Table of Contents
- Background of the Proposed Research
- Statement of the Problem
- Research Methodology
- Data Sources
- Scope and limitations of the Study
- Literature Review
Over the last few decades, as the data is exponentially growing big, the major challenge being faced by HR professionals is producing precise statistics of employee linked issues and make fact based strategic HRM decisions. Putting HR analytics into practice can offer a possible solution to ensure and develop the data driven HRM. Predicting employee churn, attrition or retention is one of the key areas of HR analytics. To accurately determine who is leaving and what is the underlying reason are the key issues of HR Workforce planning. Special education professional’s play a substantial role in empowering the gifted students who are differently abled. A special teacher may start their profession with an intention of enabling differently abled students to become productive members of society, but unfortunately they face quite a lot of challenges that make their task exceptionally difficult and attrition rates are spiking up. The shortage of competent educators intimidates the value of educating specially abled learners. Building qualified workforce and creating work environment that sustain special educators’ involvement and commitment is the question of interest. The present study aims to review the underneath literature of leveraging HR Analytics to analyse the employee turnover and retention with special reference to special education professionals.
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Background of the Proposed Research
Rowley and Jackson (2011) allude to Human Resource Management [HRM] as: Overseeing and working with individuals, creating them to such an extent that the associations they work in can embrace adequately to changes in their nearby and worldwide business conditions. According to Marler, J. and Boudreau, J. (2016), the term Human Resource Analytics (HRA) is coined around 2003 to aid human resource practitioners as an IT tool to analyze Human resource policies, procedures and activities, investment on workforce, and organizational performance data using various machine learning algorithms to predict and enable data driven decision making. Kossek (1987) stated that the main reasons of high workforce turnover in organizations are poor personnel, recruitment, supervisory policies and meagre grievance procedures or lack of motivation.
In India, the Special Needs Education (SEN) is under Ministry of Social Justice and Empowerment (MSJE). Differently abled children need special education teachers who are effectively trained and are conscious of the challenges they will face while educating them. Generally, Fresh special education teachers enters into this profession with a great enthusiasm to interact and empower the differently abled with a great commitment. Soon, they are becoming frustrated and leaving the profession which is the primary cause for special education teacher scarcities. Finding skilled experts to fill special education classrooms is a challenge across the nation. As attrition rates continue to rise, lack of special education teachers are causing significant concerns about the quality of education differently abled students are receiving. Most of the Special education schools & colleges in India irrespective of the state and region are running short of certified special education. Workforces come and go. Appropriate strategies and philosophies are prerequisite to control the budding employee attrition rate.
Statement of the Problem
Why do employees quit? Attrition in the field of academics leads to teacher shortage problem which has severe implications especially across-the-board for students with disabilities. Endeavors to lessen wearing down ought to be founded on a comprehension of components that add to exceptional instructors' choice to leave.
The proposed study focusses on investigating the factors of employee churn & retention with reference to the educators & mentors working in the schools & colleges for differently abled by applying various machine learning algorithms and statistical methods of R Studio, a popular HR analytical tool. The study further gives attention to the retention strategies being followed by the special schools and suggests the recommendations for reducing the attrition rates of special educators in turn helps in retaining the best talent.
This section defines the research questions, objectives, hypothesis, research methodology, data sources, sampling, tools, and techniques for data analysis, scope and limitations of the study.
- RQ1: Explore the evolution of HR analytics & its application in the field of Human Resource Management.
- RQ2: Predict the variables influencing the high attrition rates of special education professionals using Workforce analytics.
- RQ3: Examine the employee retention strategies adapted and recommend the appropriate measures to retain the esteemed talented educators.
- Study the scope of HR Analytics in the field of Employee Attrition and Retention.
- Analyze the factors of employee turnover in Special education institutions.
- Predict the reasons behind high turnover by examining the decisive variables influencing Employee attrition and emphasize them.
- Review and analyze the employee retention strategies adapted
- Recommend the proactive action to design a tailored employee retention program to uphold the privileged Special educators.
The proposed research is twofold. Initially descriptive research methodology is adapted, later proceeds with empirical approach. The data collected using structured questionnaires then the responses are coded into numerical form and stored in a dataset. It is then pre-processed making it ready for further analysis using statistical computations and machine learning algorithms of Python – popular analytical tool to draw precise conclusions and recommendations for evidence-based predictive decision-making.
The researcher aims to determine to what extent there exists relationship between two or more variables that initiates employee’s attrition rate in special schools. Structured questionnaires are designed to measure the perception of employees. Devised questionnaires helps to gather the required data for the research and analysis. The respondents are expected to answer the questions concerning their work area. Questionnaires ensure that the respondents will be contacted at their convenience.
Schedules are also formulated using five point Likert scale such as strongly agree-1, agree-2, neutral-3, disagree-4, strongly disagree-5. It also analyses the correlations among the satisfaction levels, and reasons for employee attrition.
As capturing genuine facts is the core of the investigation, proper care has been taken while gathering. Quality information leads to informed decisions further paves a right path for further analysis, study, and research.
Primary Data sources: It includes questionnaires, and surveys which are prepared to gather factual data from the respondents working in Special education institutions in Hyderabad, (Telangana state).
Secondary Data Sources: To support different arguments raised in the study, the secondary source of data would be considered as an important part of the research. Relevant literature survey, magazines, exit interview information, journal publications, websites etc. are the key sources.
The Judgement Sampling method - a type of non-probability sampling method is used for selecting the sample from the selected special schools and colleges in Telangana state. It suits the circumstances where the improvement of testing outline is a troublesome and tedious assignment. Initially nine institutions have been selected for the current study viz. two schools of mentally handicapped, visually impaired, deaf & dumb, physically disabled each and a college for visually challenged. Later in the due course of data collection, additional respondents will be chosen. The sample size of the respondents is assumed to be 250.
Scope and limitations of the Study
The study emphases on the employee turnover and retention of the educators of special schools only. The proposed study is limited to the chosen special education institutions in Telangana (state). The proposed work focusses on only particular factors viz. Demographics, organization culture, Job satisfaction, Work life balance, Rewards & recognition, Work environment, Superior –subordinate relationship, Retention strategies
Need of the Proposed Research Work
The National Policy for Persons with Disabilities, 2006 perceives that Persons with Disabilities are esteemed human asset for any nation and tries to make a domain that gives equivalent chances and assurance of their privileges.
Disabled children are susceptible and their life is not the bed of roses like normal children. They come across various attitudinal, physical, and monetary hurdles. It is the moral responsibility of every one of us to stretch a helping hand in not only empowering them but also providing them a chance to lead their life independently.
Churn of those special education mentors directly upsets the welfare of the gifted students. Therefore the researcher wants to penetrate into this narrow field and wants to investigate the factors affecting their turnover in turn if the management responds proximately it may lead to talent retention.
The researcher has examined different emerging concepts relating to HR analytics, its application in turn-over and retention of employees with reference to special education institutions to provide foundation for current research.
Kavanagh & Carlson, (2018) revealed that HR investigation has existed since the readiness of Second World War. HR Analytics has not been greeted wholeheartedly. Rasmussen and Ulrich (2015) accept that in spite of the investigate HR Analytics is confronting, it is still seen as having potential in the event that it tends to the prerequisites for its prosperity. The territory of HR Analytics is addressed from various view points by HR experts themselves. (Bassi, 2011; Rasmussen and Ulrich, 2016). Marler, J. furthermore, Boudreau, J. (2016) expressed that there has been just little measure of scholarly research on the point, and the hypothetically inferred speculation are regularly not tried.
Devenport et al., (2010) states that the HR analyst must have an expertise in various analytical techniques, besides Human Resource Information Systems, processes in addition to related laws. Shapiro, Harris and Davenport (2010) stated that “companies have taken the guesswork out of employee management leveraging analytics to improve their method of attracting and retaining the talent, connecting their employee data to business performance, differentiating themselves from competetors and more”.
Visier Inc. furthermore, Fisher Vista (2013) prescribe that before transforming to cutting edge workforce measurements, organizations should concentrate on three dimensional HR zones – Turnover, Recruiting and Employee execution.
In the ongoing report, the foundation of corporate profitability (2012) contends that the analytical predictions are underused for measuring human capital – even by top performing business associations. The foundation accepts that by forecasting HR investigations, organizations will have the option to address:
- The risk of probability of voluntary turnover of the employees.
- The significant factors motivating the employees to leave?
- The change over plans of potential employees who are planning to quit?
- Where can we find new perspective rewarding hires?