Review of Theories and Frameworks

Introduction

Get Free Samples Written by our Top-Notch Subject Expert Writers known for providing the No.1 Assignment writing services in Australia

1. Purpose of the Research

The purpose of this research is to “investigate what soft skills that claim assessors at Company B need to possess to meet new job requirements after the implementation of claims automation and recommend solutions to bridge the gap”.

2. Review of Theories and Frameworks

Two modern business theories and a framework that are relevant to the study are discussed in this following section, namely the Feeling Economy and Future-proof Human Capabilities. Besides, the analytical framework of Customer Service Skills, Customer Satisfaction and Customer Loyalty will also be assessed in this section.

2.1 Theories Relevant to the Topic

2.1.1 Feeling Economy

Many jobs that were formerly reserved for humans are now being mechanised via the use of artificial intelligence as robots are taught to “think”. Nevertheless, emotional intelligence is more difficult to automate, and here is where human workers now have a competitive edge over robots. According to Rust and Huang (2021), artificial intelligence (AI) is fast taking over a growing part of cognitive duties, freeing up human intellect to concentrate on emotion. As a consequence, the human being has entered a new era, called the “Feeling Economy”, in which workers and customers place an unparalleled premium on emotion while leaving most cognitive work to machines (Huang, Rust and Maksimovic, 2019). Presently, AI can do more than only automate and repeat, since its capabilities are growing to include analysis and thought. There is a shift toward a “Feeling Economy”, wherein AI takes over more and more analytical and thinking jobs, while humans focus on more people-oriented duties that need empathy and connection. Such interactions with others have always been crucial to the success of a business, but their importance is growing at an unprecedented rate. As more and more analytical and thinking activities are being handled by AI, managers in the Feeling Economy must adjust the nature of employment to accommodate for this shift, requiring human employees to put more focus on the sympathetic and emotional components of their work.

2.1.2 Future-proof Human Capabilities

The focus is not on depreciating technical knowledge and abilities, but rather on a graduate’s total employability, or how to discover high-potential people with the capability to thrive in a fast-changing world of work. Bowles, Bowes, and Wilson (2019) argue that frameworks of organisational capabilities and professional, employability, core or soft skills are gauging the very same thing: skills for future work and success in life, and that this is borne out by recent research connecting contemporary works and skill requirements. Despite the proliferation of frameworks that claim to characterise human skills, soft skills, employability, or future capabilities, there is little work done to compare these frameworks or to isolate the most significant skills within an Australasian future workforce environment (Jackson, Shan and Meek, 2021). Educators, employers, and candidates all benefit from a deeper understanding of the worth of some skills in comparison to others in terms of future employability, which may be achieved via the use of a skills framework to analyse and anticipate future skills demand in the workforce.

Bowles, Bowes, and Wilson (2019) have analysed the accumulated data already present in current frameworks using a data-driven method based on text analysis to learn about their future potential. The framework and logic provided by these future capabilities enable a more nuanced investigation of the connection between workers and occupations, as well as the development of a taxonomy that facilitates the construction of capability stacks that confirm the prerequisites for future learning and work. The following figure of “Future-proof Human Capabilities” explains the skills and knowledge identified by the validation study as being crucial for the workforce of the future, although they do not involve any technological expertise.

2.2 Analytical Frameworks

2.2.1 Customer Service Skills, Customer Satisfaction and Customer Loyalty

To set themselves apart from one another, businesses provide a variety of goods and services. The success of a company can often be traced back to the staff’s interpersonal skills and their capacity to interact with clients. Because of the high quality of the services they provide, their clients are always happy with their experience. It has become a crucial part of every successful marketing campaign these days. Hence, Ali et al. (2018) examined the impact of excellent customer service abilities on retention rates by way of patrons’ level of contentment and reached the “Customer Service Skills, Customer Satisfaction and Customer Loyalty” framework.

While consumers of most banks are aware of the services they provide, convenience and efficiency often top their lists when deciding which bank would best meet their needs. Because of this, the authors analysed the role of problem-solving abilities, reputation management, customer support culture, non-verbal and verbal communication skills, and the ability to persuade consumers’ decisions about the best banks to work with. It is suggested that, to compete with other banks in the market, financial institutions train their staff in customer service etiquette and soft skills, and that financial institutions also employ marketing strategies via social media and other marketing channels to sway customers’ opinions in favour of their institution.

3. Research Methodology and Methods

The paper summarises the data used in its analysis and discusses the research methods that were used to get those results. In addition, the gap analysis as the chosen analytical method for the secondary data analysis is described below.

3.1 Case Study Research Methodology

In this work, the researcher used a case study approach to the research process. Only one comprehensive case study was chosen for analysis. The chosen case organisation is Company B. Because of the researcher’s insider status at Company B, they have unparalleled access to pertinent policies and demands regarding skill requirements in the organisation. It was a once-in-a-lifetime chance to solve a pressing problem for the company, and that chance was offered by the case study. In this scenario, the research is tasked with figuring out what kinds of “soft skills” claims assessors at Company B would need to succeed in their new roles as a result of the introduction of claims automation. The research has also focused on coming up with recommendations on how to close the resulting skills gap. As a bonus, focusing on a single case study allowed us to thoroughly investigate the issue by surveying pertinent prior research (Noor, 2008). The implementation of claims automation necessitates a set of soft skills, and theories like the “Feeling Economy” and “Future-proof Human Capabilities” and frameworks like “Customer Service Skills, Customer Satisfaction, and Customer Loyalty” have proven helpful in understanding what they are.

3.2 Secondary Data

Based on the opinion of Koziol and Arthur (2011), the researcher has utilised secondary data such as journal articles and industry reports evaluating the effects of automation on the soft skills needed of claims assessors and other white-collar employees in enterprises most impacted by automation, like the accounting industry, as well as secondary information from Company B including the role statement, performance review and Curriculum Vitae of the claims assessors. That being said, the case organization’s internal data regarding the skill needs of its claim assessors served as the primary secondary qualitative data source for the study. To determine which soft skills are most important for claims assessors to have and which ones they already have, qualitative content analysis has been performed on the obtained data. A training needs assessment has been conducted as a direct result of the data collected here. The usage of internal resources has been approved by the relevant authorities in the organisation.

3.3 Analytical Framework

Earlier in this report, it has been discussed that a suitable analytical technique for assessing the qualitative data and sources indicated above. The “Customer Service Skills, Customer Satisfaction, and Customer Loyalty” framework is an effective method for gauging an organization’s ability to provide excellent customer service. This framework for client retention has been developed by Bowles, Bowes and Wilson’s (2019) research for use by the company’s management. According to their research, having competent customer care representatives on staff is crucial for retaining customers and winning their loyalty. Therefore, banks must train their staff in customer care techniques that result in happy and loyal clients. The model suggests that training in areas such as nonverbal and verbal communication, reputation constructing, problem-solving, and a customer support culture are the most important factors of customer service skills that increase consumer satisfaction; consequently, industries such as banking should prioritise training their employees on improving all four dimensions. Companies would do well to educate their staff on the importance of body language while interacting with clients since this aspect of communication is just as influential as verbal abilities in establishing the brand’s reputation. Customer satisfaction may be greatly improved via the development of problem-solving abilities. Companies should foster a learning culture that encourages workers to take on more responsibilities, enhances their verbal communication as a result of increased engagement, and promotes the growth of problem-solving abilities.

References

Ali, M., Iraqi, K.M., Rawat, A.S. and Mohammad, S., 2018. Role of customer service Skills on customer satisfaction and its effects on customer loyalty in Pakistan banking industry. South Asian Journal of Management Sciences, 12(2), pp.210-223.

Bowles, M., Bowes, N. and Wilson, P., 2019. Future-proof human capabilities: Raising the future employability of graduates. International Journal of Business and Social Science, 10(11), pp.18-29.

Huang, M.H., Rust, R. and Maksimovic, V., 2019. The feeling economy: Managing in the next generation of artificial intelligence (AI). California Management Review, 61(4), pp.43-65.

Jackson, D., Shan, H. and Meek, S., 2021. Enhancing graduates’ enterprise capabilities through work-integrated learning in co-working spaces. Higher Education, pp.1-20.

Koziol, N. and Arthur, A., 2011. An introduction to secondary data analysis. Research Methodology Series.

Noor, K.B.M., 2008. Case study: A strategic research methodology. American journal of applied sciences, 5(11), pp.1602-1604.

Rust, R.T. and Huang, M.H., 2021. The feeling economy: How artificial intelligence is creating the era of empathy. Cham, Switzerland: Palgrave Macmillan.

Working Futures. 2020. Human Capability Standards: Reference Model. [online] Available at: https://www.workingfutures.com.au/wp-content/uploads/2020/06/HumanCapabilityStandards_7Level_FULLSUMMARY_290420.pdf [Accessed on: 10^th September, 2022]