Data science is a piping hot topic currently. One of THE most trending buzzwords in the technical domain, data science, transforming everything it touches, helping discover insightful knowledge and sowing the seeds of intelligent automation across industries.
By design, data science involves the principles, processes and techniques used to unearth underlying information through statistical analysis of a given data set. However, the versatility of data science makes it possible to implement any data, starting from live meteorological data streams to customer buying behaviors. As a result, data science applications are far and wide, and the field’s intersection with numerous other domains has increased substantially over the years. From online mechanical engineering assignment writing services to real-time meteorological data analysis, data science applications are broad and diverse.
So, where does industrial/organizational psychology fit in? And, how can learning organizational and human psychology be hugely advantageous for data scientists? How do they intersect?
To answer these questions correctly, we need to dwell a bit deeper into both these fields.
Data Science & Organizational Psychology: Understanding Their Intersections
Data is everything and everywhere. It is ubiquitous across all disciplines and domains. From data science and AI to psychology and behavioral sciences, data keeps us going, feeding us information about subjects, surroundings, processes and phenomena.
And, therein lies one of the most significant commonalities between data science and psychology.
The primary goal of data science is knowledge discovery through data analysis. Data scientists extract non-observable information and actionable insights from datasets, which reveal underlying trends, patterns and phenomena & lead to better decision making. In this age of data, data is generated by the second; from individual browsing sessions to education, research & development & real-time processing, data sources are all around us. In addition, advancements in data storage and transfer have made it easier for companies and organizations to collate and store data, leading to the concept of ‘Big Data.
Armed with statistical analysis and advanced programming algorithms, data science comes into the picture and enables automated, in-depth interpretation of data to uncover the knowledge & intelligence within. From the application perspective, data science enables the extraction of actionable insights from any dataset. Customer buying behavior, marketing, AI, administration, education – the applications are endless.
How I/O Psychology Augments Data Science?
The benefits of Institutional/organizational psychology concepts in data science come into the picture from the business perspective of data science. Data on human behavior & preferences, when analyzed using data science techniques, can reveal startling insights about the psychology behind human actions.
When combined with organizational psychology, data science helps us understand the minds of consumers. Businesses such as Google, Amazon, Facebook, Walmart, etc., are already using data science and machine learning to fathom thinking patterns and influence human behaviors.
One key thing to note is that organizational psychology is no stranger to statistical analyses. For years, statistics allowed psychologists to study varied work-forces and understand their behavior & actions. However, with the advent of BIG DATA & DATA SCIENCE, organizational psychology has a new weapon in its arsenal. I/O psychologists learning data science and data scientists learning I/O psychology can augment research and operations in both fields.
The reasons why organizational psychologists should learn data science is a topic for another day. Today, we look into the biggest reasons why data scientists should learn human & I/O psychology.
Why Organizational Psychology & Data Science Work Well Together
From a data scientist’s perspective, concepts of human psychology can be highly beneficial to understanding data sourced from human actions. Big data sets are a treasure trove of information. A large volume of human behavioral data can be found in the massive data warehouses of businesses that depend upon human interaction.
The intersection of psychology and data science is not entirely new, however. Behavioral data science is the field that aims to
- understand human decisions from both social & economic contexts,
- apply quantitative approaches to measure human behavior & psychological phenomena using BIG DATA
- Leverage datasets for behavioral insights and more
The applications of cognitive psychology concepts in data science have led to improved decision-making for businesses and leap-frog advancements in artificial intelligence.
The inclusion of human and I/O psychology in data science for business was inevitable. When analyzed with data science, correctly identified data sets of consumer needs and different demographics reveal valuable insights about the human mind. Data scientists armed with I/O psychology will naturally be able to get more from such mined knowledge.
The result: better consumer research, better decision making, tailor-made user journeys, better user experiences.
The underpinning intersections between I/O psychology and data science for businesses & big data are impossible to ignore. The following 4 points further reinforce the benefits & necessity of learning I/O psychology for data scientists working with human data.
4 Major Reasons Why Data Scientists Should Study Human & I/O Psychology
- I/O psychology allows one to go beyond the technicalities & grasp the humane aspect
Sets of input data, clustering & classification techniques and learning models- the mathematics & statistics behind data science can process and extract patterns & trends. However, applying such insights practically and understanding them from a human perspective is equally important.
Trying to predict an outcome that involves human behavior & actions requires psychology for maximum effectiveness. Organizational psychology comes into play right there, helping data scientists determine the intricacies underlying motivations, apprehensions, preferences, mindsets, habits, etc. The result is improved business strategies and customer journeys.
Organizational psychology allows data scientists to interpret better how and why people think in a particular way, behave in a specific manner and take a specific decision. It ultimately aids them in devising better-informed strategies and design better user experiences.
Organizational psychology introduces data scientists to powerful cognitive analysis concepts.
Behavioral data science already implements numerous psychological concepts that analyze human behavior. For example, ideas such as social cognitive theory, self-perception theory, etc., are already helping data scientists to understand & trigger behavioral changes and understand thoughts, feelings & intentions better.
The inclusion of organizational psychology in data science curricula will lead to a pooling of diverse skills and help data scientists better interpret the intrinsic variables of a particular data set.
Organizational Psychology can reduce biases and assumptions during data analysis.
Concepts of I/O psychology do not just augment one’s understanding of human behavior and decision making; it also allows data scientists to note their own biases and presumptions.
We are all prone to cognitive biases that often creep in during major data science projects. Prejudices such as confirmation bias, availability biases, anchoring bias, selection bias, etc. Hamper the quality and effectiveness of any data analysis process.
Human and organizational psychology allows for a better understanding of different kinds of research bias, as such behavior have their roots in the human psyche.
I/O Psychology acquaints on with concepts of leadership styles, group dynamics, etc. to boost productivity
If appropriately implemented, the usefulness of organizational psychology may very well extend beyond the business application aspects of data science.
The concepts within organizational psychology can help data scientists boost their own performance and productivity. The subject allows one to glimpse into human minds and understand different personalities & different kinds of interactions & team dynamics better.
A data science team leader can utilize organizational psychology to augment team chemistry, improve dynamics and become a better leader. In addition, a deeper understanding of psychology concepts and subsequent implementation would result in a more productive & fulfilling work experience.
Key Takeaway: The collaboration of data science and I/O psychology has already begun. With their math, stats & programming skills, data scientists are collaborating with psychologists to conduct more profound consumer research. Another approach that’s fast gaining traction is the inclusion of psychological studies in data science courses. While the specialized domain of behavioral data science involves substantial studying of human psychology, general DS courses do not dwell into it.
One thing’s for sure; data scientists deal with data & information, and both statistics & psychology offer tools & tactics to analyze information better. Combining human and organizational psychology ideas with powerful statistical analyses models & potent computational algorithms elevates data science to a whole new level. Businesses, institutions and data scientists, everyone can reap massive benefits on effective implementation of organizational psychology in data science.
And that concludes this write-up. Hope it was informative and interesting enough for everyone alike. If you aspire to be a data science/machine learning engineer, know that deep hunger for knowledge is a prerequisite. So build your math, stats and programming skills to get started, put in some sincere effort and never, ever stop learning!
All the best!
Author-Bio: Brad Devon is a data science engineer and BI analyst with a major software firm in Delaware, the USA. He is also a part-time tutor and writer at MyAssignmenthelp.com, a leading do my homework help service operating in the US, UK, Australia, Middle East, etc.
