The Role of Psychometric Analysis in Modern Industries: A Report

This report delves into the application of psychometric analysis and counseling within the context of the Indian IT industry, emphasizing the role of industrial-organizational (I-O) psychologists. It examines the significance of employee well-being in the modern workplace and the impact of the fourth industrial revolution. The report presents a detailed analysis of the 'Resilience at Work' (RAW) scale, its seven-factor model, and its correlation with work engagement, using data from 546 IT employees. The findings highlight the importance of workplace stress and the need for proactive HR practices to enhance employee resilience. The report also references a study on professional stress among Indian journalists, demonstrating how psychometric analysis can reveal job uncertainty and its impact. The discussions based on the findings underscore the potential of psychometric analysis to guide policy-making, improve decision-making mechanisms, and contribute to more sensible HR practices. The study also discusses the benefits of integrating psychometric analysis with AI tools. The conclusion emphasizes the value of consistent psychometric analysis in driving informed decision-making and promoting a more objective approach to policy formulation in various industry sectors.

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Table of Contents
Introduction....................................................................................................................................3
The role of an industrial-organizational Psychologist in the process of psychometric analysis
and counseling..............................................................................................................................3
The case of Resilience at Work scale in Indian IT industry sector..............................................4
Discussions based on the findings...............................................................................................9
Conclusion....................................................................................................................................10
Introduction
The fourth industrial revolution has changed the face of the industry quite drastically. In the past,
the balance sheets of the companies were treating machines and tangible properties as their
assets. However, at the turn of this century the things have changed, now the industries are
moving on the wheels of the "knowledge-based economy (Sharma, 2017).” This is why employees
have become an asset to the companies. Keeping them in good physical and psychological health
has become a big challenge. Specialist psychometric analysis of the employees and the proper
counseling after the diagnosis of the problem has become a commonplace among the present
industries of the world (Ford, 2006). The scope of this practice has reached a level where it has
become an industry for the psychologists. In the current paper, we are examining two such cases
belonging to two different industries in India. Under this study, we will discuss various
psychometric tests and analysis, their assessments and their impacts on the individuals in the
form of proper counseling (Coaley, 2014).
The role of an industrial-organizational Psychologist in the process of psychometric
analysis and counseling

Prior to present a study based on the empirical evidence and psychometric analysis it is
important to understand the roles and duties of the I-O psychologist and the analysis done by
him. According to various theories, an I-O psychologist is an individual who specializes in the
psychology behind the work and human behavior. On an average an individual spends eight to
ten hours during the work, his working routines reflect on the other spheres of the life as a well.
The fundamentals of the classical conditioning tell us that a military personal follows a routine of
discipline in other spheres of life as well (Cripps, 2017). Let's understand the same thing in reverse
order, the environment outside the work can also impact their working efficiency quite
considerably. This efficiency in return can impact the overall efficiency of the organization, An
I-O psychologist understands the case on both the levels and with the help of a psychometric
analysis he can figure out some causative factors and support the policy-making of an
organization on various levels (Embreston, 2012).
The case of Resilience at Work scale in Indian IT industry sector
Under a five-stage analysis, experts Pooja Malik and Parul Garg intercepted 546 employees
working in an IT firm located in India. They offered a cross-sectional questionnaire to all the
respondents. After it, they went for confirmatory factor analysis and convergent analysis of the
data in order to mitigate the impact of the variables that were present on the scale (Parul Malik,
2018). This RAW scale was working on a seven-factor model. With the help of this psychometric
analysis, the researchers were planning to establish a relationship between work engagement and
resilience.

Image 1: Seven Factor Model as Retrieved from “Psychometric Testing of the Resilience at
Work Scale Using Using Indian Sample”. Vikalp The journal of the decision makers, 12-13.
The co-relation coefficients coming out of the data collected gives us a value of dependent on
various factors where the factor of the health emerges as the primary or the key factor after the
analysis (Parul Malik, 2018).

Image 2: Work factor Diagram, as retrieved from “Psychometric Testing of the Resilience at
Work Scale Using Using Indian Sample. Vikalp The journal of the decision makers, 13-14).
The findings of table 4 clearly show that employees’ resilience scale is not a unidimensional
measure. The findings of the second degree are dependent on the first degree of the model.
Image 3. Three Degree work model diagram, Retrieved from “Psychometric Testing of the
Resilience at Work Scale Using Using Indian Sample. Vikalp The journal of the decision makers,
12-13).
The conclusions of this CFA and CFI based study allowed the researchers to correlate the
impacts of various factors that were involved in the study. For instance, the relationship between
the two elements of the work factor model can bring out a conclusive remark. A change in the
work environment can bring down direct work engagement and bring down the resilience of the

employees (Passmore, 2012 ). Workplace stress is another factor that can bring in some adverse
effects on the resilience of the individuals.
When researchers shared the findings of this report with the HR practitioners, the data related to
the RAW scale and the work factors along with the conclusions of the researches gave them an
idea that a demanding and competitive environment and a planning prior to the change has the
potential to the increase the resilience of the employees (Maree, 2017). The findings of this
research are important because these findings prompted the researchers to compare the results of
certain other researches done in other countries in similar fields.
A psychometric analysis of the subjects can become active as a database for future researchers
quite effectively. For instance, in the current result model if we change the components of the
work scale and apply the same methodology on the other fields then we can also yield other
results as well. The findings of these results can also be checked on the extent of working
conditions for the derivation of other conclusions as well (Shavick, 2014).
The findings of the current research also give us an idea that the I-O psychologist can play a
consistent role in the development of sensible HR practices indirectly. The psychometric analysis
of the subjects can add objectivity to the actions of the policy makers (Shalini, 2017). It is
important to understand the fact that prior to the arrival of the I-O psychometric analysis
organizations was mainly dependent on the feedback was given by the employees. The current
research is also important because it gives another metrics to judge the performance of the
employees rather than the results (Klain, 2015).
Researcher Shikha Shalini conducted research under the heading of "factorial analysis of
professional stress among the journalists working in India. The team of researchers studied the

responses of 55 respondents where they answered certain questions based on a Likert scale. The
researchers took 14 factors under consideration.
The interpretation of the factorial analysis dependent on the list of 14 factors is present in the
above-mentioned chart.

The commonalities of the same 14 factors are also mentioned in the second chart. Another
important value is the eigenvalue of six components which is greater than one (Shalini, 2017).
The calculation finally brings down the list of six causative factors that may have a direct or
indirect bearing on the performance of an employee working in the Journalism sector of India.
The sample was based in the city of New Delhi which is the hub of the media activity in India.
This psychometric analysis gives us an idea that the resultant of the factors like insecure work
climate, the fast pace of the work and less freedom in executing the operations gives rise to job
uncertainty and this uncertainty may lead to job insecurity. Considering the fact that media
demands out of the box presentation ideas and other means job uncertainty can be the decisive
factor for the performance of an individual. The outcome of this report opens some scope of
action for HR practitioners to ensure a stress-free environment for the individuals working in the
sector of the media (Matthews, 2014).
Discussions based on the findings

The presence of a psychometric analysis and consistent monitoring of the results has the
potential to open a rainbow of research related possibilities for an I-O psychologist and the
policymakers. The results of the psychometric analysis have the potential to change the face of
the findings and make them more versatile. In the case of the second research, we can clearly see
that three factors out of the six factors helped the researchers in figuring out another problem
area which is job uncertainty. In the first study based on the IT sector, we can clearly see that
CFA and CFI along with the component of the work factor model helped the researchers in
finding a new area to explore. The fourth generation of the industrial revolution is heavily
dependent on the big data. The practices related to the psychometric analysis can become the
next breakthrough in this game and change the game in a big way.
In the current assignment, we discussed two cases from the industry sector. The purpose of the
studies was to co-relate many factors and churn out a conclusion with their help. The current big
data practices in the industry are studying consumer behavior on the same scale. However, they
are heavily dependent on mathematical formulas. Some experts believe that artificial intelligence
tools like intuition have taken a backseat in the process. The advanced stage of the psychometric
analysis and the presence of the artificial intelligence by adding few more components in given
research can make it more fruitful for the players that are present in the market with an intention
to prosper their decision-making mechanisms with the help of big data.
Conclusion
The inclusion of a consistent psychometric analysis department in various industry sectors can
become the next branch of the decision-making mechanisms of the industries. It adds

sophistication in the findings and allows the researchers to add new fields to their existing
research programs and convert them into action research programs or spirally structured research
programs. The biggest change we can witness in the form of the impacts is in the form of policy-
making mechanism. Now the industries can examine certain fields more objectively and make
some policies more intelligently under the light of the new facts.
References
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