ShodhKosh: Journal of Visual and Performing ArtsISSN (Online): 2582-7472
Emergence of Talent analytics in Human Resource Management with reference to music and performing arts Industry in India Dr. Priyanka Kulkarni 1 1 Associate
Professor, Lotus Business School, Pune, India 2 Assistant
Professor, Tilak Maharashtra Vidyapeeth, Vidyapeeth Bhavan, Gultekadi,
Pune, India
1. INTRODUCTION The emergence of talent analytics within the realm of Human Resource Management (HRM) has ushered in a transformative phase in understanding and harnessing talent, particularly within specialized industries such as the music and performance arts sector in India. This introduction will explore the pivotal role of talent analytics, contextualizing its significance and impact on HRM in the vibrant and diverse landscape of India’s music and performance arts industry. In recent years, HRM paradigms have shifted dramatically, propelled by the unprecedented surge in data availability and the technological advancements that enable its analysis. Talent analytics, as an integral facet of this evolution, empowers HR professionals with the tools and methodologies to navigate the intricacies of talent acquisition, management, and retention. Its application, specifically within niche domains like the music and performance arts sector, amplifies its significance due to the industry’s unique dynamics and idiosyncrasies. The music industry encompasses a broad range of activities related to the creation, production, distribution, promotion, and monetization of music. It includes artists, songwriters, composers, producers, recording engineers, record labels, music publishers, distributors, promoters, concert venues, streaming platforms, radio stations, and more. The industry is constantly evolving due to advancements in technology, changes in consumer behavior, and shifts in the way music is consumed and monetized. The music and performance arts industry in India stands as a testament to the rich cultural heritage and artistic diversity ingrained within the country’s fabric. It encompasses a multifaceted array of genres, traditions, and performances, fostering a dynamic ecosystem brimming with creativity and talent. However, the management of talent within this sphere has historically been subjective, relying heavily on intuition, personal networks, and conventional evaluation methods. Enter talent analytics – a catalyst poised to revolutionize HRM practices within the Indian music and performance arts sector. By harnessing data-driven insights and leveraging sophisticated analytical tools, stakeholders within this industry can decipher patterns, trends, and performance metrics previously obscured by subjectivity. The potential of talent analytics lies in its capacity to augment traditional approaches with empirical evidence, fostering informed decision-making that aligns with industry-specific nuances. The Indian music and performance arts industry, characterized by its diverse talent pool encompassing musicians, dancers, actors, and various supporting roles, presents a unique canvas for talent analytics application. This domain grapples with multifaceted challenges including identifying promising talent, predicting audience preferences, optimizing resource allocation, and nurturing long-term careers in an environment influenced by cultural shifts, technological advancements, and evolving audience tastes. Moreover, the role of talent analytics extends beyond mere talent identification. It delves deeper into understanding audience behavior, consumption patterns, and market dynamics, thereby enabling stakeholders to tailor their strategies for talent development, content creation, and audience engagement. By deciphering the intricate interplay between talent and audience reception, talent analytics becomes an indispensable tool in crafting resonant and impactful artistic experiences. The burgeoning digital landscape in India, characterized by the proliferation of streaming platforms, social media, and digital content consumption, further amplifies the relevance of talent analytics. These platforms generate a wealth of data, offering unprecedented insights into audience demographics, preferences, and consumption habits. Harnessing this data through talent analytics empowers industry stakeholders to fine-tune their strategies, optimize promotional activities, and enhance the discoverability of talent within this competitive landscape. 2. Review of Literature Qamar & Samad (2022) extensive review and bibliometric analysis in the domain of Human Resource (HR) analytics offer a compelling framework to understand the burgeoning field's current trends and future research agenda. Transitioning this lens to the realm of talent analytics within Human Resource Management (HRM), particularly concerning the music and performing arts industry in India, underscores the significance of harnessing data-driven insights within this specialized domain. By extrapolating from their systematic approach, the exploration of talent analytics in this context unveils a nuanced landscape where the amalgamation of bibliometric analysis and content analysis becomes pivotal. The literature, albeit nascent, elucidates the evolution and current state of talent analytics within HRM, offering glimpses into diverse research clusters. Moreover, the review identifies crucial knowledge gaps, steering the narrative towards the delineation of future research themes that resonate within the unique dynamics of India's vibrant music and performing arts industry. This approach, merging bibliometric insights with content analysis, enriches the understanding of talent analytics, presenting a framework that not only captures the theoretical foundations and recent developments but also paves the way for a comprehensive exploration of talent management strategies within this culturally rich and diverse industry. Gurusinghe et al. (2021) present a pioneering conceptual framework in their exploration of Predictive HR Analytics (PHRA) and its impact on talent management within organizations. In the rapidly evolving landscape shaped by digitization, technological advancements, and the advent of artificial intelligence, the need for novel approaches to facilitate strategic objectives becomes imperative. This theoretical endeavor not only contributes to understanding the dynamics of PHRA adoption but also underscores its potential implications for talent management, positioning it as a pivotal aspect in contemporary organizational strategies. Gaur & Riaz (2019) navigate the expanding landscape of People Analytics, recognizing its escalating application as a fundamental HR practice on a global scale. Despite the surge in adoption, challenges persist, impeding the seamless integration of People Analytics into HR practices. The study adopts a comprehensive approach, amalgamating critical reviews of existing literature, a comparative analysis of region-specific business performance indicators, and content analysis of pertinent reports. By synthesizing these qualitative themes and insights, the study not only elucidates the challenges but also provides actionable recommendations to facilitate a more seamless incorporation of People Analytics into HR practices, thereby enhancing its efficacy and relevance within organizational frameworks. Desu et al. (2019) delve into the pivotal role of Human Resource Analytics within the complex landscape of healthcare organizations. Acknowledging the intricate nature of HR capital, particularly within the healthcare sector where expertise and skills crucial for quality patient care are paramount, the study underscores the challenges of talent acquisition and retention faced by these organizations. Emphasizing the goal of administrators to align employee management strategies with organizational objectives, the study advocates for the application of data mining and analytics. By transitioning from understanding current scenarios to predicting future trends and outlining actionable steps for management, the utilization of predictive analytics emerges as a transformative tool. The study highlights the evolving landscape, indicating a significant adoption rate of HR analytics across various industries in India, notably 72% within healthcare and 80% within IT sectors, particularly in recruitment and selection processes. To leverage these benefits effectively, leadership, HR professionals, and managers are urged to grasp the significance of these analytical tools and metrics as fundamental components in talent acquisition and retention strategies. Furthermore, the study emphasizes that harnessing data analytics not only shapes the future of healthcare delivery but also aids in achieving diverse organizational objectives, including disaster management and reduction in HR costs. Crucially, it places an onus on top management and HR managers to craft strategies and initiatives that optimize data utilization for organizational benefit. Paleti Narendar & Mishra (2021) delve into the transformative impact of HR analytics on the training and development processes within modern organizations. Their work sheds light on the discernible shift from conventional training methodologies to contemporary, data-driven approaches in hiring. The study underscores the pivotal role of HR analytics in amalgamating diverse datasets within the realm of training and development. By examining the utilization of HR analytics within organizational frameworks, the study aims to ascertain the extent to which organizations integrate HR analytics into their training and development procedures. Furthermore, it investigates the efficacy of HR analytics in enhancing the effectiveness and cost efficiency of the training and development processes. This research not only delineates the evolving landscape of training paradigms but also accentuates the instrumental role of HR analytics in optimizing these practices, thereby fostering more effective and economically viable training and development initiatives within organizations. Guenole et al. (2017) navigate the intricate realm of workforce analytics, offering insights gleaned from the journeys of pioneering practitioners in this field. The book serves as a guiding beacon for transforming the vast potential of workforce analytics into tangible realities within organizational settings. Crucially, the book provides a roadmap for initiating analytics projects, garnering stakeholder support, and establishing a foundation for sustained success through effective data management, technological integration, collaborative partnerships, and skill development. Additionally, it delves into the significance of cultivating an analytical mindset across HR functions while honing vital skills in storytelling and visualization, thereby amplifying the value derived from human resources. Sedita (2008) focusses on project-based organizations (PBOs) within the performing arts realm, specifically investigating how temporary organizations are intertwined within interpersonal and inter-organizational networks. Moreover, it showcases the significance of latent networks and their deployment in fostering economic success within the live music industry, underscoring the intricate interplay between informal networks and organizational performance. Mohamed & Shehata (2023) delve into the evolving landscape of human resource analytics (HR Analytics) and its instrumental role in steering organizations towards competitive advantages in the era of artificial intelligence and new technologies. Recognizing the imperative for organizations to adapt to novel ways of working and skill sets to attain strategic objectives, the paper emphasizes Within this context, the role of big data emerges as a pivotal component, contributing to establishing human resources as strategic business partners by driving decisions rooted in analytics. The paper highlights the significance of evidence-based decision-making as a potent pathway to attain substantial competitive advantages within organizational frameworks. This approach seeks to provide empirical grounding to understand how HR analytics, in conjunction with big data, contributes to organizational competitiveness within this specific industry landscape. Kryscynski et al. (2018) delve into the evolving landscape of workforce analytics and its impact on the role of HR professionals as strategic business partners. The study underscores the increasing importance of workforce analytics in augmenting the effectiveness of HR professionals, suggesting a growing need for enhanced data proficiency and analytical abilities within the HR domain to contribute meaningfully to organizational success. The reviewed literature provides overview of the evolving landscape of human resource analytics (HR Analytics) and its applications across various industries. The studies explore diverse facets, including the integration of analytics into HR practices, the development of predictive HR analytics capabilities, and the utilization of people analytics for informed decision-making. Additionally, the literature highlights the significance of HR analytics in diverse sectors such as healthcare, training and development, and the performing arts, showcasing its versatile applications. While the existing body of literature contributes significantly to understanding the current state and potential of HR analytics, a notable research gap emerges. 3. Objectives 1) To study the emergence of talent analytics in human resource management with reference to music and performing arts industry in India. 2) To study the challenges faced by HR Managers in implementing talent analytics in human resource management in the music and performing arts industry in India. 4. Hypotheses H1: Talent analytics positively influences human resource management techniques in the music and performing arts business in India. H2: HR Managers encounter multiple challenges while incorporating talent analytics in human resource management within the music and performing arts sector in India. 5. Research Methodology The research utilized a quantitative methodology to investigate the emergence of talent analytics and the challenges encountered by HR managers in implementing these practices within the music and performing arts industry in India. A structured survey instrument was designed based on validated constructs derived from existing literature on talent analytics and HR management. The survey aimed to assess the extent of talent analytics adoption, its perceived impact on HR practices, and the challenges faced by HR managers in this domain. A stratified random sampling technique is used to select 311 participants from various organizations operating in the music and performing arts sector across different regions of India. The survey questionnaire was distributed electronically to HR professionals and managers within these organizations, yielding a sample size of 311 respondents. The survey items were designed to gauge the level of adoption of talent analytics tools, perceived effectiveness of these tools in enhancing HR management practices, and specific challenges encountered during their implementation. Additionally, inferential statistical tests were applied to assess the significance of the challenges identified by HR managers in implementing talent analytics within the industry. The quantitative findings provided empirical evidence to support or refute the hypotheses formulated. 6. Data Analysis Table 1
Age range of 30 to 40 years, is 47.6%, followed by those aged 40 to 50 years comprising 22.5%. Participants aged 18 to 30 years account for 12.5%, while individuals between 50 to 60 years and above 60 years represent 11.9% and 5.5%. Overall, the data indicates a substantial representation of individuals between 30 to 50 years old, comprising approximately 82.6% of the respondents, showcasing a relatively mature and experienced demographic within the surveyed HR managers from the music and performing arts industry in India. Table 2
The Table 2 displays the gender distribution within the sample of 311 respondents. Males constituting 49.5% and females 50.5% of the total sample. Table 3
This Table 3 outlines the responses regarding the effectiveness of talent analytics tools in enhancing HR decision-making processes, gathered from 311 respondents. A majority of participants, constituting 53.1%, strongly agreed that these tools effectively improve HR decision-making. Additionally, 25.4% agreed, while 6.1% strongly disagreed and 11.3% disagreed with the notion. A smaller proportion, 4.2%, expressed a neutral stance on the efficacy of talent analytics tools in enhancing HR decision-making processes. Table 4
This Table 4 summarizes the responses concerning the impact of implementing talent analytics on the efficiency of recruitment strategies, based on 311 respondents. A substantial majority, constituting 44.7%, strongly agreed that talent analytics implementation significantly enhanced the efficiency of their recruitment strategies. Additionally, 23.2% agreed with this improvement. On the contrary, 16.7% strongly disagreed, and 11.9% disagreed with the notion. A smaller fraction, 3.5%, maintained a neutral stance regarding the effect of talent analytics on the efficiency of their recruitment strategies. Table 5
This Table 5 presents responses reflecting the perceived contribution of talent analytics to workforce planning and optimization from 311 participants. A significant portion, accounting for 49.8%, strongly agreed that talent analytics makes a substantial contribution to workforce planning and optimization. Furthermore, 23.5% agreed with this viewpoint. Conversely, 14.5% strongly disagreed, and 8.7% disagreed with the notion. A smaller fraction, comprising 3.5%, maintained a neutral stance regarding the impact of talent analytics on workforce planning and optimization. Table 6
Table 6 represents responses on the influence of talent analytics on employee retention initiatives from 311 participants. A majority, 51.8%, strongly agreed that adopting talent analytics had a significantly positive impact on employee retention initiatives. Additionally, 24.4% agreed with this assertion. Conversely, smaller percentages disagreed, with 11.6% expressing disagreement and 7.4% strongly disagreeing. Around 4.8% maintained a neutral stance on the influence of talent analytics on employee retention initiatives. Table 7
Table 7 showcases the responses regarding the impact of talent analytics on identifying and nurturing talent within the organization, collected from 311 participants. The data indicates a substantial agreement among respondents, with 54.3% strongly agreeing and 21.5% agreeing that talent analytics have significantly improved their ability to identify and nurture talent. Conversely, smaller percentages disagreed, as 8.4% disagreed and 9.6% strongly disagreed. Additionally, 6.1% remained neutral regarding the impact of talent analytics on this aspect of HR management within their organization. Table 8
Table 8 indicates respondents' perceptions regarding the financial investment required for implementing talent analytics tools. The data reflects varying perspectives, with a notable proportion strongly agreeing (42.1%) and agreeing (25.7%) that substantial financial investment is necessary for implementing these tools. A smaller percentage disagreed, comprising 11.9% who disagreed and 14.5% who strongly disagreed. Furthermore, 5.8% of respondents remained neutral concerning the financial investment associated with implementing talent analytics tools in their organization. Table 9
Table 9 illustrates participants' perceptions regarding the availability of skilled personnel capable of effectively utilizing talent analytics tools. The majority of respondents strongly agreed (50.5%) that there is a lack of skilled personnel, while an additional 25.7% agreed with this statement. A smaller proportion disagreed, with 7.7% disagreeing and 13.2% strongly disagreeing with the notion of a lack of skilled personnel. Additionally, 2.9% of respondents remained neutral regarding the availability of personnel proficient in using talent analytics tools. Table 10
Table 10 summarizes respondents' opinions on the technical challenges associated with integrating talent analytics into existing HR systems. A notable majority, comprising 35.4% who strongly agreed and an additional 32.2% who agreed, acknowledged that this integration poses significant technical challenges. Furthermore, 13.8% disagreed, and 10.0% strongly disagreed with this perspective. About 8.7% of participants remained neutral regarding the technical challenges related to the integration of talent analytics into existing HR systems. Table 11
Table 11 presents respondents' perspectives on cultural resistance within organizations impacting the adoption of talent analytics. A significant majority, comprising 46.0% who strongly agreed and an additional 27.3% who agreed, recognized that cultural resistance hampers the adoption of talent analytics. Table 12
Table 12 indicates the challenges related to obtaining reliable and relevant data for talent analytics. The majority of respondents, comprising 57.6% who strongly agreed and an additional 19.9% who agreed, highlighted that acquiring such data poses a significant challenge. H1: Talent analytics positively influences human resource management techniques in the music and performing arts business in India. Table 13
The analysis conducted to evaluate the impact of talent analytics on human resource management practices in the music and performing arts industry in India yielded compelling results across multiple dimensions. Examining the effectiveness of talent analytics tools in enhancing HR decision-making processes revealed a substantial mean difference of 1.08039 (p< .001, 95% CI [.9405, 1.2202]), indicating a significantly positive impact. Similarly, the implementation of talent analytics showcased a substantial enhancement in the efficiency of recruitment strategies, with a mean difference of .67203 (p < .001, 95% CI [.5005, .8435]), signifying notable improvement. Furthermore, talent analytics demonstrated significant contributions to workforce planning and optimization, as indicated by a mean difference of .85531 (p < .001, 95% CI [.6910, 1.0196]). Additionally, its positive influence on employee retention initiatives was pronounced, exhibiting a mean difference of 1.01608 (p < .001, 95% CI [.8706, 1.1615]). Finally, the adoption of talent analytics significantly improved the identification and nurturing of talent within organizations, with a mean difference of 1.02572 (p < .001, 95% CI [.8755, 1.1759]). Overall, the findings from this comprehensive analysis consistently support the hypothesis (H1) that talent analytics indeed holds a significantly positive impact on various facets of human resource management practices within the music and performing arts industry in India. H2: HR Managers encounter multiple challenges while incorporating talent analytics in human resource management within the music and performing arts sector in India. Table14
The examination of challenges faced by HR Managers while implementing talent analytics in the music and performing arts industry in India revealed noteworthy insights. Across various dimensions, HR managers encountered substantial hurdles during the implementation process. Financial investment emerged as a significant concern, with talent analytics tools requiring a substantial investment, showcasing a mean difference of .69132 (p < .001, 95% CI [.5270, .8556]). This finding highlights the financial burden associated with integrating these tools within HR frameworks. Additionally, a lack of skilled personnel capable of effectively utilizing talent analytics tools posed a considerable challenge, exhibiting a mean difference of .92605 (p < .001, 95% CI [.7671, 1.0850]). Integrating talent analytics into existing HR systems also presented technical challenges, with a mean difference of .69132 (p < .001, 95% CI [.5416, .8411]), underscoring the technical complexities faced during integration. Moreover, cultural resistance within organizations significantly hindered the adoption of talent analytics, reflected by a mean difference of .90675 (p < .001, 95% CI [.7586, 1.0549]). Obtaining reliable and relevant data for talent analytics emerged as a substantial challenge, showcasing a mean difference of 1.07717 (p < .001, 95% CI [.9269, 1.2274]), indicating the difficulty in sourcing pertinent data for effective utilization. The comprehensive analysis demonstrates that HR managers indeed encounter multifaceted challenges while implementing talent analytics in the music and performing arts industry in India. These challenges encompass financial, technical, personnel, cultural, and data-related aspects, underscoring the complexity involved in effectively integrating talent analytics into HR management practices within this industry. 7. Findings The findings from the study present a nuanced perspective on the integration of talent analytics within the music and performing arts industry in India. Firstly, talent analytics showcased a significant positive impact on various human resource management practices within this industry. The analysis revealed that talent analytics tools effectively enhanced HR decision- making processes, improved recruitment strategies, contributed to workforce planning, positively influenced employee retention initiatives, and improved the identification and nurturing of talent within organizations. These results suggest that the adoption of talent analytics has led to substantial improvements across multiple facets of HR management practices. However, despite the evident benefits, HR managers faced several formidable challenges during the implementation of talent analytics. Financial investment emerged as a major concern, indicating the substantial resources required for tool implementation. Additionally, the lack of skilled personnel capable of effectively utilizing these tools, technical challenges in integration, cultural resistance within organizations, and difficulties in obtaining reliable and relevant data posed significant hurdles in the effective implementation of talent analytics. These findings provide a comprehensive view, highlighting both the positive impacts and the challenges encountered in the integration of talent analytics within the music and performing arts industry in India. Addressing these challenges could be pivotal in maximizing the potential benefits of talent analytics in enhancing HR management practices within this sector. 8. Conclusion The study's conclusions reflect a dual reality within the music and performing arts industry in India regarding talent analytics. On one hand, the findings underscore the tangible benefits and positive impacts of implementing talent analytics in various HR management domains. Enhanced decision-making, improved recruitment strategies, workforce optimization, and better talent identification signify the potential of analytics in revolutionizing HR practices within this creative sector. However, the study also sheds light on significant hurdles hindering its seamless integration. Financial investment, the shortage of skilled personnel, technical integration challenges, cultural resistance, and data reliability issues emerge as critical barriers that HR managers face when deploying talent analytics tools. These findings carry substantial implications for HR practitioners and organizational leaders within the music and performing arts industry. Recognizing the potential benefits, organizations should invest in resources to overcome the identified challenges. Training programs and capacity-building initiatives could bridge the skill gap among personnel, enhancing their proficiency in using talent analytics tools. Simultaneously, fostering a culture of openness to technological changes and data-driven decision-making could mitigate cultural resistance. Collaboration with technology partners and fostering data partnerships might address concerns related to data reliability and technical integration. Such strategic moves could transform these challenges into opportunities, unlocking the full potential of talent analytics in this industry. In terms of future research, a longitudinal study tracking the evolution of talent analytics adoption and its impact over time within the music and performing arts industry could provide valuable insights. Exploring how organizations adapt to overcome the identified challenges and the subsequent impact on HR practices could offer a dynamic understanding. Additionally, qualitative studies delving deeper into the cultural nuances, perceptions, and experiences of stakeholders could provide richer context and depth to the quantitative findings, offering a comprehensive understanding of the complexities associated with talent analytics integration in this unique industry.
CONFLICT OF INTERESTS None. ACKNOWLEDGMENTS None. REFERENCES Desu, R. M., Prasad, G. S. C. N. V., & Rao, P. S. (2019). Role of Human Resource Analytics in Health Care Organizations. Amity Journal of Training and Development, 4(1), 19-29. Gaur, B., & Riaz, S. (2019, November). A Two-Tier Solution to Converge People Analytics into HR Practices. In 2019 4th International Conference on Information Systems and Computer Networks (ISCON), 167-173. IEEE. https://doi.org/10.1109/ISCON47742.2019.9036312 Guenole, N., Ferrar, J., & Feinzig, S. (2017). The Power of People: How Successful Organizations Use Workforce Analytics to Improve Business Performance. FT Press. Gurusinghe, R. N., Arachchige, B. J., & Dayarathna, D. (2021). Predictive HR Analytics and Talent Management: A Conceptual Framework. Journal of Management Analytics, 8(2), 195-221. https://doi.org/10.1080/23270012.2021.1899857 Kryscynski, D., Reeves, C., Stice-Lusvardi, R., Ulrich, M., & Russell, G. (2018). Analytical Abilities and the Performance of HR Professionals. Human Resource Management, 57(3), 715- 738. https://doi.org/10.1002/hrm.21854 Mohamed, D., & Shehata, G. M. (2023). HR Analytics and Achieving Competitive Advantage for Organizations Through Big Data: A Conceptual Paper. Journal of Applied Business & Economics, 25(3). https://doi.org/10.33423/jabe.v25i3.6201 Paleti Narendar, D., & Mishra, M. (2021). Impact of HR Analytics on Training and Development in an Organization. Psychology and Education, 58(1), 3606-3614. https://doi.org/10.17762/pae.v58i1.1315 Qamar, Y., & Samad, T. A. (2022). Human Resource Analytics: A Review and Bibliometric Analysis. Personnel Review, 51(1), 251-283. https://doi.org/10.1108/PR-04-2020-0247 Sedita, S. R. (2008). Interpersonal and Inter-Organizational Networks in the Performing Arts: The Case of Project-Based Organizations in the Live Music Industry. Industry and Innovation, 15(5), 493-511. https://doi.org/10.1080/13662710802373833
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