An organization's internal Human Resource Management (HRM) system is referred to as human resource control, or HRC for short. HRC is responsible for managing fundamental aspects of HRM, including hiring and training employees, paying them fairly, ensuring their safety on the job, and cultivating productive working relationships between management and staff (Tursunbayeva, Di Lauro, and Pagliari, 2018). Both human resource management (HRM) and HR analytics put an emphasis on optimizing employee-related operations such as recruiting, evaluating, promoting, compensating, retaining, and letting go of staff members (Tursunbayeva, Di Lauro, and Pagliari, 2018). In this article, the benefits that HR analytics may provide to companies are discussed.
The term "human resource analytics" is very recent, having made its debut in the year 2004 (Marler and Boudreau, 2017) At the crossroads of computer science, decision making, and quantitative approaches lies a new field that goes by the name of analytics. Its purpose is to organize, analyze, and provide solutions for the massive amounts of data that are produced by modern civilization (Mortensen, Doherty, and Robinson, 2015). Incorporating the phrase "HR" into these investigations makes it abundantly clear that the employees themselves are the primary focus of these inquiries (Heuvel and Bondarouk, 2017).
HR analytics refers to the practice of carefully finding and quantifying the people-related factors that contribute to the success of an organization in order to make decisions that are more informed (Heuvel and Bondarouk, 2017). Depending on the specifics of the situation, the term "human resource analytics" may also be synonymous with "people analytics," "talent analytics," and "workforce analytics." Therefore, the goal of HR analytics is to collect data from all of the many departments and activities carried out by the firm. Information on employees, including their names, addresses, birthdays, ethnicities, jobs, years of service, earnings, marital and family statuses, educational and professional accomplishments, and so on, is stored within HR information systems (HRIS) (Heuvel and Bondarouk, 2017).
In addition to analytical data, a payroll system would typically include components such as tools for worker scheduling, application tracking systems, and satisfaction surveys. HR analytics make use of data from the management information system of the firm that is not related to HR (such as ERP). A few examples of data sources include the following: the volume, defect rates, and returned goods from the production module; the customer satisfaction and retention rates from the marketing module; and the revenue, cost, and profit figures from the finance module (Diez, Bussin, and Lee, 2019).
Analytical tools for management of human resources can be used, not only for evaluative purposes, but also for achieving descriptive and prescriptive objectives (Reddy, 2017). Optimizing processes is the goal of descriptive analytics, and the method achieves this goal by employing relationship visualizations that are based on observable patterns from both the present and the past (Reddy, 2017).
The foundation of descriptive analytics is provided by HR metrics, which are used to analyze significant HRM performance outcomes such as the level of effectiveness and efficiency. KPIs have the potential to be implemented in a wide variety of HR procedures, including strategic planning, talent acquisition, performance management, talent and career management, pay, retirement, and termination, in addition to health, safety, and employee well-being (Wawer, 2018).
Common HR metrics for measuring employee productivity and performance include employee turnover, profit, and labor costs. For instance, the profit generated by employees can be calculated by dividing annual or monthly profit by the number of employees, or profit per employee can be calculated by dividing business profit by the number of employees. Another example of a common HR metric is the number of hours worked per employee.
Businesses that have reached a high level of maturity make sophisticated use of people analytics. As a consequence of this, the mature businesses' average profit over a period of three years is 82% higher than the average profit of businesses that have not reached a high level of maturity (Deloitte Development LLC, 2017).
HR practitioners might gain a lot by developing a grasp of HR analytics as a field that works to improve the quality of data and the financial success of businesses. The recognized benefits are an important starting point when it comes to conducting surveys regarding the challenges that businesses face when attempting to integrate HR analytics.
References
Deloitte Global Hu-man Capital Trends. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/global/Do-cuments/About-Deloitte/central-europe/ce-global-human-capital-trends.pdf
Diez, F., Bussin, M., and Lee, V. (2019). Fundamentals of HR analytics: A Manual on becoming HR analytical. Emerald Group Publishing.
Hecklau, F., Galeitzke, M., Flachs, S., and Kohl, H. (2016). Holistic approach for human resource ma-nagement in industry 4.0. Procedia CIRP, 54, 1-6.
Heuvel V. D. S., and Bondarouk T. (2017). The rise (and fall?) of HR analytics, Journal of Organizatio-nal Effectivness, People and Performance Vol. 4 No 2, 2017, pp.127-148
Marler, J., and Boudreau, J. (2017). An evidence-based review of HR analytics. The International Journal of Human Resource Management, 28(1), 3-26.
Mortensen, M., Doherty, N., and Robinson, S. (2015). Operational research from Taylorism to teraby-tes: A research agenda for the analytics age. European Journal of Operational Research, 241(3), 583-595.
Reddy, P. (2017). HR analytics – an effective evidence based HRM tool. International Journal of Busi-ness and Management Invention, 6.7(2017), 23-34.
Tursunbayeva A., Di Lauro, S., and Pagliari, C. (2018). People analytics – a scoping review of con-ceptual boundaries and value propositions. International Journal of Information Management, 43, 224-247.
Wawer, M. (2018). The use of HR metrics in human resources management. Przedsiębiorczość i Za-rządzanie, 19, 3, 2, 2303-317
A great blog article Vidura, I would like to add to your content that according to Sesil, (2013), advanced analytics can aid in establishing causation, which is generally thought of as the holy grail of analytics (Sesil, 2013). Advanced analytics helps organizations not only with justifications but also to decide the bottom line. Thus, it helps in identifying what policy, practice or intervention would be beneficial in the future.
ReplyDeleteIt's great to have your feedback Afzal. I love your idea on Causation, totally agree with you. Adding to that recent research has shown that certain dimensions of effectuation overlap with causation (Chandler, DeTienne, McKelvie, & Mumford, 2011; Fisher, 2012). Fisher (2012) found evidence that entrepreneurs did employ causation behaviors alongside with effectuation behaviors. Smolka, Verheul, Burmeister-Lamp, and Heugens (2018) found that entrepreneurs’ combined use of effectuation and causation has a greater impact on venture performance than the sum of their independent effects.
ReplyDeleteGreat content Vidura. Adding to the above HR professionals will face ethical quandaries along the way. Preemptively attain this by clearly defining the principles for determining when HR analytics will and will not be used and mastering the art and science of HR analytics takes time and effort. However, it has the potential to raise the status of the profession and its practitioners by assisting them in guiding their organizations to the sweet spot—the intersection of more profitable and enlightened management and human development (Bassi & Company, 2011).
ReplyDeleteHi Safiya , thank you for sharing your valuable opinion on my Blog. Some researchers have even argued that HR Analytical Digitalization is leading to the elimination of some professions (Susskind & Susskind, 2015). For instance, ranking platforms and blockchain technology have the potential to replace the traditional verification function of audit professionals (Carter, Spence, & Muzio, 2015; Jeacle & Carter, 2011). Yet, little is known about the impact of more sophisticated digital technologies and methods promoted by new occupational groups such as data scientists (Carter et al., 2015) on settlements in the ecologies of professional projects within organizations, as well as the relations between them.
DeleteAgreed with your post Vidura. In addition, The focus on employee engagement requires serious examination if HR professionals are to become able and respected practitioners of HR analytics (Bassi and McMurrer, 2010).
ReplyDeleteThank you for commenting on my Blog Kandeepan. HR analytics is a technique promoted by data scientists which involves using software to analyze data regarding employee behavior. For example, it can be used to predict employee performance and to support HRM in making decisions about promotions. Contemporary Organizations have already implemented these in their beneficial successfully.
DeleteInteresting content Vidura. Furthermore,Nocker and Sena (2019) discussed the opportunities offered by talent analytics to HR practitioners. Their study described the benefits and costs associated with the use of talent analytics. The authors analysed case studies on how talent analytics could improve decision-making and also the costs related to the data governance and ethics that were generated. The conclusions drawn from the study are: first, talent analytics used in a proper way may help the senior management align HR strategies with value creation; second, there were three factors moderating the relationship between performance (measured by profitability, customer satisfaction, innovation, efficiency) and talent analytics: technical knowledge of analytics, access to data, and understanding how to use the results of analytics to improve the performance of organizations.
ReplyDeleteThank you for commenting on my Blog Manodya. Adding to above, extant research on analytics in organizations shows how novel technologies can spawn technical proponents and opponents whose interrelationships and symbolic actions change the practices of knowing in organizations (Pachidi, Berends, Faraj, & Huysman, 2021). In this way, technology has become involved in knowledge work previously ascribed exclusively to professionals. Another aspect is that technologies can promote transparency of expertise and enable lower status occupations to perform more complex tasks (Muzio et al., 2020).
DeleteGreat blog post Vidura, Alternative working patterns such as job-rotating, job-sharing, and flexible working have been branded as effective motivational tools by Llopis (2012). Moreover, Llopis (2012) argues that motivational aspects of alternative working patterns along with its other benefits are being appreciated by increasing numbers of organisations, however, at the same time; many organisations are left behind from benefiting from such opportunities
ReplyDeleteThank you for your feedback Isuri. Moreover, extant research on analytics in organizations shows how novel technologies can spawn technical proponents and opponents whose interrelationships and symbolic actions change the practices of knowing in organizations (Pachidi, Berends, Faraj, & Huysman, 2021)
DeleteGood Post Vidura, because people's skills and abilities are improved by training and development programs. Even organizations provide financial aid to anyone who enroll in these courses (Jehanzeb & Bashir, 2013).
ReplyDeleteSolid content. I would like to add that the term “HR analytics” (HRA) is elusive and has different meanings to different people and there are multiple definitions of the term in the literature (Madsen and Slåtten, 2020).
ReplyDelete