Data-driven decision-making is growing exponentially, and while technical skills are essential for a data scientist, it is equally important to have psychological skills as well. Data scientists are, of course, well-versed in all the technical aspects, but this isn’t what really makes a great data scientist. Industrial and Organizational (I-O) psychology applies human behavior understanding to organizations that can truly allow for ethical and effective changes. In this post, I share three reasons why data scientists should study I-O psychology.
#1 The goals of I-O psychologists align with the goals of data scientists
Data scientists have advanced, technical knowledge in statistics and coding, and they leverage Big Data through various machine-learning techniques. While data science is complex, the most simplified goal of data scientists is to use data to draw conclusions and make decisions pertaining to optimization or problem-solving in an industry or organization.
Industrial and organizational psychology are related fields of psychology focused on the study of human behavior in organizations and the workforce. One of the overarching goals of an I-O psychologist is to find solutions to problems for the sake of employees and organizations through the research of human behavior. This includes studying teamwork, leadership, motivation, performance, efficiency, and just about every aspect of a workplace that relates to human behavior.
There is a clear overlap between these two fields in that they are both working towards a goal of improving or solving organizational problems. Both fields have a large presence in consulting with organizations. Although the process of finding solutions is relatively different, data scientists can benefit greatly by applying the skills of I-O psychology to optimize actionable findings.
#2 I-O psychology helps you become a better data scientist (people aren’t just numbers)
I-O psychologists have extensive knowledge of topics pertaining to workplace behavior, worker performance, organizational development, and consumer behavior. While data scientists are known for their obvious technical skills, combining the skill sets from organizational psychology and data science can be extremely effective. For example, data scientists dealing with people analytics may work with data about employee performance, organizational outcomes, and Human Resources. Data scientists draw insights and conclusions based on data, but also need to know how to choose the next decision. Perhaps, the data indicate employee performance is low and is impacting sales of a company. Data-driven decisions are exactly that—driven by data. However, making impactful data-driven decisions for improvement require a psychological understanding of the people/organization.
#3 I-O psychologists make good team leaders and teammates
Workplace behavior and leadership are important areas of research within I-O psychology. For example, worker satisfaction and performance can be highly dependent on the leaders of the organization. Many theories and psychological models address the most effective ways of working on teams, dealing with conflict, adapting leadership styles, and considering all the pros and cons of different types. By acquiring these skills, data scientists can be more effective leaders and teammates, and in return, create long-lasting impacts in their field.
Columnist: Elizabeth Surratt