The recent COVID-19 pandemic has created grand challenges for many be it a health and pharmaceutical industry, law chambers, educational institutions, FMCG, banking, smallmicro units or supplierstransportation units. Every single organization of any size or category, faced challenges in one or other form, leaving workforce to adapt and adopt the new online work culture and advocate technology integration to their profiles. AI, Machine Learning, Talent Analytics, Automation, IoT, Gamification are recent up gradations for HRs, where HRs are pushing hard to keep up with the pace of technologies to manage employees remotely, cost cutting and developing Culture-Tech platform. The primary study was made with 64 HRs of Indian Service Industry to study the recent HR technology integration during COVID-19 to able to manage crisis, employees, projects and their own jobs.

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The correlational marker technique by Lindell and Whitney for controlling method variance by adding an unrelated variable in the study is gaining a rage of debate and demands analysis study. This article explores common method variance in HR analytics research made in the Indian context. The study makes a comparative study upon common method variance with three known techniques. In our study, we test the biases in the HR analytics data using Harman’s single-factor test, the common latent factor technique and the comprehensive confirmatory factor analysis marker approach. Common method variance was tested through Analysis of Moment Structures, version 21.0, by adding an unrelated variable. This article explains the implementation and testing of a marker variable and its impact in comparison to other practices for bias testing. The article also discusses the importance of selecting a marker variable in the questionnaire while collecting data.

Purpose: The growing and sustaining needs of today’s globalized organizations lead to a quest for competitive advantages through 3R’s: Reframing, Repositioning, and Reinventing. The current research suggests that these mutations initiate changes and provocations in almost every segment of working culture, fostering mutation for the complete organization leaving employees to accept and act. The study aims to focus on the employee experiences and the implications during the acceptance and adoption of HR analytics. Design/Methodology/Approach: Using a qualitative approach, a life-world phenomenology study with 22 employees associated with HR activities or decision-making process for employees and practicing change management were interviewed for 24 – 26 weeks before and after adopting HR analytics. The interviews were analyzed and texted, which was directed at evaluating qualitative meanings through a systematic process. It is then clustered and analyzed for defining themes and the purpose of the phenomenon. Results:The study with the sample shows that HR analytics adoption and acceptance is not a cakewalk. The organization has to prepare its employees to adjust to new technology by supporting, encouraging, training, building the right attitude to bring change, and leading in an impactful manner. Conclusion: The adoption and acceptance of HR analytics among its users have various steps and criticalities. The study was conducted to highlight the emotions of employees during the transformative move toward technology adoption and usage that will help the organization develop the right model for initiating the use of HR analytics in the working culture. It provides insights and guidance for promoting ease of acceptance and adoption of HR analytics among its users.