HR analytics is a field of analytics meant to manage manpower through improving performance, satisfaction, and retention. Analytics has emerged as an array to process, analyze, visualize, and make feasible decisions to ensure the growth of the organization. Analytics is an interactive and collaborative platform that allows users to access and visualize any report to step up for a decision.

Many theories provide explanatory approaches to understanding the adoption behavior; prominently, Innovation Diffusion Theory (IDT) [20] and Technology Acceptance Model (TAM) [21] are some suited theories in respect of the study. The adoption and acceptance of HR analytics require a reframing of the routine jobs, strategizing and repositioning HR as a strategic business partner, and reinventing the new age of tech-HR. The process of introduction of analytics is not one-sided but rather includes the involvement of top management with the right investment plans, training of the employees, shift of technique and procedure of working, support from the interconnected departments, the right leadership and stress-free execution [1]. Therefore, the organization and employee psychological factors influence the adoption process. Technology-Organisation-Environment (T-O-E) [22] seems more appropriate to the study of the adoption of HR analytics among its users as it holds wider generic constructs emphasizing the applicability and conditions involved in reshaping the working environment. T-O-E takes internal and external factors of the organization into consideration. Since analytics has a lot to do with how socially it is accepted, what least investment can give the best results, how well the concept can be put into execution and how we integrate the technology with HR working routines. TOE supports the study and helps to investigate the psychological change employee experience at the organization-technology and personal level in the adoption of the analytics process.

Technology has important features, such as internal (present prevailing technology) and external (available for adoption). The adoption of technology is dependent on the cost-benefit analysis [23], application and usage [24], requirements for adoption [7], and trialability [25]. Organization as a factor in T-O-E refers to the resources, procedures, processes, culture, and policies of an organization that impact the adoption [26]. The vision, mission, culture, values, size, structure, method of working, and available technology affect the working approach of any organization [27]. In most cases, support from top management has played an integral role in making the adoption of innovation successful, which at times deals with the training, reengineering, or waterfall approach [28]. The environment as a factor refers to the settings in which the business performs, including nature of organization, type of business, location, products and its range, customers, competitors, government regulations and support and government interventions [27]. The present scenario or changing external pressures, which are often developed from the competition, become a source of change or innovation for many, making the organizations perform for survival or gain an advantage [29]. Technology-Organization-Environment is an important factor required in the adoption of innovation in technology, considering business-related concerns in adoption decisions [30]. The study is free from any obligations and has been tested using various IT and IS studies [27]. The framework explains the holistic approach of adding change and value along with describing the impact of diffusing innovations related to technology adoption. Therefore, we adopted this framework for our study.

The process followed for conducting this research is shown in the Fig. (1).

Fig. (1). Process flowchart of research conducted.

Qualitative techniques of the phenomenological life-world approach [46-49] were adopted to understand the everyday experiences of employees, though unique for every individual but shared with dear ones or colleagues. The phenomenology approach concentrates on personal experiences one comes across and is suitable for the study in terms of understanding employee experiences of accepting and adopting change in the form of new technology that uses analytics. This study focuses on determining, analyzing, clarifying, and deciding patterns of the phenomena based on employees’ experience, participation, and attainment. It is an open-minded study based on employee experiences and with no researcher's inferences [50].

A phenomenology study is an approach to studying people and people’s approaches, beliefs, assumptions and thoughts on a phenomenon [46]. To seek an in-depth understanding of the area of interest, the study needs to be creditable with the interviews to receive enough insights into the study area but be cautious of not losing sight to study the topic. The different text suggests different size as the sample for the study, but in practice, any sample between 6 and 20 individuals are considered to be sufficient subject to information extraction [47, 49]. Thus, we executed the study with 22 as a sample as we could get sufficient insights to complete the study.

The study was performed with the HR executives, HR managers and HR specialists of a large-sized Indian manufacturing organization established in 1982, having a presence all over the country. The organization has a headquarters in Northern India, and the same location is considered for the study. The total employee strength is 4600 in the Northern region, and the HR department size lies between 1 to 2 percent of the total strength of the region. The organization follows the traditional system of hierarchy and management positioning. The organization has planned to introduce HR analytics as a competitive advantage in business functioning with the approach of quick data visualization and decision-making for strategizing the workforce. The company has studied, reviewed and understood the future needs of analytics and was ready to bring the change in the working culture.

The study includes employees from the HR department who will soon accept analytics as a daily routine, aged between 31 and 52 years. They are educated and gained graduation or post-graduate degree with 7 – 18 years of work experience and are involved in HR activities or HR-related decision-making. The employees were engaged in HR tasks, defining policies and processes, developing HR strategies, recruitment and selection, training need assessment, coordinating projects, employee engagement activities, compensation, performance appraisal, HR audit, and accounting. In totality, these groups of employees work through a defined system and record the HR data of the company in their people software. The software contains all the data of employees working in each department of the organization. Every record, from attendance to existence, is recorded and stored. This helps them in managing routine tasks like compensation, engagement, assignment of projects, circulating important information, or even greeting employees on their birthdays and anniversary.

At the time we approached the organization, they had initiated the discussion on the adoption of HR analytics in their organization. The concept was new and challenging for them as the working scenario in the HR department was not so technical. The documentation style happened on software, but all calculations and information extraction were manual. The strong bend to bring HR analytics into practice made us investigate the options of study. The organization agreed to conduct interviews with its employees. We planned the interviews in two phases: before, that is, before the adoption of HR analytics, a phase where the organization was preparing their HR employees for a new tech journey, and after, that is, after adoption and acceptance of HR analytics. The after phase focuses on registering the change after the implementation of HR analytics. We had seven months of the gap from before to after, that is, preparing employees for HR analytics from April to June, 2018, and after the implementation of HR analytics from February to April, 2019.

An appropriate time before and after practicing HR analytics was ensured, and employees (HR) were invited to participate in the study. All invited employees wanted to participate and contribute to the study to ease acceptance and adoption of HR analytics. We took permission to conduct, write, and record the study through proper channels of the organization by discussing the purpose of the study, made an appointment one week prior with the respondents to ensure their availability, and we assured to maintain the confidentiality of the organization, respondents, their work processes and data. We conducted the study by keeping the withdrawal of the employees as respondents at any time they wished.

The interviews were conducted in two phases, before the adoption of HR analytics and after the adoption of HR analytics under the identified themes. Table 1 shows the objectives of phase I and phase II of interviews as per the themes and factors.

The interviewees were 02 senior HR managers involved in strategy formulation, 02 changed managers, 07 functional heads, 03 assistant managers, and 08 were senior executives; they were all aged between 31 and 52 years and directly involved with HR activities and data. All were dealing with reports, either formulation or decision making. In the process, one senior executive changed the organization after 10 weeks of the interview, and therefore that respondent was excluded from the study. The interviews were performed with an open set of questions like Can you describe what you are experiencing when you come to know about a new change in the work scenario? What was your first reaction when you heard about HR analytics? And more explaining questions were asked - can you please explain more, what do you mean, can you please expand a bit more? The interview was conducted in an open atmosphere for 30 – 90 minutes, where the respondents strived to remain open and expressive about their experiences, and some even spoke from their hearts, explaining what was going on in their minds and hearts. The interviews were recorded in audio form and later transcribed. The respondents were assigned a number and marked as (I,x) while recording, where I referred to respondent and x referred to the number assigned to every respondent.

The employees wanted to perform in the best possible way with the usage of advanced technology. Introducing new practices requires a mutual understanding between the employee and the organization. The association of correlative relation [52] develops trust, productivity and long-term connection between the two. At the time of concerns, the employees together sort out the matter with the support of the seniors and management in practice and witness positive interrelationships [53]. Thus employee performance is affected by the support of the organization and organizational environment, resulting in an upward trend in retention graphs.

“It’s good to know that organization wants to expand through us and have some strategic planning. I noticed that when the management informed us about the new practice through HR analytics, a wave of learning flowed through us. I personally feel I want to learn and grow” (I, 12). ## “I feel a little tensed and stressed about how I will manage training and my on-going project; I am ready to learn but find it difficult to manage the time. But I definitely need it” (I, 8). ## “As far as I know, analytics is a combination of operational tasks with statistical applications; I am already using advanced excel, so I hope it would not be so different, but yes, I hope to add some new techniques to my learning curve” (I, 19). ## “In my 15 years of career, I learned a lot from new channels of recruitment to psychometric techniques of hiring, managing records on excel to port data in the software, and improving performances. I am happy that I have got the chance to learn more and move as per the trends” (I, 2).

The introduction of HR analytics was experienced as a logical improvement in the career paths of the employees. There was no reservation of thoughts about practicing the new technique. Each employee has some doubts related to the clarity of practice as to why we and why this is not associated with the IT team, debating the relevance of analytics for HRs [11], how extensively can we justify the investment on us? focusing on the rate of investment [25], does this means a shift in our role? mentioning new tasks and expectations [54]. However, it is difficult to explain the curiosity and anxiety that rush through them but to learn new is felt through the interview.

“I am not a technical person and neither into statistics, I do not know why I am in the list of making use of analytics, for now, I am little confused to say what am I expected from the new role” (I, 14). ## “I want to learn the new and trending HR development techniques, but I hope it is not too much statistics” (I, 15). ## “I am excited to be in the new role and happy I am among the selected group. I am looking forward to it” (I, 17). ## “I hope to justify with the new responsibilities, little nervous about using” (I, 13). ## “I need it, after all, every organization use marked growth, so now I want the same for my team and be a strategic partner” (I, 1). ## “Looking forward to conducting right analysis and right decision making” (I, 6). ## “ I am stressed now, already I have so much to do and now more, I hope they increase my pay” (I, 11).

Change, when supported by leadership and theory of change [55] and further social influence contributes to it [56, 57], becomes more promising. People are moving forward and are open to learning techniques of analytics. The analytics community is encouraging and provides adequate support from time to time through lectures, videos, and online support [58]. The support and encouragement from the surroundings and environment were realized for sure. This authentication came mainly from its user and the organizations, employees and trainers of analytics. It inspires the employees and organizations to adopt analytics in daily routines.

A change manager said with a smile: “no, the employee works its own, the change should be observant, it is the support comes from the team, management and the environment. It is that we need to accept.” (I, 4).

The learning curve for each employee varies as some grasp it quickly, some take time, some understand the right usage and some hold on right decision-making [59]. The variation is addressed as experience, logical framework, data exploration, and understanding of the problem. The challenges may be faced when organizations are more inclined on cost-return analysis, security, poor performance of data and leadership issues [60], making it doubtful for the organizations to practice.

“I am not sure what I am heading for, just doing routine work with dedication. It is definitely for betterment as my friend said, “you are lucky, your organization is investing wisely,” and on the same, I read in Economic Times last month about talented professionals pacing with analytics” (I, 16). ## “My friend has learned analytics on R and receives good support from the community” (I, 13). ## “Management wants to change for betterment, and we are ready for implementation. My colleges are working for it, and I am also moving along with them” (I, 12). ## “IBM, Shell and many organizations have gained advantages, and I also want to experience” (I, 2). ## “My manager and team members are fully supportive despite my health issues. I feel blessed to be part of the organization that is so supportive and could see my capabilities; I am ready for it”(I, 20).

Employees who are themselves ready see support in their environment, be peer, management, trainer or online community. Experiences have described positive affirmation for the use though sometimes reflected through the worry of learning rightly, right application or right decision making [61]. At times, when employees want to invest more time in learning, the routine jobs extract the concentration, making it difficult to participate. At times the attitude of employees makes a difference in learning and adoption, contributing to a noticeable impact.

“I want to be an early practitioner but do not have time to learn” (I, 12). ## “I spend one hour daily taking online lectures on analytics” (I, 14). ## “I am focused and talk to a friend who already uses analytics in his job” (I, 16). ## “I have joined R community; it is helping me” (I, 19). ## “I am hopeful of making a difference after analytics” (I, 1). ## “I am a slow learner, really stressed on its implementation” (I, 17).

Half a battle of change is met when supported by proper training and clarified on its purpose and application. The organization has invested rightly in training off the job for employees on analytics and supported them with online lectures. Employees were quite satisfied with the strategy of change the organization implemented but were often concerned about the completion of projects they were presently handling on time.

“I am enjoying the learning phase, and when we know where we are heading, it is more fun” (I, 2). ## “Back to school…amazing feeling to sit and only study, more relaxing” (I, 6). ## “I am better with the training sessions and live sample study” (I, 11). ## “Last day I attended a conference on analytics, it is good to know from the researchers the possibilities to applications” (I, 3). ## “I heard soon after training sessions, we would be provided with a quick workshop on the weekend; I am feeling confident to practice now” (I, 14). ## “I feel it is an extension of what I was practicing before, with quick visualization and quick reporting” (I, 15).

The implementation of desired technique by the employee adds concern to success. After training and informed use, the employees were ready to practice in real data sets. The application was on the same data set initially, which they derived from the system and tried to trace the difference with the analytics approach on work. They were cautious in its usage as it has many applications but what fits the problem is what the employees were exploring.

“I am trying to look at the same data with analytics as application, and I am happy to see a remarkable difference” (I, 8). ## “I was previously stuck with recruitment data and improving the process, and now we found a way out but were quite slow to identify” (I, 12). ## “I am surprised to see a shift in our cost curves and quite happy to report the teams who are slow performers are able to address the issues through analytics” (I, 4). ## “I am planning to explore analytics to employee engagement, employee behavior and leadership. I want to see where we are strong as manpower and how we can contribute strategically” (I, 2). ## “I made big loops initially to understand its applications. Probably the slowest in the team, but I would like to admit my colleagues helped me to pace up. Still not great but learning to my best” (I, 17). “It helped me to have ease of data visualization of the huge data set. I could analyze and even attempted predictive model” (I, 5).

Organizations invest time, money and efforts to train and bring a change towards the use of analytics. The focus starts from the need to change HR to HR business partners. The entire process has brought changes in the HR working system. The 3Rs: reframing, repositioning, and reinventing, were activated for HRs. Reframing refers to redesigning HR with technological structure, that is, through data and tools to study data. Repositioning refers to the new strategic positioning of HR in the organization. This needs an organization to prepare itself with the cost, tech infrastructure, competitors, and performance measures. Reinventing as HR must work on a new platform with a new set of performance parameters. The inducement of HR analytics has made HR strategic business partners, leading the involvement of HRs in strategic decision-making. Table 3 shows the factors (T-O-E) across the study and the frequency of respondents in acceptance of the statement.