see that every recommendation in that Chapter is either identical to or consistent with all of the recommendations we make in “Lab Dynamics.” In short, hire based on data, not on “fit” or gut instinct, create selection criteria and apply them in the same way to every candidate, use “structured” interviews not “free-form” interviews and ask every candidate the same questions, and finally, have independent interviewers make independent decisions or recommendations. It’s no surprise that our recommendations are the same, since they are based on the same body of social psychology research.

So, to past readers of “Lab Dynamics” and those who have taken our workshop “Hiring and retaining your science team” you’re way ahead of the game, having had these guidelines since 2018. For new readers and workshop participants you can feel reassured that you’re learning the most up to date and validated approach to hiring, one of the most important contributors to the success of your team.

Carl M. Cohen

President, Science Management Associates