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I/O Psychology + Data Science = Better Talent Management

Updated: May 24

Industrial/Organizational (I/O) Psychology combines Behavioral Statistics and Organizational Psychology to deliver reliable and validated world of work insights. Having partnered alongside many I/O Psychologists over the years, I have always been fascinated by the process of creating success metrics, such as well-defined competencies that align with a company's goals. Validation studies for selection purposes, from a thorough job analysis with key stakeholders to rigorous statistical data analysis, show the powerful role I/O Psychology plays within Talent Management.

Data Science pairs Computer Programming with mathematical techniques (Statistics, Calculus, and Linear Algebra). Many predictive analytics projects use modeling to gain insights into customers' behaviors so they can target company efforts and maximize profits. Python, R, and Power BI all support Data Science teams searching for better data driven deployment solutions.

Finding better ways to use data within Talent Management continues to evolve. If too focused on Computer Science you see patterns only in code. Too much focus on Statistics, and you may view problem-solving in a purely formulaic way. I believe a natural fusion between Data Science and I/O Psychology is needed to truly unlock human potential in the workplace.

Steve Jobs once said, "What a computer is to me, is it's the most remarkable tool we've ever come up with. It's the equivalent of a bicycle for our minds." Any technology platform or algorithm is simply a tool used to discover how to make the world around us that much better a place (assuming goodwill intentions).

All the elements for the next breakthrough within Talent Management exist today. How will I/O Psychology and Data Science naturally align in the future? How can the tools and techniques from each field of study come together in a more meaningful way for the average worker? These are the questions Data Driven Talent Inc. will continue to ask, explore, and share.

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